dataesr/scientific-paragraphs-categorization huggingface dataset:
Searching for cosmic strings with the LIGO-Virgo gravitational-wave experiments Presented by Florent Robinet for the LIGO Scientific Collaboration and the Virgo Collaboration Cosmic strings are linear topological defects which are expected to form during symmetry-breaking phase transitions in the early universe  [19]. Some inflation models based on string theory predict that fundamental strings and D-strings could grow to cosmic scales and constitute a network of cosmic superstrings  [20]. When forming loops, cosmic strings radiate energy through bursts of gravitational waves in the presence of cuspy features  [21]. This mechanism represents one of the most promising observational signatures to detect the existence of cosmic strings. We searched for bursts of gravitational waves produced by cosmic string cusps in 625 days of data from ground-based interferometers LIGO and Virgo.
No gravitational-wave signals were detected. We find 90 %-confidence upper limits on the coalescence rates of binary black hole systems with non-spinning components as follows: for systems with components of 5 ± 1 solar masses, a limit of 6. 4 × 10 -6 /Mpc 3 /year; for systems with components between 19 and 28 solar masses, a limit of 3. 3 × 10 -7 /Mpc 3 /year. I also discuss the science case and prospects for detection in the Advanced detector era, and technical challenges faced by current and future searches. The Advanced LIGO  [3]  and Advanced Virgo  [4]  detectors are expected to start acquiring data in 2015, and work toward their target sensitivity over the subsequent years. A major goal for LIGO and Virgo will be to detect or set limits on the energy density of a stochastic background of gravitational waves.
A stochastic background of gravitational waves is expected to arise from a superposition of a large number of unresolved cosmological and/or astrophysical sources. A cosmologically produced background would carry unique signatures from the earliest epochs in the evolution of the Universe. Similarly, an astrophysical background would provide information about the sources that generated it. Advanced LIGO and Advanced Virgo observations should be able to probe interesting regions of parameter space for these models. LIGO and Virgo's search strategies for these signals were reported in the talk. Using LIGO science run S5 data, an upper limit on the energy density of gravitational waves (from 41 to 169 Hz) was set to be Ω GW < 6. 9 × 10 -6  [32]. As Advanced LIGO and Advanced Virgo come online and work through commissioning to achieve their target sensitivities, there will be a few data collection science runs  [33].
For each reconstructed direction, its resolution and systematic error are determined using a mapping error system. To reduce the false alarm rate, triggers are vetoed using information from the spherical modes. In the near future, we expect to add a matched filter to the pipeline. This will increase GW parameter resolution and reduce the false alarm rate. As a future part of the pipeline, a cosmic ray veto was added to the Mario Schenberg setup in December 2011. Since then, it is acquiring data and we are analyzing the local multiplicity. The energy deposition due to cosmic rays on the sphere is presently being simulated.
Furthermore, we show that we can differentiate between models for rotating accretion-induced collapse of massive white dwarfs and models of rotating iron core collapse with high reliability out to several kpc. A gravitational-wave search algorithm for non-precessing spinning binary black holes. By Privitera S. , Mohapatra S. , Hanna C. , Fotpolous N. , Ajith P. , Weinstein A. , Whelan J. Previous searches for gravitational waves in LIGO-Virgo data from the inspiral, merger and ringdown of binary black holes have used a matched-filter approach with non-spinning templates. However, astrophysical black holes in binaries are expected to have significant spin; neglecting such effects in the templates may reduce the detection efficiency. Gravitational-wave signal models from the coalescences of non-precessing spinning binary black holes have recently become available, but it is not known whether using these templates in a search can improve detection efficiency of generic-spinning binary black holes signals in realistic, non-Gaussian noise from the Initial LIGO detectors.
We present the analysis methods and current status of the first ongoing search for sources in binary systems in the LIGO Science Run 6 and Virgo Science Runs 2 and 3 data sets. Resolving noise structures in Virgo and LIGO data: an application of non-linear system identification. By Piergiovanni F. , Guidi G. , Carini A. A gravitational wave detector features many kinds of non-linear physical processes. Disturbances present in auxiliary channels, including narrow spectral features, may be converted linearly and non-linearly into noise, polluting the gravitational channel in a wide frequency range. Uncovering such relationships between auxiliary channels and the gravitational wave channel can be very useful for characterizing the detector and possibly also for improving the confidence of gravitational wave searches.
Gravitational waves from SCO X-1 : prospects for detection and a comparison of methods. By Crowder G. , Dergachev V. , Galloway D. , Goetz E. , Meadors G. , Messenger C. , Premachandra S. , Riles K. , Sammut L. , Thrane E. , Whelan J. The low-mass X-ray binary Scorpius X-1 is potentially our most luminous source of continuous gravitational radiation. Unlike for the recycled pulsars already targeted by LIGO-Virgo, this radiation would be powered by the accretion of matter from its binary companion rather than its rotational energy. With the advanced detector era fast approaching, work is underway to develop an array of robust tools for maximizing the science and detection potential of Sco X-1. It will be possible with advanced detector data to attain sensitivities below the current theoretical torque-balance limits, implying that signal detection is a possibility.
Here we present some of the considerations that went into designing this search, addressing the following questions: What astrophysical priors can we use? What parameter space can we cover? How can we distribute computing power to obtain the best detection probability? How can we balance these aims with the practical constraints of an Einstein@Home search? An F-statistic based multi-detector veto for detector artifacts in continuous gravitational wave searches. By Keitel D. , Prix R. , Papa M. A. , Leaci P. , Siddiqi M. The emission of continuous gravitational waves (CWs) is expected from spinning neutron stars with non-axisymmetric deformations. Detecting these very weak signals requires very sensitive instruments and data analysis techniques. The standard multi-detector F-statistic often used for CW data analysis is optimal in Gaussian noise, but susceptible to false alarms from noise artifacts in the form of strong monochromatic lines.
In the past, ad-hoc post-processing vetoes have been used to remove these artifacts. Here we provide a systematic framework to derive a generalized form of such line vetoes (LVs). With an extended noise model including a hypothesis for single-detector lines, we can use a Bayesian odds ratio to derive a generalized detection statistic: the LV-statistic. Compared to the F-statistic, it requires very little extra computational effort. We test this LV-statistic on both simulated and real detector data from the first year of the fifth LIGO science run. We show that the LV-statistic retains most of the detection power of the F-statistic in Gaussian noise, while being much more robust in the presence of line artifacts. Furthermore, we briefly describe the advantages, in the context of Einstein@Home, of applying the LV-statistic directly on the host machines, as done in a recent search that analyzed data from the sixth LIGO science run, and whose post-processing is currently underway.
Impact of noise cancellation on the search for gravitational wave transient signals. By Re V. , Drago M. , Klimenko S. , Mazzolo G. , Necula V. , Prodi G. , Salemi F. , Tiwari V. , Vedovato G. , Yakushin I. One of the prominent problems in the search for GW is the presence of non gaussian excess noise which may hide a GW signal due to increased false alarm rate. Regression analysis of auxiliary environmental and instrumental channels can provide a partial noise cancellation by measuring the linear (or non linear) coupling of the auxiliary channels to the GW channel, thus subtracting such predicted contributions from the noise. In this work we explore the impact that this method has on the search for transient GW signals. We present preliminary results of the application of noise cancellation on a set of real data from the first joint LIGO-Virgo run.
The efficiency of the method and the impact on the search sensitivity is tested by means of software injections simulating transient signals in the data. Investigations are being pursued in particular within the lower frequency band (<100 Hz ) which will be of particular astrophysical interest in future observations by the advanced detectors, being crucial for the achievable range of BH-BH coalescences. Searching for a stochastic GW background from populations of neutron stars in data from the LIGO & Virgo detectors. By Bose S. We describe a search in LIGO and Virgo data for a stochastic gravitational-wave background from populations of rotating non-axisymmetric neutron stars in our galaxy and in the Virgo cluster. Employing multi-baseline radiometry, bounds on the GW strain power from these populations can be obtained.
Acknowledgments We wish to thank the organizers of the GR 20/Amaldi 10 conference, and our hosts at the  University of Warsaw , for an excellently organized, smoothly run and extremely stimulating meeting. The authors gratefully acknowledge the support of the  United States National Science Foundation  for the construction and operation of the  LIGO Laboratory , the  Science and Technology Facilities Council of the United Kingdom , the  Max-Planck-Society , and the  State of Niedersachsen/Germany  for support of the construction and operation of the GEO600 detector, and the  Italian Istituto Nazionale di Fisica Nucleare  and the  French Centre National de la Recherche Scientifique  for the construction and operation of the Virgo detector. The authors also gratefully acknowledge the support of the research by these agencies and by the  Australian Research Council , the  International Science Linkages program of the Commonwealth of Australia , the  Council of Scientific and Industrial Research of India , the  Istituto Nazionale di Fisica Nucleare of Italy , the  Spanish Ministerio de Economía y Competitividad , the  Conselleria d'Economia Hisenda i Innovació of the Govern de les Illes Balears , the  Foundation for Fundamental Research on Matter  supported by the  Netherlands Organisation for Scientific Research , the  Polish Ministry of Science and Higher Education , the  FOCUS Programme of Foundation for Polish Science , the  Royal Society , the  Scottish Funding Council , the  Scottish Universities Physics Alliance , The  National Aeronautics and Space Administration, OTKA of Hungary , the  Lyon Institute of Origins (LIO) , the  National Research Foundation of Korea, Industry Canada  and the  Province of Ontario  through the  Ministry of Economic Development and Innovation , the  National Science and Engineering Research Council Canada , the  Carnegie Trust , the  Leverhulme Trust , the  David and Lucile Packard Foundation , the  Research Corporation , and the  Alfred P.
Improvements in structural biology methods, in particular crystallography and cryo-electron microscopy, have created an increased demand for the refinement of atomic models against low-resolution experimental data. One way to compensate for the lack of high-resolution experimental data is to use a priori information about model geometry that can be utilized in refinement in the form of stereochemical restraints or constraints. Here, the definition and calculation of the restraints that can be imposed on planar atomic groups, in particular the angle between such groups, are described. Detailed derivations of the restraint targets and their gradients are provided so that they can be readily implemented in other contexts. Practical implementations of the restraints, and of associated data structures, in the Computational Crystallography Toolbox (cctbx) are presented.
This knowledge may serve as a restraint that can be applied to the refinement of such models. Adding a new restraint into the refinement target means developing a corresponding algorithm to calculate its value, as well as an algorithm to calculate the gradient of this restraint function. We use the example of the parallelity restraint, implemented in cctbx (Grosse-  Kunstleve et al. , 2002) , to illustrate the general approach of adding new restraints in cctbx and PHENIX  (Adams et al. , 2010)  and also to reinforce the general principles of crystallographic refinement programs. This article describes the algorithms in a ready-to-program manner, with sufficient mathematical and computational details to serve a didactic purpose as well. Practical examples of the application of this new restraint function to model refinement will be presented elsewhere.
Computational Crystallography Toolbox The Computational Crystallography Toolbox (cctbx) is an open-source library with numerous functionalities necessary to construct crystallography-oriented programs. In fact, it finds applications beyond crystallography, such as small-angle scattering (sastbx;  Liu et al. , 2012)  or cryo-EM  (Afonine et al. , 2013). cctbx contains tools to handle various objects such as crystal symmetry, diffraction data, maps (crystallographic or cryo-EM) and atomic models, and provides an array of building blocks necessary to construct complex procedures such as model refinement  (Afonine et al. , 2012)  or diffraction data analysis  (Sauter et al. , 2013; Parkhurst et al. , 2014). In particular, to support macromolecular refinement algorithms cctbx includes tools to handle various geometry restraints (Grosse-Kunstleve &  Adams, 2004).
Technically, adding additional restraints means adding additional terms to equation (  22 ), which in turn means that an algorithm for calculating the additional restraint target and its gradient with respect to atomic coordinates, and the data structures for holding information about the atoms involved, are required. The implementation of the parallelity restraint in cctbx is very similar to other restraints (angle, dihedral angle, planarity etc. ) and therefore may serve as an example of the common framework for restraints.
General approach to defining stereochemical restraints in cctbx The source code for commonly used restraints is located at http://sourceforge. net/p/cctbx/code/HEAD/tree/trunk/cctbx/ geometry_restraints in the files bond. h, bond_bpl. cpp, angle. h, angle_bpl. cpp, dihedral. h, dihedral_bpl. cpp, chirality. h, chirality_bpl. cpp, nonbonded. h, nonbonded_bpl. cpp, planarity. h, planarity_bpl. cpp, parallelity. h and parallelity_bpl. cpp. Files with the name <type of restraint>_bpl. cpp contain boost. python (Abrahams & Grosse-Kunstleve, 2003)  descriptions of classes and functions for the restraint, and the bpl in the file names stands for 'boost. python library'. Generally, these files contain boost. python wrappers for classes describing the restraint and the associated data structure (termed proxy; see below) holding the information necessary to calculate the restraint.
Class to handle parallelity restraint The parallelity restraint itself [equation (  4 )] and its modifications [equations (  7 ) and (  11 )] are implemented as a C++ class parallelity available in Python via boost. python from cctbx. geometry_restraints. parallelity. It has two constructors. One requires providing all parameters to define a parallelity proxy (such as target value, type of function etc. ) and two sets of Cartesian atomic coordinates corresponding to the two planes. The other constructor takes an array with Cartesian coordinates of atoms and an instance of the paral-lelity proxy class that contains the rest of the required information. All constructors contain a call to the init_deltas() function which calculates all necessary values, such as the overall restraint value and the gradients.
Acknowledgements This work was supported by the  NIH  (project  1P01 GM063210 ), by the  PHENIX Industrial Consortium , and in part by the  US Department of Energy  under contract No. DE-AC02-05CH11231. AU thanks the  French Infrastructure for Integrated Structural Biology (FRISBI)  (grant No. ANR-10-INSB-05-01 ) and Instruct, part of the  European Strategy Forum on Research Infrastructures (ESFRI).
This paper presents a framework for considering quality control of volunteered geographic information (VGI). Different issues need to be considered during the conception, acquisition and post-acquisition phases of VGI creation. This includes items such as collecting metadata on the volunteer, providing suitable training, giving corrective feedback during the mapping process and use of control data, among others. Two examples of VGI data collection are then considered with respect to this quality control framework, i. e. VGI data collection by National Mapping Agencies and by the most recent Geo-Wiki tool, a game called Cropland Capture. Although good practices are beginning to emerge, there is still the need for the development and sharing of best practice, especially if VGI is to be integrated with authoritative map products or used for calibration and/or validation of land cover in the future.
INTRODUCTION The ease of geolocation through mobile phones and the ability to create and share online maps and georeferenced photographs have resulted in a phenomenon known as Volunteered Geographic Information (VGI)  (Goodchild, 2007). VGI encompasses a vast range of citizen-contributed geographic data, and some very different forms of contributor engagement, from actively mapping spatial features in OpenStreetMap (OSM) to sharing holiday photos in Flickr. As new low cost sensors become available to measure environmental variables such as atmospheric temperature, air quality, and soil moisture, VGI has the potential to play a considerable role in environmental monitoring and the collection of in-situ data  (Connors et al. , 2012). However, concerns over data quality remain one of the main barriers to use of VGI in authoritative databases  (Flanagin and Metzger, 2008; Coleman, 2013).
This degree of confidence can provide valuable information about the degree of subjectivity or difficulty associated with a particular set of data, or may be used to weight several contributions, if majority rules are used. Such an approach has been used in Geo-Wiki in the post-acquisition phase to filter the data for quality before they were used in subsequent research  (Fritz et al. , 2013). During the post-acquisition phase traditional methods for controlling data quality, mainly related to the positional, thematic and completeness aspects, can be used. For example, confusion matrices can be generated or data matching between vector features can be undertaken by experts, comparing the VGI with authoritative data such as topographic data or in-situ data collected from professional surveys.
However, the particular characteristics of VGI raise difficulties with these approaches, since there are usually fewer, if any, strict protocols for data collection. Authoritative data generally have a single accepted level of detail across the coverage, very precise rules on selection (e. g. buildings having less than 20m 2 are not captured) and geometric capture (e. g. the capture fits the outer perimeter of the building) and a well-defined list of possible attributes. In contrast, VGI can be highly heterogeneous so that completeness varies depending on location and scale. In addition, discrepancies between VGI and reference data can potentially stem from the fact that the VGI could be more current (and therefore, for many purposes, more 'correct') than the reference data. Therefore, for any detailed assessment of contributors' credibility and contribution reliability, the control data should be not only correct but also cotemporaneous with the contributions, unless the phenomenon or feature under consideration changes very rarely.
VGI collected by NMAs As part of COST Action TD1202 activities -a survey conducted from December 2013 to February 2014 and recent meetings (February 2015 and March 2014) involving representatives of many European NMAs -the workflows and processes by which VGI was being managed or introduced were discussed. In this section a preliminary analysis of the presented framework is made in terms of experiences of NMAs in VGI collection, based on the data gathered in the aforementioned activities.
VGI collection procedures of NMAs A detailed analysis of the protocols for VGI collection and quality assessment is still to be performed. However, it was identified that NMA protocols defined to collect authoritative data were universally seen as too detailed and complex to be used by the crowd. This means that protocols defined by the NMAs to assess the quality of authoritative data cannot be reused for VGI either, since the collection process is not the same. A typical workflow illustrating the acquisition and postacquisition phase in terms of experiences of NMAs with VGI is shown in Figure  2. Gray boxes can be viewed as good practices for NMAs engaged with VGI or which plan to get involved in VGI data collection in the near future. What seems important for most of the NMAs is to ensure that the feedback flow is visible and to manage quality control in order to guarantee the quality of the contributions.
As indicated in section 3. 1, all NMAs that collect VGI reported that they use it for change detection and error reporting of the official information. For this aim no control data or 'gold standard' data are available, since the aim is actually to identify deficiencies in the authoritative data. Due to the objective of the VGI collected by these authorities, all NMAs reported that quality control of all collected VGI is necessary and must be performed by experts within the NMAs. Self-checking or selfvalidation by the crowd is the only procedure that cannot be considered as acceptable by NMAs. However, the NMAs found that, in general, there are few bad contributions in their VGI data collection programmes. Many NMAs found that more than 80% of citizen contributions are actually useful and can be used, which often correspond to small contributions or changes submitted by citizens, but which also corresponded to the largest amount of work required to validate and then implement the changes.
The quality control procedures implemented in NMAs vary by NMA. Each NMA has its own policy and direction on this issue. Some NMAs allow the VGI to flow into the same data processing workflows as expert-collected data, while other NMAs have developed separate parallel data processing workflows. Establishing workflows for processing VGI data within the NMA was identified as one of the most important issues in VGI data collection. One of the concerns of NMAs is the amount of VGI collected. If redundancy is allowed, since all VGI collected by NMAs needs to be checked by experts, an overload of information may became easily useless due to the amount of work required for its validation. Therefore, repeated contributions of the same event are not usually desirable, since in general no automated filtering procedures are implemented.