dataesr/scientific-paragraphs-categorization huggingface dataset:
Euclid plans to image a billion galaxies and measure nearly 100 million galaxy redshifts. These impressive numbers will allow Euclid to realize a detailed reconstruction of the clustering of galaxies out to a redshift 2 and the pattern of light distortion from weak lensing to redshift 3. The two main probes, redshift clustering and weak lensing, are complemented by a number of additional cosmological probes: cross correlation between the cosmic microwave background and the large scale structure; abundance and properties of galaxy clusters and strong lensing and possible luminosity distance through supernovae Ia. To extract the maximum of information also in the nonlinear regime of perturbations, these probes will require accurate high-resolution numerical simulations. Besides cosmology, Euclid will provide an exceptional dataset for galaxy evolution, galaxy structure, and planetary searches.
All Euclid data will be publicly released after a relatively short proprietary period and will constitute for many years the ultimate survey database for astrophysics. A huge enterprise like Euclid requires highly considered planning in terms not only of technology but also for the scientific exploitation of future data. Many ideas and models that today seem to be abstract exercises for theorists will in fact finally become testable with the Euclid surveys. The main science driver of Euclid is clearly the nature of dark energy, the enigmatic substance that is driving the accelerated expansion of the universe. As we discuss in detail in Part 1, under the label "dark energy" we include a wide variety of hypotheses, from extradimensional physics to higherorder gravity, from new fields and new forces to large violations of homogeneity and isotropy.
In f (T ) cosmology, structure formation is modified because of a time dependent effective gravitational constant. [282]  analysed two viable f (T ) gravity models and showed that both are in very good agreement with a wide set of data, including SNIa and GRB Hubble diagrams, BAOs at different redshifts, Hubble expansion rate measurements and the WMAP7 distance priors. Yet, that wide dataset is unable to severely constrain the model parameters and hence discriminate amongst the considered f (T ) models and the ΛCDM scenario. Therefore,  [267]  investigated the imprints of f (T ) gravity on galaxy clustering and weak gravitational lensing in the context of Euclid, finding that with such a combination of probes it will indeed be possible to tightly constrain f (T ) model parameters.
For this reason, bulk flows are reliable indicators to deviations from homogeneity and isotropy on large scale, should they exist. Constraints on the power spectrum and growth rate can be obtained by comparing the bulk flow estimated from the volume-averaged motion of the sphere of radius R: B R ≡ v(x)W (x/R) d 3 x W (x/R) d 3 x , (1. 7. 41) with expected variance: σ 2 B,R = H 2 0 f 2 g 6π 2 P (k)W(kR) 2 (k) dk , (1. 7. 42) where the window function W (x/R) and its Fourier transform W(kR) describe the spatial distribution of the dataset. Over the years the bulk flows has been estimated from the measured peculiar velocities of a large variety of objects ranging from galaxies  [528, 529, 408, 345, 363, 1038]  clusters of galaxies  [730, 226, 618]  and SN Ia  [1013]. Conflicting results triggered by the use of error-prone distance indicators have fueled a long lasting controversy on the amplitude and convergence of the bulk flow, that is still ongoing.
g. , 920]) The large, homogeneous dataset expected from Euclid has the potential to settle these issues. The idea is to measure bulk flows in large redshift surveys, based on the apparent, dimming or brightening of galaxies due to their peculiar motion. The method, originally proposed by  [1146] , has been recently extended by  [914]  who propose to estimate the bulk flow by minimizing systematic variations in galaxy luminosities with respect to a reference luminosity function measured from the whole survey. It turns out that, if applied to the photo-z catalog expected from Euclid, this method would be able to detect at 5σ significance a bulk flow like the one of  [1233]  over ∼ 50 independent spherical volumes at z ≥ 0. 2, provided that the systematic magnitude offset over the corresponding areas in the sky does not exceed the expected random magnitude errors of 0.
Note in particular that the combined BAO+SN constraint is dominated by the BAO data if the coupling between photons and dark energy is included at the currently allowed level, but gets dominated by SN (and the combined constraint improves dramatically) if constraints on this coupling improve by more than one order of magnitude. In these forecasts we are assuming that the SN data will come from a SNAP-like or other DETF IV dataset. However, the need for this external dataset may be alleviated if Euclid carries out its own SN survey; this scenario is also discussed in  [89]. Figure  55 : Forecasted 68% and 95% likelihood contours for SN (filled blue), H(z) (dashed line transparent) and combined SN+H(z) (solid line transparent), assuming Euclid BAO is accompanied by a SNAP-like (or Dark Energy Task Force stage IV) supernova sample.
Particularly important can be the issue of dataset contamination. For instance, spurious transients such as core-collapse supernovae could end up in SNIa catalogs with the effect of biasing the best fit (i. e. affecting the accuracy of an experiment) rather than increasing the errors (i. e. affecting the precision) [see 55, Figure  3 ]. The way out is to look for deviating subpopulations in data in order to purge the dataset of possible contaminations. A possible tool for this task is the internal robustness introduced in  [55] , which uses bayesian evidences to assess if the dataset at hand is better described by a single cosmological model or rather by two models, a cosmological one for unbiased data and a systematical one for contaminated data. It will be necessary to develop fast algorithms in order to scan the vast datasets that will be generated by Euclid in order to find partitions that minimize the value of internal robustness.
Acknowledgments It is a pleasure to thank the  Euclid theory science working group , all science working group members, the  Euclid Consortium Board  and the whole  Euclid consortium  for fruitful discussions. We also kindly thank  Rene Laureijs ,  Ana Heras ,  Philippe Gondoin ,  Ludovic Duvet  and  Marc Sauvage  for their continuous work and support, and  Thomas Buchert  for comments on the draft. Stefano Camera  is funded by  FCT-Portugal  under  Post-Doctoral Grant  No. SFRH/BPD/80274/2011. Carlos J. Martins  is supported by an  FCT Research Professorship , contract reference  IF/00064/2012 , funded by  FCT/MCTES (Portugal)  and  POPH/FSE (EC). Valeria Pettorino  acknowledges the  Transregio TRR33 grant  on 'The  Dark Universe '. Claudia de Rham  is supported by a  Department of Energy  grant  DE-SC0009946.
e. patients with an intake below 10 days per month, on the border of medication overuse: could it     5  presents data about the methods used in main epidemiological studies concerning MOH  [5, [8] [9] [10] [11] [12] [13]. For each study, we specified the questions or criteria used for the MOH diagnosis, and specified if these questions were validated or not. One can notice that the only author using a validated questionnaire was Hagen  [14]. In the general population he determined the diagnostic performances of the association of 2 questions: headaches which are present for more than 14 days per month and the use of analgesics 4 times per week or more. With such an association, a lower sensitivity was found: 75%, specificity was 100%. Other questionnaires do exist  [14] [15] [16] [17] , but they concern research on dependence  [15, 16].
Site, environmental data and measurements The sampling programme was conducted at a fixed station R1 (668 39. 223?S, 1408 00. 139?E; Fig. 1 ) at a water depth of 53 m, ca. 300 m off the Dumont d'Urville Station on Petrel Island (I ˆle des Petrels) in East Antarctica, from 1 November (day 1) to 29 December 2001 (day 59). The station R1 was the same one visited in previous expeditions  (Riaux-Gobin et al. 2000; Riaux-Gobin et al. 2003; Riaux-Gobin et al. 2005). The ice conditions and structure were the same as described by  Riaux-Gobin et al. (2003) , with the ice break-up occurring on 10 January 2002 in this study. Discrete daily sampling was performed on the Bi, Pi and under-ice water at 5 m (UIW5). Infrared satellite images (Fig. 2 ) and meteorological data (Fig. 3 ) were provided by the Dumont d'Urville meteorological station (Meteo France and MeteoSat).
The top trap was located at 3 m under the land-fast ice, with an RCM7 current meter (Aanderaa Data Instruments, Nesttun, Norway) directly underneath it, while the bottom trap was positioned at 6 m above the seafloor (Fig. 3 ). The whole array system was stabilized with a mooring anchor. After the recovery of the sediment traps, the sample cups were split into sub-samples for later determinations of POC, nitrogen (PON) and chloropigments. The current meter, which was equipped with a temperature sensor, was programmed to register data every 20 min. The progressive diagram of currents was calculated with Aanderaa software. Sub-ice salinity and temperature profiles (0Á50 m) were obtained from 3 November to 14 December using an SBE 37-SI MicroCAT conductivityÁtemperature profiler equipped with an SBE ST pump (Sea-Bird Electronics, Bellevue, WA, USA).
Acknowledgements The authors thank the over-wintering team members for their field assistance and fellowship during EPONTA programmes, and the crew of the icebreaker Astrolabe. Many thanks are also due to the  Meteo France meteorological team at the Dumont d'Urville Station , particularly  Raymond Beugin  and Genevieve Caisso. They also thank  Francis Gallois  ( Centre de Noumea, Research Institute for Development, Noumea, France ),  Louise Oriol  and  Jocelyne Caparros  ( Banyuls-sur-Mer Biological Oceanography Laboratory), Jean-Claude Duchene (UniteMixte de Recherche, Environnements et Paleoenvironnements Oceaniques et Continentaux, Bordeaux, France ) and  Melanie Simard (Institut des sciences de la mer de Rimouski, L'Universitedu Quebec aRimouski)  for their collaboration. They thank two anonymous reviewers for their helpful comments.
Subjects Twenty adult male (mean age 24 months, range 10-41 months) zebra finches (Taeniopygia guttata) recruited from the breeding colony of the Max Planck Institute for Ornithology (Seewiesen, Germany) were used in this experiment. Birds were raised by their parents from 0 to 7 days post hatching (DPH), by their mother from 8 to 34 DPH and were kept alone from 35 to 42 DPH. The birds were then housed singly with one adult male tutor from 43 to 100 DPH (one-to-one paradigm). Thirteen different tutors were used in the present experiment. These tutors previously learnt their own song from one of three song models via tape playback. Song data collected on the experimental birds and their tutors indicate that the three song models elicited similar amount of song copy. Following tutoring (after 100 DPH), the experimental birds were housed together, first in aviaries then in large cages.
Song Recording and Analysis Prior to the fMRI experiment, each experimental bird was placed alone during 48 hours in a soundproof chamber and its song was recorded using the Sound Analysis Pro (SAP) 2. 0 software (  [21] ; http://soundanalysispro. com/). Acoustic similarity between songs was assessed using the similarity score implemented in SAP. This measure is based on five acoustic features: pitch, frequency modulation, amplitude modulation, goodness of pitch and Wiener entropy and comprises two components: 'the percentage of similarity', measuring at a large scale (70 ms) the amount of sound shared between two songs and the 'accuracy', measuring the local, fine grained (10 ms) similarity (for more details, see SAP user manual, available at http:// soundanalysispro. com/). The final score corresponds to the product of these two components.
Experimental setup and design During the experiment, birds were continuously anaesthetized with 1. 5% isoflurane. Auditory stimuli were played back at a mean intensity (in term of Root Mean Square) of 70 dB through small loudspeakers (Visation, Germany) from which magnets were removed. An equalizer function was applied to the stimuli using WaveLab software (Steinberg, Germany) to correct for enhancement of frequencies between 2500 and 5000 Hz in the magnet bore (see  Poirier et al, 2010). Stimulus delivery was controlled by Presentation 0. 76 software (Neurobehavioral Systems Inc. , Albany, CA, USA). During fMRI acquisition, the three stimuli were randomly presented in an ON/OFF blocked design where 16 s stimulation (ON blocks) and 16 s rest periods (OFF blocks) were alternated. Each ON block included repetitions of the same stimulus interleaved with silent periods.
Image processing Data processing was carried out using SPM8 (Wellcome Trust Centre for Neuroimaging, London, UK; http://www. fil. ion. ucl. ac. uk/spm/). To enable an accurate localization of the functional activations, the high-resolution anatomical 3D images of each subject were normalized to the MRI atlas of the zebra finch brain  [23]. Each fMRI time series was realigned to correct for head movements, co-registered to the high-resolution 3D image of the same bird and up-sampled to obtain a resolution of 12561256400 mm, as classically done in fMRI data processing. These steps resulted in a good correspondence between the fMRI data and the anatomical data from the atlas. Finally, the fMRI images were smoothed with a Gaussian kernel (width of 50065006800 mm 3 ).
Only the ATLAS and CMS Collaborations are in a position to perform such detailed investigations and preliminary studies have already started  [42]. level) and how they are implemented in the programs HPAIR  [44] , VBFNLO  [45]  and a code developed by us to evaluate the inclusive cross sections in Higgs-strahlung processes. In section 3, we evaluate the various theoretical uncertainties affecting these cross sections and collect at M H = 125 GeV the double Higgs production cross sections at the various LHC energies. We also study the sensitivity in the different processes to the trilinear Higgs self-coupling. Section 4 will be devoted to a general discussion of the channels that could allow for the detection of the two Higgs boson signal at a high-luminosity 14 TeV LHC, concentrating on the dominant gg → HH process, together with an analysis of the major backgrounds.
[11]  as well as the NLO QCD corrections in the LET approximation in Ref. [18]. The full LO expressions for F △ , F and G are used wherever they appear in the NLO corrections in order to improve the perturbative results, similar to what has been done in the single Higgs production case where using the exact LO expression reduces the disagreement between the full NLO result and the LET result  [7, 19]. For the numerical evaluation we have used the publicly available code HPAIR  [44]  in which the known NLO corrections are implemented. As a central scale for this process we choose µ 0 = µ R = µ F = M HH , (7) where M HH denotes the invariant mass of the Higgs boson pair. This is motivated by the fact that the natural scale choice in the process gg → H is µ 0 = M H. Extending this to Higgs pair production naturally leads to the scale choice of Eq.
The MSTW collaboration estimates this uncertainty for α s at NLO to ∆α s (M Z ) = ±0. 003 [60]. However this uncertainty is already included in the scale uncertainty on the input data sets used to fit the PDF and has been taken into account in the definition of the PDF+α s uncertainty. Thus, it does not have to be taken into account separately and the combined PDF+α s error calculated with the MSTW 2008 PDF set will be our default PDF+α s uncertainty. However, even if all these uncertainties for the MSTW PDF set are taken into account, the different PDF set predictions do not agree. There might be agreement if also uncertainties of the other PDF sets are taken into account, as done in Ref. [37]  for the case of single Higgs production. This means that the PDF uncertainty might be underestimated, but this issue is still an open debate (see for example Ref.
Prospects at the LHC As shown in the previous section, inclusive Higgs boson pair production is dominated by gluon fusion at LHC energies. Other processes, such as weak boson fusion, qq ′ → qq ′ HH, associated production with heavy gauge bosons, q q′ → V HH (V = W, Z), or associated production with top quark pairs, gg/q q → t tHH, yield cross sections which are factors of 10 -30 smaller than that for gg → HH. Since at the LHC Higgs boson pair production cross sections are small, we concentrate on the dominant gluon fusion process. In the following, we examine channels where At the time of the analysis, no generator existed for the signal process, but the matrix element for Higgs pair production in the gluon fusion channel was available in the Fortran code HPAIR  [18, 44]. In parallel to the approach used by the program described in  [63, 64] , the HPAIR matrix element was added to Pythia 6  [65].
The b bγγ decay channel In this subsection, the b bγγ final state for the production of two Higgs bosons with a mass of 125 GeV at √ s = 14 TeV is investigated. Earlier studies can be found in Ref. [38]. The calculation of the signal, pp → HH → b bγγ, is performed as described above by incorporating the matrix element extracted from the program HPAIR into Pythia 6. We include the effects of NLO QCD corrections on the signal by a multiplicative factor, K N LO = 1. 88, corresponding to a 125 GeV Higgs boson and a c. m. energy of 14 TeV. The Higgs boson mass is assumed to be M H = 125 GeV. Here we set the factorization and renormalization scales equal to M HH. The generated background processes are the QCD process b bγγ and the associated production of a Higgs boson with a t t pair, t tH, with the Higgs boson subsequently decaying into a photon pair and the top quarks decaying into a W boson and a b quark, as well as single Higgsstrahlung ZH with the Higgs boson decaying into γγ and the Z boson decaying into b b.
Acknowledgements: We are grateful to  G. Salam ,  C. Grojean  and  M. Spannowsky  for discussions as well as  S. Moretti  for clarifications. J. B. and R. G. also thank  S. Palmer ,  M. Rauch  and  D. N. Le  for clarifications and discussions about the VBF and Higgs-strahlung processes. A. D. and J. Q. thank  CERN  for its kind hospitality. J. B. , R. G. and M. M. M. acknowledge the support from the  Deutsche Forschungsgemeinschaft  via the Sonderforschungsbereich/Transregio SFB/TR-9 Computational Particle Physics. R. G. acknowledges the financial support from the  Landesgraduiertenkolleg. A. D. is supported by the  ERC  advanced grant Higgs@LHC.
The Cassini flyby of Jupiter in late 2000 provided highresolution images that were also used to study the zonal winds system  (Porco et al. 2003; Vasavada & Showman 2005). The New Horizons flyby of Jupiter in 2007 also provided valuable data of Jupiter's atmospheric dynamics  (Reuter et al. 2007) , but an analysis of the global wind profile over this dataset has not yet been published. The latest Jupiter overall wind profile was measured using  HST observations acquired in 2008 (Asay-Davis et al. 2011). A summary of the characteristics of these observations and wind retrievals is given in Table  1. Considering the results of these studies as a whole, there have been very few changes since the early measurements by the Voyagers to the latest wind fields from HST observations in 2008. The mean intensity of the winds has shown temporal variability on the order of ∼10 ms - 1  (Asay-Davis et al.
2012). There are also some local changes in the NTB and in the westward 17 • N (planetocentric) jet  (Barrado-Izagirre et al. 2009a ) that seem to be linked to planetary-size disturbances. Up to now Jupiter zonal wind profiles at cloud level have been measured either by using either very high-resolution observations, attainable only from HST or spacecraft missions, or by performing detailed tracking of selected features over a long period to determine their motions with enough accuracy. The latter procedure is only applicable to relatively large-scale structures that survive over many days, and although it provides accurate zonal drifts, it lacks latitudinal spatial resolution to resolve the structure of the jets. Typical precision of wind retrievals from ground-based data spanning a few weeks can be 1 ms -1 , but the latitudinal precision may be only 0.
2006 ). This technique is based on selecting the best quality images from a stream of frames obtained by high-sensitivity electronic detectors. Each frame is blurred differently due to atmospheric seeing. Specialized software (such as Registax 1 ) is used to automatically select the best frames that coregister and stack a final image of high signal-to-noise ratio and reduced blurring. In good seeing conditions, telescopes with diameters in the range of ∼20-50 cm provide images that attain their diffraction limit; this translates into spatial resolutions of 1500-600 km over the Jovian disk at opposition  (Parker 2007). The large number of amateur astronomers observing Jupiter provides a nearly continuous monitoring of the planet. Selecting the best images obtained close to opposition by observers from different locations on Earth, we can find high-quality Jupiter images of the same area obtained after one or two Jupiter rotations.
Observations The atmosphere's node of the International Outer Planet Watch (IOPW) manages an open access database of outer planet images called Planetary Virtual Observatory (PVOL 2  ) which is documented in  Hueso et al. (2010). It currently stores a large number of images (more than 15 500 of Jupiter and Saturn) that have been mainly contributed by an international network of amateur astronomers and by some planetary scientists. Most of the amateur observations come from telescopes with diameters in the range of 25-40 cm. The IOPW-PVOL observations have a wide temporal coverage starting from the year 2000. The spatial resolution, overall quality of the images and the number of observers contributing to this database are improving year after year (the number of Jupiter observations per year doubles every four years and reached 2600 individual observations in 2011).
For this telescope, taking a mean distance between Jupiter and the Earth of approximately 6. 26×10 8 km from September to December 2011, the diffraction-limited spatial resolution over the Jovian disk is about 1200 km (0. 95 • of longitude). Although most of the contributions to the IOPW-PVOL database come from amateurs, there are also observations obtained by professional observatories. In particular we used images from the Pic-du-Midi 1050 mm telescope with a diffraction limit of 0. 13 arcsec at red wavelengths translating into maximum spatial resolutions of 0. 3 • /pixel (381 km/pixel over Jupiter's disk at opposition). Images used in this work are red green blue (RGB) color compositions obtained in broadband filters and processed from video observations to get a single jpg file, which is the result of a strong contrast enhancement.
Methodology and analysis Image pairs were selected according to their quality and time separation. The RGB images were transformed into gray-scale images with a principal component analysis algorithm, which ensures that the gray-scale image contains most of the spatial information and the minimum amount of noise  (Petrou & Petrou 2010). The gray-scale images were navigated using the software LAIA  (Cano 1998) , which allows a pixel position (x,y) to be transformed on the image into longitude-latitude planetary coordinates  (Barrey 1984). The orientation of the images is a critical factor for navigation since a small error in the tilt of the planetary axis introduces a noticeable error in the wind measurement; for instance, a tilt error of 1 • translates into a zonal velocity error of 4 ms -1 at 30 • of latitude for a 10 h image pair.