arXiv subjects

F. Paz-Chinchón

Publications and source records attributed to F. Paz-Chinchón.

At least 55 records · Page 3Linked to original sources

arXiv2022

Dark Energy Survey Year 3 Results: Deep Field Optical + Near-Infrared Images and Catalogue

We describe the Dark Energy Survey (DES) Deep Fields, a set of images and associated multi-wavelength catalogue ($ugrizJHKs$) built from Dark Energy Camera (DECam) and Visible and Infrared Survey Telescope for Astronomy (VISTA) data. The DES Deep Fields comprise 11 fields (10 DES supernova fields plus COSMOS), with a total area of $\sim30~$ square degrees in $ugriz$ bands and reaching a maximum $i$-band depth of 26.75 (AB, $10σ$, 2 arcsec). We present a catalogue for the DES 3-year cosmology analysis of those four fields with full 8-band coverage, totalling $5.88~$ sq. deg. after masking. Numbering $2.8~$million objects ($1.6~$million post masking), our catalogue is drawn from images coadded to consistent depths of $r=25.7, i=25, z=24.3$ mag. We use a new model-fitting code, built upon established methods, to deblend sources and ensure consistent colours across the $u$-band to $Ks$-band wavelength range. We further detail the tight control we maintain over the point-spread function modelling required for the model fitting, astrometry and consistency of photometry between the four fields. The catalogue allows us to perform a careful star-galaxy separation and produces excellent photometric redshift performance (${\rm NMAD} = 0.023$ at $i<23$). The Deep-Fields catalogue will be made available as part of the cosmology data products release, following the completion of the DES 3-year weak lensing and galaxy clustering cosmology work.

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arXiv2022

Robust sampling for weak lensing and clustering analyses with the Dark Energy Survey

Recent cosmological analyses rely on the ability to accurately sample from high-dimensional posterior distributions. A variety of algorithms have been applied in the field, but justification of the particular sampler choice and settings is often lacking. Here we investigate three such samplers to motivate and validate the algorithm and settings used for the Dark Energy Survey (DES) analyses of the first 3 years (Y3) of data from combined measurements of weak lensing and galaxy clustering. We employ the full DES Year 1 likelihood alongside a much faster approximate likelihood, which enables us to assess the outcomes from each sampler choice and demonstrate the robustness of our full results. We find that the ellipsoidal nested sampling algorithm $\texttt{MultiNest}$ reports inconsistent estimates of the Bayesian evidence and somewhat narrower parameter credible intervals than the sliced nested sampling implemented in $\texttt{PolyChord}$. We compare the findings from $\texttt{MultiNest}$ and $\texttt{PolyChord}$ with parameter inference from the Metropolis-Hastings algorithm, finding good agreement. We determine that $\texttt{PolyChord}$ provides a good balance of speed and robustness, and recommend different settings for testing purposes and final chains for analyses with DES Y3 data. Our methodology can readily be reproduced to obtain suitable sampler settings for future surveys.

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arXiv2022

Cosmological Constraints from DES Y1 Cluster Abundances and SPT Multi-wavelength data

We perform a joint analysis of the counts of redMaPPer clusters selected from the Dark Energy Survey (DES) Y1 data and multi-wavelength follow-up data collected within the 2500 deg$^2$ South Pole Telescope (SPT) SZ survey. The SPT follow-up data, calibrating the richness--mass relation of the optically selected redMaPPer catalog, enable the cosmological exploitation of the DES cluster abundance data. To explore possible systematics related to the modeling of projection effects, we consider two calibrations of the observational scatter on richness estimates: a simple Gaussian model which account only for the background contamination (BKG), and a model which further includes contamination and incompleteness due to projection effects (PRJ). Assuming either a $Λ$CDM+$\sum m_ν$ or $w$CDM+$\sum m_ν$ cosmology, and for both scatter models, we derive cosmological constraints consistent with multiple cosmological probes of the low and high redshift Universe, and in particular with the SPT cluster abundance data. This result demonstrates that the DES Y1 and SPT cluster counts provide consistent cosmological constraints, if the same mass calibration data set is adopted. It thus supports the conclusion of the DES Y1 cluster cosmology analysis which interprets the tension observed with other cosmological probes in terms of systematics affecting the stacked weak lensing analysis of optically--selected low--richness clusters. Finally, we analyse the first combined optically-SZ selected cluster catalogue obtained by including the SPT sample above the maximum redshift probed by the DES Y1 redMaPPer sample. Besides providing a mild improvement of the cosmological constraints, this data combination serves as a stricter test of our scatter models: the PRJ model, providing scaling relations consistent between the two abundance and multi-wavelength follow-up data, is favored over the BKG model.

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arXiv2022

From the Fire: A Deeper Look at the Phoenix Stream

We use six years of data from the Dark Energy Survey to perform a detailed photometric characterization of the Phoenix stellar stream, a 15-degree long, thin, dynamically cold, low-metallicity stellar system in the southern hemisphere. We use natural splines, a non-parametric modeling technique, to simultaneously fit the stream track, width, and linear density. This updated stream model allows us to improve measurements of the heliocentric distance ($17.4 \pm 0.1\,{\rm (stat.)} \pm 0.8\,{\rm (sys.)}$ kpc) and distance gradient ($-0.009 \pm 0.006$ kpc deg$^{-1}$) of Phoenix, which corresponds to a small change of $0.13 \pm 0.09$ kpc in heliocentric distance along the length of the stream. We measure linear intensity variations on degree scales, as well as deviations in the stream track on $\sim 2$-degree scales, suggesting that the stream may have been disturbed during its formation and/or evolution. We recover three peaks and one gap in linear intensity along with fluctuations in the stream track. Compared to other thin streams, the Phoenix stream shows more fluctuations and, consequently, the study of Phoenix offers a unique perspective on gravitational perturbations of stellar streams. We discuss possible sources of perturbations to Phoenix including baryonic structures in the Galaxy and dark matter subhalos.

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arXiv2022

The Evolution of AGN Activity in Brightest Cluster Galaxies

We present the results of an analysis of Wide-field Infrared Survey Explorer (WISE) observations on the full 2500 deg^2 South Pole Telescope (SPT)-SZ cluster sample. We describe a process for identifying active galactic nuclei (AGN) in brightest cluster galaxies (BCGs) based on WISE mid-infrared color and redshift. Applying this technique to the BCGs of the SPT-SZ sample, we calculate the AGN-hosting BCG fraction, which is defined as the fraction of BCGs hosting bright central AGNs over all possible BCGs. Assuming {\bf an evolving} single-burst stellar population model, we find statistically significant evidence (>99.9%) for a mid-IR excess at high redshift compared to low redshift, suggesting that the fraction of AGN-hosting BCGs increases with redshift over the range of 0 < z < 1.3. The best-fit redshift trend of the AGN-hosting BCG fraction has the form (1+z)^(4.1+/-1.0). These results are consistent with previous studies in galaxy clusters as well as field galaxies. One way to explain this result is that member galaxies at high redshift tend to have more cold gas. While BCGs in nearby galaxy clusters grow mostly by dry mergers with cluster members, leading to no increase in AGN activity, BCGs at high redshift could primarily merge with gas-rich satellites, providing fuel for feeding AGNs. If this observed increase in AGN activity is linked to gas-rich mergers, rather than ICM cooling, we would expect to see an increase in scatter in the P_cav vs L_cool relation at z > 1. Lastly, this work confirms that the runaway cooling phase, as predicted by the classical cooling flow model, in the Phoenix cluster is extremely rare and most BCGs have low (relative to Eddington) black hole accretion rates.

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arXiv2022

DES Y3 results: Blending shear and redshift biases in image simulations

As the statistical power of galaxy weak lensing reaches percent level precision, large, realistic and robust simulations are required to calibrate observational systematics, especially given the increased importance of object blending as survey depths increase. To capture the coupled effects of blending in both shear and photometric redshift calibration, we define the effective redshift distribution for lensing, $n_γ(z)$, and describe how to estimate it using image simulations. We use an extensive suite of tailored image simulations to characterize the performance of the shear estimation pipeline applied to the Dark Energy Survey (DES) Year 3 dataset. We describe the multi-band, multi-epoch simulations, and demonstrate their high level of realism through comparisons to the real DES data. We isolate the effects that generate shear calibration biases by running variations on our fiducial simulation, and find that blending-related effects are the dominant contribution to the mean multiplicative bias of approximately $-2\%$. By generating simulations with input shear signals that vary with redshift, we calibrate biases in our estimation of the effective redshfit distribution, and demonstrate the importance of this approach when blending is present. We provide corrected effective redshift distributions that incorporate statistical and systematic uncertainties, ready for use in DES Year 3 weak lensing analyses.

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arXiv2022

Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

We describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey's (DES) Year 3 (Y3) dataset. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with traditional generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source" galaxies and magnification biases of nearer "lens" galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ~1-8 millimagnitudes, but for a small subset of objects we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

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arXiv2022

The DES Bright Arcs Survey: Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey 5,000 Sq. Deg. Footprint

We report the combined results of eight searches for strong gravitational lens systems in the full 5,000 sq. deg. of Dark Energy Survey (DES) observations. The observations accumulated by the end of the third observing season fully covered the DES footprint in 5 filters (grizY), with an $i-$band limiting magnitude (at $10σ$) of 23.44. In four searches, a list of potential candidates was identified using a color and magnitude selection from the object catalogs created from the first three observing seasons. Three other searches were conducted at the locations of previously identified galaxy clusters. Cutout images of potential candidates were then visually scanned using an object viewer. An additional set of candidates came from a data-quality check of a subset of the color-coadd "tiles" created from the full DES six-season data set. A short list of the most promising strong lens candidates was then numerically ranked according to whether or not we judged them to be bona fide strong gravitational lens systems. These searches discovered a diverse set of 247 strong lens candidate systems, of which 81 are identified for the first time. We provide the coordinates, magnitudes, and photometric properties of the lens and source objects, and an estimate of the Einstein radius for 81 new systems and 166 previously reported. This catalog will be of use for selecting interesting systems for detailed follow-up, studies of galaxy cluster and group mass profiles, as well as a training/validation set for automated strong lens searches.

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arXiv2021

Dark Energy Survey Year 3 Results: Galaxy mock catalogs for BAO analysis

The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of baryon acoustic oscillation (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey (DES) Year 3 BAO sample over its full photometric redshift range $0.6<z_{\rm photo}<1.1$. The mocks are based upon 488 ICE-COLA fast $N$-body simulations of full-sky light cones and were created by populating halos with galaxies, using a hybrid halo occupation distribution - halo abundance matching model. This model has ten free parameters, which were determined, for the first time, using an automatic likelihood minimization procedure. We also introduced a novel technique to assign photometric redshift for simulated galaxies, following a two-dimensional probability distribution with VIMOS Public Extragalactic Redshift Survey (VIPERS) data. The calibration was designed to match the observed abundance of galaxies as a function of photometric redshift, the distribution of photometric redshift errors, and the clustering amplitude on scales smaller than those used for BAO measurements. An exhaustive analysis was done to ensure that the mocks reproduce the input properties. Finally, mocks were tested by comparing the angular correlation function $w(θ)$, angular power spectrum $C_\ell$, and projected clustering $ξ_p(r_\perp)$ to theoretical predictions and data. The impact of volume replication in the estimate of the covariance is also investigated. The success in accurately reproducing the photometric redshift uncertainties and the galaxy clustering as a function of redshift render this mock creation pipeline as a benchmark for future analyses of photometric galaxy surveys.

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arXiv2021

Multi-wavelength Optical and NIR Variability Analysis of the Blazar PKS 0027-426

We present multi-wavelength spectral and temporal variability analysis of PKS 0027-426 using optical griz observations from DES (Dark Energy Survey) between 2013-2018 and VOILETTE (VEILS Optical Light curves of Extragalactic TransienT Events) between 2018-2019 and near infrared (NIR) JKs observations from VEILS (VISTAExtragalactic Infrared Legacy Survey) between 2017-2019. Multiple methods of cross-correlation of each combination of light curve provides measurements of possible lags between optical-optical, optical-NIR, and NIR-NIR emission, for each observation season and for the entire observational period. Inter-band time lag measurements consistently suggest either simultaneous emission or delays between emission regions on timescales smaller than the cadences of observations. The colour-magnitude relation between each combination of filters was also studied to determine the spectral behaviour of PKS 0027-426. Our results demonstrate complex colour behaviour that changes between bluer when brighter (BWB), stable when brighter (SWB) and redder when brighter (RWB) trends over different timescales and using different combinations of optical filters. Additional analysis of the optical spectra is performed to provide further understanding of this complex spectral behaviour.

astro-ph.GA↗

arXiv2021

The Dark Energy Survey Supernova Program: Cosmological biases from supernova photometric classification

Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on state-of-the-art simulations of photometrically identified SN Ia samples and determine cosmological biases due to such 'non-Ia' contamination in the Dark Energy Survey (DES) 5-year SN sample. As part of the analysis, we test on our DES simulations the performance of SuperNNova, a photometric SN classifier based on recurrent neural networks. Depending on the choice of non-Ia SN models in both the simulated data sample and training sample, contamination ranges from 0.8-3.5 %, with the efficiency of the classification from 97.7-99.5 %. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension 'BEAMS with Bias Correction' (BBC), we produce a redshift-binned Hubble diagram marginalised over contamination and corrected for selection effects and we use it to constrain the dark energy equation-of-state, $w$. Assuming a flat universe with Gaussian $Ω_M$ prior of $0.311\pm0.010$, we show that biases on $w$ are $<0.008$ when using SuperNNova and accounting for a wide range of non-Ia SN models in the simulations. Systematic uncertainties associated with contamination are estimated to be at most $σ_{w, \mathrm{syst}}=0.004$. This compares to an expected statistical uncertainty of $σ_{w,\mathrm{stat}}=0.039$ for the DES-SN sample, thus showing that contamination is not a limiting uncertainty in our analysis. We also measure biases due to contamination on $w_0$ and $w_a$ (assuming a flat universe), and find these to be $<$0.009 in $w_0$ and $<$0.108 in $w_a$, hence 5 to 10 times smaller than the statistical uncertainties expected from the DES-SN sample.

astro-ph.CO↗

arXiv2021

Probing gravity with the DES-CMASS sample and BOSS spectroscopy

The DES-CMASS sample (DMASS) is designed to optimally combine the weak lensing measurements from the Dark Energy Survey (DES) and redshift-space distortions (RSD) probed by the CMASS galaxy sample from the Baryonic Oscillation Spectroscopic Survey (BOSS). In this paper, we demonstrate the feasibility of adopting DMASS as the equivalent of BOSS CMASS for a joint analysis of DES and BOSS in the framework of modified gravity. We utilize the angular clustering of the DMASS galaxies, cosmic shear of the DES METACALIBRATION sources, and cross-correlation of the two as data vectors. By jointly fitting the combination of the data with the RSD measurements from the BOSS CMASS sample and Planck data, we obtain the constraints on modified gravity parameters $μ_0 = -0.37^{+0.47}_{-0.45}$ and $Σ_0 = 0.078^{+0.078}_{-0.082}$. We do not detect any significant deviation from General Relativity. Our constraints of modified gravity measured with DMASS are tighter than those with the DES Year 1 redMaGiC galaxy sample with the same external data sets by $29\%$ for $μ_0$ and $21\%$ for $Σ_0$, and comparable to the published results of the DES Year 1 modified gravity analysis despite this work using fewer external data sets. This improvement is mainly because the galaxy bias parameter is shared and more tightly constrained by both CMASS and DMASS, effectively breaking the degeneracy between the galaxy bias and other cosmological parameters. Such an approach to optimally combine photometric and spectroscopic surveys using a photometric sample equivalent to a spectroscopic sample can be applied to combining future surveys having a limited overlap such as DESI and LSST.

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arXiv2021

Galaxy-galaxy lensing with the DES-CMASS catalogue: measurement and constraints on the galaxy-matter cross-correlation

The DMASS sample is a photometric sample from the DES Year 1 data set designed to replicate the properties of the CMASS sample from BOSS, in support of a joint analysis of DES and BOSS beyond the small overlapping area. In this paper, we present the measurement of galaxy-galaxy lensing using the DMASS sample as gravitational lenses in the DES Y1 imaging data. We test a number of potential systematics that can bias the galaxy-galaxy lensing signal, including those from shear estimation, photometric redshifts, and observing conditions. After careful systematic tests, we obtain a highly significant detection of the galaxy-galaxy lensing signal, with total $S/N=25.7$. With the measured signal, we assess the feasibility of using DMASS as gravitational lenses equivalent to CMASS, by estimating the galaxy-matter cross-correlation coefficient $r_{\rm cc}$. By jointly fitting the galaxy-galaxy lensing measurement with the galaxy clustering measurement from CMASS, we obtain $r_{\rm cc}=1.09^{+0.12}_{-0.11}$ for the scale cut of $4~h^{-1}{\rm Mpc}$ and $r_{\rm cc}=1.06^{+0.13}_{-0.12}$ for $12~h^{-1}{\rm Mpc}$ in fixed cosmology. By adding the angular galaxy clustering of DMASS, we obtain $r_{\rm cc}=1.06\pm 0.10$ for the scale cut of $4~h^{-1}{\rm Mpc}$ and $r_{\rm cc}=1.03\pm 0.11$ for $12~h^{-1}{\rm Mpc}$. The resulting values of $r_{\rm cc}$ indicate that the lensing signal of DMASS is statistically consistent with the one that would have been measured if CMASS had populated the DES region within the given statistical uncertainty. The measurement of galaxy-galaxy lensing presented in this paper will serve as part of the data vector for the forthcoming cosmology analysis in preparation.

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arXiv2021

C/2014 UN271 (Bernardinelli-Bernstein): the nearly spherical cow of comets

C/2014 UN271 (Bernardinelli-Bernstein) is a comet incoming from the Oort cloud which is remarkable in having the brightest (and presumably largest) nucleus of any well-measured comet, and having been discovered at heliocentric distance $r_h\approx29$ au farther than any Oort-cloud member. We describe the properties that can be inferred from images recorded until the first reports of activity in June 2021. The orbit has $i=95^\circ,$ with perihelion of 10.97 au to be reached in 2031, and previous aphelion at $40,400\pm260$ au. Backwards integration of the orbit under a standard Galactic tidal model and known stellar encounters suggests this is a pristine new comet, with a perihelion of $q\approx18$ au on its previous perihelion passage 3.5 Myr ago. The photometric data show an unresolved nucleus with absolute magnitude $H_r=8.0,$ colors that are typical of comet nuclei or Damocloids, and no secular trend as it traversed the range 34--23 au. For $r$-band geometric albedo $p_r,$ this implies a diameter of $150 (p_r/0.04)^{-0.5}$ km. There is strong evidence of brightness fluctuations at $\pm0.2$ mag level, but no rotation period can be discerned. A coma consistent with a ``stationary' $1/ρ$ surface-brightness distribution grew in scattering cross-section at an exponential rate from $A f ρ\approx1$ m to $\approx150$ m as the comet approached from 28 to 20 au. The activity is consistent with a simple model of sublimation of a surface species in radiative equilibrium with the Sun. The inferred enthalpy of sublimation matches those of $CO_2$ and $NH_3$. More-volatile species -- $N_2,$ $CH_4,$ and $CO$ -- must be far less abundant on the sublimating surfaces.

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arXiv2021

Finding quadruply imaged quasars with machine learning. I. Methods

Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass function. Finding them in astronomical images is a classic "needle in a haystack" problem, as they are outnumbered by other (contaminant) sources by many orders of magnitude. To solve this problem, we develop state-of-the-art deep learning methods and train them on realistic simulated quads based on real images of galaxies taken from the Dark Energy Survey, with realistic source and deflector models, including the chromatic effects of microlensing. The performance of the best methods on a mixture of simulated and real objects is excellent, yielding area under the receiver operating curve in the range 0.86 to 0.89. Recall is close to 100% down to total magnitude i~21 indicating high completeness, while precision declines from 85% to 70% in the range i~17-21. The methods are extremely fast: training on 2 million samples takes 20 hours on a GPU machine, and 10^8 multi-band cutouts can be evaluated per GPU-hour. The speed and performance of the method pave the way to apply it to large samples of astronomical sources, bypassing the need for photometric pre-selection that is likely to be a major cause of incompleteness in current samples of known quads.

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arXiv2021

OzDES Reverberation Mapping Program: The first Mg II lags from five years of monitoring

Reverberation mapping is a robust method to measure the masses of supermassive black holes (SMBHs) outside of the local Universe. Measurements of the radius -- luminosity ($R-L$) relation using the Mg II emission line are critical for determining these masses near the peak of quasar activity at $z \approx 1 - 2$, and for calibrating secondary mass estimators based on Mg II that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg II lags from our five-year Australian Dark Energy Survey (OzDES) reverberation mapping program, which substantially improves the number and quality of Mg II lag measurements. As the Mg II feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multi-epoch spectra before analyzing the Mg II line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H$β$ and Mg II $R-L$ relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $4\%$.

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arXiv2021

The Dark Energy Survey Data Release 2

We present the second public data release of the Dark Energy Survey, DES DR2, based on optical/near-infrared imaging by the Dark Energy Camera mounted on the 4-m Blanco telescope at Cerro Tololo Inter-American Observatory in Chile. DES DR2 consists of reduced single-epoch and coadded images, a source catalog derived from coadded images, and associated data products assembled from 6 years of DES science operations. This release includes data from the DES wide-area survey covering ~5000 deg2 of the southern Galactic cap in five broad photometric bands, grizY. DES DR2 has a median delivered point-spread function full-width at half maximum of g= 1.11, r= 0.95, i= 0.88, z= 0.83, and Y= 0.90 arcsec photometric uniformity with a standard deviation of < 3 mmag with respect to Gaia DR2 G-band, a photometric accuracy of ~10 mmag, and a median internal astrometric precision of ~27 mas. The median coadded catalog depth for a 1.95 arcsec diameter aperture at S/N= 10 is g= 24.7, r= 24.4, i= 23.8, z= 23.1 and Y= 21.7 mag. DES DR2 includes ~691 million distinct astronomical objects detected in 10,169 coadded image tiles of size 0.534 deg2 produced from 76,217 single-epoch images. After a basic quality selection, benchmark galaxy and stellar samples contain 543 million and 145 million objects, respectively. These data are accessible through several interfaces, including interactive image visualization tools, web-based query clients, image cutout servers and Jupyter notebooks. DES DR2 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

astro-ph.IM↗

arXiv2021

Dark Energy Survey Year 3 Results: Covariance Modelling and its Impact on Parameter Estimation and Quality of Fit

We describe and test the fiducial covariance matrix model for the combined 2-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) dataset. Using a variety of new ansatzes for covariance modelling and testing we validate the assumptions and approximations of this model. These include the assumption of a Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot-noise, galaxy weighting schemes and other, sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness-of-fit and parameter estimation. The largest impact on best-fit figure-of-merit arises from the so-called $f_{\mathrm{sky}}$ approximation for dealing with finite survey area, which on average increases the $χ^2$ between maximum posterior model and measurement by $3.7\%$ ($Δχ^2 \approx 18.9$). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for $Ω_m$ and $σ_8$ by about $3\%$ and for the dark energy equation of state parameter by about $5\%$.

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