arXiv subjects

F. J. Castander

Publications and source records attributed to F. J. Castander.

At least 199 records · Page 11Linked to original sources

arXiv2022

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

Two of the most sensitive probes of the large scale structure of the universe 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 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 5000 sq. deg. of the Dark Energy Survey 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 cosmological models, flat $Λ$CDM and $w$CDM. In $Λ$CDM we obtain for the matter density $Ω_m = 0.320^{+0.041}_{-0.034}$ and for the clustering amplitude $S_8 = 0.778^{+0.037}_{-0.031}$, at 68% C.L. The latter is only 1$σ$ smaller than the prediction in this model informed by measurements of the cosmic microwave background by the Planck satellite. In $w$CDM we find $Ω_m = 0.32^{+0.044}_{-0.046}$, $S_8=0.777^{+0.049}_{-0.051}$, and dark energy equation of state $w=-1.031^{+0.218}_{-0.379}$. We find that including smaller scales while marginalizing over non-linear galaxy bias improves the constraining power in the $Ω_m-S_8$ plane by $31$% and in the $Ω_m-w$ 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 (3x2pt).

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arXiv2022

Dark Energy Survey Year 3 Results: Measurement of the Baryon Acoustic Oscillations with Three-dimensional Clustering

The three-dimensional correlation function offers an effective way to summarize the correlation of the large-scale structure even for imaging galaxy surveys. We have applied the projected three-dimensional correlation function, $ξ_{\rm p}$ to measure the Baryonic Acoustic Oscillations (BAO) scale on the first-three years Dark Energy Survey data. The sample consists of about 7 million galaxies in the redshift range $ 0.6 < z_{\rm p } < 1.1 $ over a footprint of $4108 \, \mathrm{deg}^2 $. Our theory modeling includes the impact of realistic true redshift distributions beyond Gaussian photo-$z$ approximation. To increase the signal-to-noise of the measurements, a Gaussian stacking window function is adopted in place of the commonly used top-hat. Using the full sample, $ D_{\rm M}(z_{\rm eff} ) / r_{\rm s} $, the ratio between the comoving angular diameter distance and the sound horizon, is constrained to be $ 19.00 \pm 0.67 $ (top-hat) and $ 19.15 \pm 0.58 $ (Gaussian) at $z_{\rm eff} = 0.835$. The constraint is weaker than the angular correlation $w$ constraint ($18.84 \pm 0.50$) because the BAO signals are heterogeneous across redshift. When a homogeneous BAO-signal sub-sample in the range $ 0.7 < z_{\rm p } < 1.0 $ ($z_{\rm eff} = 0.845$) is considered, $ξ_{\rm p} $ yields $ 19.80 \pm 0.67 $ (top-hat) and $ 19.84 \pm 0.53 $ (Gaussian). The latter is mildly stronger than the $w$ constraint ($19.86 \pm 0.55 $). We find that the $ξ_{\rm p} $ results are more sensitive to photo-$z$ errors than $w$ because $ξ_{\rm p}$ keeps the three-dimensional clustering information causing it to be more prone to photo-$z$ noise. The Gaussian window gives more robust results than the top-hat as the former is designed to suppress the low signal modes. $ξ_{\rm p}$ and the angular statistics such as $w$ have their own pros and cons, and they serve an important crosscheck with each other.

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arXiv2022

Euclid preparation: XXII. Selection of Quiescent Galaxies from Mock Photometry using Machine Learning

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15,000 sq deg of the sky. Euclid is expected to detect ~12 billion astronomical sources, facilitating new insights into cosmology, galaxy evolution, and various other topics. To optimally exploit the expected very large data set, there is the need to develop appropriate methods and software. Here we present a novel machine-learning based methodology for selection of quiescent galaxies using broad-band Euclid I_E, Y_E, J_E, H_E photometry, in combination with multiwavelength photometry from other surveys. The ARIADNE pipeline uses meta-learning to fuse decision-tree ensembles, nearest-neighbours, and deep-learning methods into a single classifier that yields significantly higher accuracy than any of the individual learning methods separately. The pipeline has `sparsity-awareness', so that missing photometry values are still informative for the classification. Our pipeline derives photometric redshifts for galaxies selected as quiescent, aided by the `pseudo-labelling' semi-supervised method. After application of the outlier filter, our pipeline achieves a normalized mean absolute deviation of ~< 0.03 and a fraction of catastrophic outliers of ~< 0.02 when measured against the COSMOS2015 photometric redshifts. We apply our classification pipeline to mock galaxy photometry catalogues corresponding to three main scenarios: (i) Euclid Deep Survey with ancillary ugriz, WISE, and radio data; (ii) Euclid Wide Survey with ancillary ugriz, WISE, and radio data; (iii) Euclid Wide Survey only. Our classification pipeline outperforms UVJ selection, in addition to the Euclid I_E-Y_E, J_E-H_E and u-I_E,I_E-J_E colour-colour methods, with improvements in completeness and the F1-score of up to a factor of 2. (Abridged)

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arXiv2022

The Dark Energy Survey Year 3 high redshift sample: Selection, characterization and analysis of galaxy clustering

The fiducial cosmological analyses of imaging galaxy surveys like the Dark Energy Survey (DES) typically probe the Universe at redshifts $z < 1$. This is mainly because of the limited depth of these surveys, and also because such analyses rely heavily on galaxy lensing, which is more efficient at low redshifts. In this work we present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around $z \sim 0.9$, $1.2$ and $1.5$, which significantly extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal-to-noise $S/N \sim 70$ after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe $Ω_m$ and the Hubble parameter $h$, $Ω_m h = 0.195^{+0.023}_{-0.018}$, and 2-3% measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, $b σ_8$. A companion paper $\textit{(in preparation)}$ will present the cross-correlations of these high-$z$ samples with CMB lensing from Planck and SPT, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work.

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arXiv2022

Euclid preparation XXVI. The Euclid Morphology Challenge. Towards structural parameters for billions of galaxies

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper by Merlin et al. focuses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes DeepLeGATo, Galapagos-2, Morfometryka, Profit and SourceXtractor++ on a sample of about 1.5 million simulated galaxies resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic Sérsic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (10% scatter on ideal Sérsic simulations) down to an apparent magnitude of about 23 in one component and 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5 respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the Euclid official Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters.

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arXiv2022

Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters

Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrate a simple model to accurately describe the clustering covariance. Then, we use such a model to quantify the likelihood analysis response to variations of the covariance, and investigate the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the 2-point correlation function of galaxy clusters. By introducing few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with 10 per cent accuracy, with differences of about 5 per cent on the figure of merit of the cosmological parameters $Ω_{\rm m}$ and $σ_8$. Also, we find that the cosmology-dependence of the covariance adds valuable information that is not contained in the mean value, significantly improving the constraining power of cluster clustering. Finally, we find that the cosmological figure of merit can be further improved by taking mass binning into account. Our results have significant implications for the derivation of cosmological constraints from the 2-point clustering statistics of the Euclid survey of galaxy clusters.

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arXiv2022

Mapping gas around massive galaxies: cross-correlation of DES Y3 galaxies and Compton-$y$-maps from SPT and Planck

We cross-correlate positions of galaxies measured in data from the first three years of the Dark Energy Survey with Compton-$y$-maps generated using data from the South Pole Telescope (SPT) and the {\it Planck} mission. We model this cross-correlation measurement together with the galaxy auto-correlation to constrain the distribution of gas in the Universe. We measure the hydrostatic mass bias or, equivalently, the mean halo bias-weighted electron pressure $\langle b_{h}P_{e}\rangle$, using large-scale information. We find $\langle b_{h}P_{e}\rangle$ to be $[0.16^{+0.03}_{-0.04},0.28^{+0.04}_{-0.05},0.45^{+0.06}_{-0.10},0.54^{+0.08}_{-0.07},0.61^{+0.08}_{-0.06},0.63^{+0.07}_{-0.08}]$ meV cm$^{-3}$ at redshifts $z \sim [0.30, 0.46, 0.62,0.77, 0.89, 0.97]$. These values are consistent with previous work where measurements exist in the redshift range. We also constrain the mean gas profile using small-scale information, enabled by the high-resolution of the SPT data. We compare our measurements to different parametrized profiles based on the cosmo-OWLS hydrodynamical simulations. We find that our data are consistent with the simulation that assumes an AGN heating temperature of $10^{8.5}$K but are incompatible with the model that assumes an AGN heating temperature of $10^{8.0}$K. These comparisons indicate that the data prefer a higher value of electron pressure than the simulations within $r_{500c}$ of the galaxies' halos.

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arXiv2022

Consistent lensing and clustering in a low-$S_8$ Universe with BOSS, DES Year 3, HSC Year 1 and KiDS-1000

We evaluate the consistency between lensing and clustering probes of large-scale structure based on measurements of projected galaxy clustering from BOSS combined with overlapping galaxy-galaxy lensing from three surveys: DES Y3, HSC Y1, and KiDS-1000. An intra-lensing-survey study finds good agreement between these lensing data. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck, with $S_8=0.83$, and a Lensing cosmology with $S_8=0.76$. For a joint analysis limited to scales with $R>5.25h^{-1}$Mpc, we find that both cosmologies provide an acceptable fit to the data. Full utilisation of the small-scale clustering and lensing measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic scaling parameter for each redshift bin, $A$, that decouples the lensing and clustering to capture any inconsistency. When a wide range of scales ($0.15<R<60h^{-1}$Mpc) are incorporated, we find different results for the consistency of clustering and lensing between the two cosmologies. Limiting the analysis to the bins for which the impact of the selection of the lens sample is expected to be minimal, for the low-$S_8$ Lensing cosmology, the measurements are consistent with $A$=1; $A=0.91\pm0.04$ using DES+KiDS and $A=0.97\pm0.06$ using HSC. For the Planck cosmology case, we find a discrepancy: $A=0.79\pm0.03$ using DES+KiDS and $A=0.84\pm0.05$ using HSC. We demonstrate that a kSZ-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of these small-scale measurements, but also indicates that caution is still warranted given current uncertainties in modelling baryonic effects, assembly bias, and selection effects in the foreground sample.

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arXiv2022

Cosmic Shear in Harmonic Space from the Dark Energy Survey Year 1 Data: Compatibility with Configuration Space Results

We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spectra using the Metacalibration catalogue and perform a likelihood analysis within the framework of CosmoSIS. We set scale cuts based on baryonic effects contamination and model redshift and shear calibration uncertainties as well as intrinsic alignments. We adopt as fiducial covariance matrix an analytical computation accounting for the mask geometry in the Gaussian term, including non-Gaussian contributions. A suite of 1200 lognormal simulations is used to validate the harmonic space pipeline and the covariance matrix. We perform a series of stress tests to gauge the robustness of the harmonic space analysis. Finally, we use the DES-Y1 pipeline in configuration space to perform a similar likelihood analysis and compare both results, demonstrating their compatibility in estimating the cosmological parameters $S_8$, $σ_8$ and $Ω_m$. The methods implemented and validated in this paper will allow us to perform a consistent harmonic space analysis in the upcoming DES data.

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arXiv2022

Euclid preparation. XXV. The Euclid Morphology Challenge -- Towards model-fitting photometry for billions of galaxies

The ESA Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real time is being developed by the Science Ground Segment of the Euclid Consortium; this pipeline will include a model-fitting algorithm, which will provide photometric and morphological estimates of paramount importance for the core science goals of the mission and for legacy science. The Euclid Morphology Challenge is a comparative investigation of the performance of five model-fitting software packages on simulated Euclid data, aimed at providing the baseline to identify the best suited algorithm to be implemented in the pipeline. In this paper we describe the simulated data set, and we discuss the photometry results. A companion paper (Euclid Collaboration: Bretonnière et al. 2022) is focused on the structural and morphological estimates. We created mock Euclid images simulating five fields of view of 0.48 deg2 each in the $I_E$ band of the VIS instrument, each with three realisations of galaxy profiles (single and double Sérsic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double Sérsic realisation, we also simulated images for the three near-infrared $Y_E$, $J_E$ and $H_E$ bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands ($u$, $g$, $r$, $i$, and $z$). To analyse the results we created diagnostic plots and defined ad-hoc metrics. Five model-fitting software packages (DeepLeGATo, Galapagos-2, Morfometryka, ProFit, and SourceXtractor++) were compared, all typically providing good results. (cut)

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arXiv2022

Characterising the Intracluster Light over the Redshift Range $0.2 < z < 0.8$ in the DES-ACT Overlap

We characterise the properties and evolution of Bright Central Galaxies (BCGs) and the surrounding intracluster light (ICL) in galaxy clusters identified in overlapping regions of the Dark Energy Survey and Atacama Cosmology Telescope Survey (DES-ACT), covering the redshift range $0.20 $14.4. We also measure the stellar mass - halo mass (SMHM) relation for the BCG+ICL system and find that the slope, $β$, which characterises the dependence of $M_{\rm 200m,SZ}$ on the BCG+ICL stellar mass, increases with radius. The outskirts are more strongly correlated with the halo than the core, which supports that the BCG+ICL system follows a two-phase growth, where recent growth ($z<2$) occurs beyond the BCG's core. Additionally, we compare our observed SMHM relation results to the IllustrisTNG 300-1 cosmological hydrodynamic simulations and find moderate qualitative agreement in the amount of diffuse light. However, the SMHM relation's slope is steeper in TNG300-1 and the intrinsic scatter is lower, likely from the absence of projection effects in TNG300-1. Additionally, we find that the ICL exhibits a colour gradient such that the outskirts are bluer than the core. Moreover, for the lower halo mass clusters (log$_{10}(M_{\rm 200m,SZ}$/M$_{\odot})<$14.59 ), we detect a modest change in the colour gradient's slope with lookback time, which combined with the absence of stellar mass growth may suggest that lower mass clusters have been involved in growth via tidal stripping more recently than their higher mass counterparts.

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arXiv2022

The Dark Energy Survey 5-year photometrically identified Type Ia Supernovae

As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multi-band light-curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNova (SNN; Möller et al. 2019) trained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1,863 SNe Ia from which we select 1,484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically-selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).

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arXiv2022

Dark Energy Survey Year 3 results: imprints of cosmic voids and superclusters in the Planck CMB lensing map

The CMB lensing signal from cosmic voids and superclusters probes the growth of structure in the low-redshift cosmic web. In this analysis, we cross-correlated the Planck CMB lensing map with voids detected in the Dark Energy Survey Year 3 (Y3) data set ($\sim$5,000 deg$^{2}$), expanding on previous measurements that used Y1 catalogues ($\sim$1,300 deg$^{2}$). Given the increased statistical power compared to Y1 data, we report a $6.6σ$ detection of negative CMB convergence ($κ$) imprints using approximately 3,600 voids detected from a redMaGiC luminous red galaxy sample. However, the measured signal is lower than expected from the MICE N-body simulation that is based on the $Λ$CDM model (parameters $Ω_{\rm m} = 0.25$, $σ_8 = 0.8$), and the discrepancy is associated mostly with the void centre region. Considering the full void lensing profile, we fit an amplitude $A_κ=κ_{\rm DES}/κ_{\rm MICE}$ to a simulation-based template with fixed shape and found a moderate $2σ$ deviation in the signal with $A_κ\approx0.79\pm0.12$. We also examined the WebSky simulation that is based on a Planck 2018 $Λ$CDM cosmology, but the results were even less consistent given the slightly higher matter density fluctuations than in MICE. We then identified superclusters in the DES and the MICE catalogues, and detected their imprints at the $8.4σ$ level; again with a lower-than-expected $A_κ=0.84\pm0.10$ amplitude. The combination of voids and superclusters yields a $10.3σ$ detection with an $A_κ=0.82\pm0.08$ constraint on the CMB lensing amplitude, thus the overall signal is $2.3σ$ weaker than expected from MICE.

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arXiv2022

A galaxy-driven model of type Ia supernova luminosity variations

Type Ia supernovae (SNe Ia) are used as standardisable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame $U-R$ colour. Identifying the cause of these steps is key to cosmological analyses and provides insight into SN physics. Here we investigate the effects of SN progenitor ages on their light curve properties using a galaxy-based forward model that we compare to the Dark Energy Survey 5-year SN Ia sample. We trace SN Ia progenitors through time and draw their light-curve width parameters from a bimodal distribution according to their age. We find that an intrinsic luminosity difference between SNe of different ages cannot explain the observed trend between step size and SN colour. The data split by stellar mass are better reproduced by following recent work implementing a step in total-to-selective dust extinction ratio $(R_V)$ between low- and high-mass hosts, although an additional intrinsic luminosity step is still required to explain the data split by host galaxy $U-R$. Modelling the $R_V$ step as a function of galaxy age provides a better match overall. Additional age vs. luminosity steps marginally improve the match to the data, although most of the step is absorbed by the width vs. luminosity coefficient $α$. Furthermore, we find no evidence that $α$ varies with SN age.

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arXiv2022

Euclid preparation: XIX. Impact of magnification on photometric galaxy clustering

We investigate the importance of lensing magnification for estimates of galaxy clustering and its cross-correlation with shear for the photometric sample of Euclid. Using updated specifications, we study the impact of lensing magnification on the constraints and the shift in the estimation of the best fitting cosmological parameters that we expect if this effect is neglected. We follow the prescriptions of the official Euclid Fisher matrix forecast for the photometric galaxy clustering analysis and the combination of photometric clustering and cosmic shear. The slope of the luminosity function (local count slope), which regulates the amplitude of the lensing magnification, and the galaxy bias have been estimated from the Euclid Flagship simulation.We find that magnification significantly affects both the best-fit estimation of cosmological parameters and the constraints in the galaxy clustering analysis of the photometric sample. In particular, including magnification in the analysis reduces the 1$σ$ errors on $Ω_{\text{m},0}, w_{0}, w_a$ at the level of 20-35%, depending on how well we will be able to independently measure the local count slope. In addition, we find that neglecting magnification in the clustering analysis leads to shifts of up to 1.6$σ$ in the best-fit parameters. In the joint analysis of galaxy clustering, cosmic shear, and galaxy-galaxy lensing, magnification does not improve precision, but it leads to an up to 6$σ$ bias if neglected. Therefore, for all models considered in this work, magnification has to be included in the analysis of galaxy clustering and its cross-correlation with the shear signal ($3\times2$pt analysis) for an accurate parameter estimation.

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arXiv2022

Dark Energy Survey Year 3 Results: Three-Point Shear Correlations and Mass Aperture Moments

We present high signal-to-noise measurements of three-point shear correlations and the third moment of the mass aperture statistic using the first 3 years of data from the Dark Energy Survey. We additionally obtain the first measurements of the configuration and scale dependence of the four three-point shear correlations which carry cosmological information. With the third-order mass aperture statistic, we present tomographic measurements over angular scales of 4 to 60 arcminutes with a combined statistical significance of 15.0$σ$. Using the tomographic information and measuring also the second-order mass aperture, we additionally obtain a skewness parameter and its redshift evolution. We find that the amplitudes and scale-dependence of these shear 3pt functions are in qualitative agreement with measurements in a mock galaxy catalog based on N-body simulations, indicating promise for including them in future cosmological analyses. We validate our measurements by showing that B-modes, parity-violating contributions and PSF modeling uncertainties are negligible, and determine that the measured signals are likely to be of astrophysical and gravitational origin.

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arXiv2022

Dark Energy Survey Year 3 Results: Calibration of Lens Sample Redshift Distributions using Clustering Redshifts with BOSS/eBOSS

We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors due to the galaxy clustering bias, finding our method to be generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for eleven different photometrically-selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift to be below $|Δz|=0.01$ in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9\%. We discuss how these results calibrate the photometric redshift distributions used in companion DES Year 3 Results papers.

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arXiv2022

Overview of the Instrumentation for the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the Baryon Acoustic Oscillation method to measure distances from the nearby universe to z > 3.5, as well as measure the growth of structure and probe potential modifications to general relativity. In this paper we describe the significant instrumentation we developed for the DESI survey. The new instrumentation includes a wide-field, 3.2-deg diameter prime-focus corrector that focuses the light onto 5020 robotic fiber positioners on the 0.812 m diameter, aspheric focal surface. The positioners and their fibers are divided among ten wedge-shaped petals. Each petal is connected to one of ten spectrographs via a contiguous, high-efficiency, nearly 50 m fiber cable bundle. The ten spectrographs each use a pair of dichroics to split the light into three channels that together record the light from 360 - 980 nm with a resolution of 2000 to 5000. We describe the science requirements, technical requirements on the instrumentation, and management of the project. DESI was installed at the 4-m Mayall telescope at Kitt Peak, and we also describe the facility upgrades to prepare for DESI and the installation and functional verification process. DESI has achieved all of its performance goals, and the DESI survey began in May 2021. Some performance highlights include RMS positioner accuracy better than 0.1", SNR per \sqrtÅ > 0.5 for a z > 2 quasar with flux 0.28e-17 erg/s/cm^2/A at 380 nm in 4000s, and median SNR = 7 of the [OII] doublet at 8e-17 erg/s/cm^2 in a 1000s exposure for emission line galaxies at z = 1.4 - 1.6. We conclude with highlights from the on-sky validation and commissioning of the instrument, key successes, and lessons learned. (abridged)

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