Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

Photometric redshifts (photo-zs) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with photometrically selected galaxies (GCph) and weak lensing. In the next decade, space missions such as Euclid will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the Euclid mission. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-zs. When combining GCph and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-z degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints

Euclid preparation : XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

Photometric redshifts (photo-zs) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with photometrically selected galaxies (GC(ph)) and weak lensing. In the next decade, space missions such as Euclid will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the Euclid mission. We focus on GC(ph) and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GC(ph) and its combination with GGL, respectively. For GC(ph), an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-zs. When combining GC(ph) and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-z degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints.Peer reviewe

IgG cryoglobulinemia

OBJECTIVE: Mixed Cryoglobulinemia is the most well-known Hepatitis C Virus (HCV)-associated extrahepatic manifestation. MC is both an autoimmune and B-lymphoproliferative disorder. Cryoglobulins (CGs) are classified into three groups according to immunoglobulin (Ig) composition: type I is composed of one isotype or Ig class. Type II and type III mixed CGs are immune complexes composed of polyclonal IgGs acting as autoantigens and mono, polyclonal or oligoclonal IgM with rheumatoid factor activity. IgG1 and IgG3 are the predominant subclasses involved. This study shows the simultaneous presence of IgG-RF and IgG3, supporting the hypothesis of an involvement of this subclass in the initiation of early stages of CGs. PATIENTS AND METHODS: We describe a case series of six HCV-positive patients, all of whom had peripheral neuropathy and transient ischemic attacks, presenting cryoprecipitates formed by IgG3 and IgG1. Cryoprecipitate IgG subclass research was carried out by immunofixation electrophoresis by using antisera against IgG1, IgG2, IgG3, and IgG4. RESULTS: Our six patients presented with an immunochemical pattern characterized by the mere presence of IgG1 and IgG3 subclasses with probable RF activity and one of these six patients exhibited monoclonal IgG3 in his cerebrospinal fluid. CONCLUSIONS: We can hypothesize that the IgG passage through the blood-brain barrier could have contributed to the cause of TIAs, through a mechanism involving the precipitation of circulating immune complexes formed by the two subclasses in the intrathecal vessels

Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and galaxy-galaxy lensing using the MagLim lens sample

DES Collaboration: A. Porredon et al.The cosmological information extracted from photometric surveys is most robust when multiple probes of the large scale structure of the Universe are used. Two of the most sensitive probes are the clustering of galaxies and the tangential shear of background galaxy shapes produced by those foreground galaxies, so-called galaxy-galaxy lensing. Combining the measurements of these two two-point functions leads to cosmological constraints that are independent of the way galaxies trace matter (the galaxy bias factor). The optimal choice of foreground, or lens, galaxies is governed by the joint, but conflicting requirements to obtain accurate redshift information and large statistics. We present cosmological results from the full 5000deg2 of the Dark Energy Survey’s first three years of observations (Y3) combining those two-point functions, using for the first time a magnitude-limited lens sample (MagLim) of 11 million galaxies, especially selected to optimize such combination, and 100 million background shapes. We consider two flat cosmological models, the Standard Model with dark energy and cold dark matter (ΛCDM ) a variation with a free parameter for the dark energy equation of state (wCDM). Both models are marginalized over 25 astrophysical and systematic nuisance parameters. In ΛCDM we obtain for the matter density Ωm=0.320+0.041−0.034 and for the clustering amplitude S8≡σ8(Ωm/0.3)0.5=0.778+0.037−0.031, at 68% C.L. The latter is only 1σ smaller than the prediction in this model informed by measurements of the cosmic microwave background by the Planck satellite. In wCDM we find Ωm=0.32+0.044−0.046, S8=0.777+0.049−0.051 and dark energy equation of state w=−1.031+0.218−0.379. We find that including smaller scales, while marginalizing over nonlinear galaxy bias, improves the constraining power in the Ωm−S8 plane by 31% and in the Ωm−w plane by 41% while yielding consistent cosmological parameters from those in the linear bias case. These results are combined with those from cosmic shear in a companion paper to present full DES-Y3 constraints from the three two-point functions (3×2pt).Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministerio da Ciência, Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciencies de l’Espai (IEEC/CSIC), the Institut de Física d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES data management systemis supported by the National Science Foundation under Grants No. AST-1138766 and No. AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under Grants No. AYA2015-71825, No. ESP2015-66861, No. FPA2015-68048, No. SEV-2016-0588, No. SEV-2016-0597, and No. MDM-2015-0509, some of which include ERDF funds fromthe European Union. I. F. A. E. is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC Grant Agreements No. 240672, No. 291329, and No. 306478. We acknowledge support from the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through Project No. CE110001020, and the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) e-Universe (CNPq Grant No. 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DEAC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive paid-up irrevocable world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. Computations were made on the supercomputer Guillimin from McGill University, managed by Calcul Quebec and Compute Canada. The operation of this supercomputer is funded by the Canada Foundation for Innovation (CFI), the ministere de l’Économie, de la science et de l’innovation du Quebec (MESI) and the Fonds de recherche du Quebec-Nature et technologies (FRQ-NT). This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (Grants No. OCI-0725070 and No. ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. This research used resources of the Ohio Supercomputer Center (OSC) [117] and of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231.Peer reviewe

Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

Photometric redshifts (photo-zs) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with photometrically selected galaxies (GCph) and weak lensing. In the next decade, space missions such as Euclid will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the Euclid mission. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-zs. When combining GCph and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-z degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints

Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

Photometric redshifts (photo-zs) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with photometrically selected galaxies (GCph) and weak lensing. In the next decade, space missions such as Euclid will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the Euclid mission. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-zs. When combining GCph and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-z degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints

Euclid preparation: VIII. The Complete Calibration of the Colour–Redshift Relation survey: VLT/KMOS observations and data release

The Complete Calibration of the Colour–Redshift Relation survey (C3R2) is a spectroscopic effort involving ESO and Keck facilities designed specifically to empirically calibrate the galaxy colour–redshift relation – P(z|C) to the Euclid depth (iAB = 24.5) and is intimately linked to the success of upcoming Stage IV dark energy missions based on weak lensing cosmology. The aim is to build a spectroscopic calibration sample that is as representative as possible of the galaxies of the Euclid weak lensing sample. In order to minimise the number of spectroscopic observations necessary to fill the gaps in current knowledge of the P(z|C), self-organising map (SOM) representations of the galaxy colour space have been constructed. Here we present the first results of an ESO@VLT Large Programme approved in the context of C3R2, which makes use of the two VLT optical and near-infrared multi-object spectrographs, FORS2 and KMOS. This data release paper focuses on high-quality spectroscopic redshifts of high-redshift galaxies observed with the KMOS spectrograph in the near-infrared H- and K-bands. A total of 424 highly-reliable redshifts are measured in the 1.3 ≤ z ≤ 2.5 range, with total success rates of 60.7% in the H-band and 32.8% in the K-band. The newly determined redshifts fill 55% of high (mainly regions with no spectroscopic measurements) and 35% of lower (regions with low-resolution/low-quality spectroscopic measurements) priority empty SOM grid cells. We measured Hα fluxes in a 1. 002 radius aperture from the spectra of the spectroscopically confirmed galaxies and converted them into star formation rates. In addition, we performed an SED fitting analysis on the same sample in order to derive stellar masses, E(B − V), total magnitudes, and SFRs. We combine the results obtained from the spectra with those derived via SED fitting, and we show that the spectroscopic failures come from either weakly star-forming galaxies (at z 2 galaxies

The PAU Survey & Euclid: Improving broad-band photometric redshifts with multi-task learning

Current and future imaging surveys require photometric redshifts (photo-z) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge to advance our understanding of cosmology. In this paper, we explore how the synergies between narrow-band photometric data and large imaging surveys can be exploited to improve broad-band photometric redshifts. We use a multi-task learning (MTL) network to improve broad-band photo-z estimates by simultaneously predicting the broad-band photo-z and the narrow-band photometry from the broad-band photometry. The narrow-band photometry is only required in the training field, which enables better photo-z predictions also for the galaxies without narrow-band photometry in the wide field. This technique is tested with data from the Physics of the Accelerating Universe Survey (PAUS) in the COSMOS field. We find that the method predicts photo-z that are 14% more precise down to magnitude i_AB<23, while reducing the outlier rate by 40% with respect to the baseline network mapping broad-band colours to only photo-zs. Furthermore, MTL significantly reduces the photo-z bias for high-redshift galaxies, improving the redshift distributions for tomographic bins with z>1. Applying this technique to deeper samples is crucial for future surveys like \Euclid or LSST. For simulated data, training on a sample with i_AB <23, the method reduces the photo-z scatter by 15% for all galaxies with 24<i_AB<25. We also study the effects of extending the training sample with photometric galaxies using PAUS high-precision photo-zs, which further reduces the photo-z scatter.Comment: 20 pages, 16 figure