IAU Symposium 306
Lisbon, Portugal, 25-29 May, 2014

Book of Abstracts

Contents
General information

7

Conference Programme

15

Tutorials

25

Keynote talks

29

Invited talks

37

Contributed talks

43

Posters

67

List of participants

125Foreword
Full exploitation of the very large surveys of the Cosmic Microwave Background, Large-Scale Structure, weak gravitational lensing and future 21cm
surveys will require use of the best statistical techniques to answer the major
cosmological questions of the 21st century, such as the nature of Dark Energy
and gravity.
Thus it is timely to emphasise the importance of inference in cosmology,
and to promote dialogue between astronomers and statisticians. This has beenrecognized by the creation of the IAU Working Group in Astrostatistics andAstroinformatics in 2012.
IAU Symposium 306 – Statistical Challenges in 21st Century Cosmology
is devoted to problems of inference in cosmology, from data processing tomethods and model selection, and will have an important element of crossdisciplinary involvement.

Keynote speakers
David van Dyk (UK) on Bayesian methods
Aurore Delaigle (Australia) on Errors and nonparametric estimation
Graca Rocha (USA) on Cosmic Microwave Background
Ben Wandelt (France) on Massive parameter estimation
Masahiro Takada (Japan) on Weak Gravitational Lensing
Licia Verde (Spain) on Large-scale structure
Sabino Matarrese (Italy) on Statistics of fields
Alex Szalay (USA) on Overwhelmingly large datasets
Jalal Fadili (France) on Sparsity
Mario Santos (South Africa / Portugal) on 21cm cosmology
Anais Rassat (Switzerland) on Combining probes

Invited speakers
Denis Barkats for BICEP2 (ESO) on B-mode polarization
Hiranya Peiris (UK) on Anomalies
Narciso Benı́tez (Spain) on Statistical aspects of photo-z
Mike Hobson (UK) on Machine-learning in AstronomyJérôme Bobin (France) on Sparsity based CMB reconstruction
Mario Hamuy (Chile) on Supernovae Cosmology
Joseph Hilbe (USA), for closing remarks from a statistician
Andrew Jaffe (UK) for closing remarks from a cosmologist

Scientific Organizing Committee
Alan Heavens (UK) Chair

Jean-Luc Starck (France) Chair

Raul Abramo (Brasil)

Adrian Baddeley (Australia)

Bruce Bassett (South Africa)

Dalia Chakrabarty (UK)

Joseph Hilbe (USA)Alberto Krone-Martins (Portugal)

Vicent Martinez (Spain)

Thanu Padmanabhan (India)

Enn Saar (Estonia)

Ralf Siebenmorgen (ESO)

Qingjuan Yu (China)

Yanxia Zhang (China)

Local Organizing Committee
Alberto Krone-Martins (Lisboa) Chair André Moitinho (Lisboa) Co-Chair
Sónia Antón (Granada | Porto)

Carlos Martins (Porto)

Ana Mourão (Lisboa)

António da Silva (Lisboa | Porto)

The symposium secretary service is assured by
Raquel Brito (Lisboa)

Angélica Ruivo (Abreu)

Nelma Alas Silva (Porto)Ângela Antunes (Lisboa)

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IAUS306–SCCC21 is supported byInternationa Astronomical Union
http://www.iau.org

European Research Council
http://erc.europa.eu

http://astro.ic.ac.uk/research/imperialcentre-inference-and-cosmology-icic

Commissariat à l'énergie atomiqueet aux énergies alternatives
http://www-centre-saclay.cea.fr

Laboratoy for Systems,
Instrumentation and Modelling
http://www.sim.ul.pt

http://wuala.com

http://www2.acad-ciencias.pt

http://www.cienciaviva.pt/home/

General information

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Moving around
The Tutorial sessions and the Symposium sessions will take place at theauditorium of the Pavilhão do Conhecimento science museum, near the Oriente
metro station (10 minutes walking slowly from the station). There is a map in
the next page showing the surroundings of the venue.
The Welcome cocktail and the Public lecture will take place at the Academia
das Ciências de Lisboa. If you walk from the metro stop Baixa–Chiado, youwill need less than 20 minutes to arrive there walking slowly. Make sure you
leave at the metro at the Chiado exit (there are several escalators to take). You
can find a map indicating the path to follow from the Chiado exit in two pages.
The Conference dinner will take place at the Zambeze restaurant. You canfind a map to arrive there from the Baixa–Chiado metro station (10 minutes
walking) in three pages. To enter the restaurant, bring your conference badge!
Finally, four pages from now, you can find a map of Lisbon’s metro.
Alternatively, you can find interactive maps in the following links:
Pavilhão do Conhecimento: http://bit.ly/1vnJvgU
Academia das Ciências de Lisboa: http://bit.ly/1jrznjo
Zambeze restaurant: http://bit.ly/1lBHOFQMetro lines: http://www.metrolisboa.pt/eng/

Internet
Free and open internet connection is available at the Symposium venue.
You can use any of the following two wifi networks to connect:
cv public
cv auditorio

Lunch
There are several restaurants around the Symposium venue. For those in ahurry, there are also fast food options almost at the door. The map indicatessome regions where you can find restaurants for your lunch.

Secretary desk
The secretary desk is located at the entrance of the Symposium venue.
It will be open during the whole conference. You can also contact it at
sccc21@sim.ul.pt. If you need any kind of assistance (ex. taxi, hospital,
language), do not hesitate in contacting us.

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Map: Pavilhão do Conhecimento

Restaurants

METRO

Restaurants (Mall)

Restaurants

IAUS306

Restaurants

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Rua da Academia dasCiências

Rua do Século

Map data ©2014 3D Cities SA, Google

Rua do Loreto

100 m

Map: Academia das Ciências

Baixa/Chiado
Metro (Baixa exit)

Restaurante Zambeze
Calçada Marquês de Tancos
Edifício EMEL
T: 218877056

ZAMBEZERESTAURANT

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Map: Conference dinnerIAU Symposium 306 – SCCC21, 2014 — 12/130

Academia das Ciências

Airport

IAUS306

Map: Lisbon metro network

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Useful contacts
Emergencies (police and medical)

The European Emergency Number is: 112
This number can be called from any phone, including mobile phones without
a SIM card. Calls are answered within 6 seconds.
Taxi services

Taxis in Lisbon are relatively cheap compared to other cities in Europe. A trip
from the Airport to the city center (or vice-versa, as it should be a bijection,and thus invertible!) should cost you between 8 and 13 euros, depending on
where you are heading to.1
Teletaxis: +351–218 111 111
Hospitals

Hospital da Luz (http://www.hospitaldaluz.pt/en/): +351–217 104 400
British Hospital: +351–217 213 410 / 1
Hospital St. Maria: +351–217 805 000 / +351–217 805 111
Copy and print services

PrintWork (printwork@printwork.pt): +351–218 967 185
Printpoint (expo@printpoint.pt): +351–218 951 122
Conference dinner restaurant

Zambeze restaurant: +351–218 877 056

In case of emergencies: If you are in a real emergency situation (e.g life
threatening), you can contact the LOC chair directly at: +351–916 185 386.

1 A trip between the airport and the Expo region, where the Symposium venue is located,should cost from 8 to 10 euros. But note that you can easily arrive at Expo from the airport using
the metro as well – just make sure you leave at the Oriente station.

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Conference Programme
In a nutshell
The Symposium sessions will take place at Pavilhão do Conhecimento. It will
open the doors all days at 8h30, except on the Sunday, when it will open at
10h00. Note that the Welcome cocktail and the Public lecture will take placeat Academia das Ciências de Lisboa.
Sunday10h00 :: Registration starts
10h20 – 17h00 :: Tutorials
18h00 – 20h00 :: Welcome cocktail
Monday9h00 – 18h10 :: Symposium sessions: Bayes & CMB
18h10 – 18h40 :: IAA Cosmostatistics Working Group meeting
Tuesday

9h00 – 18h10 :: Symposium sessions: Bayes, Weak-Lensing & Large Scale
Structure
19h30 – 20h15 :: Public lecture
Wednesday

9h00 – 18h10 :: Symposium sessions: Data, Sparsity & Statistics
18h10 – 18h40 :: Poster session
20h00 :: Conference dinnerThursday9h00 – 17h10 :: Symposium sessions: Radio, Supernovae & Joint probes
17h10 :: Symposium closes

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Sunday, 25th May
This is the first day of IAUS306-SCCC21! Note that everyone is welcome
to register in the symposium at the secretary desk at any moment during the
Sunday, but in order to participate in the tutorials you must have registered.
10h00

10h00
10h30

The venue opens for participants

Registration opens
Statistical Methodology and R

Eric Feigelson

Sparsity 1: Blind Source SeparationJérôme Bobin

12h00

Lunch

13h00

Statistical Methodology and R

Eric Feigelson

Sparsity 2: Sparse regularization

François Lanusse

of inverse problems
Bayesian Cosmology

Daniel Mortlock &Andrew Jaffe

17h00

Session ends

17h30

18h00 – 20h00

The venue closes for participants

Welcome cocktail at Academia das Ciências

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Monday, 26th May
This is the second day of IAUS306-SCCC21! If you did not registered on
the Sunday, you can register at any moment during the entire week. Nevertheless, note that you will not be allowed to enter the Symposium before theregistration, so please arrive early. The doors are open from 8h30, so you canregister before the Symposium starts.
On Monday you also have a free night, so you can enjoy the city as you
please! If you need any help, let the LOC know.
8h30

9h00

The venue opens for participants

Welcome messages

Session: Bayes
9h20

The Advantages of “Shrinkage Estimates” inAstronomyDavid van Dyk

10h05

Bayesian model comparison in cosmology

Daniel Mortlock

10h25

Coffee break

10h50

Nonparametric estimation and measurement
errorsAurore Delaigle

11h35

Phase-space reconstruction of the cosmologicallarge scale structure

Francisco-Shu
Kitaura11h55

What we talk about when we talk about fields

Ewan Cameron

12h15

Lunch

Session: CMB
14h00

Cosmic Microwave BackgroundGraça Rocha

14h45

Detection of B-mode polarization at at degree
angular scales using BICEP2

Denis Barkats

15h25

Spin scale-discretised wavelets on the sphere
for the analysis of CMB polarization

Jason McEwen

15h45

Coffee breakIAU Symposium 306 – SCCC21, 2014 — 18/130

Session: CMB
16h15

Anomalies

Hiranya Peiris

16h50

Transforming Data into Science: Planck data
and the CMB non-Gaussianity

Anna Mangilli

17h10

Applications of the Gaussian Kinematic
Formula in Cosmology

Yabebal Fantaye

17h30

Detectability of multi-connected topologies

Ophélia Fabre

17h50

Cosmology with photometric quasars

Boris Leistedt

18h10

18h10 – 18h40

Session ends

Meeting of the IAA Working Group

Hosted byon Cosmostatistics

Rafael de Souza

18h50

The venue closes for participants

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Tuesday, 27th May
In this third day of IAUS306-SCCC21, besides the Symposium sessions,
you are also welcome to attend Alex Szalay’s Public Lecture on the Fourth
Paradigm of Science and learn about its impact from Genes to Stars!

8h30 The venue opens for participantsSession: Bayes
9h00

Massive parameter estimation

BenjaminWandelt

9h45

Bayesian Photometric Redshifts v2.0

Txitxo Benı́tez

10h20

Coffee break

10h50 Statistical challenges
cosmology

in

weak

lensing Masahiro
Takada11h35 The Potential of Likelihood-Free Inference of Michael Vespe
Cosmological Parameters with Weak Lensing
Data
11h55 The probability distribution of ellipticity: impli- Massimo Violacations for weak lensing measurement
12h15

Lunch

Session: Large Scale Structure
14h00 Precision cosmology, accuracy cosmology and Licia Verdestatistical cosmology
14h45 Errors on errors - estimating cosmological Benjaminparameter covariance
Joachimi
15h05 Bayesian large-scale structure inference: initial Florent Leclercq
conditions and cosmic voids
15h25 Marked point processes for morpho-statistical Radu Stoica
characterization of the cosmic web
15h45

Coffee breakIAU Symposium 306 – SCCC21, 2014 — 20/130

16h10 Low/High Redshift Classification of Emission Viviana
Line Galaxies in the HETDEX survey
Acquaviva
16h30 Distribution of maximal luminosity of galaxies Eniko Regosin the Sloan Digital Sky Survey
16h50 Bootstrap: a valid alternative for clustering Pablo
analyses?
Arnalte-Mur
17h10 Detection of a Supervoid Aligned with the Cold András Kovács
Spot of the Cosmic Microwave Background17h30 Sufficient observables for galaxy surveys

Julien Carron

17h50 Improved distance measurements with recon- Eyal Kazin
structed WiggleZ
18h10

Session ends

18h30 The venue closes for participants

19h30 From Genes to Stars: the Fourth Paradigm of Science Alex Szalay
Public lecture at Academia das Ciências de Lisboa

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Wednesday, 28th May
In this fourth day of IAUS306-SCCC21, besides the Symposium sessions,the poster session will also take place. Also, do not forget the conference
dinner, and remember that you must bring your conference badge to haveaccess to the restaurant.

8h30 The venue opens for participantsSession: Data
9h00

Statistics of Fields

SabinoMatarrese

9h45

Machine-learning in astronomy

Mike Hobson

10h20

Coffee break

10h50 Overwhelmingly large datasets

Alex Szalay

11h35 Machine Learning in Astronomy

Lise du Buisson

11h55 Euclid space mission: a cosmological challenge Roberto
for the next 15 years
Scaramella
12h15

Lunch

Session: Sparsity
14h00 Sparsity

Jalal Fadili

14h45 Estimating the distribution of Galaxy Morpholo- Giuseppe Vinci
gies
15h05 PURIFY: a new approachinterferometric imaging

toradio- Yves Wiaux

15h25 PRISM: Sparse Recovery of the Primordial Paniez PaykariPower Spectrum
15h45

Coffee break

Session: Statistics
16h15 Sparsity-based CMB reconstructionJérôme BobinIAU Symposium 306 – SCCC21, 2014 — 22/130

16h50 Maximum-likelihood determination of the Jonathan
galaxy LF, evolution and selection function
Loveday
17h10 Transformatively Taming Spatial Statistics

Mark Neyrinck

17h30 Clipping the Galaxy Power Spectrum in GAMA Fergus Simpson
17h50 How accurate are measurements of primordial Nina Rothnon-Gaussianity parameters from large-scale
structure?
18h10

Session ends

18h10 – 18h40 Poster session

19h00 The venue closes for participants

20h00 Conference dinner at Restaurante Zambeze

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Thursday, 29th May
Unfortunately, there is a last day in all Symposia! We planned this last
day to be a bit shorter so you can catch your flights if you are leaving Lisbon.
On the other hand, if you are staying a bit longer, and if you are willing to,
you can try to get tickets for the Rolling Stones concert (also the last one?) or
Beethoven’s 9th Symphony (surely not the last one) concert!

8h30 The venue opens for participantsSession: Radio
9h00

21cm Cosmology

Mario Santos

9h45

Beyond confusion: A Bayesian P(D) analysis Jasper Wallof the Deepest Radio Survey

10h05 Bayesian Inference for Radio Observations Michelle(BIRO) – A new technique for simultaneously Knights
estimating instrumental errors and science parameters directly from radio visibility data
10h25

Coffee break

Session: Supernovae
11h00 Supernovae Cosmology

Mario Hamuy

11h35 Testing the consistency of different supernova Natallia
surveys
Karpenka
11h55 Improved Kernel Principal Component Analysis Emille Ishida
for Supernova Photometric Classification
12h15

Lunch

Session: Joint probes
14h00 Combining Probes

Anais Rassat

14h45 Cross Correlation between Astrophysical and Federico
Cosmological Datasets: Precision of Covariance Bianchini
Estimation and Impact on the Signal Detection
SignificanceIAU Symposium 306 – SCCC21, 2014 — 24/130

15h05 Information Gains from Cosmic Microwave Sebastian
Background Experiments
Seehars
15h25 How well can the evolution of the scale factor Sandro Vitenti
be reconstructed by the current data?
15h45

Coffee break

16h10 Cosmology with photometric surveys & an Filipe Abdalla
update on the Dark Energy Survey
16h30 Statistics and the Future of Astronomy

Joseph Hilbe

16h50 Closing remarks from a Cosmologist

Andrew Jaffe

17h10

IAUS306 – SCCC21 ends

18h00 The venue closes for participantsTutorials
The IAU Symposium 306 – Statistical Challenges in 21st Century Cosmology
includes a full tutorial day, with the goal to present advanced statistical methods, and to demonstrate how one may use readily available codes, relevant for
new and exciting applications in Cosmology and Astronomy!
These tutorials will take place on the Sunday, 25th May 2014, at thePavilhão do Conhecimento.
For the most up to date information, please check:
http://www.sccc21.ul.pt/tutorials.html

Statistical Methodology and R
Eric Feigelson
Pennsylvania State University, USA

The fields of astronomy and statistics were, in past centuries, essentiallymerged but they diverged in the 20th century. The result today is that astronomers are poorly informed about the wealth of powerful methodologies
developed by statisticians, and statisticians know little about contemporary
challenges in modern astronomy. Statistics is needed for: understanding astronomical images, spectra and lightcurves; inference about underlying populations from limited samples; linking astronomical observations to astrophysicaltheories; and more. Fortunately, a very large, integrated and user friendly
public domain software system has emerged in recent years to implement
modern methods. R with its > 5000 add-on CRAN packages has ∼ 100, 000
statistical functionalities with extensive graphics, links to other languages, andmore. Over 100 textbooks and extensive on-line support provide guidance forthe sophisticated R user.

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The tutorial will be in five segments:• Introduction to astrostatistics and statistical computing (lecture)• Basic data analysis with R• Density estimation (data smoothing) with R and CRAN
• Multivariate clustering and classification with R and CRAN
• Spatial point processes with R and CRAN

Sparsity 1: Blind Source SeparationJérôme Bobin
CEA – Commissariat à l’Énergie Atomique – Saclay, FranceThis tutorial will give essential insights into the use of blind source separation methods in astrophysics with a particular application in cosmology.
Multichannel or multiwavelengths data are more than common in the field ofastronomy and astrophysics. Analyzing this particular multidimensional datarequires specific tools; these data are commonly modeled as the superposition of elementary components or sources which generally do not contribute
similarly in each observation channel. The aim of blind source separation isto estimate simultaneously the sources and their contribution weight in eachof these channels. Think for instance of a symphonic concert recorded withdifferent microphones (i.e. the observation channels) and imagine the problem
of separating out the contribution of each individual instrument from thiscacophony. This tutorial will review the basics of blind source separation as
well as more recently introduced sparsity-based techniques. An application to
WMAP data will also be at the menu.

Sparsity 2: Sparse regularization of inverse
problems
François Lanusse
CEA – Commissariat à l’Énergie Atomique – Saclay, France

In this tutorial we will introduce powerful sparse regularization techniques
to address ill-posed linear inverse problems. For such problems, the inverse
operator is potentially unbounded and there is no unique solution in the absence

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of prior. As an example of this class of problems we will be introducing
the specific case of deconvolution which is a recurring problem in signal
processing and has been extensively covered for the past 30 years.
The aim of this tutorial is to have a hands on experience with sparse
regularization techniques and with the selection of appropriate dictionaries
to address the deconvolution problem. Several practical problems will be
proposed illustrating the strength of the sparsity prior.

Bayesian Cosmology
Daniel Mortlock & Andrew Jaffe
Imperial College London, United Kingdom

Most researchers will at some point be required to perform some form of data
analysis. This may be anything from simple line-fitting, through parameter
estimation, to complex and computationally-demanding sampling for model
selection on large datasets. Bayesian inference is a practical methodology forsolving such problems that is built up from the fundamentals of probability
theory.
The purpose of this short course is to provide understanding of Bayesiandata analysis, especially in a cosmological context, concentrating on theunderpinnings of probability theory, Bayes’ theorem itself, and its application
to the estimation of parameters. To apply these ideas, the tutorial will include
discussion problems and a hands-on workshop implementing Monte Carlo
Markov Chain (MCMC) samplers.

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Keynote talks

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The Advantages of “Shrinkage Estimates” inAstronomyDavid van Dyk
Imperial College London, United Kingdom

Astronomical studies often involve samples or populations of exchangeable
sources. The parameters describing such sources can either be fit to each source
in a separate analysis, or all be fit in a single unified analysis. The latter strategy
allows us to incorporate the population distribution into a coherent statisticalmodel and exhibits district statistical advantages. In particular, objects withsmaller error bars and well-constrained parameters allow us to estimate thepopulation distribution, which in turn can be used to better estimate the weaklyconstrained parameters associated with objects with larger error bars. The
fitted values of such weakly-constrained parameters will “shrink towards” thepopulation mean, and are thus called “shrinkage estimates”. This talk describes
both frequentist and Bayesian advantages of shrinkage estimates and illustrates
how they can be used in astronomy. In the first of two examples we estimate
the absolute magnitudes of a SDSS sample of 288 Type Ia Supernovae using
shrinkage estimates and illustrate how they differ from naive estimates. In thesecond example, we use photometric magnitudes of three galactic halo whitedwarf stars to simultaneously obtain shrinkage estimates of the stellar ages
and an estimate the age of the halo.

Nonparametric estimation and measurement errors
Aurore Delaigle
University of Melbourne, Autralia

In this talk I will introduce nonparametric methods for estimating curves(density, regression) nonparametrically, that is, without making parametricassumptions about the shape of the curves. Popular nonparametric methods
include kernel smoothing approaches and spline techniques.
In many cases, the data that are available can only be observed withmeasurement errors, and techniques have to be developed that take this noise
into account. I will introduce nonparametric methods to this problem, in cases
where the error distribution is either known or unknown. In the statistics
literature, this inverse problem is often refereed to as as a deconvolution
problem.

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If time permits I will also introduce methods which mix parametric andnonparametric approaches, and nonparametric methods which enable one toincorporate some a priori knowledge about the curve, such as for example
monotonicity of the curve.

Cosmic Microwave BackgroundGraça Rocha
Jet Propulsion Laboratory, California Institute of Technology, USA

In this talk I will give an overview of the progress made in Cosmology and in
our understanding of the Universe by observing and analyzing the anisotropies
in the Cosmic Microwave Background (CMB) radiation. The increase of the
CMB data volume required the application and development of sophisticatedstatistical approaches as well as optimized computational implementations ofdata analysis and parameter inference.
These techniques and algorithms enabled an optimal scientific exploitationof the CMB data resulting in major scientific breakthroughs. In this talk I will
give an overview of these scientific advances along with the corresponding
statistical and algorithmic developments that made it possible.
Special mention will be given to the statistical and algorithmic implementation challenges encountered when analyzing Planck data and resulting major
scientific findings. An overview of other experiments and recent cosmologicalresults will be also given including the recent BICEP2 results.

Massive parameter estimation
Benjamin Wandelt
Institut d’Astrophysique de Paris, FranceInstitut Lagrange de Paris, France
University of Illinois at Urbana-Champaign, USA

The goal of cosmostatistics is to derive quantitative insights into the outstanding puzzles of cosmological physics from astronomical data sets. How did
the Universe begin? What are the properties of dark energy? How did thelargest structures in the Universe form? In many cases these inferences involve
non-Gaussian and/or non-linear data models, and involve tens of millions ofparameters. I will describe two solution approaches to analysis of galaxy
surveys: one based on Bayesian forward modeling, and the other using computational geometry methods that extract features from the observed galaxy

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distribution. These approaches have led to the first quantitative reconstructionsof the cosmological initial conditions from galaxy surveys, the discovery of auniversal profile for cosmic voids, the development of new cosmological tests,
and an exceptionally detailed characterization the cosmic web underlying theobserved galaxy distribution.

Statistical challenges in weak lensing cosmology
Masahiro Takada
Kavli Institute for the Physics and Mathematics of the Universe (IPMU)
Todai Institutes for Advanced Study (TODIAS) – University of Tokyo, Japan

There are various ongoing and upcoming wide-area galaxy surveys aimed atachieving a high-precision measurement of weak gravitational lensing due tolarge-scale structure in the Universe. Even though the initial density field isnearly Gaussian, the nonlinear gravitational clustering in structure formationinduces substantial non-Gaussian features in the weak lensing field. Hence,
the most conventionally used two-point correlation function or the Fouriercounterpart, the power spectrum, can no longer extract the full information.
Thus, which statistical method to extract the full information, more generally
from large-scale structure probes, is still an open question. In this talk, I review
the statistical challenges in the weak lensing cosmology, and discuss whether
or not we can recover (or perhaps cannot recover?) the information content
of the original Gaussian field, by combining different statistical observables
we can obtain from galaxy surveys. Hope this talk will raise some open
issues/questions, then followed by discussion during the conference.

Precision cosmology, accuracy cosmology andstatistical cosmology
Licia Verde
Universidad de Barcelona, Spain & University of Oslo, Norway

The avalanche of data over the past 10-20 years has propelled cosmology inthe “precision era”. The next challenge cosmology has to meet is to enter theera of accuracy. Because of the intrinsic nature of studying the Cosmos and forthe sheer amount of data both available and coming soon, the only way to meetthese challenges is by developing suitable and specific statistical techniques. I
will outline some open challenges and discuss some specific examples.

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Statistics of Fields
Sabino Matarrese
Università degli Studi di Padova, Italy

I will review both general problem of the statistics of the primordial curvature
perturbation field in cosmology. The search for non-Gaussian signatures incosmological perturbations, originated from inflation in the early Universe
will be discussed both from the theoretical point of view and in connection
with constraints coming from recent observations and future prospects forobserving/constraining them.

Overwhelmingly large datasets
Alex Szalay
The Johns Hopkins University, USA

Astronomy surveys are collecting data from hundreds of millions to billions
of celestial objects. These data are accessible through large public databases.
These surveys are taken at different wavelengths, and one needs to performstatistical cross-matches to associate the detections with real physical objects.
During the statistical analyses of the data astronomers are realizing that withbillions of objects statistical noise is less of a problem, but systematic errors
are becoming more important. We will discuss various ways, like optimal
subspace filtering, of how the known systematic errors can be removed. We
also explore the scaling behavior of different algorithms, and conclude that weneed increasingly use streaming versions of the different statistics. Finally, as
the amount of data collected is going to explode further, it is timely to consider
how we could collect less, by focusing on parts of the data with the highest
information content. The talk will present examples of these challenges.

A Sparsity Tour of Inverse Problems andApplications
Jalal Fadili
Ecole Nationale Supérieure d’Ingénieurs de Caen, France

In the last decade sparsity has emerged as one of the leading concepts in a wide
range of data processing applications (restoration, inverse problems, feature extraction, source separation, compression, to name only a few). Sparsity-based

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methods also enjoy solid theoretical guarantees. Its domains of application
are incredibly wide, including imaging and signal processing in astronomy,
physics and the natural sciences etc. In this talk, I’ll explore several classicalinverse problems for which sparsity offers a unified and grounded framework
to analyze and solve. Both theoretical and practical issues will be discussed
and exemplified.

21cm Cosmology
Mario Santos
University of the Western Cape, South Africa

The “21 cm” line from neutral hydrogen provides an effective way to trace
the matter content of the Universe, mapping its large scale structure in three
dimensions and allowing exquisite constraints on cosmology. This can bedone using the line to detect large numbers of galaxies or by using the novel
technique of “HI intensity mapping” which relies on measuring the intensityof the redshifted 21cm line over the sky and a range of redshifts without
the requirement to resolve individual galaxies. HI IM surveys can provide
powerful tests of dark energy models and modifications to General Relativity
as well as probe physics on ultra-large scales. I will describe the basics ofthe HI cosmological signal and what can be achieved with future surveys andthen address the statistical challenges that we will need to face with these hugedatasets, in particular the foreground cleaning methods and the calibration
issues involving measurements with radio telescopes.

Combining Probes
Anais Rassat
EPFL - École Polytechnique Fédérale de Lausanne, Switzerland

With the advent of wide-field surveys, cosmology has entered a new golden
age of data where our cosmological model and the nature of dark universe
will be tested with unprecedented accuracy, so that we can strive for highprecision cosmology. Observational probes like weak lensing, galaxy surveys
and the cosmic microwave background as well as other observations will all
contribute to these advances. These different probes trace the underlying
expansion history and growth of structure in complementary ways and canbe combined in order to extract cosmological parameters as best as possible.

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With future wide-field surveys, observational overlap means these will trace
the same physical underlying dark matter distribution, and extra care must be
taken when combining information from different probes. Consideration ofprobe combination is a fundamental aspect of cosmostatistics and important toensure optimal use of future wide-field surveys.

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Invited talks

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Detection of B-mode polarization at degree angularscales using BICEP2
Denis Barkats1 on behalf of the BICEP2 collaboration
1. ALMA - ESO, European Southern Observatory

BICEP2 recently reported a detection of B-modes in the CMB polarization atdegree angular scales. This B-mode pattern is widely interpreted as the likely
signature from primordial gravitational waves, consistent with those predicted
to arise in the first 10− 34 seconds of the history of the universe, stretched fromquantum to classical scales by the exponential expansion of cosmic inflation.
BICEP2 is a CMB polarimeter that was specifically designed to search forthe elusive signal from inflationary gravitational waves in the B-mode power
spectra around l = 80. BICEP2 has accumulated 3 years of data from the South
Pole from 2010 to 2012, integrating continuously on a low-foreground regionof effective size 1% of the whole sky. I will describe the experimental strategy,
tests for foreground or systematics contamination, and results in the map andpower spectra. The reported B-mode spectrum is well fit by a lensed-LCDM
plus tensor theoretical model with tensor/scalar ratio r = 0.20 + 0.07 − 0.05
with r = 0 is strongly disfavored.

Anomalies
Hiranya Peiris
University College London, United Kingdom

Anomaly detection drives scientific discovery - it is correlated with the cuttingedge of the research frontier, and thus inevitably involves small signal-tonoise. In astronomy, the prevalence of systematics – both “known unknowns”
and “unknown unknowns” – combined with increasingly large datasets, theprevalence of ad hoc estimators for anomaly detection, and the “look elsewhere”
effect, can lead to spurious false detections. I will argue that anomaly detection
leading to discoveries of new (astro)physics needs a combination of physicalunderstanding, careful experimental design to avoid confirmation bias, andself-consistent statistical methods. I will illustrate these points with several
concrete examples from cosmology.

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Bayesian Photometric Redshifts v2.0
Txitxo Benı́tez
Instituto de Astrofı́sica de Andalucı́a – CSIC, Spain

Photometric Redshifts have become crucial for large field (> 5000 sq.deg) Astrophysical Surveys, whether as their main technique or as a preliminary target
selection step. The application of a rigorous Bayesian approach to photometricredshift estimation helps to solve many of the practical problems arising in
the design and implementation of such surveys. Using a properly calibrated
redshift/magnitude prior is essential to produce posteriors p(z) for individual
galaxies which not only are more compact, but also describe accurately the fullsample redshift distribution n(z). In addition, a Bayesian framework enables
an easy characterisation of the spread of p(z) via quality indicators as the odds
ratio. This feature is key to design filter systems which maximise photo-z
depth and precision, an overlooked issue since traditional broad-band, contiguous filter systems are far from optimal for redshift estimation. These photo-z
quality indicators can be employed to efficiently extract subsamples with very
high precision and purity from lower average quality datasets. This is essential
for problems like radial BAO measurements, which require dz/(1 + z) < 0.3%.
I present the latest version of the BPZ code, which includes new priors and aempirically calibrated template library.

Machine-learning in astronomy
Mike Hobson
University of Cambridge, United Kingdom

In modern astronomy, one is increasingly faced with the problem of analysing
large, complicated and multidimensional data sets. Such analyses typically
include tasks such as: data description and interpretation, inference, patternrecognition, prediction, classification, compression, and many more. One wayof performing such tasks is through the use of machine learning methods. An
intuitive and well-established approach to machine learning, both supervisedand unsupervised, is based on the use of artificial neural networks (NNs), which
consist of a group of interconnected nodes, each of which processes information that it receives and then passes this product on to other nodes via weighted
connections. In particular, I discuss the first public release of the generic neuralnetwork training algorithm, called SkyNet, and demonstrate its application to anumber of toy problems, and to astronomical problems focusing on the recov-

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ery of structure from blurred and noisy images, the identification of gamma-ray
bursters, and the compression and denoising of galaxy images. The SkyNet
software, which is implemented in standard ANSI C and fully parallelisedusing MPI, is available at http://www.mrao.cam.ac.uk/software/skynet/.

Sparsity-based CMB reconstructionJérôme Bobin, Florent Sureau & Jean-Luc Starck
CEA – Commissariat à l’Énergie Atomique – Saclay, France

The reconstruction of an accurate map of the Cosmological Microwave Background radiation (CMB) from multi-wavelength surveys such as Planck is
crucial for cosmology. However, this turns to be a challenging statisticalproblem as the CMB can hardly be measured directly and has to be disentangled from various sources of foreground emissions using so-called component
separation methods. We will present a radically new component separation
methods which makes profit of the natural sparsity of astrophysical components in the wavelet domain. In contrast to state-of-the-art methods proposedso far in astrophysics, the use of sparsity allows for a much better modelingof complex inhomogeneous components that mainly originate from galactic emissions. This sparsity-based method, coined LGMCA, has recently
provided a very clean full-sky estimate of the CMB map with particularly
low foreground contamination and without detectable remainings of thermal
Sunyaev-Zel’Dovich effect.

Supernovae Cosmology
Mario Hamuy
Universidad de Chile, Chile

Type Ia Supernovae have played a central role in the measurement of the
expansion history of the Universe and the determination of fundamental cosmological parameters, since the discovery of acceleration and dark energy in1998 (Nobel Prize in Physics 2011). However, the nature of dark energy remains a mystery and understanding its origin is to be of paramount importance,
as it offers the promise of revealing new physics. The answer to this question
will arise in part from the analysis of large volumes of data emanating frommassive wide-field surveys, through different complementary techniques suchas weak lensing, large scale structure, galaxy clusters, and Type Ia supernovae

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themselves. The supernova method will require the measurement of precise
and accurate distances over a wide range in redshifts. Achieving such goal will
require careful analysis of large statistical samples of supernova light curves
and a thorough understanding of the systematic errors that could bias ourconclusions. Here I summarize the main challenges that need to be addressedin order to measure reliable distances derived from Type Ia supernovae andI will discuss the prospects for the use of Type II supernovae as independent
cosmological probes in the effort to understand dark energy.

Statistics and the Future of Astronomy
Joseph M. Hilbe
Arizona State University & Jet Propulsion Laboratory, USA

Given the generic definition of statistics, it is clear that astronomers haveengaged in statistical analysis of some variety since astronomy first emerged
as a science. However, from the early nineteenth century until the beginningof the twenty-first the two disciplines have been somewhat estranged – there
has been no formal relationship between the two. This has now changed, as isevidenced by this symposium. The challenge for us to come is in establishing how statisticians and astronomers relate in developing the discipline ofastrostatistics. Astronomers currently recognize that statistics is driving many
areas of cosmology and astrophysics, and will likely play an important, if notleading, role in our future understanding of the structure and foremost featuresof our universe. I shall propose a direction for how the discipline can progressin both the short term as well as for future generations of astrostatisticians.

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Contributed talks

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Bayesian model comparison in cosmology
Daniel Mortlock & Alex Khanin
Imperial College London, United Kingdom

Bayesian inference provides a self-consistent method of model comparison,provided that i) there are at least two models under consideration and ii)
all the models in question have fully-specified and proper parameter priors.
Unfortunately, these requirements are not always satisfied in astronomy andcosmology: despite the existence of exquisitely-characterised measurements
and quantitative physical models (i.e., sufficient to compute a believable
likelihood), these models generally have parameters without well-motivatedpriors, making completely rigorous model comparison a formal impossibility.
Still, huge advances have been made in cosmology, in particular, in the last few
decades, implying that model comparison (and testing) is possible in practiceeven without fully specified priors. I will describe a method for Bayesianmodel comparison that can be used when prior information on parameters is
weak, showing its application to the problem of ultra-high energy cosmic ray
origins.

Phase-space reconstruction of the cosmologicallarge scale structure
Francisco-Shu Kitaura
Leibniz-Institut für Astrophysik Potsdam (AIP), Germany

I present an approach to recover the phase-space distribution from galaxy
redshift surveys. This method is based on a Bayesian approach and includes animproved perturbation theory approach to model structure formation including
nonlinear and stochastic galaxy biasing. I present the analysis of the 2-point,
3-point statistics and the bispectrum and quadrupole in redshift space showingthat the method is accurate down to a few Mpc.

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What we talk about when we talk about fields
Ewan Cameron
University of Oxford, Department of Zoology, United Kingdom

It often occurs in application of the physical sciences that we wish to makestatistical inferences as to the nature of some unknown signals over continuous
space (i.e. “fields”) given a limited set of observational data. Examples
include: mapping the large-scale distribution of mass in the local universe
and inferring its power spectrum based the observed distribution of brightgalaxies; or predicting the volume of exploitable minerals within a particularregion given a series of drill core measurements at irregularly spaced test sites.
In this talk I will review the Bayesian approach to this problem on both thediscrete (finite pixel grid) and continuous (infinite dimensional signal) problem
spaces in which our inference challenge may be defined, and I will describe anumber of important mathematical subtleties key to a robust treatment of thisdichotomy (i.e., Kolmogorov’s extension theorem, convergence in distribution
vs convergence in mean, Prokhorov’s theorem, and the nature of stochastic
process priors). I will then give a brief overview of various contemporary
Bayesian techniques for exploring the field space posterior (i.e., Hamiltonian
MCMC, and the Integrated Nested Laplace Approximation) and I will discuss
a number of technical difficulties for implementation of these methods (e.g.
the problem of joint simulation for gauging large scale uncertainty in the caseof high resolution spatial grids).
This work will draw on my diverse, cross-disciplinary experience in astronomy, statistics, and epidemiology/zoology.

Spin scale-discretised wavelets on the sphere forthe analysis of CMB polarization
Jason D. McEwen1 , Martin Buettner1 , Boris Leistedt1 , Hiranya V. Peiris1 ,Pierre Vandergheynst2 & Yves Wiaux3
1. University College London, United Kingdom
2. EPFL - École Polytechnique Fédérale de Lausanne, Switzerland
3. Heriot-Watt University, United Kingdom

We construct a new spin scale-discretized wavelet transform on the sphere that
supports a directional and steerable wavelet analysis of spin signals. Scalediscretized wavelets allow in practice the exact synthesis of a signal from its
wavelet coefficients. We present new exact and efficient algorithms to computeIAU Symposium 306 – SCCC21, 2014 — 46/130

the spin scale-discretized wavelet transform of band-limited signals on thesphere up to high band-limits. Finally, we highlight the application of spin
scale-discretized wavelets to analysis polarized CMB data, which is a spin-2
signal on the sphere.

Transforming Data into Science: Planck data and the
CMB non-Gaussianity
Anna Mangilli1 on behalf of the Planck Collaboration
1. Institut d’Astrophysique de Paris, France

Studying the non-Gaussianity (NG) of the Cosmic Microwave Background(CMB) is an extremely powerful tool to investigate the properties of the very
early Universe, complementary e.g. to the search of B-modes in the CMB
polarization. The Planck nominal mission CMB maps yielded unprecedented
constraints on primordial non-Gaussianity. Thanks to Planck’s high sensitivity,
we also got the first evidence of the “late-time” non-Gaussianity arising fromthe Lensing-Integrated Sachs Wolfe (ISW) cross correlation. In this talk I
will give details on the Planck data analysis and I will discuss the theoretical
implications of the results.

Applications of the Gaussian Kinematic Formula in
Cosmology
Yabebal Fantaye
Università degli Studi di Roma Tor Vergata, Italy

Minkowski Functionals (MFs) have been used extensively in Cosmology, forinstance to test for Gaussianity and Isotropy of the Cosmic Microwave Background maps. Although some analytical predictions of MFs for a Gaussian
and mild non-Gaussian fields are known in the astrophysical community, much
more refined results can be provided exploiting recent advances in the mathematical literature. In this work, we exploit the so-called Gaussian kinematicformula by J.Taylor and R.Adler to provide exact analytic expressions for the
expected values of MFs in multipole and needlet space. Our results cover
Gaussian fields and their power transformations, for instance quadratic andcubic polynomials; the latter can be used to obtain local estimates of the angular power spectrum, local estimates of nonGaussianity, tests for anisotropies
and asymmetries and many other applications. We also show how to derive

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exact and efficient analytical predictions on the expected values of MFs forspherical random fields on a cut sky, such as those arising from WMAP and
Planck masks. All our theoretical results are found to be in extremely good
agreement with CMB simulations under realistic experimental conditions.

Detectability of multi-connected topologies
Ophélia Fabre, Simon Prunet & Jean-Philippe Uzan
Institut d’Astrophysique de Paris, France

The global shape, or topology, of the universe is not constrained by the equations of General Relativity, which only describe the local universe. As aconsequence, the boundaries of space are not fixed and topologies different
from the trivial infinite Euclidean space are possible. The cosmic microwave
background (CMB) is the most efficient tool to study topology and test alternative models. Multi-connected topologies, such as the 3-torus, are of greatinterest because they are anisotropic and allow us to test a possible violationof isotropy in CMB data.
In this presentation, the signature of a multi-connected topology on theproperties of the CMB anisotropies is revisited. We show that the correlation
function of the coefficients of the expansion of the temperature and polarization
anisotropies in spherical harmonics encodes a topological signature. Thissignature can be used to distinguish an infinite space from a multi-connected
space on sizes larger than the diameter of the last scattering surface.
With the help of the Kullback-Leiber divergence, we set the size of theedge of the biggest distinguishable torus with CMB temperature fluctuations
and E-modes of polarization to 1.15 times the diameter of the last scattering
surface. We also notice that CMB temperature fluctuations allow us to detect
universes bigger than the observable universe, whereas E-modes are more
efficient that temperature fluctuations to detect universes smaller than theobservable universe.

Cosmology with photometric quasars
Boris Leistedt & Hiranya Peiris
University College London, United Kingdom

Quasars are highly biased tracers of the large-scale structure and therefore
powerful probes of the initial conditions and the evolution of the universe.

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However, current spectroscopic catalogues are too small for studying theclustering of quasars on large-scales and over extended redshift ranges. Henceone must resort to photometric catalogues, which include large numbersof quasars identified using imaging data but suffer from significant stellar
contamination and systematic uncertainties. We will present a detailed analysisof the clustering of photometric quasars from the Sloan Digital Sky Survey,
and demonstrate that the effects of observational systematics can be robustly
eliminated with appropriate techniques. In particular, we will show how to
mitigate the impact of spatially varying systematics, such as calibration andobserving conditions, using an extended mode projection approach whencorrelating the quasar samples. We will finally present constraints on thequasar bias in the range 0.5 < z < 3.5 derived using an optimal estimator that
exploits both the clustering of the quasar samples and their cross-correlation
with CMB lensing.

The Potential of Likelihood-Free Inference of
Cosmological Parameters with Weak Lensing Data
Michael Vespe
Carnegie Mellon University, USA

In the statistical framework of likelihood-free inference, the posterior distribution of model parameters is explored via simulation rather than direct
evaluation, permitting inference on models where the likelihood function isanalytically intractable. We consider the problem of estimating cosmologicalparameters using measurements of the weak gravitational lensing of galaxies;
specifically, we use a likelihood-free approach to investigate the posterior
distribution of some parameters in the ΛCDM model upon observing a large
number of sheared galaxies. As the choice of summary statistic used in comparison of observed data and candidate data in the likelihood-free inference
framework is critical, we work toward a principled method of choosing thesummary statistic, aiming for dimension reduction while seeking a statisticthat is as close as possible to being sufficient for the parameters. Using simulated data, we evaluate the resulting statistic, as compared with others usedin existing work, according to their ability to constrain the model parameters.
This work is in collaboration with Peter Freeman, Rachel Mandelbaum, andChad Schafer.

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The probability distribution of ellipticity:
implications for weak lensing measurement
Massimo Viola
Leiden Observatory, Netherlands

The weak lensing effect generates spin-2 distortions, referred to as ‘shear’, on
the observable shape of distant galaxies induced by some intervening gravitational tidal field. Traditionally the spin-2 distortion in the light distributionof distant galaxies is measured in terms of a galaxy ”ellipticity”. This is avery good unbiased estimator of the shear field in the limit that a galaxy is
measured at infinite signal-to-noise. However the ellipticity is always defined
as a ratio of two quantities (the polarisation and a measurements of the galaxysize, or the semi-major and semi-minor axis of the galaxy to mention just two
possibilities) and therefore requires some non-linear combination of the image
pixels. This leads to biases in the measurement of the shear (and hence inthe cosmological parameters) in any realistic case, where noise is present in
the image. I will describe how this type of bias can be understood from theparticular shape of the 2D probability distribution of the ellipticity of an object
measured from data. Moreover I will discuss how this probability distribution
can be used to explore strategies for calibration of noise biases in present andfuture weak lensing surveys(KiDS, DES, Euclid...).

Errors on errors - estimating cosmologicalparameter covariance
Benjamin Joachimi1 & Andy Taylor2
1. University College London, United Kingdom
2. University of Edinburgh, United Kingdom

Current and forthcoming cosmological data analyses share the challenge ofhuge datasets alongside increasingly tight requirements on the precision andaccuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central
values of parameters but, equally important, also to the error bars. Due tonon-linear effects in the astrophysics, the instrument, and the analysis pipeline,
data covariance matrices are usually not well known a priori and need to be
estimated from the data itself, or from suites of large simulations. In either
case, the finite number of realisations available to determine data covariances

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introduces significant biases and additional variance in the errors on cosmological parameters in a standard likelihood analysis. I am going to review
recent work on quantifying these biases and additional variances, including
the new results presented in Taylor & Joachimi (2014, astro-ph/1402.6983). I
will discuss approaches to remedy these effects and the resulting requirementson the analysis and simulation effort of cosmological surveys.

Bayesian large-scale structure inference: initialconditions and cosmic voids
Florent Leclercq1,2,3 , Jens Jasche1,2 , Paul M. Sutter1,2,4 ,Nico Hamaus1,2,5 & Benjamin D. Wandelt1,2,5
1. Institut d’Astrophysique de Paris, France
2. Institut Lagrange de Paris, France
3. École Polytechnique ParisTech, France
4. Ohio State University, USA
5. University of Illinois, USA

Establishing a link between cosmological observations and theories describing
the early Universe is important because it can further our knowledge of fundamental physics on a wide range of energy and distance scales. In this talk, I
will describe recently proposed statistical data analysis methods designed to
study the primordial large-scale structure via physical inference of the initialconditions in a fully Bayesian framework, and demonstrate its application
to the Sloan Digital Sky Survey data release 7. Our algorithm explores thejoint posterior distribution of all parameters involved via efficient HamiltonianMarkov Chain Monte Carlo sampling.
Building upon these results, I will show how to generate a set of dataconstrained reconstructions of the present large-scale dark matter distribution.
As a physical illustration, we apply a void identification algorithm to them. In
this fashion, we access voids defined by the inferred dark matter field, not bygalaxies, greatly alleviating the bias problem. In addition, the use of full-scale
physical density fields yields a drastic reduction of statistical uncertainty invoid catalogs. This new catalog is an enhanced data set for cross-correlation
with other cosmological surveys.
Finally, as three-dimensional large-scale structure surveys contain a wealthof information which cannot be trivially extracted due to the non-linear dynamical evolution of the density field, I will discuss methods designed to improveupon previous approaches by including the salient features of the non-linear
regime.

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Marked point processes for morpho-statisticalcharacterization of the cosmic web
Radu S. Stoica
Université Lille 1, Laboratoire Paul Painlevé, France &Institut de Mécanique Céleste et Calcul d’Ephémérides, Observatoire de Paris, France

The cosmic web is the intricate network of filaments outlined by the galaxy
distribution in our Universe. One possible manner to break the complexityof such an elaborate geometrical structure is to assume it made of simple
interacting objects. Under this hypothesis, the filamentary network can beconsidered as the realization of a marked point process.
Marked point process are probabilistic models dealing with configurationsof random points having random characteristics or marks. If the marks represent properties of some geometrical object, the marked point process is also
called an object point process. Here, the filamentary network is considered as
the realization of such a random process, with the objects being cylinders thatalign and connect in order to form the network.
The aim of this talk is to present the use of marked point processes tothe detection and to the morpho-statistical characterization of the galactic
filaments. The talk follows the standard steps of a probability and statistics
based methodology : exploratory statistics, marked point processes modelling,
Monte Carlo simulation and statistical inference. In the conclusion and perspective part, we will discuss how this methodology can be applied to otherproblems coming from astronomy.

Low/High Redshift Classification of Emission Line
Galaxies in the HETDEX survey
Viviana Acquaviva1 , Eric Gawiser2 , Andrew Leung2 & Mario R. Martin1
1. CUNY New York City College of Technology, USA
2. Rutgers University, USA

We discuss different methods to separate high- from low-redshift galaxies
based on a combination of spectroscopic and photometric observations. Our
baseline scenario is the Hobby-Eberly Telescope Dark Energy eXperiment(HETDEX) survey, which will observe several hundred thousand Lyman Alpha
Emitting (LAE) galaxies at 1.9 < z < 3.5, and for which the main source ofcontamination is [OII] emitters at z < 0.5. Additional information useful for

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the separation comes from empirical knowledge of LAE and [OII] luminosity
functions and equivalent width distributions as a function of redshift. We consider three separation techniques: a simple horizontal cut in equivalent width,a Bayesian separation method, and machine learning algorithms, including
support vector machines. We show how the latter two can be easily applied toother surveys and used on simulated data in the framework of survey planning.

Distribution of maximal luminosity of galaxies in the
Sloan Digital Sky Survey
Eniko Regos1 , Manu Taghizadeh-Popp2 , Katalin Ozogány1 ,Zoltán Rácz1 & Alex S. Szalay2
1. Eötvös Loránd Tudományegyetem (Eotvos University), Hungary
2. The Johns Hopkins University, USA

Extreme value statistics is applied to the distribution of galaxy luminosities
in the Sloan Digital Sky Survey. We analyze the DR8 Main Galaxy Sample(MGS), as well as the luminous red galaxies (LRGs). Maximal luminosities
are sampled from batches consisting of elongated pencil beams in the radial
direction of sight. For the MGS, results suggest a small and positive tailindex ξ , effectively ruling out the possibility of having a finite maximum
cutoff luminosity, and implying that the luminosity distribution function may
decay as a power law at the high-luminosity end. Assuming, however, ξ = 0,
a non-parametric comparison of the maximal luminosities with the FisherTippett-Gumbel distribution (limit distribution for variables distributed by
the Schechter fit) indicates a good agreement provided that uncertainties
arising from both the finite batch size and the batch-size distribution areaccounted for. For a volume-limited sample of LRGs, results show that they
can be described as being the extremes of a luminosity distribution with an
exponentially decaying tail, provided that the uncertainties related to batch-size
distribution are taken care of.

Bootstrap: a valid alternative for clustering
analyses?
Pablo Arnalte-Mur & Peder Norberg
Durham University, United Kingdom

Modern surveys are measuring the two-point correlation function of the galaxy

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distribution to unprecedented precision, a trend that will continue with ongoingand planned projects. In order to make use of these data to obtain cosmologicalinformation, it is essential to accurately estimate the covariance matrix of themeasurements. Recent works have based this estimation on the use of a large
number of simulated mock catalogues, taken as independent realisations of thedata. However, the needed number of simulated realisations makes this a very
computationally intensive method. An alternative is to use internal varianceestimators such as jackknife and block bootstrap, based on re-sampling subregions of the original data. These are much cheaper computationally, and do
not depend on the accuracy of external simulations. The bootstrap method
has the advantage of providing a nearly unlimited number of data realisations.
However, in the standard bootstrap method, these realisations cover only afraction of the total volume and thus the variance is over-estimated. We
developed a new bootstrap method that avoids this problem by assigning
continuous weights to the different sub-regions of the data. It thus provides
a more accurate estimation of the covariance matrix. In this talk, we will
present this new method and compare the performance of the different internal
error estimations. Using a set of mock galaxy surveys, we will assess theapplicability of these methods in a cosmological context.

Detection of a Supervoid Aligned with the Cold Spotof the Cosmic Microwave Background
István Szapudi1 , András Kovács2 , Benjamin R. Granett3 , Zsolt Frei1 , Joseph
Silk4 , Will Burgett1 , Shaun Cole5 , Peter W. Draper5 , Daniel J. Farrow5 , Nicholas
Kaiser1 , Eugene A. Magnier1 , Nigel Metcalfe5 , Jeffrey S. Morgan1 , Paul Price6 ,John Tonry1 & Richard Wainscoat1
1. University of Hawaii, USA
2. Eötvös Loránd Tudományegyetem (Eotvos University), Hungary
3. Istituto Nazionale di Astrofisica Brera, Italy
4. The Johns Hopkins University, USA
5. Durham University, United Kingdom
6. Princeton University, USA

We use the WISE-2MASS infrared galaxy catalog matched with Pan-STARRS1(PS1) galaxies to search for a super-void in the direction the Cosmic Microwave
Background Cold Spot. Our imaging catalog has median redshift z ' 0.14,
and we obtain photometric redshifts from PS1 optical colours to create a tomographic map of the galaxy distribution. The radial profile centred on the

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Cold Spot shows a large low density region, extending over 10’s of degrees.
Motivated by previous Cosmic Microwave Background results, we test forunderdensity at two angular radii, 5◦ , and 15◦ . The counts in photometricredshift bins show significantly low densities at high significance, & 5σ and& 6σ , respectively, for the two fiducial radii. The line-of-sight position of
the deepest region of the void is z ' 0.15 − 0.25. Our data, combined withan earlier measurement by Granett et al. (2010), are consistent with a large
Rvoid = (192 ± 15)h−1 Mpc (2σ ) supervoid with δ ' 0.12. Such a super-void,
constituting a ' 3.5 − 5σ fluctuation in a Gaussian distribution in the ΛCDM
model, is large enough to affect the Cosmic Microwave Background throughthe integrated Sachs-Wolfe effect.

Sufficient observables for galaxy surveys
Julien Carron
Institute for Astronomy, University of Hawaii, USA

Statistical inference on cosmology from galaxy surveys requires a thoroughunderstanding of the statistical properties of the cosmological matter density
field. The non-linear nature of gravity distorts the Gaussianity of the primordial
fluctuation field, making the efficient extraction of useful information on
cosmological models a difficult challenge. Using simplified yet sufficiently
realistic statistical models, this talk will describe the ‘sufficient statistics’of the matter field, observables designed to capture its entire information
content, just like the power spectrum does for Gaussian fields. This talkwill also discuss consequences for inference on parameters from traditionalcosmological observables such as the two-point function, or power spectrum,and tight connections to the log-density field.

Improved distance measurements withreconstructed WiggleZ
Eyal Kazin1 , Jun Koda1 , Chris Blake1 , Nikhil Padmanabhan2 &the WiggleZ Dark Energy Survey
1. Swinburne University of Technology, Australia
2. Yale University, USA

The baryonic acoustic oscillations in galaxy maps has been shown to be acentral tool in constraining cosmology. However, due to the growth of structure,

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which causes ∼ 5 Mpc shifts in galaxy positions, this 150 Mpc feature in the
two-point correlation function becomes slightly blurred causing a degradationof its ability to constrain distances. In this talk I present the reconstruction
technique which, by restoring information encoded in the matter density field,
sharpens this standard ruler, and by so enhances its constraining power. We
have recently applied this technique on the galaxy maps of the WiggleZ Dark
Energy Survey (0.2 < z < 1), and find the method successful, significantly
improving distance measurements.

Machine Learning in Astronomy
Lise du Buisson1,2 , Bruce A. Bassett1,2,3 & Navin Sivanandam2
1. University of Cape Town, South Africa
2. African Institute for Mathematical Sciences, South Africa
3. South African Astronomical Observatory, South Africa

The use of machine learning techniques in the field of astronomy has gained
impetus in the last few years, as the sheer amount of data produced by astronomical surveys are putting an increasing amount of strain on human and otherresources in their efforts to classify and sort data in such a way as to be able togain insight and extract valuable results from it. Some examples of problems
where the use of machine learning is employed for astronomical data analysis
include the classification of stars, galaxies and AGNs, the identification andselection of possible quasars from surveys and the finding or classification ofsupernovae (SNe).
The next generation of surveys and telescopes, such as the Dark Energy
Survey (DES) and the Large Synoptic Survey Telescope (LSST), will produce
a vast amount of photometric data. Selecting SNe for spectroscopic follow-up
from such data sets can be a very time-consuming task, one that can be moreeasily addressed using machine learning techniques in order to arrive at an
automated and accurate selection/classification process.
For this investigation, photometric difference images obtained from Year
II and III of the Sloan Digital Sky Survey (SDSS) are used to investigate
which machine learning algorithms are best suited for classifying SNe fromother objects in photometric data sets. Feature extraction techniques, including
principal component analysis (PCA) and linear discriminant analysis (LDA),
are used in combination with different machine learning algorithms, such asa naı̈ve Bayes classifier, an artificial neural network (ANN), a support vector
machine (SVM), a k-nearest neighbour algorithm and a self-organising map in

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order to find the most effective and accurate technique. This technique will theneither be applied to similar SNe classification problems (e.g. classifying SNeusing data from DES) or to other slightly different photometric classification
problems.

Euclid space mission: a cosmological challenge forthe next 15 years
Roberto Scaramella1 on behalf of Euclid Consortium
1. Osservatorio Astronomico di Roma, Italy

Euclid is the next ESA mission devoted to cosmology. It aims at covering mostof the extragalactic sky, studying both gravitational lensing and clustering over
15000 square degrees. The mission is expected to be launched in year 2020
and to last six years.
The sheer amount of data of different kinds, the variety of (un)known
systematic effects and the complexity of measures require large efforts both insophisticated simulations and techniques of data analysis. We will review themission main characteristic, focus on the survey aspects and highlight some of
the areas of interest to this meeting.

Estimating the distribution of Galaxy Morphologies
Giuseppe Vinci1 , Peter Freeman1 , Christopher Genovese1 ,Jeffrey A. Newman2 & Larry Wasserman1
1. Carnegie Mellon University, USA
2. University of Pittsburgh, USA

Estimating the distribution of galaxy morphologies is one means to test theoriesof the formation and evolution of the Universe. Galaxy images are intrinsicallyhigh-dimensional data. Thus, statistical methods based on a lower-dimensional
representation of the images of galaxies are required. Summary statistics basedon the ”persistent homology” of the density of the lfight intensity distribution
produced by the galaxies can be helpful to classify mergers and non-mergers.
However, crude 0-1 classifications are not enough to describe the complexityof the galaxies. ”Dictionary learning” and ”sparse coding” allow us to reduce
the high dimensional space of shapes into a manageable low dimensional
continuous vector space of coefficients. The corresponding estimated continuous probability distribution can be used to identify clusters of shapes in an

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unsupervised way, and to compare the population of real galaxy shapes withthat of simulated ones.

Spin scale-discretised wavelets on the sphere forthe analysis of CMB polarization
Jason D. McEwen1 , Martin Buettner1 , Boris Leistedt1 , Hiranya V. Peiris1 ,Pierre Vandergheynst2 & Yves Wiaux3
1. University College London, United Kingdom
2. EPFL - École Polytechnique Fédérale de Lausanne, Switzerland
3. Heriot-Watt University, United Kingdom

We construct a new spin scale-discretized wavelet transform on the sphere that
supports a directional and steerable wavelet analysis of spin signals. Scalediscretized wavelets allow in practice the exact synthesis of a signal from its
wavelet coefficients. We present new exact and efficient algorithms to computethe spin scale-discretized wavelet transform of band-limited signals on thesphere up to high band-limits. Finally, we highlight the application of spin
scale-discretized wavelets to analysis polarized CMB data, which is a spin-2
signal on the sphere.

PRISM: Sparse Recovery of the Primordial PowerSpectrum
Paniez Paykari, François Lanusse, Jean-Luc Starck,
Florent Sureau & Jérôme Bobin
CEA – Commissariat à l’Énergie Atomique – Saclay, France

The primordial power spectrum describes the initial perturbations in the Universe which eventually grew into the large-scale structure we observe today,
and thereby provides an indirect probe of inflation or other structure-formation
mechanisms. Here, we introduce a new method to estimate this spectrum fromthe empirical power spectrum of cosmic microwave background (CMB) maps.
A sparsity-based linear inversion method, coined PRISM, is presented. This
technique leverages a sparsity prior on features in the primordial power spectrum in a wavelet basis to regularise the inverse problem. This non-parametricapproach does not assume a strong prior on the shape of the primordial power
spectrum, yet is able to correctly reconstruct its global shape as well as localised features. These advantages make this method robust for detecting

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deviations from the currently favoured scale-invariant spectrum. We investigate the strength of this method on a set of WMAP 9-year simulated data
for three types of primordial power spectra: a nearly scale-invariant spectrum,a spectrum with a small running of the spectral index, and a spectrum witha localised feature. This technique proves to easily detect deviations from apure scale-invariant power spectrum and is suitable for distinguishing between
simple models of the inflation. We process the WMAP 9-year data and findno significant departure from a nearly scale-invariant power spectrum withthe spectral index ns = 0.972. A high resolution primordial power spectrum
can be reconstructed with this technique, where any strong local deviations
or small global deviations from a pure scale-invariant spectrum can easily bedetected.

Maximum-likelihood determination of the galaxy LF,
evolution and selection function
Jonathan Loveday
University of Sussex, United Kingdom

With the creation of larger and larger galaxy redshift surveys, it is becoming
more and more important to minimise systematic errors so that they do not
dominate over the rapidly-shrinking random errors. One common source ofsystematic error in clustering analyses comes from inaccurate modelling of
the radial selection function, which is required in order to generate random
catalogues to correct for survey sampling effects.
In this contribution, I will describe modifications made to the joint stepwise
maximum likelihood method of Cole (2011) in order to simultaneously fit
the galaxy luminosity function (LF), corrected for radial density variations,and its evolution with redshift. I will present the r-band LF and evolution
parameters for galaxy subsamples drawn from the Galaxy and Mass Assembly(GAMA) survey, and show how this allows random catalogues with accurate
radial number densities to be produced. Finally, I will present type-dependent
clustering results from GAMA.

Transformatively Taming Spatial Statistics
Mark Neyrinck
The Johns Hopkins University, USA

Cosmological spatial statistics typically start (and sometimes end) with two-

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point correlation functions, or power spectra. I will show some advantagesof an approach that is nearly as simple, but much more statistically powerful:splitting the information in a field into the 1-point PDF, and the spatial statisticsof the Gaussianized field (i.e. the field subjected to a function, such as a logarithm, that turns its 1-point PDF more Gaussian). In the matter density field,
such an operation makes features more localized in the initial power spectrum,and greatly decreases small-scale cosmic variance. In more-observable, tracer
fields, on scales large enough to have small discreteness noise, this operation
splits the information into the ‘biasing’ part (encoded in the PDF), and theessential clustering of the matter (encoded in the Gaussianized-field statistics).

Clipping the Galaxy Power Spectrum in GAMA
Fergus Simpson1 , GAMA Collaboration
Universitat de Barcelona, Spain

I will present preliminary results from a new analysis of redshift space distortions in the GAMA survey. By down-weighting the highest density regions of
the galaxy field, contributions to the power spectrum from nonlinear structure
are suppressed. This extends the range of scales over which perturbation theory
remains valid, allowing the extraction of more cosmological information, suchas the growth of structure.

How accurate are measurements of primordial
non-Gaussianity parameters from large-scale
structure?
Nina Roth1 & Cristiano Porciani2
1. University College London, United Kingdom
2. Argelander-Institut für Astronomie, Universität Bonn, Germany

The scale-dependent galaxy bias generated by primordial non-Gaussianity(PNG) can be used to detect and constrain deviations from standard single-field
inflation. The strongest signal is expected in the local model for PNG, where
the amplitude of non-Gaussianity can be expressed by a set of parameters( fnl , gnl , ...). Current observational constraints from galaxy clustering on fnl
and gnl assume that the others PNG parameters are vanishing. Using two
sets of cosmological N-body simulations where both fnl and gnl are non-zero,
we show that this strong assumption generally leads to biased estimates andIAU Symposium 306 – SCCC21, 2014 — 60/130

spurious redshift dependencies of the parameters. Additionally, if the signs of
fnl and gnl are opposite, the amplitude of the scale-dependent bias is reduced,
possibly leading to a false null detection. Finally, we show that model selection
techniques like the Bayesian evidence can (and should) be used to determine
if more than one PNG parameter is required by the data. This is particularlyinteresting in light of the next generation of galaxy and cluster surveys likeeROSITA, Euclid or LSST which are expected to significantly reduce the error
bars of the PNG parameters measured from galaxy clustering.

Beyond confusion: A Bayesian P(D) analysis of the
Deepest Radio Survey
Jasper Wall, Tessa Vernstrom & Douglas Scott
University of British Columbia, Canada

We present a Bayesian method to estimate the count of faint radio sources from
P(D) (probability of deflection) data obtained in the deepest radio survey yet.
The deep count is critical in establishing the nature of faint radio sources andtheir role in galaxy formation. The method makes minimal assumptions on theform of the count and uses MCMC chains to perform accurate error analysis.
Full large-scale simulations included clustering and resolution effects, andshowed that the method is accurate and robust. We find that the source countcan be constrained by P(D) data to a factor of 20 below the conventionallydefined confusion limit. With our 3-GHz deep JVLA data, this translates to alevel of 50 nano-Jansky. The count obtained implies modification of current
estimates of evolution of faint-source populations, and sets a hard upper limit
to the sky surface-brightness contribution from faint radio sources.

Bayesian Inference for Radio Observations (BIRO) –A new technique for simultaneously estimating
instrumental errors and science parameters directlyfrom radio visibility data
Michelle Knights1,2 , Bruce Bassett2,1,3 , Oleg Smirnov4,5 , Jon Zwart6 ,Iniyan Natarajan1 & Martin Kunz7,2
1. University of Cape Town, South Africa
2. African Institute for Mathematical Sciences, South Africa
3. South African Astronomical Observatory, South Africa

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4. SKA Africa, South Africa
5. Rhodes University, South Africa
6. University of the Western Cape, South Africa
7. Université de Genève, Switzerland

When creating a radio image from an interferometer, certain assumptions
about instrumental errors must be made. The science extracted from theresulting image could be seriously affected by these parameters if the estimates
are wrong. Additionally, accurately estimating the uncertainties on these
instrumental parameters is challenging. We propose Bayesian Inference forRadio Observations (BIRO): a new technique for simultaneously estimating the
instrumental and science parameters, as well as the error on these parameters,
directly from the visibility data.
A popular method in radio astronomy, a standard least squares approach,is only able to obtain the best fitting parameters. However, with a Bayesian
approach we can obtain the full posterior probability distribution. This means
we can determine the uncertainties for all parameters and the correlations
between parameters. In this talk, I will give an overview of BIRO and show
a specific application for the case of estimating the pointing errors, beam
parameters and fluxes of a set of sources with known positions. Even inthis simple case, important correlations between the parameters arise. These
correlations, if not taken into account in the uncertainty estimates, could
produce biased estimates of the science parameters, such as the fluxes. I will
also briefly touch on other applications of BIRO and it’s feasibility for use
with SKA data.

Testing the consistency of different supernova
surveysNatallia Karpenka1 , Farhan Feroz2 & Mike Hobson2
1. Stockholms universitet (Stockholm University), Sweden
2. University of Cambridge, United Kingdom

SNe catalogues typically contain data from a number of different surveys. In
constraining cosmological parameters, most studies perform an analysis of
the full SNe catalogue. The key assumption underlying such analyses is thatthe different SN data-sets comprising the catalogue are mutually consistent.
It is possible, however, to have some unaccounted for systematics in SN
data-sets, so it is extremely important to establish whether these data-sets are

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mutually consistent before performing a coherent joint analysis. It is evenmore important for the set to be consistent if one is attempting to find “new”
signatures, such as anisotropy of the cosmological expansion. I apply robust
statistical tests to determine whether different SNe data-sets are mutuallyconsistent. My preliminary studies indicate that some inconsistencies do arise
in terms of the model parameter constraints derived from them.

Improved Kernel Principal Component Analysis forSupernova Photometric Classification
Emille E. O. Ishida1 & Filipe Abdalla2
1. Max-Planck-Institut für Astrophysik, Germany
2. University College London, United Kingdom

The problem of supernova photometric identification will be extremely important for large surveys in the next decade. In a previous investigation (Ishida& de Souza, 2013, presented in the XXVIII IAU General Assembly under
special section: Data Intensive Astronomy), we showed how the use of Kernel Principal Component Analysis (kPCA) and Nearst Neighbour algorithms
were capable of photometricaly classifying supernovae with a high rate ofsuccess. In the present work, we demonstrate that the introduction of GaussianProcess Regression (GPR) in determining each light curve highly improves
the efficiency and purity rates of our previous results. This is due to two
crucial GPR features: (1) it provides not only a best-fit functional form but
also an uncertainty over each point in the new function and (2) it allows for
extrapolation beyond the domain covered by the data. Given an uncertainty
around each light curve, we were able to address, to each supernova, the probability of being an Ia. Beyond that, the possibility to extrapolate the measured
light curve prevents us from neglecting to classify many objects which do nothave a proper epoch coverage. Consequently, the classification process was
highly simplified and results were significantly improved. We present detailed
comparison with our previous results and those reported in the literature, basedon simulations as well as real data. The method proved to be satisfactorily
efficient, providing extremely high purity rates when compared with standard
algorithms, without needing any information on astrophysical properties ofthe local environment, host galaxy or redshift.

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Cross Correlation between Astrophysical andCosmological Datasets: Precision of Covariance
Estimation and Impact on the Signal Detection
SignificanceFederico Bianchini
SISSA – Scuola Internazionale Superiore di Studi Avanzati, Italy

We study the statistical properties of estimators of cross-correlation between
astrophysical and cosmological datasets, focusing on the case of gravitational
lensing of the Cosmic Microwave Background anisotropies from Large Scale
Structure. We study the impact that signal modeling and covariance estimation may have onto the signal measurement in the perspective of estimating
astrophysical and cosmological parameters out of cross-correlation studies.

Information Gains from Cosmic Microwave
Background Experiments
Sebastian Seehars, Adam Amara, Alexandre Refregier,Aseem Paranjape & Joel Akeret
ETH Zurich – Eidgenössische Technische Hochschule Zürich, Switzerland

To shed light on dark energy and dark matter, a large number of experiments
have been performed and combined to constrain cosmological models. Comparing these parameter constraints is crucial for finding ways to challenge
existing models with observations. We present the Kullback-Leibler divergence as a measure for the differences between the posterior distributions of
the model parameters from a pair of experiments. We distinguish contributions
from the reduction of statistical errors and the ‘surprise’ corresponding to asignificant shift of the parameters’ central values. Applying it to a historicalsequence of CMB experiments, we discuss how this technique provides a useful tool for both quantifying the constraining power of data from cosmologicalprobes and detecting tensions between experiments.

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How well can the evolution of the scale factor bereconstructed by the current data?
Sandro Vitenti1 & Mariana Penna-Lima2
1. Institut d’Astrophysique de Paris, France
2. Instituto Nacional de Pesquisas Espaciais, Brazil

Distance measurements are currently the most powerful tool to study the expansion history of the universe without assuming its matter content nor any theoryof gravitation. In general, the reconstruction of the scale factor derivatives,
such as the deceleration parameter q(z), are computed using two different
methods: fixing the functional form of q(z), which yields biased estimates, orapproximating q(z) by a piecewise nth-order polynomial function, whose variance is large. In this presentation, we address these two methods reconstructing
q(z) in the redshift interval [0.01, 1.4], using the Supernova Legacy Survey
3-year (SNLS3) sample and assuming only an isotropic and homogeneous
universe. For this, we approximate q(z) by a piecewise cubic spline function,
considering 8 knots in z. The cubic spline has its third derivative discontinuous
at its knots, thus, we add a Gaussian prior, with scatter given by σ , on thethird derivative of q(z) with respect to z for each knot. This prior allows us
to vary continuously between the full 8 knots spline, σ → ∞, and a single
cubic polynomial, σ → 0. The q(z) reconstruction is overfitting dominated forlarge σ . On the other hand, for small σ , q(z) is better constrained but biased.
We estimate the coefficients of q(z) using the Monte Carlo approach, where
the realizations are generated considering ΛCDM as a fiducial model. We
perform this analysis for different values of σ to find the best balance between
variance and bias. We also compute the significance of the decelerated toaccelerated expansion of the universe fitting simultaneously q(z) with three
nuisance parameters of the supernovae, namely, the magnitude MB and thelight curve parameters α and β . In this case, we use a combined likelihoodof SNLS3, baryonic acoustic oscillations and Hubble function measurements,
where now z ∈ [0, 2.3].

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Cosmology with photometric surveys & an updateon the Dark Energy Survey
Filipe B. Abdalla
University College London, United Kingdom

I will discuss the potential cosmology we can learn from photometric redshift
surveys and how these studies it will lead the way in the next few years interms of cosmological measurements. I will give an update on the status of
the Dark Energy Survey, present some preliminary results on the data and data
quality taken in science verification and the status of the first year data.

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Posters

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Bayesian CMB foreground separation with acorrelated log-normal model
Niels Oppermann1 & Torsten A. Enßlin2
1. Canadian Institute for Theoretical Astrophysics, Canada
2. Max-Planck-Institut für Astrophysik, Germany

The extraction of foreground and CMB maps from multi-frequency observations relies mostly on the different frequency behavior of the different
components. Existing Bayesian methods additionally make use of a Gaussianprior for the CMB whose correlation structure is described by an unknown
angular power spectrum. We argue for the natural extension of this by using
non-trivial priors also for the foreground components. Focusing on diffuse
Galactic foregrounds, we propose a log-normal model including unknown
spatial correlations within each component and cross-correlations between the
different foreground components. We present case studies at low resolutionthat demonstrate the superior performance of this model when compared to an
analysis with flat priors for all components.

A high-dimensional look at VIPERS galaxies
Ben Granett1 & the VIPERS team
1. Istituto Nazionale di Astrofisica Brera, Italy

The VIMOS Public Extragalactic Redshift Survey (VIPERS) is targeting 100k
galaxies with spectroscopy at redshifts z=0.5 to 1.2. With complementary photometric coverage from UV to IR and morphological measures from CFHTLS,
this unique dataset is providing unprecedented detail on the properties ofgalaxies and the formation of structure at intermediate redshifts.
We investigate how galaxies in VIPERS inhabit the cosmological density
field by examining the correlations across the observable parameter space ofgalaxy properties, local density and clustering strength. The high-dimensional
analysis is made manageable by the use of group-finding and regression tools.
We find that the major trends in galaxy properties can be explained by asingle parameter related to stellar mass. After subtracting this trend, residual
correlations remain between galaxy properties and the local environment
pointing to complex formation dependencies. As a specific application of thiswork we build subsamples of galaxies with specific clustering properties foruse in cosmological tests.

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Detecting filamentary pattern in the cosmic web:method and applications
Elmo Tempel1 , Radu S. Stoica2 & Enn Saar1
1. Tartu Observatoorium (Tartu Observatory), Estonia
2. Université Lille 1, France

The main feature of the spatial large-scale galaxy distribution is its intricate
network of galaxy filaments. This network is spanned by the galaxy locations that can be interpreted as a three-dimensional point distribution. In mytalk I give an overview about an object point process with interactions (theBisous model) to trace and extract the filamentary network. This method
works directly on the galaxy distribution and does not require any additionalsmoothing, it only requires fixing the scale of structures. The main advantage
of our method is in its probabilistic nature. I give an example, how single
realisations of the model are sensitive to noise (observational uncertainties andsmall number densities of galaxies). Still, averaging many realisations reduces
the noise influence, and allows computation of robust statistical quantities.
Our filament finder (the Bisous model) is probabilistic in the sense thatit gives us the filament detection probability field together with the filamentorientation field. Using these two fields, we define the spines of the filaments
and extract single filaments from the data. To trace and extract the filamentary
network, we applied our model to the presently largest galaxy redshift survey,
the Sloan Digital Sky Survey (SDSS). We divided the detected network into
single filaments and constructed a catalogue of filaments. In my talk, I givean overview about the detected filaments in the SDSS and present some basic
properties (e.g. length distribution, radial profiles) of filaments.
Using the SDSS filaments, we have studied the correlation between galaxy
spin axes and filament spines. I give an brief overview, how filaments affectthe orientation of galaxy spin axes.

Line-of-sight density field analysis for the WHIM
searchLauri Juhan Liivamagi
Tartu Observatoorium (Tartu Observatory), Estonia

The whereabouts of up to half of the baryons is unknown in the low-ledshift(z<2) universe. These are thought to be in the form of the so-called WHIM

IAU Symposium 306 – SCCC21, 2014 — 70/130(warm-hot intragalactic matter). This gas would be slightly enriched with metals and would reside in low-density environment of the large-scale structures,such as filaments and outskirts of superclusters. It’s temperature is 105 . . . 107
K and density 10−6 . . . 10−4 cm−3 , making it both too ionized to effectively
absorb radiation and too cool and sparse to observe the emission. So far, only
a few tentative detections have been made, observing OVII absorbtion in X-ray
spectra of background blazars.
Using various simulations, we have determined a rough relation between
the column density of the WHIM and luminosity density of observed largescale structures of galaxies. We analyse the line-of-sight density field profiles
derived from large galaxy redshift surveys (SDSS, 2dF, 2MASS) and attempt
to delineate areas where detecting the X-ray absorption in spectre of brightbackground objects is most probable. We also study the plausibility of using
gamma-ray burst afterglows as background X-ray sources.

Learning the Gravitational Mass Density of Real
Galaxies in the Absence of Training Data
Dalia Chakrabarty
Department of Mathematics, University of Leicester, United Kingdom &Department of Statistics, University of Warwick, United Kingdom

Learning the gravitational mass density function of a galaxy given (missing)data on some of the phase space coordinates of one or more samples of tracers
in the system, is fundamentally an inverse problem. However, it is an inverse
problem that is unusually difficult since it is characterised by our ignorance
about the functional relation between the measurable and the sought model
function. While this unknown functional relation can in principle be trainedusing training data, no reliable training data set may exist for an observed
galaxy. In lieu of such training sets, one resorts to learning a discretised
version of the gravitational mass density function, i.e. values of the function–
treated as iid, albeit distribution-free parameters–at N chosen points in its
support X ∈ R3 . Thus the problem is reduced to the learning of the unknown
gravitational mass density vector ρ, the i-th component of which is the value ofthe function at the i-th chosen value of X, namely xi , i = 1, . . . , N. Within thisparadigm, ρ is learnt by embedding it within the definition of the support ofthe phase space density, where the latter is invoked to write the likelihood. The
phase space density is modelled as an anisotropic function of the phase spacecoordinates. Priors motivated by literature are used to define the posterior of

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the unknown distribution-free parameters, given the data. Posterior samples
are taken with an adaptive Metropolis-Hastings scheme. Application to thereal galaxy NGC3379 are included.

A new photometric typing technique for normal andpeculiar type Ia supernovae
Filomena Bufano1 & Santiago González-Gaitán2
1. Universidad Andres Bello, Chile
2. Universidad de Chile, Chile

Although type Ia supernovae (SNe Ia) are powerful distance indicators, only asubset of them, ”normal SNe Ia”, are suitable for precise cosmology. Current
and future transient surveys will routinely discover hundreds to thousandsof supernovae at various redshift ranges. As their spectroscopic follow-up
becomes expensive, new photometric classifiers capable of identifying peculiar
objects becomes imperative. We present a new photometric classification
technique capable of identifying several peculiar subsets of SNe Ia such as
subluminous SNe Ia, SNe Iax and super-Chandrasekhar SNe Ia. We showthat these objects present remarkably similar light-curve properties such aslater maxima in all photometric filters and the absence of a secondary peak in
redder filters. By performing different light-curve fits, we demonstrate that ourclassification methodology is a powerful technique to identify such harmful
outliers and to obtain pure normal SN Ia sample for cosmological studies.

Simulation of the analysis of interferometricmicrowave background polarization data
Emory F. Bunn1 , Ata Karakci2 , Paul M. Sutter3,4 , Le Zhang5 ,Gregory S. Tucker2 , Peter Timbie5 & Benjamin D. Wandelt4
1. University of Richmond, USA
2. Brown University, USA
3. Ohio State University, USA
4. Institut d’Astrophysique de Paris, France
5. University of Wisconsin - Madison, USA

We present results from an end-to-end simulation pipeline interferometricobservations of cosmic microwave background polarization. We use bothmaximum-likelihood and Gibbs sampling techniques to estimate the power

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spectrum. In addition, we use Gibbs sampling for image reconstruction frominterferometric visibilities. The results indicate the level to which various
systematic errors (e.g., pointing errors, gain errors, beam shape errors, crosspolarization) must be controlled in order to successfully detect and characterizeprimordial B modes as well as other scientific goals.

PCA of type II SNe light-curves
Lluı́s Galbany1 & and collaborators
1. Departamento de Astronomı́a, Universidad de Chile, Chile

We present a Principal Component Analysis (PCA) of the light-curves of asample of more than 200 Core-collapse supernovae (SNe) from several sources,
and most of them previously unpublished. We used different reference epochs
in order to extract the common properties of these light-curves and searched
for correlations to some physical parameters such as the burning of Ni56,
amount of Hydrogen, and morphological parameters such as the length of theplateau, the stretch or the light-curve, and the decrements in brightness after
maximum and after the plateau. We also used these similarities to produce
SNe II light-curve templates that will be used in the future for standardizethese objects and determine cosmological distances.

Cosmological Constraints from the Anisotropic
Clustering Analysis using BOSS DR9Eric V. Linder1,2 , MinJi Oh2,3 , Teppei Okumura4 ,Cristiano G. Sabiu5 & Yong-Seon Song2,3
1. University of California, Berkeley, USA
2. KASI – Korea Astronomy and Space Science Institute, Korea
3. UST – University of Science and Technology, Korea
4. IPMU – Institute for the Physics and Mathemaics of the Universe, University of Tokyo, Japan
5. KIAS – Korea Institute for Advanced Study, Korea

Our observations of the Universe are fundamentally anisotropic, with data fromgalaxies separated transverse to the line of sight coming from the same epoch
while that from galaxies separated parallel to the line of sight coming fromdifferent times. Moreover, galaxy velocities along the line of sight change theirredshift, giving redshift space distortions. We perform a full two-dimensional
anisotropy analysis of galaxy clustering data, fitting in a substantially model

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independent manner the angular diameter distance DA, Hubble parameter
H, and growth rate dδ /dlna without assuming a dark energy model. The
results demonstrate consistency with ΛCDM expansion and growth, hence
also testing general relativity. We also point out the interpretation dependenceof the effective redshift ze f f , and its cosmological impact for next generation
surveys.

Precision growth index using the clustering of
cosmic structures
Athina Pouri1,2 , Spyros Basilakos1 & Manolis Plionis3,4,5
1. Academy of Athens, Greece
2. National and Kapodistrian University of Athens, Greece
3. Aristotle University of Thessaloniki, Greece
4. Instituto Nacional de Astrofı́sica Óptica y Electrónica, México
5. National Observatory of Athens, Greece

In order to test the validity of General Relativity (GR) on cosmological scales,
it has been proposed that measuring the so called growth index, γ, could
provide an efficient way to discriminate between scalar field dark energy
models which admit to general relativity and modified gravity models. Using
the clustering properties of the Luminous Red Galaxies and galaxy clusters
we attempt to place tight constraints on the growth index γ and thus testing
possible departures from GR.

Compressed Convolution
Franz Elsner1 & Benjamin D. Wandelt2
1. University College London, United Kingdom
2. Institute d’Astrophysique de Paris, France

I present the concept of compressed convolution, a technique to convolve a
given data set with a large number of non-orthogonal kernels. In typical applications the method drastically reduces the effective number of computations.
It is based on linear compression of the collection of kernels into a small
number of coefficients in an optimal eigenbasis. The final result can then be
decompressed in constant time for each desired convolved output.
The algorithm is fully general, applicable to convolutions with symmetricand asymmetric kernels, and can be easily controlled for an optimal trade-IAU Symposium 306 – SCCC21, 2014 — 74/130

off between speed and accuracy. I give explicit examples in the context ofsimulation challenges for upcoming multi-kilo-detector cosmic microwave
background (CMB) missions. For a CMB experiment with O(10,000) detectors
with similar beam properties, I demonstrate that the algorithm can decrease thecosts of beam convolution by two to three orders of magnitude with negligible
loss of accuracy.

Cross-correlating photometric and spectroscopic
surveys
Martin B. Eriksen
Universiteit Leiden, Netherlands

This talk discuss how to constrain cosmological models with the combinationof spectroscopic and photometric galaxy surveys. On one hand, the photometric survey measures 2D Weak Lensing (WL) information from galaxy shape
distortions and 2D clustering information from galaxy number density counts,
including magnification. On the other hand, the higher redshift precision of anspectroscopic survey allows measurements of redshift space distortions (RSD)from 3D galaxy clustering counts. Here the theoretical constraints that could
be obtained from a complete tomographic analysis of 2D cross-correlations in
narrow (δ z ' 0.01) redshift bins, including the exact contributions (of RSD,
BAO, WL shear and magnification) for combining 2D photometric and 3D
spectroscopic galaxy populations including all error covariances. In this talk
we first study the effect of the Limber approximation, RSD and Baryon Accustic Oscillations in narrow redshift bins. Second we present forecast of
combined photometric and spectroscopic samples, focusing on the benefit ofoverlapping surveys. Last, we comment on the sensitivity to the galaxy bias.

Understanding Cosmological Measurements with aLarge Number of Galaxy Mock Catalogues.
Marc Manera1 & collaborators of the BOSS galaxy working group
1. University College London, United Kingdom

Mock galaxy catalogues are essential to the analysis of cosmological measurements from big galaxy surveys covering thousands of degrees of the sky, like
BOSS, WiggleZ, DES or Euclid. In my talk I will introduce the 1600 mockgalaxy catalogues created for the analysis of BOSS survey data. I will explain

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how we have used them for producing covariance matrices, characterising thedifferent galaxy clustering estimators,and understanding and correcting forsystematic errors. I will also comment on the error budget and error propagation when using likelihood analysis from mocks. Finally, I will present someof the challenges that the new and ongoing surveys like DES bring in terms
data analysis and management.
For further information see papers from BOSS collaboration,specially,
Manera et al. 2013&2014, Percival et al. 2013, and Anderson et al. 2014.

Searching for non-Gaussianity in the Planck data
Marcelo J. Reboucas1 & A. Bernui2
1. Centro Brasileiro de Pesquisas Fisicas, Brazil
2. Observatorio Nacional, Brazil

The statistical properties of the temperature and polarization anisotropies
of cosmic microwave background (CMB) radiation and of the large-scale
structure of the Universe offer a powerful probe of the physics of the early
universe. It is conceivable that no single statistical estimator can be sensitive
to all forms and levels of non-Gaussianity that may be present in observed
CMB data. In recent works a statistical procedure based upon the calculationof the skewness (S) and kurtosis (K) of the patches of CMB sky-sphere
has been proposed and used and use to examine the large-angle deviationfrom Gaussianity WMAP maps [PRD 79, 063528 (2009); PRD 81, 063533(2010); PRD 85, 023522 (2012)]. We address the question as to how the
our analysis of Gaussianity of WMAP maps is modified if the foregroundcleaned Planck maps are used. As the foreground is cleaned through different
component separation procedures, each of the resulting Planck maps is tested
for Gaussianity. We determine quantitatively the effects for Gaussianity ofmasking the foreground-cleaned Planck maps with the INPMASK, VALMASKand U73 Planck masks. We show that although the foreground-cleaned Planck
maps present significant deviation from Gaussianity of different degrees when
the less severe INPMASK and VALMAKS are used, they become consistent
with Gaussianity as detected by one of our indicator, S, when masked with theunion mask U73. A slightly smaller consistency with Gaussianity is foundwhen the K indicator is employed, which seems to be associated with largeangle anomalies reported the Planck team. The results of our analyses provide
important information about the suitability of the foreground-cleaned Planck
maps as Gaussian reconstructions of the CMB sky.

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The impact of superstructures in the Cosmic
Microwave BackgroundStéphane Ilic1 , Mathieu Langer2 & Marian Douspis2
1. IRAP – Institut de Recherche en Astrophysique et Planétologie, Toulouse, France
2. IAS – Institut d’Astrophysique Spatiale, Orsay, France

In 2008, Granett et al. claimed a direct detection of the integrated SachsWolfe (iSW) effect by a stacking approach of patches of the CMB at thepositions of identified superstructures. However, the high measured amplitudeof the effect seems to be at odds with predictions from the standard model ofcosmology. The limited number of structures used might also raise concerns
over the statistics of such extreme objects. I first revisited this study with a
new protocol, completed and associated with a thorough variety of statisticaltests to check the significance of these results – particularly difficult to assessand subject to possible selection bias. After extending the study to other,larger catalogues of structures, my new results suggest there the presenceof a signal more consistent with theory, albeit with moderate significance.
Multiple questions arise from these results and their expected value : this led
me to propose an original theoretical prediction of the iSW effect produced bysuch superstructures. I use simulations based on GR and the LTB metric toreproduce cosmic structures and predict their exact full theoretical iSW effect.
Expected amplitudes are consistent with the measured signal ; however thelatter shows non-reproducible features that are hardly compatible with LCDM
predictions.

Combining cluster counts and galaxy angularcorrelation functions : forecasts for the Dark Energy
SurveyFabien Lacasa & Rogerio Rosenfeld
ICTP International Center for Theoretical Physics, São Paulo, Brasil

In the course of its 5-year observation of the southern sky, the Dark Energy
Survey (DES) is forecast to detect ∼ 300 millions galaxies and thousands
clusters up to redshift ∼ 1.3, with photometric redshift determinations. This
will enable unprecedented studies of galaxy clustering and cluster constraints
on cosmology. I will show ongoing work to combine these two probes toreach tighter cosmological constraints. The halo model can be used to model

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the cross covariance between cluster counts and galaxy power spectrum (orreal-space correlation function), and I will introduce a diagrammatic method
to compute easily the different terms implied and have a simple representation.
Furthermore I will show how the Gram-Charlier series can be used to computethe joint likelihood of cluster counts and galaxy power spectrum, a likelihood
which is highly non-Gaussian due to the Poissonian character of cluster counts.
I will conclude with forecasts of cosmological constraints achievable by DES
with this method.

Data Rich Astronomy: Mining Sky Surveys
Stefano Cavuoti1 , Massimo Brescia1 & Giuseppe Longo2
1. INAF-Astronomical Observatory of Capodimonte, Italy
2. Department of Physical Sciences, University Federico II, Italy

In the last decade a new generation of telescopes and sensors has allowed
the production of a very large amount of data and astronomy has become adata-rich science. New automatic methods largely based on machine learning
are needed to cope with such data tsunami. We present some results in thefields of photometric redshifts and galaxy classification obtained using the
MLPQNA algorithm available in the DAMEWARE (Dat Mining and Web
Application Resource) for the SDSS galaxies (DR9 and DR10) paying special
attention to the so called “catastrophic outliers”.

Adapting Predictive Models For Cepheid Variable
Star Classification Using Linear Regression And
Maximum Likelihood
Ricardo Vilalta1 , Vicken Asadourian1 , Kinjal Dhar Gupta1 & Lucas Macri2
1. University of Houston, USA
2. Texas A&M University, USA

We describe an approach to automate the classification of Cepheid variable
stars into two subtypes according to their pulsation mode. Automating suchclassification is relevant to obtain a precise determination of distances tonearby galaxies, which in addition helps reduce the uncertainty in the current
expansion of the universe. One main difficulty lies in the compatibility ofmodels trained using different galaxy datasets; a model trained using a training
dataset may be ineffectual on a testing set. A solution to such difficulty is toIAU Symposium 306 – SCCC21, 2014 — 78/130

adapt predictive models across domains; this is necessary when the training
and testing sets do not follow the same distribution. Automatically classifying
variable stars is a prime example of such a scenario, because switching fromone galaxy dataset to another inevitably carries a sample bias due to ourlimitation to observe faint stars; as the distance to a galaxy increases, our starsample will inevitably concentrate on higher-luminosity stars. Additionally,a noticeable displacement across datasets is to be expected along Apparent
Mean Magnitude.
The gist of our methodology is to train a predictive model on a nearby
galaxy (e.g., Large Magellanic Cloud), followed by a model-adaptation step tomake the model operable on other nearby galaxies. We follow a parametricapproach to density estimation by modeling the training data (anchor galaxy)using a mixture of linear models. We then use maximum likelihood to compute the right amount of variable displacement, until the testing data closely
overlaps the training data. At that point, the model can be directly used in
the testing data (target galaxy). Our approach differs from previous work in
the probabilistic model used to characterize the Cepheid variable star population; we favor a linear model that more closely resembles the distribution of
Cepheid variable stars. Experimental results with several galaxy datasets show
the effectiveness of our approach.

Semi-analytical Study on the Generic Degeneracy for
Galaxy Clustering Measurements
Alejandro Guarnizo1 , Luca Amendola1 , Martin Kunz2,3 & Adrian Vollmer1
1. Institut Für Theoretische Physik, Ruprecht-Karls-Universität Heidelberg, Germany
2. Département de Physique Théorique, Université de Genève, Switzerland
3. Center for Astroparticle Physics, Université de Genève, Switzerland

Future galaxy surveys will provide new opportunities to verify the current
standard cosmological model, and also to constrain modified gravity theories
invoked to explain the present accelerated expansion of the universe. Fromthe galaxy power spectrum in redshift space, we derive semi-analytical resultson the generic degeneracy of galaxy clustering measurements. Defining theobservables Ā = Gbδm,0 and R = G f δm,0 , (being G the growth function, b thebias, f the growth rate, and δm the dark matter density contrast today), we
perform a Fisher matrix formalism to forecast the expected precision of thesequantities for a Euclid-like survey. Among the results we found that galaxy
surveys have generically a slightly negative correlation between Ā and R̄, andIAU Symposium 306 – SCCC21, 2014 — 79/130

they can always measure R̄ about 3.5 to 4.5 times better than Ā. Finally, we
briefly present results on the precision in which galaxy surveys can measure
the anisotropic stress η, based on a model-independent analysis.

Cosmography with high-redshift probes
Vincenzo Vitagliano
IST - Instituto Superior Técnico, Universidade de Lisboa, Portugal

Cosmography is the tool that makes possible to untie the interpretation ofcosmological observations from the definition of any dynamical prior. We
review the constraints on the cosmographic parameter obtained using the mostthorough data set ensemble available. We focus on some specific topics about
the statistically based selection of the most stringent fitting expansion.

Darth Fader: Analysing galaxy spectra at low signal
to noise
Adrienne Leonard1 , Daniel Machado1,2 , Filipe Abdalla1 & Jean-Luc Starck1
1. University College London, United Kingdom
2. CEA – Commissariat à l’Énergie Atomique – Saclay, France

Spectroscopic redshift surveys are an incredibly valuable tool in cosmology, allowing us to trace the distribution of galaxies as a function of distance and, thus,
trace the evolution of structure formation in the Universe. However, estimating
the redshifts from spectra with low signal-to-noise is difficult, and such data areoften either discarded or require human classification of spectral lines to obtain
the galaxy redshift. Darth Fader offers an automated method for estimating theredshifts of galaxies in the low signal-to-noise regime. Using a sophisticated,wavelet-based technique, galaxy spectra can be separated into continuum, line
and noise components, and the lines can then be cross-correlated with template
spectra in order to estimate the redshifts. Cross-matching of the identified lines
then allows for a cleaning of the resulting catalogue, effectively removing thevast majority of erroneous redshift estimates and resulting in a highly pure,highly accurate redshift catalogue. Darth Fader allows us to effectively use low
signal-to-noise galaxy spectra, and dramatically reduces the number of human
hours required to do this, allowing spectroscopic surveys to probe deeper into
the formation history of the Universe.

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Biased cosmological parameter estimation withgalaxy cluster counts in the presence of primordial
non-Gaussianities.
Arlindo M. M. Trindade, Pedro P. Avelino & Pedro T. P. Viana
CAUP – Centro de Astrofı́sica da Universidade do Porto, Portugal
FCUP – Faculdade de Ciências da Universidade do Porto, Portugal

The redshift dependence of the abundance of galaxy clusters is very sensitive tothe statistical properties of primordial density perturbations. It can thus be used
to probe small deviations from Gaussian initial conditions. Such deviations
constitute a very important signature of many inflationary scenarios, and arethus expected to provide crucial information on physical processes which
took place in the very early Universe. We have determined the biases which
may be introduced in the estimation of cosmological parameters by wrongly
assuming the absence of primordial non-Gaussianities. Although we find thatthe estimation of the present-day dark energy density using cluster counts is
not very sensitive to the non-Gaussian properties of the density field, we showthat the biases can be considerably larger in the estimation of the dark energy
equation of state parameter w and of the amplitude of the primordial density
perturbations. Our results suggest that a significant level of non-Gaussianity atcluster scales may be able to reconcile the constraint on the amplitude of theprimordial perturbations obtained using galaxy cluster number counts fromthe Planck Sunyaev-Zeldovich Catalog with that obtained from the primary
Cosmic Microwave Background anisotropies measured by the Planck satellite.

Photometric classification of Supernovae from the
SUDARE survey
Giuliano Pignata
Universidad Andrés Bello, Chile

I will present first results from the algorithm we developed to photometricallyclassify the supernovae discovered by the Supernova Diversity and Rate Evolution (SUDARE). The classification outcome is compared with other methods
reported in literature.

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Search for bias and correlations within a Bayesianframework
Caroline Heneka1 , Valerio Marra2 , Alexandre Posada2 & Luca Amendola2
1. DARK Cosmology Center, Københavns Universitet (University of Copenhagen), Denmark
2. Institut Für Theoretische Physik, Ruprecht-Karls-Universität Heidelberg, Germany

A range of Bayesian tools has become widely used for the treatment of cosmological data and parameter inference. With bigger data sets and increasing
precision, tools that enable us to further enhance the accuracy of our measurements will gain importance. Here we present a Bayesian how-to for theidentification of biased subsets of data as well as the search for hidden correlations in a model-independent way using as an example SN Ia data. We discussdifferent approaches for the identification of hidden biases and correlations andpresent our results on SN Ia data used for cosmological parameter estimates.

OCAAT: automated analysis of star cluster
colour-magnitude diagrams for gauging the local
distance scale
Gabriel Perren1 , Rubén A. Vázquez1 , Andrés Piatti2 & André Moitinho3
1. CONICET, Universidad Nacional de La Plata, Argentina
2. OA, Universidad de Córdoba, Argentina
3. SIM – Universidade de Lisboa, Portugal

Star clusters are among the fundamental astrophysical objects used in setting
the local distance scale. Despite its fundamental importance, the accurate
determination of the distances to the Magellanic Clouds (SMC/LMC) remains
a fuzzy step in the cosmological distance ladder. The exquisite astrometryof the recently launched ESA Gaia mission is expected to deliver extremely
accurate statistical parallaxes, and thus distances, to the SMC/LMC. However,an independent SMC/LMC distance determination via main sequence fitting ofstar clusters provides an important validation check point for the Gaia distances.
This has been a valuable lesson learnt from the famous Hipparcos Pleiades
distance discrepancy problem. Current observations will allow hundreds of
LMC/SMC clusters to be analysed in this light.
Today, the most common approach for star cluster main sequence fitting
is still by eye. The process is intrinsically subjective and affected by large
uncertainties, especially when applied to poorly populated clusters. It is

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also, clearly, not an efficient route for addressing the analysis of hundreds,or thousands, of star clusters. These concerns, together with a new attitude
towards advanced statistical techniques in astronomy and the availability of
powerful computers, have led to the emergence of software packages designed
for analysing star cluster photometry. With a few rare exceptions, thosepackages are not publicly available.
Here we present OCAAT, a suite of publicly available open source toolsthat fully automatises cluster isochrone fitting. The code will be applied toa large set of hundreds of open clusters observed in the Washington system,
located in the Milky Way and the Magellanic Clouds. This will allow us togenerate an objective and homogeneous catalogue of distances up to ∼60 kpc
along with its associated reddening, ages and metallicities and uncertainty
estimates.

Quantifying correlations between galaxy emission
lines and stellar continua using a PCA-based
technique
Robert Beck, Laszlo Dobos & Istvan Csabai
Department of Physics of Complex Systems, Eötvös Loránd Tudományegyetem (Eotvos University),
Hungary

We analyse the correlations between continuum properties and emission line
equivalent widths of star-forming and narrow-line active galaxies from SDSS.
We show that emission line strengths can be predicted reasonably well fromthe PCA coefficients of the stellar continuum using the “local multiple linear
regression” method. Since upcoming large sky surveys will make broadband
observations only, theoretical modelling of spectra will be essential to estimate
physical properties of galaxies. Combined with stellar population synthesis
models, our technique will help generate more accurate model spectra andmock catalogues of galaxies to be used to fit data of the new surveys. The moreaccurate modelling of emission lines is also expected to improve templatebased photometric redshift estimation techniques. We also show that, by
combining PCA coefficients from the pure continuum and the emission lines,
a plausible distinction can be made between weak AGNs and quiescent starforming galaxies. The method makes use of a support vector machine, andallows a more refined separation of active and star-forming galaxies than theempirical curve of Kewley et al.

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The Stochastic gravitational wave backgroundgenerated by cosmic string networks
Lara Sousa & Pedro P. Avelino
CAUP – Centro de Astrofı́sica da Universidade do Porto, Portugal

Cosmic string interactions often result in the formation of cosmic string loops
that detach from the long string network, and radiate their energy in the formof gravitational waves. Loop production occurs copiously throughout thecosmological evolution of a cosmic string network and the superimposition of
their emissions gives rise to a stochastic gravitational wave background witha characteristic shape. Computations of the this background are often basedon the assumption that cosmic string networks experience scale-invariant
evolution throughout their evolution. Here, we relax this assumption anddemonstrate that it leads to an underestimation of the amplitude and broadnessof the characteristic peak of the spectrum, that may consequently lead toinaccurate observational constraints on the cosmic string tension.

Cluster strong lensing: a new strategy for testingcosmology with simulations
Madhura Killedar
Ludwig-Maximilians Universität, Germany

Comparisons between observed and predicted strong lensing properties ofgalaxy clusters have been used to claim either tension or consistency withLCDM cosmology. However, standard approaches to such cosmological tests
are unable to quantify the preference for one cosmology over another. We
advocate a Bayesian approach whereby the parameters defining the scaling
relation between Einstein radii and cluster mass are treated as the observables.
We demonstrate a method of estimating the likelihood for observing slope andintercept of this relation under the LCDM framework, using the X-ray selectedz > 0.5 MACS clusters as a case in point and employing both N-body andhydrodynamic simulations of clusters. Besides non-radiative hydrodynamics,
these simulations have been also carried out by including star formation,
chemical evolution, supernovae and AGN feedback, so as to produce a realistic
population of galaxy clusters. We account for the large (mock) sample-tosample variation due to cluster lens triaxiality, within the modelling of thelikelihood function. Cluster selection criteria and characterisation of theIAU Symposium 306 – SCCC21, 2014 — 84/130

Einstein radius are found to play as important a role as the uncertainty related
to the description of star formation and feedback. The relation between triaxial
cluster masses at various overdensities provide a possible alternative to thestrong lensing test.

Using neural networks to estimate redshift
distributions, applied to CFHTLenS and the Dark
Energy Survey
Christopher Bonnett
Institut de Fisica d’Altes Energies – Barcelona, Spain

We present a novel way of using neural networks (NN) to estimate the redshift
distribution of a galaxy sample. We are able to obtain a probability density
function (PDF) for each galaxy using a classification neural network. The
method is applied to 58714 galaxies in CFHTLenS that have spectroscopic
redshifts from DEEP2, VVDS and VIPERS. Using this data we show thatthe stacked PDF’s give an excellent representation of the true N(z) using
information from 5, 4 or 3 photometric bands. Finally a brief overview of thephotometric redshift in the Dark Energy survey obtained by several state of
the art methods will be presented.

Hierarchical probabilistic inference of cosmic shear
Josh Meyers1 , Debbie Bard2 , Dominique Boutigny2 , Will Dawson3 ,David Hogg4 , Dustin Lang5 , Phil Marshall2 & Michael Schneider3
1. Stanford University, USA
2. SLAC – Stanford Linear Accelerator Center, USA
3. LLNL – Lawrence Livermore National Laboratory, USA
4. NYU – New York University, USA
5. CMU – Carnegie Mellon University, USA

Point estimators for the gravitational lensing induced shearing of galaxy images
are complicated by the presence of noise, pixelization, and model uncertainties.
We present a probabilistic forward modeling approach to gravitational lensing
inference that has the potential to avoid the biased inferences in most common
point estimators and is practical for upcoming lensing surveys. The first partof our statistical framework requires specification of a likelihood function
for the pixel data in an imaging survey given parameterized models for theIAU Symposium 306 – SCCC21, 2014 — 85/130

galaxies in the images. We derive the lensing shear posterior by marginalizing
over all intrinsic galaxy properties that contribute to the pixel data (i.e., notlimited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy
properties via hierarchical inference with a suitably flexible intermediate probability distribution specification. We use importance sampling to separate
the modeling of small imaging areas from the global shear inference, thereby
rendering our algorithm computationally tractable for large surveys. With asimple numerical example, we demonstrate the importance of the prior specification for the intrinsic galaxy properties when the data are generated from an
unknown number of distinct galaxy populations with different morphologicalcharacteristics.

High cadence supernova survey with DECamFrancisco Forster1 , Juan-Carlos Maureira1 , Jaime San Martin1 ,Guillermo Cabrera1 , Eduardo Vera1 , Jorge Littin1 , Salvador Flores1 ,Santiago González-Gaitán2 , Lluı́s Galbany2 , Mario Hamuy2 , Thomas de Jaeger2 ,Giuliano Pignata3 , Filomena Bufano3 , Joseph Anderson4 , Robert C. Smith5 &the PESSTO collaboration
1. Universidad de Chile – Centro de Modelamiento Matemático, Chile
2. Universidad de Chile – Departamento de Astronomı́a, Chile
3. Universidad Andrés Bello, Chile
4. ESO – European Southern Observatory
5. CTIO – Cerro Tololo Inter-American Observatory

We report the results of a novel high cadence transient survey with DECam. We
have observed 90 deg2 with a cadence of two hours during 5 nights, transferred
the data to the Center for Mathematical Modelling (CMM) and processed it inreal time using a new pipeline we have specially developed for this purpose.
Candidates were generated three minutes after each observation, allowing us
to change the observational schedule in real time. We found a dozen very
young SNe events, some of them spectroscopically confimed using NTT and
VLT. We have collected some of the earliest light curves known of both corecollapse and Type Ia supernovae, as well as a plethora of transient objets. I
will discuss some progenitor constraints that can be derived from this uniquedata set and implications for future large field of view surveys looking for very
young supernovae and shock breakout events.

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Euclid Space Mission: the current sky survey
Carla Sofia Carvalho1 , Antonio da Silva2,3 , Ismael Tereno1 , on behalf of ECSURV and ESSWG
1. CAAUL – Universidade de Lisboa, Portugal
2. Instituto de Astrofśica e Ciências do Espaço, Portugal
2. Faculdade de Ciências da Universidade de Lisboa, Portugal

We show the current implementation of the Sky Survey for the Euclid ESA
Mission. This is a core deliverable that incorporates scientific goals andtechnical specifications. It demonstrates the feasibility of the mission to cover
the required area within the time span of operations.

Euclid space mission: building the sky survey
J.Amiaux1 , C. Burigana2 , C.S. Carvalho3 , J.C. Cuillandre1 , A. da Silva4,5 , A.
Derosa2 , J. Dinis5,6 , E. Maiorano2 , M. Maris1 0, D. Oliveira7 , R. Scaramella8 , I.
Tereno3 , P. Franzetti9 , B. Garilli9 , M. Meneghetti1 1, S. Wachter12 & the Euclid
Sky Survey Working Group
1. CEA – Comissariat à l’Energie Atomique, France
2. INAF – IASF Bologna, Italy
3. CAAUL – Universidade de Lisboa, Portugal
4. Instituto de Astrofśica e Ciências do Espaço, Portugal
5. Faculdade de Ciências da Universidade de Lisboa, Portugal
6. LOLS – Universidade de Lisboa, Portugal
7. Max-Planck-Institut für Astrophysik, Germany
8. INAF – Osservatorio Astronomico di Roma, Italy
9. INAF – IASF Milano, Italy
10. INAF – Osservatorio Astronomico di Trieste, Italy
11. INAF – Osservatorio Astronomico di Bologna, Italy
12. Max-Planck-Institut für Astronomie, Germany

The Euclid space mission will survey 15000 sq.deg of the extragalactic sky
during 6 years, with a step-stare technique. The scheduling of optimized
observation sequences is constrained by the primary scientific objectives,
spacecraft operations, calibration requirements and sky background. We
present technical aspects of on-going work on the implementation of various
survey scenarios.

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How isotropic is the Universe really?
Dagoberto Contreras & Douglas Scott
University of British Columbia, Canada

The Copernican principle along with General Relativity leads to the FriedmannLemaı̂tre-Robertson-Walker metric has been incredibly successful at describing the large scale structure of our universe. Though like any hypothesis, theCopernican principle should and can be rigorously tested. On the largest scales(up to ` ∼ 64) there are hints that the temperature power is dipole modulated,while the significance of this signal is marginal and not without debate, if true
it would imply that our universe has some preferred direction. Recent tests
suggest that while the dipole modulation goes away for ` ≥ 64 the power stillshows an asymmetry that picks the same direction of the dipole asymmetry up
to ` ≤ 600. The significance of such claims lie at the 3σ level and are unlikely
to change using only temperature data.

Statistical assesment of the relation between theinferred morphological type and the emission-line
activity type of a large sample of galaxies.
René A. Ortega-Minakata, Juan Pablo Torres-Papaqui,Heinz Andernach & Juan Manuel Islas-Islas
Universidad de Guanajuato, México

There is anecdotical evidence of galaxies with different morphologies having
different dominant emission-line activity types. We present here statisticalevidence of the relation between these two characteristics of galaxies for a large
sample of ∼ 800, 000 galaxies from the SDSS-DR7, in the form of confidence
intervals for the differences in the mean morphological type between galaxies
with different activity types.
Using a standard diagnostic diagram based on emission-line ratios, weclassified our large sample of galaxies according to their dominant activity
type. We used the STARLIGHT code to measure the emission-line flux of all
the lines seen in the spectra of the entire sample of galaxies. For our analysis,
we only considered galaxies with the lines relevant to the diagnostic diagramwith S/N > 3.
Also, using known relations between the broad-band colours and a concentration index of their brightness profile of subsamples of these galaxies andIAU Symposium 306 – SCCC21, 2014 — 88/130

their morphology classified by eye, we inferred the morphological type of theaforementioned ∼ 800, 000 galaxies.
Using the R suite of statistical analysis, we then compared the distributionof the inferred morphologies of galaxies of different dominant activity types,
showing the significance of the difference in the median morphological type
between the activity-type samples. We also tested the significance of the difference in the mean morphological type between all the activity-type samples
using an ANOVA model with a modified Tukey test that takes into accountheteroscedasticity and the unequal sample sizes. We show this test in the formof simultaneous confidence intervals for all pairwise comparisons of the meanmorphological types of the samples.

VEJA - Visual Exploration Just Anywhere
André Moitinho1 , Tiago Mendes2 , Bruno Rodrigues2 , Miguel Gomes1 ,Alberto Krone-Martins1 & Francisco M. Couto3
1. SIM – Universidade de Lisboa, Portugal
2. Universidade de Lisboa, Portugal
3. LASIGE – Universidade de Lisboa, Portugal

Visual data exploration is essential to the scientific process. It can provide
scientific insight that blind statistical analysis cannot. Often, this visual insightis the starting point and even the guiding reference for scientific thought.
The extremely large archives produced by today’s astronomical surveys
and observatories, together with the Virtual Observatory standards for datainterexchange and application messaging are producing a paradigm shift in theway data is explored. The tendency is becoming not to download the data to
the user’s workstation and explore it locally, but instead to use on-line services
for querying and exploring those archives. Thus, it also becomes natural toaddress modern visual data exploration with on-line services. Indeed, thisis becoming a reality and recent services such as rapidgraph and plotly arereceiving attention from the astronomical community.
Here we present VEJA , a package for implementing an interactive visual
exploration web service. VEJA is being developed as part of a course workin the Bioinformatics master at the University of Lisbon and is the result of
collaboration between astronomy (SIM) and informatics (LASIGE) Centres.
Although conceived for the needs of astronomers, it can be used with any kindof tabular point data. VEJA supports multiple panels with linked views foreasing the exploration of multi-dimensional data sets. It currently accesses any

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table made available by CDS-Vizier. The plots can be annotated and publishedon social networks, providing a collaborative data exploration facility. Because
VEJA is web based, no software besides a browser is required on the clientside, thus enabling data exploration and collaboration also on mobile phones
and tablets.

Pulsar data interpolation via curvlet transform andRadon transform based dedispersion
Hao ShanXinjiang Observatory of Chinese Academy of Sciences, China

Curvelet is a multiresolution and multidirection transform, which belong
to a family, including redgelet, shearlet, physical wavelet. They all comefrom wavelet, adding a direction information. The algrithm of curvelet isfirst transform the original image into frequency doman, then use a wedge
like window to split the whole frequency plane, at last take a inverse fouriertransform for every window. Curvelet is proven to be the optimal sparse
representation for 2-order continuous curve. We assume that pulsar data has
missing data of some frequencies for filterbank. A simultaneous denoise
and interpolation method is taken. A simple idea of compressive sensing
is to transform the objective function to a proximate operator and solve amore simple problem. Then the non-differential l1 term can be split into two
differential term. We take iterative threshold/shrinkage method to solve thisproblem in this work. Radon tranform is another sparse transform for pulsar
data. Different from curvlet tranform, it is not multiscale or multidirection,
but it is not necessary for pulsar data. The interpolation result with radontransform shows bad performance. Thus we know, radon transform is used fordectetion, not for processing, except special designed radon transform. Radontransform is an idea, or a theory frame. We can construct radon transform for
integration on any continuous curve and a fast radon transform accompanied.
We know that in theory pulse arrive time has a hyperbolic relationship withfrequency. So we can construct a hyperbolic radon transform for pulsar data.
A parabolic in original is transformed into a point in radon domain. One axis
coresponding to time and another to curve bending degree, which is related to
DM. So this method is a fast algrithm to find the right DM value. Once theDM is found, we can use incoorelated method to continue dedispersion.

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The first analytical expression to estimate
photometric redshifts suggested by a machine
Alberto Krone-Martins1 , Emille E. O. Ishida2,3 & Rafael S. de Souza4,5
1. SIM – Universidade de Lisboa, Portugal
2. Max-Planck-Institut für Astrophysik, Germany
3. Universidade de São Paulo, Brazil
4. Korea Astronomy & Space Science Institute, Korea
5. Eötvös Loránd Tudományegyetem (Eotvos University), Hungary

Symbolic regression is a novel methodology that was recently proposed toautomatically search for underlying analytical laws in data (Schmidt, 2009). Its
importance has been highlighted into astronomy by Graham et al., (2013), andthis work is the first attempt to use it in a cosmological context. To demonstrate
the potential of machine proposed analytical relations in providing simple andreliable photo-z estimates, we applied the aforementioned method to derive
an analytic expression for photometric redshift (photo-z) determination from
Sloan Digital Sky Survey 10th data release (SDSS-DR10, Ahn et al., 2013).
We report the first analytical expression purely constructed by a machine
to determine photometric redshifts (zphot ) of galaxies. A simple and reliable functional form is derived using 41, 214 galaxies from the SDSS-DR10
spectroscopic sample. The method automatically dropped the u and z bands,
relying only on g, r and i for the final solution. Applying this expression
to other 1, 417, 181 SDSS-DR10 galaxies, with measured spectroscopic redshifts (zspec ), we achieved a mean h(zphot − zspec )/(1 + zspec )i . 0.0086 and ascatter σ(zphot −zspec )/(1+zspec ) . 0.045 when averaged up to z . 1.0. This is thefirst use of symbolic regression in cosmology, representing a leap forward inastronomy-data-mining connection.

Entropy in universes evolving from initial to final deSitter eras.
José Pedro Mimoso1,2 & Diego Pavón3
1. Faculdade de Ciências da Universidade de Lisboa, Portugal
2. CAAUL – Centro de Astronomia e Astrofı́sica da Universidade de Lisboa, Portugal
3. Universidad Autónoma de Barcelona, Spain

This work studies the behavior of entropy in recent models of cosmic evolutionthat start with an initial de Sitter expansion phase, go through the conventional

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radiation and matter dominated eras to be followed by a final and everlasting deSitter expansion. In spite of their seemingly similarities (from the observational
viewpoint they are arbitrary close to the conventional Lambda-CDM model),different models deeply differ in their underlying physics. Our study reveals
that thermodynamic equilibrium is approached in the last de Sitter era. This
happens in the sense that the entropy of the apparent horizon plus that ofmatter and radiation inside it increases and is concave. Accordingly, this classof models is thermodynamically correct. Cosmological models that do not
approach equilibrium at the last phase of their evolution appear in conflict withthe second law of thermodynamics. [Based on the Ref: Phys.Rev. D87 (2013)047302]

A Lemaitre-Tolman-Bondi Void Imprinting theCosmic Microwave Background Cold Spot
F. Finelli1 , J. Garcia-Bellido2 , A. Kovacs3 , F. Paci4 & I. Szapudi5
1. INAF Istituto di Astrofisica Spaziale e Fisica Cosmica di Bologna, Italy
2. Instituto de Fı́sica Teórica, Universidad Autónoma de Madrid, Spain
3. Eötvös Loránd Tudományegyetem (Eotvos University), Hungary
4. SISSA – Scuola Internazionale Superiore di Studi Avanzati, Italy
5. University of Hawaii, USA

The Cold Spot, one of the most significant of anomalies in the Cosmic Microwave Background, could be of primordial origin or caused by a foregroundstructure. The recently constructed WISE-2MASS all-sky infrared catalogue
has an underdensity in the direction of the Cold Spot with an angular size 10’sof degrees, and as deep as δ ' −0.16 in the center. We show that a spherical
Lemaitre-Tolman-Bondi (LTB) void model with a novel profile can simultaneously fit the underdensity in the WISE-2MASS catalogue and the Cold Spotas observed by the Wilkinson Anisotropy Probe and Planck satellites. Thus an
LTB supervoid is a prime candidate for an explanation of this anomaly, whilea texture model gives a poor fit of the Cosmic Microwave Background profile.
When the galaxy bias measured from the large scale angular power spectrum
is taken into account, a simultaneous three parameter fit for the void modeland the temperature profile gives z = 0.21 for the redshift of the supervoid,r0 = 235h−1 M pc for the size of the void, and δ0 = −0.11 for the depth ofthe void. These parameters fit from the projected data alone are in excellent
agreement with the results of Szapudi et al. 2014, who used photometricredshifts from Pan-STARRS1 for direct tomographic imaging of the void.

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Sparse Inpainting and Isotropy
Stephen Feeney1 , Domenico Marinucci2 , Jason McEwen3 , Hiranya Peiris3 ,Benjamin Wandelt4 & Vamentina Cammarota2
1. Imperial College London, United Kingdom
2. Università degli Studi di Roma Tor Vergata, Italy
3. University College London, United Kingdom
4. Institute d’Astrophysique de Paris, FranceSparse inpainting techniques are gaining popularity as a tool for cosmological
data analysis, in particular for handling data with masked regions or missing
observations. We investigate here the relationship between sparse inpainting
techniques using the spherical harmonic basis as a dictionary and the isotropy
properties of cosmological maps, as for instance those arising from cosmic
microwave background (CMB) experiments. In particular, we investigate
the possibility that inpainted maps may exhibit anisotropies in the behaviourof higher-order angular polyspectra. We provide analytic computations andsimulations of inpainted maps for a Gaussian isotropic model of CMB data,suggesting that the resulting angular trispectrum may exhibit small but nonnegligible deviations from isotropy.

The halo mass of GAMA galaxy groups frommaximum-likelihood weak lensing
Jiaxin Han1 ,Vincent Eke1 , Carlos Frenk1 , Rachel Mandelbaum2 , Peder Norberg1 ,Michael Schneider3,4 , John Peacock5 ,Yipeng Jing6 , Ivan Baldry7 , Joss BlandHawthorn8 & Jon Loveday9
1. Durham University, United Kingdom
2. Carnegie Mellon University, USA
3. LLNL – Lawrence Livermore National Laboratory, USA
4. University of California Davis, USA
5. University of Edinburgh, United Kingdom
6. Shanghai Jiaotong University, China
7. University of Liverpool, United Kingdom
8. University of Sydney, Australia
9. University of Sussex, United Kingdom

We present a maximum-likelihood weak lensing analysis of the mass distribution in optically selected Galaxy Groups (G3Cv1) in the Galaxy And Mass

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Assembly (GAMA) survey, using background SDSS galaxies. The scalingof halo mass, Mh, with various group observables is investigated. Our main
results are: 1) the measured relations of halo mass with group luminosity, virial
volume and central galaxy stellar mass, M? , agree very well with predictions
from mock group catalogues constructed from a GALFORM semi-analyticalgalaxy formation model; 2) the measured relations of halo mass with velocity
dispersion and projected half-abundance radius show weak tension with mockpredictions, hinting at problems in the mock galaxy dynamics and their small
scale distributions; 3) the median Mh|M? , which can be measured using weaklensing, depends more sensitively on the dispersion in M? at fixed Mh than it
does on the median M? |Mh . Our measurement suggests an intrinsic dispersion of σ log(M? ) ∼ 0.15; 4) Comparing our mass estimates with those in the
catalogue, we find that the G3Cv1 mass can give biased results when used to
select subsets of the group sample. Of the various new halo mass estimatorsthat we calibrate using our weak lensing measurements, group luminosity is
the best single-proxy estimator of group mass.

Sizes and Magnitudes in Weak Gravitational Lensing
Justin Alsing1 , Alan Heavens1 , Andrew Jaffe1 & Donnacha Kirk2
1. Imperial College London, United Kingdom
2. University College London, United Kingdom

Light from distant galaxies is continuously deflected by the gravitational fieldof intervening large-scale density inhomogeneities in the Universe on its way
to Earth. This weak gravitational lensing results in distortions in the projected
images of galaxies on the sky, modifying their shapes (cosmic shear), sizes
and magnitudes (through the convergence field) at the % level. The intrinsic
shape, size or flux of an observed galaxy is not known a priori, so the lensing
effect is detected statistically.
Traditionally, the statistic of choice has been cosmic shear. However, othereffects such as the magnification of sizes and magnitudes can be used to add
statistical power. Furthermore, each observable is subject to its own set ofobservational and theoretical systematic effects. This provides very strong
motivation for developing a number of independent probes, each sufferingfrom different systematic effects.
In this work we compute the additional information in sizes and magnitudes
of individual sources in addition to galaxy shapes. This question neatly splits
into two parts: firstly, we explore how well we can (statistically) determine theIAU Symposium 306 – SCCC21, 2014 — 94/130

convergence field from sizes and magnitudes given their intrinsic distribution;
we measure the joint distribution of galaxy sizes and magnitudes in CFHTLenS
data and find that expect to recover the convergence with an effective dispersionof 0.7 per galaxy; secondly, we show that considerable gains may be possible
from combining size and magnitude information with a cosmic shear analysis.
Neglecting systematic errors, we find a 30% improvement in the Dark Energy
Figure of Merit. In a more optimistic scenario, including intrinsic alignments
for shear (but neglecting intrinsic size-magnitude correlations) the FoM isincreased by as much as 80%, from the same data.

The Gaia archive: delivering the promise of Gaia
Alberto Krone-Martins1 , Andre Moitinho1 , Xavier Luri2 , William O’Mullane3 ,Anthony Brown4 , Timo Prusti5 , on behalf of the Gaia Data Processing andAnalysis Consortium’s Coordination Unit 9
1. Universidade de Lisboa, Portugal
2. Universitat de Barcelona, Spain
3. European Space Agency – ESAC
4. Universiteit Leiden, Netherlands
5. European Space Agency – ESTEC

ESA’s Gaia mission is the next European breakthrough in Astronomy, a cornerstone mission launched in december 2013 aimed at producing the mostaccurate 3D map of the Milky Way. The resulting census of our Galaxy will
represent a giant leap in astrometric accuracy, complemented by the only fullsky homogeneous photometric survey with angular resolution comparable
to the Hubble Space Telescope, as well as the largest spectroscopic survey
ever undertaken. Its scientific bounty will be immense, not only unravellingthe formation history and evolution of our Galaxy, but also providing precise
and accurate calibrations of the cosmic distance ladder, revealing and classifying thousands of extra-solar planetary systems, minor bodies within oursolar system and millions of extragalactic objects - including about a million
quasars.
In this context, to support the main goals of Gaia the archive must beable to answer complex questions involving the analysis of more than one
billion sources that will comprise one petabyte at the end of the mission.
But what makes this archive unique is that beyond its size it will also be
intricately interrelated: no other survey exists or is planned which delivers all
sky astrometry, photometry and spectroscopy.

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The Gaia archive is being designed largely through science requirements
gathered from the astronomical community. Accordingly, its structure covers
from detailed documentation to visualization, passing through management,
the actual architecture and development, data validation, operation and services, education and outreach and science enabling applications.
In this poster we will present an overview of the planned Gaia data releases
and the near term archive structure with its functionalities, specially emphasizing the first two data releases planned for end-2015 and mid-2016. Finally, we
will also present a glimpse of what might be available in the archive by thetime the final catalogue is ready, seven years from now.

1-point Statistics of Reionization
Catherine A. Watkinson & Jonathan R. Pritchard
Imperial College London, United Kingdom

Much attention to date has been focussed on the power spectrum of the 21-cm
brightness temperature during reionization; I will discuss several potentially
useful signatures exhibited by the simpler and more easily measured 1-point
statistics. To do so I shall consider a selection of semi-analytical simulations
that each model different physical processes that may have occurred during
reionization such as, [1] the clumping of LLS and residual neutral hydrogenthat we expect to see embedded in large-scale ionized bubbles forged by thecollective radiation of galaxy clustering, and [2] spin-temperature fluctuations
resulting from the inhomogeneous heating of the IGM. We will see how eventhe current generation of radio telescope should be able to provide insight into
the nature and timing of reionization using 1-point statistics.

Weak Gravitational Lensing with Future Radio
SurveysPrina Patel
University of the Western Cape, South Africa

Weak gravitational lensing is a promising cosmological probe with futureradio surveys with upcoming radio facilities such as eMERLIN, LOFAR andeventually the SKA. Since weak lensing has up till now primarily been in
the optical domain, exploration of it’s feasibility through simulations has
recently begun. In this talk I highlight the reasons why radio weak lensing is

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an attractive cosmological prospect and also why it has several advantages over
it’s optical counterpart. I shall also describe a weak lensing simulation pipelinethat we have begun to develop and how we have used it to begin exploring
the problem of shape measurement with radio interferometric data. In lightof the vastly improved data rate capabilities of future radio interferometers I
also describe potential issues that need to be considered for the future radio
surveys.

Extreme-Value Statistics for Testing Dark Energy
Simone Aiola
University of Pittsburgh, USA

The accelerated expansion of the universe leaves an imprint in the cosmic microwave background temperature fluctuations on large angular scales, known
as the late-time integrated Sachs-Wolfe Effect. A detection of this signal
has been claimed at 4.4-sigma significance by stacking temperature patchesaligned with superstructures identified in the Sloan Digital Sky Survey. Recently, several authors have argued that this strong detection is in tension
with the standard Lambda-CDM model at more than a 3-sigma level. I will
present estimates of the expected signal by computing extreme-value statistics
on Gaussian random realizations of the microwave sky temperature fluctuations. Such simulations include the effect of anisotropies on small angularscales as well as the correlations between various temperature components,
and are simpler to construct and interpret than models of the signal basedon large-scale structure simulations. I will also discuss prospects for using
extreme-value statistics with weak lensing of the microwave background, andfor constraining properties of dark energy.

The Needlet CMB Trispectrum
Antonino Troja1 , Domenico Marinucci2 , Simona Donzelli3 & Davide Maino1
1. Università degli Studi di Milano, Department of Physics, Italy
2. Università degli Studi di Roma Tor Vergata, Department of Mathematics, Italy
3. INAF – Istituto di Astrofisica Spaziale e Fisica Cosmica, Milano, Italy

The Inflationary models describe the dynamics of the first instants of the
Universe. Each model introduces a characteristic track of non-Gaussianity
into the anisotropy distribution of the Cosmic Microwave Background (CMB)

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radiation. The amount of non-Gaussianity is parametrized by the constants fNL
and gNL . Constrain fNL and gNL then means constrain the inflationary models.
fNL and gNL parametrize also the amplitude of the bispectrum and trispectrumof the anisotropy distribution, that are the harmonic counterpart of the 3point and 4-point correlation function. Although there exist several optimal
bispectrum estimators that allowed to evaluate fNL with high confidence, thelack of an optimal trispectrum estimator prevented the evaluation of strong
contraints on gNL . I derived for the first time an optimal estimator for thetrispectrum based on the Fourier transform on the sphere, using in particular
the Spherical Needlets system. Spherical Needlets are a wavelet system on
the sphere whose property make them the closest system to the Spherical
Harmonics, i.e. the orthonormal basis of the functions defined on the sphere,
and improve the statistics in presence of incomplete maps with respect to theSpherical Harmonics. Moreover, I implemented a software able to calculate
the trispectrum on CMB data. The software will be applied on Planck data.
It should allow to compute the amplitude of gNL with a statistical precision
never achieved before in order to put strongest constraints on the inflationary
scenarios.

Evidence for a Lower Value for H0 from Cosmic
Chronometers Data
Vinicius C. Busti1 , Chris Clarkson1 & Marina Seikel2,1
1. University of Cape Town, South Africa
2. University of Western Cape, South Africa

An intriguing discrepancy emerging in the concordance model of cosmology
is the tension between the locally measured value of the Hubble rate, and theglobal value inferred from the cosmic microwave background (CMB). This
could be due to systematic uncertainties when measuring H0 locally, or it could
be that we live in a highly unlikely Hubble bubble, or other exotic scenarios.
We point out that H0 can be found by extrapolating H(z) data points at high-z
down to z = 0. By doing this in a Bayesian non-parametric way we can find amodel-independent value for H0 . We apply this to 19 measurements based on
differential age of passively evolving galaxies as cosmic chronometers. We
find H0 = 64.9 ± 4.2 km s−1 Mpc−1 (1σ ), in agreement with the CMB value,
but reinforcing the tension with the local value. An analysis of possible sourcesof systematic errors shows that the stellar population synthesis model adopted
may change the results significantly, being the main concern for subsequent

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studies. Forecasts for future data show that distant H(z) measurements canbe a robust method to determine H0 , where a focus in precision and a carefulassessment of systematic errors are required.

Cosmic Infrared Background (CIB) anisotropies with
Planck and their correlation with Large Scale
Structures
Paolo Serra1 on behalf of Planck Collaboration
1. Institut d’Astrophysique Spatiale, Orsay, France

The power spectrum of Cosmic Infrared Background (CIB) anisotropies issensitive to the link between star formation and dark matter halos over theentire cosmic star formation history. We present a model that associates
star-forming galaxies with dark matter halos and their sub-halos and that has
been used by the Planck collaboration to interpret the latest (2013) accurate
measurements of the CIB power spectra at all scales. We discuss constraints
on the cosmic star formation history, cosmic dust evolution and dark matter- galaxy bias. We finally present results from the cross-correlation of CIB
sources with other tracers of the dark matter field.

Methods of Cosmological Models Selection
Wlodzimierz Godłowski1 , Marek Biesiada2 & Zong-Hong Zhu3
1. Institute of Physics, Uniwersytet Opolski, Poland
2. Department of Astrophysics and Cosmology, Institute of Physics, University of Silesia, Poland
3. Department of Astronomy, Beijing Normal University, China

One of the crucial problem of modern observational cosmology is the problem of discrimination between different cosmological models. This difficulty,
called as the degeneracy problem is that many different scenarios are compatible with the present day observations. To solved this problem we use the
combined analysis of astronomical data like supernovae type Ia (SNIa) data,
Fanaroff-Riley type IIb (FRIIb), Radio Galaxy (RG) data, baryon oscillation
peak and cosmic microwave background radiation (CMBR) We use the Akaike
and Bayesian information criteria of model selection as well as evidence andinformation entropy to overcome this degeneracy and to determine a modelwith such a set of parameters which gives the most preferred fit to the data.
Moreover we show that different cosmological models give different predic-

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tions for value of parameters like for example Ωm,0 . These value could becompared with independent astrophysical measurements and as results theyalso could be used for discrimination between models.

X-ray cross-correlation analysis of low-mass X-ray
binary 4U 1636-53
Yajuan Lei
National Astronomical Observatory, Chinese Academy of Sciences, China

With Rossi X-ray Timing Explorer data, we analyze the cross-correlations of
the soft and hard X-rays of the atoll source 4U 1636-53. The results show thatthe cross-correlations evolve along the different branches of the color–color
diagram. The cross-correlations of two atoll sources 4U 1735-44 and 4U
1608-52 have been studied in previous work. We compare the results of 4U
1636-53 with those of 4U 1735-44 and 4U 1608-52.

Shape estimation for Košice, Almahata Sitta andBassikounou meteorites
Vladimir Vinnikov1 , Maria Gritsevich1,2,3 & Leonid Turchak1
1. Dorodnicyn Computing Centre of the Russian Academy of Sciences, Russia
2. Finnish Geodetic Institute, Finland
3. Lomonosov Moscow State University, Institute of Mechanics, Russia

Each meteorite sample can provide data on chemical and physical properties
of interplanetary matter. The set of recovered fragments can give additional
insights into the history of the parent asteroid. A reliably estimated meteoroid
shape is a valuable input parameter for for the atmospheric entry scenario,
since the pre-entry mass, terminal meteorite mass, and fireball luminosity areproportional to the pre-entry shape factor of the meteoroid to the power of
3 [1]. We present a statistical approach to the estimation of meteoroid preentry shape [2], based on the detailed data on surviving meteorite fragments
recovered on the ground. This is a continuation of our recent study on the
fragment mass distribution functions for the Košice meteorite fall [3]. It is
known that the brittle shattering has fractal properties similar to many othernatural phenomena [4]. This self-similarity for scaling mass sequences is
described by power law statistical expressions [5]. We apply the technique ofscaling analysis of shapes to statistically abundant empirical data on the mass
distributions for Košice, Almahata Sitta and Bassikounou meteorites.

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Based on: [1] Gritsevich M. and Koschny D. 2011. Constraining theluminous efficiency of meteors. Icarus, 212(2): 877-884. [2] OddershedeL., Meibom A. and Bohr J. 1998. Scaling analysis of meteorite shower mass
distributions. Europhys. Lett, 43(5): 598-604. [3] Gritsevich M., Vinnikov
V., Kohout T., T’oth J., Peltoniemi J., Turchak L., and Virtanen J. 2014. A
comprehensive study of distribution laws for the fragments of Košice meteorite.
Meteorit. Planet. Sci. 49: 1-19, in print. [4] Lang B. and Franaszczuk K. 1986.
Fractal Viewpoint of Fragmentation of the Lowicz Meteorite. Meteoritics,
21:428 [5] Oddershede L, Dimon P and Bohr J. 1993. Self-organized criticality
in fragmenting. Phys Rev Lett. 71(19):3107-3110.

Insights into physical properties of meteoroids fromempirical distributions of meteorite fragments
Maria Gritsevich1,2 , Vladimir Vinnikov2 , Tomáš Kohout3,4 , Juraj Tóth5 ,Jouni Peltoniemi3,1 , Leonid Turchak2 & Jenni Virtanen1
1. Finnish Geodetic Institute, Finland
2. Russian Academy of Sciences, Russia
3. University of Helsinki, Finland
4. Academy of Sciences of the Czech Republic, Czech Republic
5. Comenius University, FinlandThis study focuses on evaluating pre-atmospheric meteoroid mass and its
other properties based on the recovered meteorite fragments and observed
atmospheric trajectory. Meteorite studies represent a low-cost possibility toprobe cosmic matter reaching planetary surface and it complements resultsof sample-return missions bringing back pristine samples of the materials.
As example, we study the details of the Košice meteorite fall (February 28,2010) and derive a reliable law describing the mass distribution among therecovered fragments (Gritsevich et al. 2014). Bimodal Weibull, bimodal Grady
and bimodal lognormal distributions are found to be the most appropriate fordescribing the Košice fragmentation process. Based on the assumption ofbimodal lognormal, bimodal Grady, bimodal sequential and bimodal Weibull
fragmentation distributions, we suggest that, prior to further extensive fragmentation in the lower atmosphere, the Košice meteoroid was initially represented
by two independent pieces with cumulative residual masses of approximately
2 kg and 9 kg respectively. The smaller piece produced about 2 kg of multiple
lightweight meteorite fragments with the mean around 12 g. The larger one
resulted in 9 kg of meteorite fragments, recovered on the ground, including

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the two heaviest pieces of 2.374 kg and 2.167 kg with the mean around 140
g. Based on our investigations, we conclude that two to three larger Košice
meteorite fragments of 500-1000g each should exist, but were either not recovered or not reported by illegal meteorite hunters. The proposed approachhelps to summarize the data on existing terrestrial impacts and to formulate
recommendations for further studies valuable for planetary defense.

Statistical analysis of cross-correlation samples of
3XMM-DR4 with SDSS-DR10 and UKIDSS-DR10
Yanxia Zhang1 , Yongheng Zhao1 , Xue-Bing Wu2 & Haijun Tian1
1. National Astronomical Observatory, China
2. Peking University, China

We match the XMM-Newton 3XMMi-DR4 catalog with the Sloan Digital
Sky Survey (SDSS) Data Release 10. Based on this the X-ray/optical catalog,
we probe the distribution of various types of X-ray emitters in the multidimensional photometric parameter space. It is found that quasars, galaxies
and stars have some kind distribution rule, especially for stars. Then wecross-correlate this X-ray/optical catalog with United Kingdom Infrared DeepSky Survey (UKIDSS) Data Release 10, obtain a X-ray/optical/near-infraredcatalog. The result shows that the dominant soft-X-ray-source populationis relatively nearby coronally-active stars while the hard-X-ray-source population remains uncertain considering the known classes of accreting andnon-accreting systems.

Data-mining based expert platform for the spectra
inspecting
Haijun Tian, Yang Tu, Yanxia Zhang, Yongheng Zhao & Xuelei Chen
National Astronomical Observatory, China

With the surveys ongoing, such as LAMOST, Pan-STARRS1, etc., more andmore spectra are collected, which are critically important for the scientificresearch. However, except the good qualified data, there still exist many
“unknown” spectra. Usually most of these spectra are normal objects with
low SNR, which can not be classified by the automated pipeline. These partsof data should be integrated of the survey. Moreover, some important new
discoveries are probably hided in these data. Therefore, we should not give up

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these seemingly discarded data. How to handle these data is one of the biggest
challenges to the modern statistics and data mining techniques. If the SNR ofspectra are too low to be processed automatedly, we must motivate experts
to inspect them by eye. Due to a large amount of such spectra generated
continuously by the survey, it will take much time and efforts to check these
spectra one by one.
We propose a scheme aiming to set up a platform to efficiently manage
these datasets and assist the experts to inspect the spectra. The platform is athree-tier structure, including the database layer, data mining layer and expert
layer. The key part is the data mining. Before the inspecting, the dataset will be
preprocessed with various statistical and data-mining techniques. For instance,
the dataset can be classified roughly according to the limited information, thebest-fit templates could be found by the chi-square technique, the redshift
could be estimated through dividing the spectra into multiple photometricfilters, etc. All of the results from the data-ming could efficiently assist theexperts. The expert layer provides an interface by which experts with different
weight levels may check the spectra and give the results. Finally the systemgives a more reliable result according to the experts’. The VO-enalbed client
will be of diverse forms, such as Matlab-GUI, Java-application, Java-applet,etc.

Markov Chain Monte Carlo Constraints on the
Evolution of the Far-IR Luminosity Function
Noah Kurinsky
Tufts University, USA

We have developed a novel Markov Chain Monte Carlo fitting software package which enables a user to combine multi-wavelength, high redshift galaxy
observations with SED templates to constrain the evolutionary properties ofa generic luminosity function. This is achieved through Monte Carlo simulation of galaxy populations, observed through band passes with user-definedproperties. I will demonstrate the application of this program to far-infrared
galaxies, particularly those observed with Herschel, and discuss how it may
easily be adapted to other regimes, or used to simulate surveys conducted with
future instruments, given assumed luminosity functions and SED models. The
MCMC functionality and simulation aspect of this package has been written
entirely in C++ and should be highly portable to other programs, and the classbased approach allows various aspects of the simulation to be modified without

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interfering with the main functionality. We have also created an interactive
widget written for IDL, which may also be used to modify inputs and plot
outputs and run simulations through simple point and click functionality. Our
hope is to share this new program with the astrostatistics community such that
others with similar analyses may find use for it in their own research.

The new method of the analysis on the orientation ofgalaxies in structures
Wlodzimierz Godłowski1 , Paulina Piwowarska1 & Piotr Flin2
1. Institute of Physics, Uniwersytet Opolski, Poland
2. Institute of Physics, Jan Kochanowski University, Poland

Problem of large structure formation is one of the most important problems inmodern cosmology and extragalactic astronomy. Investigating the orientationof galaxies is a standard test for scenarios of galaxy formation since different
theories of galaxy formation make various predictions regarding the angularmomentum of galaxies. A new method of analyzing galaxy alignments inclusters proposed by Godłowski 2012 now is improved The distribution of
position angles for galaxy major axes was analyzed, as well as the distributionof the two angles describing the spatial orientation of the galaxy plane, bothof which provide information about galaxy angular momenta. The orientationof galaxies in groups and clusters of galaxies is discussed, and the results
illustrate the dependence of alignment with respect to cluster richness. The
implications for theories of galaxy formation are also discussed.

Exploring the total Galactic extinction with SDSSBHB stars
Hai-Jun Tian, Chao Liu, Jing-Yao Hu, Yang Xu & Xue-Lei Chen
National Astronomical Observatory, China

Aims: We use 12,530 photometrically-selected BHB stars from Sloan Digital
Sky Survey to estimate, the total extinction of the Milky Way in high Galactic
latitude, RV and AV in each line of sight.
Methods: A Bayesian method is developed to estimate the reddening
values in the given lines of sight. Based on the most likely values of reddening
in multiple colors, we are able to derive the values of RV and AV .

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Results: We select 94 zero-reddened BHB stars from 7 globular cluster as
the template. The reddening in the 4 SDSS colors for the northern Galactic cap
are estimated by comparing the field BHB stars with the template stars. The
accuracy of this estimation is around 0.01mag for the most line of sights. We
also obtain <RV> to be around 2.40 ± 1.05 and AV map with in uncertaintyof 0.1mag. The results, including reddening values in the 4 SDSS colors, AV ,and RV in each line of sight, are released on line. In this work, we employ an
up-to-date parallel technique on GPU card to overcome the time-consuming
computation. We plan to release online the C++ CUDA code used for thisanalysis.
Conclusions: The extinction map derived from BHB stars is highly consistent with that from Schlegel, Finkbeiner & Davis (1998). The derived RV
is around 2.40 ± 1.05. The contamination probably makes the RV tend to belarger.

Automatic stellar spectral parametrization pipeline
for LAMOST survey
Yue Wu, Ali Luo, Bing Du, Yongheng Zhao
Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of
Sciences, China

The LAMOST project is performing the 2nd year of its general survey. It
finished its pilot survey and the 1st year generally survey with First Data
Release (DR1) of more than 2.2 million medium resolution spectra as an
output. One of the two main components of the project is the LAMOST
Experiment for Galactic Understanding and Exploration (LEGUE) which is
focusing on the formation and evolution of the Milky Way. To automatedand credibly derive the intrinsic physical properties of the Galactic member
stars plays a significant role between the large survey database and the goodscience outcomes. Thus, we developed and implemented the LAMOST stellar
parameter pipeline (LASP) which is an automatic parameterization for thefundamental stellar atmospheric parameters (effective temperature, surface
gravity, metallicity and radial velocity) for AFGK-type stars observed during
the LEGUE survey. Based on the algorithms CFI and ULySS, by fitting thespectra, LASP executed in two stages. First we exploit CFI to quickly get a
set of coarse estimations, second by using CFI results as an initial guesses,
we adopt ULySS to obtain the final determined credible measurements. With
using some external data set, we tested the performance of the LASP through

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various comparisons and validations in a serials of previous work. LASP was
integrated into the LAMOST Spectra Analysis Pipeline which was combinedwith three modular, 2D pipeline (raw data reduction), 1D pipeline (classification) and LASP. With the LAMOST DR1, a stellar atmospheric parameterscatalogue, which contains 1,085,404 stars was simultaneous released, till now
this product was characterized as the largest one in the world. Consideringof five years operation, further LAMOST survey will yield more than 10
million objects covering in a wider sky area and depth, this will broaden the
expected Science especially for the characterization of the Galaxy with various
evolutionary stages of the stars collected.

Effects of primordial magnetic fields on CMB
Hector J. Hortua1,2 & Leonardo Castaneda2
1. Fundacion Los Libertadores, Colombia
2. Universidad Nacional de Colombia, Colombia

The origin of large-scale magnetic field is an unsolved problem in modern
cosmology. In order to overcome this problem, a possible scenario comes fromthe idea that these fields emerged from a small primordial field produced in
the early universe. This field could lead to the observed large-scales magnetic
fields but also, would have left an imprint on the CMB. In this work wesummarize some statistical properties of this primordial magnetic fields on
the FLRW background Universe. Then, we show the resulting magnetic
field power spectrum using the gauge invariant approach in cosmologicalperturbation theory and we describe some effects of primordial magnetic fields
on the CMB anisotropies.

ANNz2 - A new code for galaxy redshift estimation,using machine-learning methods.
Iftach Sadeh
University College London, United Kingdom

Large photometric galaxy surveys are increasingly becoming an important toolfor exploring the large-scale structure of the universe. As such they allow the
study of questions at the forefront of science, such as the nature of dark energy.
The success of photometric surveys greatly depends on the ability to measure
the photometric redshifts of objects (photo-zs) based on limited spectral data. A

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new major version of the public photo-z estimation software, ANNz, has beendeveloped. The new code incorporates several machine-learning methods, suchas artificial neural networks, boosted decision trees and k-nearest neighbours,
implemented in the TMVA software package. The different algorithms are usedin concert in order to optimize the photo-z reconstruction performance, andto estimate the uncertainties of the photometric solutions. The uncertainties
are further used to derive probability density functions (PDFs), in addition
to the corresponding best-fit solutions. An alternative method is also used to
calculate PDFs, in which the redshift region is divided into multiple bins; thePDFs are derived from the combined probabilities of an object occupying agiven redshift-bin, estimated using machine-learning classification techniques.
The new code is also adapted to provide solutions to general classification
problems, where the different machine-learning methods are dynamically
optimized and compared.

Biases on cosmological parameter estimators fromgalaxy cluster number counts
Mariana Penna-Lima1 , Martı́n Makler2 & Carlos Alexandre Wuensche1
1. Instituto Nacional de Pesquisas Espaciais, Brazil
2. Centro Brasileiro de Pesquisas Fı́sicas, Brazil

The abundance of galaxy clusters is becoming a standard cosmological probe.
In particular, Sunyaev-Zel’dovich (SZ) surveys are promising probes of the
Dark Energy equation of state, given their ability to find distant clusters andprovide estimates for their mass. However, current SZ catalogs contain tens tohundreds of objects. In this case, it is not guaranteed that maximum likelihood
estimators of cosmological parameters are unbiased. In this presentation weshow the study of estimators from cluster abundance for some cosmologicalparameters. We use the Monte Carlo approach to determine the presence ofbias and its behavior with both area and depth of the survey, and the numberof cosmological parameters fitted simultaneously. Our fiducial models are
based on the South Pole Telescope SZ survey. Assuming perfect knowledge onmass and redshift, we obtain that some estimators have non negligible biases.
For example, the bias of σ8 corresponds to 37% of its statistical error bar
when it is fitted together with the cold dark matter density parameter Ωc andthe dark energy equation of state parameter w0 . Including mass and redshiftuncertainties, decreases the relevance of the bias in comparison with the error
bars. Considering a joint likelihood for cluster abundance and distance priors

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from the cosmic microwave background, we obtain that, in most cases, thebiases are negligible compared to the statistical error bars. Finally, we computethe error bars of Ωc , σ8 , and w0 using Fisher matrix and profile likelihood
approaches, showing that they are compatible with the Monte Carlo ones.
The results of this work validate the use of the current maximum likelihood
methods for cluster abundance.

Anisotropic orientations of polarisations fromquasars ligth: a new statistical method and analysis
Vincent Pelgrims & Jean-Rene Cudell
IFPA, AGO Dept., Université de Liège, Belgium

We recently built a new statistical method dedicated to the study of the dispersion of polarisation vector directions coming from sparse cosmic sources.
We propose to review the content of the paper Pelgrims and Cudell, 2014
(arxiv:1402.4313); namely, we will present the basis of the new method andwe will discuss the results of its application to the sample of quasar polarisation
measurements in optical wavelength compiled in Hutsemékers et al., 2005
(A&A, 332, 410). Using the new method, we found that the probability thatthe large-scale alignments of polarisation vectors are due to chance is as low
as 0.003%.

The European Extremely Large Telescope: Preparinga Revolution (in Cosmology and Fundamental
Physics)
Carlos J. A. P. Martins
CAUP – Centro de Astrofı́sica da Universidade do Porto, Portugal

The E-ELT is the top priority of European ground-based astronomy, cf. Astronet and ESFRI. In this talk I will present a very brief summary of the statusof the project, and then discuss its key science drivers in the area of cosmology
and fundamental physics, including some detailed forecasts of its performance.
Particular emphasis will be given to the synergies between the E-ELT andother facilities, specifically ALMA, Euclid, the SKA and planned intensity
mapping experiments.

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Machine Learning Classification of Transient Survey
Images
Bruce A. Bassett1,2,3 , Lise du Buisson1,2,3 , Navin Sivanandam1 &Mathew Smith4
1. African Institute for Mathematical Sciences, South Africa
2. University of Cape Town, South Africa
3. South African Astronomical Observatory, South Africa
4. University of the Western Cape, South Africa

We explore various machine learning feature extraction and classification
algorithms for distinguishing between objects and artifacts in automaticallydetected transient survey images. SDSS difference images are used to compare
the strength and weaknesses of various approaches. These include PCA andLDA for feature extractions and SVM, neural networks and nearest neighbors
for classifiers. Results for different approaches are reported and discussed.

Towards a better understanding of galaxy clusters
Pedro Viana
CAUP – Centro de Astrofı́sica da Universidade do Porto, Portugal

Clusters of galaxies are the largest gravitationally collapsed structures in the
Universe. The hierarchical growth of large-scale structure also ensures they
are the rarest. Further, although not all important physical processes involvedin the assembly of galaxy clusters are well known, they are relatively simple
astrophysical objects. All of these characteristics make clusters of galaxies
excellent probes of the growth of structure in the Universe and of its large-scaleevolution.
Within the next few years, several surveys of the sky will detect many
thousands of galaxy clusters. The largest catalogue is expected to result fromthe Euclid mission. However, the accuracy with which we will be able todistinguish, for example, competing hypothesis for the cause of the present
accelerating expansion of the Universe, will be limited by our understandingof the galaxy cluster catalogue selection function, systematic errors and theuncertainty in the galaxy cluster mass determinations. The combination of
Euclid data with that obtained through other galaxy cluster surveys, based on
the detection of the galaxy cluster signal on the X-rays (XCS and eROSITA
surveys) and due to the Sunyaev-Zeldovich effect in the mm/sub-mm (SPT andIAU Symposium 306 – SCCC21, 2014 — 109/130

Planck surveys), can help in this respect, by enabling the cross-calibration ofboth the selection functions of those surveys and the mass-observable relations,
unearthing possible systematic errors in the process.
We are presently developing an integrated bayesian framework that willallow for the characterization of galaxy clusters using Euclid data jointlywith data gathered on other wavelengths. For the moment, data from the
XMM Cluster Survey (XCS), Sloan Digital Sky Survey (SDSS) and Planck isbeing used. Our immediate aim is to understand better the selection functionsof these catalogues, estimate the joint posterior distribution function of themost relevant cluster properties, and characterize correlations between suchproperties.

Detecting Particle Dark Matter Signatures via
Cross-Correlation of Gamma-Ray Anisotropies andCosmic Shear
Stefano Camera
CENTRA, Instituto Superior Técnico, Universidade de Lisboa, Portugal

Both cosmic shear and cosmological gamma-ray emission stem from the presence of Dark Matter (DM) in the Universe: DM structures are responsible forthe bending of light in the weak lensing regime and those same objects can emit
gamma-rays, either because they host astrophysical sources (active galactic
nuclei or star-forming galaxies) or directly by DM annihilation/decay (depending on the properties of the DM particle). Such gamma-rays should therefore
exhibit strong correlation with the cosmic shear signal. Here, I present recent results on the cross-correlation angular power spectrum of cosmic shearand gamma-rays produced by the annihilation/decay of Weakly Interacting
Massive Particle (WIMP) DM, as well as from astrophysical sources. I showthat this observable provides novel information on the composition of theextra-galactic gamma-ray background, since the amplitude and shape of thecross-correlation signal strongly depends on which class of source is responsible for the gamma-ray emission. Furthermore, I also outline how to extract
the maximum information by means of a tomographic approach - namely, we
bin the signal in redshift slices (thanks to cosmic shear) and energy intervals(thanks to gamma-ray detection). By performing a Fisher matrix analysis of
this method, I show that future data coming from the Fermi-LAT satellite andthe Dark Energy Survey will enable us to put strict constraints on the particle
properties of WIMP DM - and even to detect WIMP DM signatures.

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The Planck Legacy Archive: data and tools to mine
the Cosmic Microwave Background
Xavier Dupac1 , et al.
European Space Agency – ESAC

The ESA Planck space telescope has recently (March 2013) released its firstmajor dataset. It includes Cosmic Microwave Background full-sky maps,
Extragalactic sources and Galactic foreground emissions. Full-sky intensity
maps are released at nine frequencies (30 GHz to 857 GHz) with unprecedented
angular resolution (4’ for the High-Frequency Instrument dust channels) andsensitivity. In this presentation, I will explain what is in the data and how tosearch and process them from the Planck Legacy Archive user interface. I
will also present the broader context of the Planck archive and its current andfuture developments, emphasizing the next major data release to come in thefall 2014 and the associated improvements to appear in the Planck Legacy
Archive.

A Close Examination of CMB Mirror-Parity after
PlanckAssaf Ben-David1 & Ely D. Kovetz2
1. The Niels Bohr Institute, Copenhagen, Denmark
2. The University of Texas at Austin, USA

Large scale symmetries in the CMB, breaking statistical isotropy, can provide
insight into pre-inflationary physics as well as the topology of the Universe.
Evidence for such a symmetry, large scale mirror-parity, has been previously
claimed significant in data from both WMAP and Planck. In this talk, based on
the recent work arXiv:1403.2104, I revisit these claims with a careful analysisof the latest data available. The data are analyzed using statistical estimators
in both harmonic and pixel spaces. These estimators are compared using
tests on simulations with and without mirror-parity, and after applying various
Galactic masks. The dependence of the results on arbitrary choices of freeparameters is also studied. While the data indeed show significant signs of odd
mirror-parity, under some circumstances, the broad study shows that given
the inherent biases and the dependence on the choice of Galactic mask andother parameters, the results should not be regarded significant, and are not intension with ΛCDM.

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Multi-property Statistics for Clusters of Galaxies
August E. Evrard1 , Dragan Huterer1 , Arya Farahi1 & Pablo Arnault2
1. University of Michigan, USA
2. École Normale Superieure, Cachan, France

Observable properties of the massive dark matter halos that host groups andclusters of galaxies appear to be log-normally distributed about power-law
mean scaling relations in halo mass. Coupling this assumption with either
quadratic or cubic approximations to the halo mass function in log space, we
derive closed-form expressions for the space density of groups and clusters as
a function of multiple observables, as well as forms for the low-order moments
of properties of observable-selected samples. Using a Tinker mass function
in a ΛCDM cosmology, we show that the cubic analytic model reproduces
results obtained from direct, numerical convolution at the 10% level or better
over nearly the full range of observables covered by current observations andfor redshifts extending to z = 1.5. The model provides an efficient framework
for estimating effects arising from selection and covariance among observable
properties in survey samples. Applications to ongoing and future X-ray, SZ
and optical surveys are presented.

Reconstructing light curves from imaging
observations of Hard X-ray Modulation Telescope
HUO Zhuo-Xi
Tsinghua University, China

The Hard X-ray Modulation Telescope (HXMT) is a Chinese space telescope
mission. As the first dedicated astronomical space telescope of China, it isscheduled for launch in the first half of 2015. The telescope will perform
an all-sky survey in hard X-ray band (1 – 250 keV), a series of deep imaging observations of small sky regions as well as pointed observations. It’s
expected that various X-ray objects (e.g., AGNs, binaries, transients) to be
detected with imaging observations, namely, the all-sky survey and imaging
observations, while light curves and energy spectra of these objects are investigated through pointed observations. In this talk we will discuss the feasibilityof reconstructing light curves from HXMT imaging observation directly. A
conceptual pipeline design is also presented. An initial estimate is achieved
through multi-energy image reconstruction, including hardness of spectra andIAU Symposium 306 – SCCC21, 2014 — 112/130

a static image. From the image bright sources are detected and extracted. Then
precise locations and time-varying fluxes are estimated through a Kalman filter
approach. High-time-resolution light curves are reconstructed by time-domain
demodulation. We hope it’s possible to monitor time-varying objects such as
GRB, AXP and SGR in hard X-ray band with HXMT imaging observations.

Modelling Galaxy Populations in the Era of Big Data
Steven Murray, Chris Power & Aaron Robotham
International Centre for Radio Astronomy Research, University of Western Australia, Australia

The coming decade will witness a deluge of data from next generation galaxy
surveys such as the Square Kilometre Array, Euclid, etc. . . How can we
optimally and robustly analyse these data to maximise scientific returns fromthese surveys? In this talk I will discuss my recent work developing both theconceptual and software frameworks for carrying out such analyses and theirapplication to the dark matter halo mass function (Murray, Power & Robotham
2013 a,b). I will summarise what we have learned about the halo mass function
from the last 10 years of precision CMB data using my open-source HMFcalc
framework, before discussing how this framework is being extended to model
halo occupation statistics and fast approximate schemes for synthetic galaxy
surveys.

The ALHAMBRA survey: evolution of galaxy
clustering since z ∼ 1
Lluı́s Hurtado-Gil1 , Pablo Arnalte-Mur2 , Vicent Martı́nez1 ,Peder Norberg2 & Alberto Fernández1
1. IFCA – Universitat de València, Spain
2. Durham University, United Kingdom

We study the clustering of galaxies as function of luminosity and redshift in
the range 0.35 < z < 1.25 using data from the Advanced Large Homogeneous
Area Medium Band Redshift Astronomical (ALHAMBRA) survey. The ALHAMBRA data used in this work covers 2.38deg2 in 7 independent fields,
after applying a detauled angular selection mask, with accurate photometricredshifts, σz < 0.014(1 + z), down to IAB < 24. Given the depth of the survey
we select samples in B-band luminosity down to Lth = 0.16L∗ at z = 0.9. We
mesure the real-space clustering using the projected correlation function, ac-

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counting for photometric redshift uncertainties. In addition, for galaxies with
MBth < −18.6, we perform the analysis of the clustering evolution with segregated populations using ALHAMBRA templates, separating the populationin early and late type galaxies. The high quality of ALHAMBRA photometric redshifts and the high galaxy density of the covered fields, allow us toextend the projected correlation function down to very small scales (0.03h−1
Mpc), below any other previous calculation. We study the effect of sample
variance, and confirm earlier results that the COSMOS and ELAIS-N1 fields
are dominated by the presence of large structures.

New Challenges in Cosmology Posed by the Sloan
Digital Sky Survey Quasar Data
Adrija Banerjee & Arnab Kumar Pal
Indian Statistical Institute, India

According to the Hubble Law, under the assumption of the universe being
homogeneous and isotropic, the galaxies appear to be receding with a velocity
v proportional to their distance d from the observer: v = H0d , where H0 iscalled the Hubble constant. There are two luminosity functions i.e. absolute
luminosity and apparent luminosity. Normally astronomers work with absolutemagnitude M and apparent magnitude m, where d ≈ m − M is known as
distance modulus and is related to the luminosity distance. Therefore, therelation between the distance modulus and logz is considered to test Hubble
law. Efron and Petrosian studied the viability of various statistical tests fortruncated data in connection with redshift survey of galaxies and quasars. Fromthe plot of redshifts zi and log luminosities (=yi) for 210 quasars they foundthe data to be doubly truncated data. Roy et al studied the bivariate distributionof redshift and apparent magnitude observed in Sloan Digital Sky Survey(SDSS) for quasar redshift (2005) in which the data was truncated. However,
the redshift data in SDSS quasar survey of 2007 was no longer truncated.
Mukhopadhayay et al (2009) discussed a general framework to study data forredshift and apparent magnitude in quasar sample and found a nonlinearityof the fitting curve for Hubble like relation. Now the intriguing issue is, for
SDSS quasar data (2005) we have truncated data structure whereas for thesurvey of 2007 the data is no longer truncated. This calls for development or
use of completely different statistical methodology to study the data for theevolution of the same objects like quasars. These two different methodologies
suggest different interpretation for a particular phenomenon in nature. ThisIAU Symposium 306 – SCCC21, 2014 — 114/130

leads to the issue of validation of the data. More intriguing and challenging
issue crops up as, given all of the data, what can be said about the laws ofphysics that have been operating over the universe?

The cosmic radio dipole and local density effects
Matthias Rubart
Universität Bielefeld, Germany

In our work we investigate the contribution that a local over-density or underdensity can have on linear cosmic dipole estimations. We focus here on
radio surveys, such as the NVSS, and forthcoming surveys such as those with
LOFAR and the Square Kilometre Array. The NVSS has already been used toestimate the cosmic radio dipole; it was shown recently that this radio dipole
amplitude is larger than expected from a purely kinematic effect, assuming thevelocity measured by the dipole in the CMB. We show here that a significant
contribution to this excess could come from a local void or similar structure.

A new model to predict weak lensing peak counts
Chieh-An Lin & Martin Kilbinger
CEA – Commissariat à l’Énergie Atomique – Saclay, France

Peak statistics from weak gravitational lensing has been shown as a promising
tool for cosmology. Weak lensing peaks probe the high density, non-linear
regions of the large scale structure and encompass a wealth of information on
cosmology and structure formation.
Here we propose a new approach to predict weak lensing peak counts,
by generating fast simulations of halos without the use of time-consuming
N-body simulations. Our method can model peak counts in any cosmology,
for which the halo mass function is known. Predictions can be done for peaks
obtained from the linearly filtered shear field, but also for non-linear estimatorsof the reconstructed convergence field.
We validate our method by comparing our fast lensing simulations of halos
with N-body runs. We replace identified halos with analytical NFW profiles
and show that the peak abundance remained unchanged for high signal-tonoise peaks (& 5). Further, randomization of the halo positions does notchange the peak counts, demonstrating that halo clustering has a minor impact
on weak lensing peak statistics. In addition, we compare our method to theanalytical peak abundance prediction model from Fan et al. (2010).

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As a preliminary result, we show that some cosmological parameters, suchas σ8 , can be constrained by the abundance. The optimal combinations ofparameters sensitive to our approach is under studying.

Statistical Challenges in the Photometric Calibration
for the 21st Century Cosmology: The J-PAS Case
Jesús Varela1 ,David Cristóbal-Hornillos1 , Mariano Moles Villamate1 , Javier
Cenarro Lagunas 1 , Alessandro Ederoclite1 , Héctor Vázquez Ramió1 , Javier
Hernández Fuertes1 , Ángel López Sainz1 , David José Muniesa Gallardo1 ,Tamara Civera Lorenzo 1 & Nicolas Gruel2
1. Centro de Estudios de Fı́sica del Cosmos de Aragón, Spain
2. University of Sheffield, UK

The success of many cosmological surveys in the near future is highly groundedon the quality of their photometry. The Javalambre-PAU Astrophysical Survey(J-PAS) will image more than 8500deg2 of the Northern Sky Hemispherein 54 narrow + 2 medium/broad optical bands plus Sloan u, g and r bands.
The main goal of J-PAS is to provide the best constrains on the cosmologicalparameters before the arrival of projects like Euclid or LSST. To achieve thisgoal the uncertainty in photo-z cannot be larger than 0.3% for several millionsof galaxies and this is highly dependent on the photometric accuracy.
The photometric calibration of J-PAS will imply the intensive use of hugeamounts of data and the use of statistical tools is unavoidable. I will present
some of the key steps in the photometric calibration of J-PAS that will demanda suitable statistical approach.

Foreground Removal on LOFAR-EoR Data: First
Results
Emma Chapman1 , Filipe Abdalla1 , LOFAR-Epoch of Reionization Core Team2
1. University College London, United Kingdom
2. Groningen, Netherlands

The accurate and precise removal of 21-cm foregrounds from EoR data isessential to make the first detection of this epoch. With the current generationof radio interferometers edging ever closer to a detection I will discuss how
non-parametric foreground removal methods such as FASTICA and GMCA

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can be utilised with great success on the incoming data and showcase some ofthe preliminary results.

The Epoch of Reionization with LOFAR: current
results and predictions
Ajinkya Patil1 , Saleem Zaroubi1 & the LOFAR Epoch of Reionization team
1. Kapteyn Astronomical Institute, Netherlands

The Epoch of Reionization (EoR) is the epoch in which most of the neutralhydrogen in the Universe was reionized by the radiation from the first stars andgalaxies. Many projects are underway to detect the EoR signal, i.e. the cosmic
redshifted 21-cm signal from neutral hydrogen, using low frequency radio
telescopes. I will present the current results from the Low Frequency Array(LOFAR) EoR experiment. I will show the upper limit on the EoR signal in
the redshift range 6 to 11 based on analysis of 200 hours of the observed data.
I will also show that the LOFAR should be able to detect the variance andpower spectrum of the signal with a 3 sigma confidence with 600 hours ofintegration. The variance and power spectrum statistics of the EoR signal canbe used to constrain the evolution of the neutral hydrogen in the Universe.

Transformed Auto-correlation
Jianfeng Zhou & Yang Gao
Center for Astrophysics, Tsinghua University, China

Echo signals probably exist in the light curves of some sorts of astronomical
objects, such as supernovae, x-ray binaries and AGNs etc.. If the distance
between central radiator and a reflecting object is fixed, then auto-correlation
can be used to detect the reflected signal and estimate the distance thereafter.
However, in common situation, the nearby reflecting objects are always moving, therefore, the lags between radiated and reflected signal are variable,
which means no echo signals could be detected by auto-correlation. Here,
we propose a transformed auto-correlation method in which a received light
curve is transformed based on a priori model, then the adjusted light curveis cross-correlated to the original one. After transformation, a small part ofreflected signal and its counterpart in radiated signal have a constant lag. Theselags can be removed dynamically so that a long period of signal would hasa peak at zero lag in a transformed auto-correlation curve. The priori model

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is parameters dependent. By searching the maximum in a series of the peakvalues of transformed auto-correlation curves in the whole parametric space,
the real values of the parameters can be determined.

Type Ia supernova cosmology with CMAGIC
Santiago González-Gaitán
Universidad de Chile, Chile

Type Ia supernovae (SNe Ia) have been successfully used as standardizable distance indicators for cosmology providing primary evidence for the accelerated
expansion of the universe. Traditional SN Ia standardization methods use theknown relations between lightcurve-shape and brightness, as well as color andbrightness, to correct for peak luminosity and reduce the intrinsic luminosity
scatter. We present here a method based on post-maximum color-magnituderelations (CMAGIC, Wang et al. 2003, Conley et al. 2006), which reveal a
linear regime where the luminosity scatter is small and the effects of host extinction by dust are less important. We apply this technique to a mutli-redshift
dataset from the literature and obtain first Hubble diagrams.

Probing cosmology with Intensity Mapping of highredshift emission lines
Marta Silva & Mario Santos
CENTRA, Instituto Superior Técnico, Universidade de Lisboa, Portugal

The intensity mapping technique consists in measuring the overall intensity ofan emission line, at a given redshift, from galaxies and from the IGM without
attempting to resolve individual sources. This method was first thought for the
21 cm line but it can also be used for measuring the intensity of other lines.
Since intensity mapping experiments can cover large volumes and are able todetect the emission from even the faintest sources, out of the reach of galaxy
surveys, these experiments are particularly useful for probing the nonlinear
underlying density field. In this study I show how intensity maps of highredshift emission lines trace density fluctuations and what are the signatures
non linearities in the mass distribution or different cosmologies leave in the
power spectra of different emission lines.

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Unraveling general relationships into
multidimensional datasets
Rafael S. de Souza
Korea Astronomy and Space Science Institute, Korea

I will present a set of tools for mining multidimensional datasets. In particular,
an application to the Millennium-II Simulation dataset, where we automatically recover all groups of linear and non-linear associations within a setof 30 parameters from thousands of galaxies. Also, I will show alternative
ways to visualize general correlations and how dimensionality reduction techniques and graph theory can help us to understand the temporal evolutionof galaxy properties. Finally I will give a short introduction of the recently
created working group of cosmostatistics within the international astrostatistics
association.

Adaptive density estimator for galaxy surveys
Enn Saar
Tartu Observatoorium (Tartu Observatory), Estonia

Galaxy number or luminosity density serves as a basis for many structureclassification algorithms. Several methods are used to estimate this density.
Among them kernel methods have probably the best statistical properties andaillow also to estimate the local sample errors of the estimate. We introduce
a kernel density estimator with an adaptive data-driven anisotropic kernel,
describe its properties and demonstrate the wealth of additional information it
gives us about the local properties of the galaxy distribution.

3D-Needlets on the unit ball
Claudio Durastanti1 , Yabebal Fantayé1 , Domenico Marinucci1 &Isaac Pesenson2
1. Università degli Studi di Roma Tor Vergata, Italy
2. Temple University, Philadelphia, USA

In this talk, we will present a new frame of wavelets defined on the unit ball.
These wavelets, named 3D-needlets, are built following, on one hand, theconstruction of band-limited localized frames on compact manifolds, developed by Geller and Pesenson [2010] (see also Pesenson, 2013), and, on the

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other hand, the characterization of (2-dimensional) needlets on the sphere, as
described in Narcowich, Petrushev and Ward [2006a,2006b]. The coordinate
system chosen on the ball is the combination of the set of spherical harmonics(for the spherical coordinates) and the set of properly modified trigonometric functions (for the radial coordinate): The 3D-needlets can be viewed as
the convolution of a finite linear combination of elements of this coordinate
system computed on a generic point and on a set of cubature points on theball, balanced by a suitable weight function. This framework features somerelevant properties, as for instance precisely quantifiable localization in both
spatial and harmonic domains, and seems to fit naturally into the experimental
set-up of astrophysical observations on large scale structure. The results areillustrated both by analitycal arguments and numerical evidence. Based on
joint work with Yabebal Fantaye, Domenico Marinucci and Isaac Pesenson. Geller, D., Pesenson, I. (2010) Band-Limited Localized Parseval Frames andBesov Spaces on Compact Homogeneous Manifolds, Submitted; - Pesenson, I.
(2013). φ -Transform on Domains. Submitted; - Narcowich, F.J., Petrushev, P.
and Ward, J.D. (2006a) Localized Tight Frames on Spheres, SIAM Journal of
Mathematical Analysis Vol. 38, p. 574; - Narcowich, F.J., Petrushev, P. and
Ward, J.D. (2006b) Decomposition of Besov and Triebel-Lizorkin Spaces on
the Sphere, Journal of Functional Analysis, Vol. 238, 2, 530.

Application of Statistical Method on Automatic
Detecting Solar Active Phenomena and Analyzing
Their Correlation
Ganghua Lin
National Astronomical Observatories, Chinese Academy of Sciences, China

Not only observational data volume from space, but also data volume fromground are tend to very high produce rate in solar physics field. So there
has been an increased need to automatically detect, extract solar features andevents for now and further solar active warn and prediction and to help tostream-line the process in solar physics analysis. Many of these automation
methods are closely related to the statistical methods. Author investigations
the extensive literatures to clarify the function of statistical methods and theiradvantages in detecting automatically solar features and analyzing solar active
phenomena correlation. This review summarizes the results of the study, theresults will be helpful to promote further automation processing for us.

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Back to Normal: Gaussianizing posterior
distributions for arbitrary cosmological probes
Robert Schuhmann, Benjamin Joachimi & Hiranya Peiris
University College London, United Kingdom

We present a method to map multivariate non-gaussian posterior probability
densities into gaussian ones via non-linear Box-Cox transformations, andgeneralizations thereof. This is analogous to the search for normal parametersin the CMB, but can in principle be applied to any probability density that iscontinuous and unimodal. The search for the optimally gaussianizing transformation amongst the Box-Cox family is performed via a maximum-likelihood
formalism; the quality can be judged a posteriori: qualitatively via statisticaltests of gaussianity, and more illustratively by how well the confidence regions are reproduced. The method permits an analytical reconstruction of theposterior from a sample, e.g. a Markov chain, and simplifies the subsequent
combination with other experiments. Furthermore, it allows for the reportingof a non-gaussian posterior in a compact and efficient way. The expression for
the non-gaussian posterior can be employed to find analytic formulae for theBayesian evidence, and consequently be used for model comparison.

Generic inference of inflation models by local
non-Gaussianity
Sebastian Dorn1 , Erandy Ramirez2 , Kerstin Kunze3 , Stefan Hofmann4 &Torsten Enßlin1,4
1. Max-Planck-Institut für Astrophysik, Germany
2. Universidad Nacional Autónoma de México, Mexico
3. Instituto Universitario de Fı́sica Fundamental y Matemáticas, Universidad de Salamanca, Spain
4. Ludwig-Maximilians Universität, Germany

In this talk a generic inference method for inflation models from observational
data by the usage of higher-order statistics of the curvature perturbation ispresented. This method is based on the calculation of the posterior for theprimordial, local non-Gaussianity parameters fNL and gNL , which in generaldepend on specific parameters of inflation and reheating models, and enables
to discriminate among the still viable inflation models. To keep analyticity as
far as possible to dispense with numerically expensive sampling techniques asaddle-point approximation is introduced, whose precision is validated for a

IAU Symposium 306 – SCCC21, 2014 — 121/130

numerical toy example. The mathematical formulation is done in a generic
way so that the approach remains applicable to cosmic microwave backgrounddata as well as to large scale structure data. To demonstrate the efficiency ofthe higher-order statistics method I present numerical toy examples of twocurrently interesting inflation models. Reference: arXiv:1403.5067

Reconstruction of cosmic density fields from
non-Poisson statistics
Metin Ata, Francisco-Shu Kitaura & Volker Müller
Leibniz-Institut für Astrophysik Potsdam (AIP), Germany

We use Hamiltonian Monte Carlo solvers, (see e.g. Kitaura et al. 2010) toreconstruct the cosmic matter density fields from simulated halo distributions
in real and redshift space. To describe deviations from Poisson expectations ofcounts in cells, we employ the negative binominal distribution and gravitational
thermodynamics in the reconstruction and a lognormal prior function of theoverdensity δ . Our aim is to evaluate the local non-linear bias in relation to
the cosmic web characteristics.

Testing the Equivalence Principle with
MICROSCOPE: the data analysis challenge
Joel Bergé1 & Sandrine Pires2
1. Onera – Office National d’Études et de Recherches Aérospatiales, France
2. CEA – Commissariat à l’Énergie Atomique – Saclay, France

The Weak Equivalence Principle (WEP), which states the equality of theinertial and the gravitational masses, is a corner stone of General Relativity(GR). While it has currently been tested down to a few 10e-13, most theories
of modified gravity predict its violation at a level between 10e-18 and 10e-13.
Those theories may explain the accelerated expansion of the Universe without
requiring dark energy. They can be tested on cosmological scales by observing
large scale structures, and on laboratory scales by looking for a WEP violation.
MICROSCOPE (“Micro-Satellite à trainee Compensée pour l’Observation
du Principe d’Equivalence”, French for ”Drag-free micro-satellite for theobservation of the Equivalence Principle”) is a funded mission of the French
space agency that aims to test the WEP in space, down to a level 10e-15. It
will therefore allow us to experimentally test theories beyond GR. However,IAU Symposium 306 – SCCC21, 2014 — 122/130

we expect a possible WEP violation signal to be buried in the noise (hence, its
analysis will be statistical) and plagued by systematics; moreover, we expect
to lose some data. Although we can calibrate the measurement to control
instrumental systematics, the data analysis will be hampered by missing data
and therefore will require advanced statistical techniques. In this talk, I will
first present Microscope, with an emphasis on its links with cosmology. Then
I will present the challenges that we will face to analyze its data, as well assome solutions to the challenges we are working on.

Intuitive model for 21 cm power spectrum of theepoch of reionization
Sander Bus & Saleem Zaroubi
Kapteyn Astronomical Institute, Netherlands

The epoch of reionization (EoR) is a pivotal era in the history of the universe,
where the first stars and galaxies ionize their surroundings. Several teams
around the globe, among which the LOFAR EoR team we are part of, areworking very hard on making a detection of the EoR using the redshifted
21cm line. The first detections of the EoR will be statistical in nature. The
power spectrum is a statistic which is sensitive to astrophysical processes
during the EoR. In this talk, we argue that the power spectrum can be fit by asimple model that intuitively encapsulates the physical properties of the power
spectrum evolution. We discuss the properties of this fit and how it can beused to learn about astrophysics during the epoch of reionization.

Sparsity based high resolution density mappingfrom 3D weak lensing
François Lanusse1 , Adrienne Leonard2 & Jean-Luc Starck1
1. CEA – Commissariat à l’Énergie Atomique – Saclay, France
2. University College London, United Kingdom

From current and next generation weak lensing surveys with photometricredshift follow up it has recently become possible to map the matter density in
3D. However, the linear methods introduced to address this complex inverse
problem were limited in resolution (both angular and along the line of sight)
and only produced Signal to Noise maps.

IAU Symposium 306 – SCCC21, 2014 — 123/130

We recently proposed a new non linear, sparsity based, weak gravitational
lensing technique, coined GLIMPSE, allowing us to reconstruct the 3D matter
density contrast (not SNR maps) from weak gravitational lensing with highresolution. Having access to the value of the density contrast allows us to put
constraints on the masses of reconstructed structures.
Tested on a large set of simulated isolated dark matter halos, we showthat GLIMPSE provides a good sensitivity to clusters of virial mass above a
few 1013 solar masses/h for a Euclid-like space-based survey. In particular,
our technique proves very efficient at probing the high-mass end of the massfunction (≥ 8 × 1014 Msol/h) as we still expect to detect above 60% of clusters
at redshift 0.75. Furthermore GLIMPSE provides an unbiased estimator of
the redshift of detected clusters as well as a largely unbiased estimator for themass which can be constrained to below 5% accuracy if the actual redshift is
known.

Weak lensing with size and magnitude magnification
Justin Alsing1 , Alan Heavens1 , Andrew Jaffe1 , Hendrik Hildebrandt2
1. Imperial Centre for Inference and Cosmology, Department of Physics, Imperial College, Blackett
Laboratory, Prince Consort Road, London SW7 2AZ, U.K.
2. Argelander-Institut fur Astronomie, Universitat Bonn, Auf dem Hugel 71, 53121 Bonn, Germany

Light from distant galaxies is continuously deflected by the gravitational fieldof intervening large-scale density inhomogeneities in the Universe on its way
to Earth. This so-called weak gravitational lensing results in distortions in the
projected images of galaxies on the sky, modifying their shapes (cosmic shear),sizes and magnitudes (through the convergence field) at the % level. The
intrinsic shape, size or flux of an observed galaxy is not known a priori, so thelensing effect on individual sources is not accessible. However, if the intrinsic
distribution of these properties is known, then a weak lensing analysis can be
performed at the statistical level by observing a large number of galaxies andlooking for a signal through deviations in the observed distribution.
Traditionally, the statistic of choice has been cosmic shear. However,since weak lensing has other effects (such as the magnification of sizes andmagnitudes) one would ideally like to use all of the available information toelicit the full statistical power of a weak lensing survey. Furthermore, eachof the weak lensing observables comes with its own set of observational andtheoretical hurdles; systematic effects are rife in any weak lensing analysis
and this is one of the major challenges in the field. This provides very strong

IAU Symposium 306 – SCCC21, 2014 — 124/130

motivation for developing a number of independent probes, each sufferingfrom different systematic effects.
In this work we are concerned with how much additional information
is available from analysing the sizes and magnitudes of individual sources(probing the convergence field), in addition to galaxy shapes (cosmic shear).
This question neatly splits into two parts: Firstly, we explore how well wecan (statistically) determine the convergence field from sizes and magnitudes,
given their intrinsic distribution. We measure the joint distribution of galaxy
sizes and magnitudes in CFHTLenS data and demonstrate that with this measured intrinsic size-magnitude distribution, we could expect to recover κ with
an effective dispersion of ∼ 0.7. Secondly, we show that in light of theseresults we expect magnification to have roughly half of the signal-to-noisefor cosmological parameter inference compared to cosmic shear (neglecting
systematics).

List of participants

IAU Symposium 306 – SCCC21, 2014 — 126/130

Adrienne Leonard
Adrija Banerjee
Ajinkya Patil

adrienne.leonard@ucl.ac.uk
adrija@isichennai.res.in
patil@astro.rug.nl

Alan Heavens
Alberto Krone-Martinsa.heavens@imperial.ac.uk
algol@sim.ul.pt

Alejandro Guarnizo Trillerasa.guarnizo@thphys.uni-heidelberg.de

Alex Szalay
Ana Mourãoszalay@jhu.edu
amourao@ist.utl.pt

Anais Rassat

anais.rassat@epfl.ch

Andras Kovacs
André Moitinho

andraspankasz@gmail.com
andre@sim.ul.pt

Andrew Jaffe
Anna Mangilli

a.jaffe@imperial.ac.uk
mangilli@iap.fr

Antonino Troja

antonino.troja@unimi.it

Arlindo Trindade

Arlindo.Trindade@astro.up.pt

Arnab Pal
Assaf Ben-David

arnabandstats@gmail.com
bendavid@nbi.dk

Athina Pouri
August Evrard
Aurore Delaigle
Denis Barkats
Ben Granett
Ben Wandelt

ath.pouri@gmail.com
gus.evrard@gmail.com
A.Delaigle@ms.unimelb.edu.au
dbarkats@alma.cl
ben.granett@brera.inaf.it
bwandelt@illinois.edu

Benjamin Joachimi
Boris Leistedt
Carla Sofia Carvalho

b.joachimi@ucl.ac.uk
boris.leistedt.11@ucl.ac.uk
cscarvalho@oal.ul.pt

Carlos Martins

Carlos.Martins@astro.up.pt

Caroline Heneka

caroline@dark-cosmology.dk

Catherine Watkinson
Chieh-An Lin
Chris Pritchet
Christopher Bonnett
Claudio Durastanticatherine.watkinson@gmail.com
chieh-an.lin@cea.fr
pritchet@uvic.ca
c.bonnett@gmail.com
durastan@mat.uniroma2.it

Dagoberto Contreras

dagocont@phas.ubc.ca

Dalia Chakrabartyd.chakrabarty@warwick.ac.uk

Daniel Mortlock
David van Dyk
Elena Sellentin

mortlock@ic.ac.uk
dvandyk@imperial.ac.uk
sellentin@stud.uni-heidelberg.de

Elmo Tempel
Emille Ishidaelmo.tempel@to.ee
emille@mpa-garching.mpg.deEmma Chapman
Emory Bunn
Eniko Regos Dr
Enn Saar
Ewan Cameron
Eyal Kazin

eow@star.ucl.ac.uk
ebunn@richmond.edu
Enikoe.Regoes@cern.ch
saar@to.ee
dr.ewan.cameron@gmail.com
eyalkazin@gmail.com

Fabien Lacasa

fabien@ift.unesp.br

University College London
Indian Statistical Institute
Kapteyn Astronomical Institute
Imperial College London
Universidade de Lisboa SIM
Ruprecht-Karls-Universität
Heidelberg
Johns Hopkins University
University of Lisbon - CENTRA/IST
Ecole
PolytechniqueFédérale de Lausanne
Eotvos University
Universidade de Lisboa SIM
Imperial College London
Insitut d’Astrophysique deParis
University of Milan Physics department
Centro de Astrofı́sica da
Universidade do Porto
Indian Statistical Institute
The Niels Bohr Institute,
Copenhagen
UOA/RCAAM
University of Michigan
University of Melbourne
ALMA - ESO
INAF Brera Observatory
Institut d’Astrophysique deParis
University College London
University College London
CAAUL, University of Lisbon
Centro de Astrofı́sica da
Universidade do Porto
DARK,
UniversityofCopenhagen
Imperial College London
CEA Saclay
University of Victoria
IFAE
University of Tor Vergata,
Roma
UniversityofBritishColumbia
University of Leicester &Warwick
Imperial College London
Imperial College London
ITP – Universität Heidelberg
Tartu Observatory, KBFIMax Planck Institute for Astrophysics
University College London
University of Richmond
Eotvos University
Tartu Observatory
Oxford Zoology
Swinburne University ofTechnology
ICTP - SAIFR

United Kingdom
India
Netherlands
United Kingdom
Portugal
Germany
United States of America
Portugal
Switzerland
Hungary
Portugal
United Kingdom
France
Italy
Portugal
India
Denmark
GreeceUnited States of America
Australia
Chile
Italy
FranceUnited Kingdom
United Kingdom
PortugalPortugal
Denmark
United Kingdom
FranceCanadaSpain
Italy
CanadaUnited Kingdom
United Kingdom
United Kingdom
Germany
Estonia
Germany
United Kingdom
United States of America
Hungary
Estonia
United Kingdom
Australia
BrazilIAU Symposium 306 – SCCC21, 2014 — 127/130

Federico Bianchini
Fergus Simpson
Filipe Abdalla
Filomena Bufano
Florent Leclercq

fbianchini@sissa.it
fergus2@icc.ub.edu
fba@star.ucl.ac.uk
milena.bufano@gmail.com
florent.leclercq@polytechnique.org

Francisco Forster
Francisco Kitaura

francisco.forster@gmail.com
kitaura@aip.de

Francois Lanusse
Franz Elsner
Giuliano Pignata
Giuseppe Vinci
Godlowski Wlodzimierz
Graca Rocha
Haijun Tian

francois.lanusse@cea.fr
f.elsner@ucl.ac.uk
pignago@gmail.com
giuseppevinci88@gmail.com
godlowski@uni.opole.plgraca@caltech.edu
hjtian2000@gmail.com

Hector Javier Hortua Orjuela

hjhortuao@unal.edu.co

Hiranya Peiris
Hyerim Nohh.peiris@ucl.ac.uk
hr@kasi.re.kr

Iftach Sadeh
Ismael Tereno

i.sadeh@ucl.ac.uk
tereno@fc.ul.pt

Jalal Fadili

Jalal.Fadili@greyc.ensicaen.fr

Jason McEwen
Jasper Walljason.mcewen@ucl.ac.uk
jvw@phas.ubc.ca

Jean-Luc Starck

jstarck@cea.fr

Jérome Bobin
Jesus Torrado Cacho

jbobin@cea.fr
torradocacho@lorentz.leidenuniv.nl

Jesús Varelajvarela@cefca.es

Jianfeng Zhou

zhoujf@tsinghua.edu.cn

Joel Bergé
Jon Loveday
Jonathan Aumontjoel.berge@onera.fr
J.Loveday@sussex.ac.uk
jonathan.aumont@ias.u-psud.fr

José Fonseca

josecarlos.s.fonseca@gmail.com

José Pedro Mimoso
Joseph Hilbe
Josh Meyers
Jufu Lu
Julien Carron
Konrad Kuijken
Lara Sousa

jpmimoso@fc.ul.pt
hilbe@asu.edu
jmeyers3@stanford.edu
lujf@xmu.edu.cn
carron julien@hotmail.com
kuijken@strw.leidenuniv.nl
Lara.Sousa@astro.up.pt

Lauri Juhan Liivamägi
Licia Verde
Lin Ganghua

wire@ut.ee
liciaverde@icc.ub.edu
lgh@bao.ac.cn

Lise du Buisson

lisedubuisson@gmail.com

Lluis Galbany
Lluı́s Hurtado-Gil

lluisgalbany@gmail.com
lluis.hurtado@uv.es

Madhura Killedar

killedar@usm.lmu.de

Maggie Lieu

mlieu@star.sr.bham.ac.uk

SISSA
University of Barcelona
University College London
Universidad Andres Bello
Institut d’Astrophysique deParis
Universidad de Chiles
Leibniz Institute for Astrophysics
CEA Saclay
University College London
Universidad Andrés Bello
Carnegie Mellon University
Opole University
JPL, Caltech
China Three Gorges University
Instituicion
losLibertadores/O.A.NUniversidad Nacional
University College London
Korea Astronomy and Space
Science Institute
University College London
CAAUL - Universidade deLisboaEcole Nationale Supérieured’Ingénieurs de Caen
University College London
UniversityofBritishColumbia
CEA–
Serviced’Astrophysique
CEA-Saclay
Instituut-Lorentz,
LeidenUniversity
Centro de Estudios de Fı́sicadel Cosmos de AragónCenter for Astrophysics, Tsinghua University
ONERA
University of Sussex
Institutd’Astrophysique
Spatiale
University of the Western
Cape
Universidade de Lisboa
Arizona State University
Stanford University
Xiamen University
IfA Hawaii
Leiden Observatory
Centro de Astrofı́sica da
Universidade do Porto
Tartu Observatory
Universidad de Barcelona
National
Astronomical
Observatories,
ChineseAcademy of Sciences
University of Cape Town /AIMS
DAS - Universidad de Chile
Observatori Astronómic dela Universitat de Valêcia
Ludwig-Maximilians Universitaet
University of Birmingham

Italy
Spain
United Kingdom
Chile
FranceChile
Germany
FranceUnited Kingdom
Chile
United States of America
PolandUnited States of America
China
Colombia

United Kingdom
South Korea
United Kingdom
Portugal
FranceUnited Kingdom
CanadaFranceFranceNetherlands
Spain
China
FranceUnited Kingdom
FranceSouth Africa
Portugal
United States of America
United States of America
China
United States of America
Netherlands
PortugalEstonia
Spain
China

South Africa
Chile
Spain
Germany
United Kingdom

IAU Symposium 306 – SCCC21, 2014 — 128/130

Manuel da Silva

madusilva@gmail.com

Marc Manera
Marcelo Reboucas

m.miret@ucl.ac.uk
reboucas.marcelo@gmail.com

Mariana Penna Lima Vitenti

pennalima@gmail.com

Mario Santos

mgrsantos@ist.utl.pt

Mario Hamuy
Mark Neyrinck
Marta Bruno Silva

mhamuy@das.uchile.cl
neyrinck@pha.jhu.edu
marta.bruno.silva@ist.utl.pt

Martin Børstad Eriksen
Masahiro Takada

martin.b.eriksen@gmail.com
masahiro.takada@ipmu.jp

Massimo Viola
Matthias Rubart
Metin Ata

viola@strw.leidenuniv.nl
matthiasr@physik.uni-bielefeld.demata@aip.de

Michael Vespe
Michelle Knights

mvespe@andrew.cmu.edu
michelle.knights@gmail.com

Mike Hobson
Minji Oh

mph@mrao.cam.ac.uk
minjioh@kasi.re.kr

Narciso Benı́tez

txitxo@pha.jhu.edu

Natallia Karpenka
Navin Sivanandamnkarp@fysik.su.se
navin.sivanandam@gmail.com

Niels Oppermann

niels@cita.utoronto.ca

Nina RothNoah Kurinsky
Ophélia Fabren.roth@ucl.ac.uk
Noah.Kurinsky@tufts.edu
fabre@iap.fr

Pablo Arnalte-Mur
Paniez Paykari
Paolo Serra
Pedro Viana

pablo.arnalte-mur@durham.ac.uk
paniez.paykari@cea.fr
paoloserr@gmail.com
viana@astro.up.pt

Prina Patel
Radu Stoica

prina83@gmail.com
radu.stoica@univ-lille1.fr

Rafael S. de Souza

rafael.2706@gmail.com

Ralf Siebenmorgen
René A. Ortega-Minakata
Robert Schuhmann
Robert Beck
Roberto Scaramella

ralf.siebenmorgen@eso.org
rene@astro.ugto.mx
robert.schuhmann.13@ucl.ac.uk
robert.beck23@gmail.com
kosmobob@oa-roma.inaf.it

Sabino Matarrese

sabino.matarrese@pd.infn.it

Sander Bus

s.bus@astro.rug.nl

Sandro Dias Pinto Vitenti

dias@iap.fr

Santiago Gonzalez-Gaitan
Sebastian Dorngongsale@gmail.com
sdorn@mpa-garching.mpg.de

Sebastian Seehars
Shan Hao
Simone Aiola
Sonia Antónseehars@phys.ethz.chshanhao@xao.ac.cn
sia21@pitt.edu
santon@fc.ul.pt

Universidade de Lisboa SIM
University College London
CentroBrasileirodePesquias Fisicas
National Institute for Space
Research (INPE/Brazil)
University of the Western
Cape
Universidad de Chile
Johns Hopkins University
University of Lisbon - CENTRA/IST
Leiden University
University of Tokyo - IPMU
/ TODIAS
Leiden University
Bielefeld University
Leibniz-Institut fuer Astrophysik Potsdam AIP
Carnegie Mellon University
UniversityofCape
Town/AIMS
University of Cambridge
UST – KASI(Korea Astronomy and Space Science Institute)
Instituto de Astrofı́sica deAndalucı́a
Stockholm University
African Institute for Mathematical Sciences
Canadian Institute for Theoretical Astrophysics
University College London
Tufts University
Institut d’Astrophysique deParis
ICC Durham University
CEA-Saclay
IAS-Orsay
Centro de Astrofı́sica da
Universidade do Porto
UWC, Cape Town
Université Lille 1 IMCCE
Paris
Korea Astronomy and Space
Science Institute
ESO
Universidad de Guanajuato
University College London
Eotvos Lorand University
Osservatorio Astronomico
di Roma
Università degli Studi di
PadovaKapteyn Astronomical Institute
Institut d’Astrophysique deParis
Universidad de Chile
Max-Planck-Institut for Astrophysics
ETH Zurich
Xinjiang Observatory
University of Pittsburgh
Universidade de Lisboa SIM e IAA-CSIC

Portugal
United Kingdom
BrazilBrazilSouth Africa
Chile
United States of America
Portugal
Netherlands
Japan
Netherlands
Germany
Germany
United States of America
South Africa
United Kingdom
South Korea

Spain
SwedenSouth Africa
CanadaUnited Kingdom
United States of America
FranceUnited Kingdom
FranceFrancePortugal
South Africa
FranceKorea
Germany
MexicoUnited Kingdom
Hungary
Italy
Italy
Netherlands
FranceChile
Germany
Switzerland
China
United States of America
Portugal

IAU Symposium 306 – SCCC21, 2014 — 129/130

Stefano Cavuoti

stefano.cavuoti@gmail.com

Stefano Camera

stefano.camera@tecnico.ulisboa.pt

Stéphane Ilic

stephane.ilic@irap.omp.eu

Stephen Feeney
Steven MurrayVallery Stanishev

s.feeney@imperial.ac.uk
steven.murray@uwa.edu.auvallery.stanishev@ist.utl.pt

Vanessa Bøhm

vboehm@mpa-garching.mpg.de

Vicent Martı́nez

martinez@uv.es

Vicken Asadourian
Vincent Pelgrims

vickenasadourian@gmail.com
pelgrims@astro.ulg.ac.be

Vincenzo Vitagliano

vitaglia@gmail.com

Vinicius Consolini Busti
Viviana Acquaviva

vinicius.busti@iag.usp.br
vacquaviva@citytech.cuny.edu

Vladimir Vinnikov

vvinnikov@list.ru

Volker Muellervmueller@aip.de

Xavier Dupac
Yabebal Fantaye

xdupac@sciops.esa.int
fantaye@mat.uniroma2.it

Yajuan Lei

leiyj@lamost.org

Yanxia Zhang

zyxsunny@gmail.com

Yen-Chi Chen
Yue Wuga014528@gmail.com
wuyue@bao.ac.cn

Yves Wiaux
Zhuoxi Huo

y.wiaux@hw.ac.uk
huozx@tsinghua.edu.cn

INAF - Osservatorio Astronomico di Capodimonte
Universidade de Lisboa–
CENTRA/IST
Institut de Recherche en Astrophysique et Planétologie
Imperial College London
ICRAR UWA
University of Lisbon - CENTRA/IST
Max-Planck-Institut für Astrophysik
Astronomical Observatory University of Valencia
University of Houston
IFPA, AGO dept., University of Liège
University of Lisbon - CENTRA/IST
University of Cape Town
New York City College ofTechnology
Dorodnicyn
ComputingCentre of the RAS
Leibniz-Institut fuer Astrophysik Potsdam AIP
ESA
University of Rome2 Tor
Vergata
National Astronomical Observatory, Chinese Academyof Sciences
National Astronomical Observatory, Chinese Academyof Sciences
Carnegie Mellon University
National
Astronomical
Observatories,
ChineseAcademy of Sciences
Heriot-Watt University
Tsinghua University

Italy
Portugal
FranceUnited Kingdom
Australia
Portugal
Germany
Spain
United States of America
Belgium
Portugal
South Africa
United States of America
RussiaGermany
Spain
Italy
China

China

United States of America
China

United Kingdom
China