arXiv subjects

Eduardo Rozo

Publications and source records attributed to Eduardo Rozo.

At least 37 records · Page 2Linked to original sources

arXiv2022

Optical selection bias and projection effects in stacked galaxy cluster weak lensing

Cosmological constraints from current and upcoming galaxy cluster surveys are limited by the accuracy of cluster mass calibration. In particular, optically identified galaxy clusters are prone to selection effects that can bias the weak lensing mass calibration. We investigate the selection bias of the stacked cluster lensing signal associated with optically selected clusters, using clusters identified by the redMaPPer algorithm in the Buzzard simulations as a case study. We find that at a given cluster halo mass, the residuals of redMaPPer richness and weak lensing signal are positively correlated. As a result, for a given richness selection, the stacked lensing signal is biased high compared with what we would expect from the underlying halo mass probability distribution. The cluster lensing selection bias can thus lead to overestimated mean cluster mass and biased cosmology results. We show that the lensing selection bias exhibits a strong scale-dependence and is approximately 20 to 60 percent for $ΔΣ$ at large scales. This selection bias largely originates from spurious member galaxies within +/- 20 to 60 Mpc/h along the line of sight, highlighting the importance of quantifying projection effects associated with the broad redshift distribution of member galaxies in photometric cluster surveys. While our results qualitatively agree with those in the literature, accurate quantitative modelling of the selection bias is needed to achieve the goals of cluster lensing cosmology and will require synthetic catalogues covering a wide range of galaxy-halo connection models.

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arXiv2022

A Better Way to Define Dark Matter Haloes

Dark matter haloes have long been recognized as one of the fundamental building blocks of large scale structure formation models. Despite their importance -- or perhaps because of it! -- halo definitions continue to evolve towards more physically motivated criteria. Here, we propose a new definition that is physically motivated, and effectively unique and parameter-free: ''A dark matter halo is comprised of the collection of particles orbiting in their own self-generated potential.'' This definition is enabled by the fact that, even with as few as $\approx 300$ particles per halo, nearly every particle in the vicinity of a halo can be uniquely classified as either orbiting or infalling based on its dynamical history. For brevity, we refer to haloes selected in this way as physical haloes. We demonstrate that: 1) the mass function of physical haloes is Press-Schechter, provided the critical threshold for collapse is allowed to vary slowly with peak height; and 2) the peak-background split prediction of the clustering amplitude of physical halos is statistically consistent with the simulation data, with an accuracy no worse than $\approx 5\%$.

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arXiv2022

Map-based cosmology inference with lognormal cosmic shear maps

Most cosmic shear analyses to date have relied on summary statistics (e.g. $ξ_+$ and $ξ_-$). These types of analyses are necessarily sub-optimal, as the use of summary statistics is lossy. In this paper, we forward-model the convergence field of the Universe as a lognormal random field conditioned on the observed shear data. This new map-based inference framework enables us to recover the joint posterior of the cosmological parameters and the convergence field of the Universe. Our analysis properly accounts for the covariance in the mass maps across tomographic bins, which significantly improves the fidelity of the maps relative to single-bin reconstructions. We verify that applying our inference pipeline to Gaussian random fields recovers posteriors that are in excellent agreement with their analytical counterparts. At the resolution of our maps -- and to the extent that the convergence field can be described by the lognormal model -- our map posteriors allow us to reconstruct \it all \rm summary statistics (including non-Gaussian statistics). We forecast that a map-based inference analysis of LSST-Y10 data can improve cosmological constraints in the $σ_8$--$Ω_{\rm m}$ plane by $\approx 30\%$ relative to the currently standard cosmic shear analysis. This improvement happens almost entirely along the $S_8=σ_8Ω_{\rm m}^{1/2}$ directions, meaning map-based inference fails to significantly improve constraints on $S_8$.

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arXiv2022

LINNA: Likelihood Inference Neural Network Accelerator

Bayesian posterior inference of modern multi-probe cosmological analyses incurs massive computational costs. For instance, depending on the combinations of probes, a single posterior inference for the Dark Energy Survey (DES) data had a wall-clock time that ranged from 1 to 21 days using a state-of-the-art computing cluster with 100 cores. These computational costs have severe environmental impacts and the long wall-clock time slows scientific productivity. To address these difficulties, we introduce LINNA: the Likelihood Inference Neural Network Accelerator. Relative to the baseline DES analyses, LINNA reduces the computational cost associated with posterior inference by a factor of 8--50. If applied to the first-year cosmological analysis of Rubin Observatory's Legacy Survey of Space and Time (LSST Y1), we conservatively estimate that LINNA will save more than US $\$300,000$ on energy costs, while simultaneously reducing $\rm{CO}_2$ emission by $2,400$ tons. To accomplish these reductions, LINNA automatically builds training data sets, creates neural network surrogate models, and produces a Markov chain that samples the posterior. We explicitly verify that LINNA accurately reproduces the first-year DES (DES Y1) cosmological constraints derived from a variety of different data vectors with our default code settings, without needing to retune the algorithm every time. Further, we find that LINNA is sufficient for enabling accurate and efficient sampling for LSST Y10 multi-probe analyses. We make LINNA publicly available at https://github.com/chto/linna, to enable others to perform fast and accurate posterior inference in contemporary cosmological analyses.

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arXiv2022

Incorporating galaxy cluster triaxiality in stacked cluster weak lensing analyses

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters' shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modeling the richness-mass relation as a log-linear relation, we find that the log-richness amplitude $\ln(A)$ is boosted from the lowest to highest orientation bin with a significance of $14σ$, while the orientation dependence of the richness-mass slope and intrinsic scatter is minimal. We also find that the weak lensing shear-profile ratios of cluster-associated dark halos in different orientation bins resemble a "bottleneck" shape that can be quantified with a Cauchy function. We test the correlation of orientation with two other leading systematics in cluster cosmology -- miscentering and projection -- and find a null correlation. Analytic templates for the triaxiality bias of observed-richness and lensing profiles are mapped as corrections to the observable of richness-binned lensing profiles for redMaPPer clusters. The resulting mass bias confirms the DES Y1 finding that triaxiality is a leading source of bias in cluster cosmology. However, the richness-dependence of the bias confirms that triaxiality does not fully resolve the tension at low-richness between DES Y1 cluster cosmology and other probes. Our model can be used for quantifying the impact of triaxiality bias on cosmological constraints for upcoming weak lensing surveys of galaxy clusters.

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arXiv2022

KaRMMa -- Kappa Reconstruction for Mass Mapping

We present KaRMMa, a novel method for performing mass map reconstruction from weak-lensing surveys. We employ a fully Bayesian approach with a physically motivated lognormal prior to sample from the posterior distribution of convergence maps. We test KaRMMa on a suite of dark matter N-body simulations with simulated DES Y1-like shear observations. We show that KaRMMa outperforms the basic Kaiser-Squires mass map reconstruction in two key ways: 1) our best map point estimate has lower residuals compared to Kaiser-Squires; and 2) unlike the Kaiser-Squires reconstruction, the posterior distribution of KaRMMa maps are nearly unbiased in all summary statistics we considered, namely: one-point and two-point functions, and peak/void counts. In particular, KaRMMa successfully captures the non-Gaussian nature of the distribution of $κ$ values in the simulated maps. We further demonstrate that the KaRMMa posteriors correctly characterize the uncertainty in all summary statistics we considered.

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arXiv2021

Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe

Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3$\times$2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modeling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude ($Q_1$) generally reflects the strength of baryon feedback. With the upper limit of $Q_1$ prior being bound by the Illustris feedback scenarios, we reach $\sim 20\%$ improvement in the constraint of $S_8=σ_8(Ω_{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3$\times$2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative $Q_1$ prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than $2 σ$.

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arXiv2021

Linear Systematics Mitigation in Galaxy Clustering in the Dark Energy Survey Year 1 Data

We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment: 1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself; 2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints; 3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field; 4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalog minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness of fit statistic of the DES Y1 3$\times$2pt data set ($Δχ^2 = -6.5$ with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

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arXiv2021

The HST See Change Program: I. Survey Design, Pipeline, and Supernova Discoveries

The See Change survey was designed to make $z>1$ cosmological measurements by efficiently discovering high-redshift Type Ia supernovae (SNe Ia) and improving cluster mass measurements through weak lensing. This survey observed twelve galaxy clusters with the Hubble Space Telescope spanning the redshift range $z=1.13$ to $1.75$, discovering 57 likely transients and 27 likely SNe Ia at $z\sim 0.8-2.3$. As in similar previous surveys (Dawson et al. 2009), this proved to be a highly efficient use of HST for SN observations; the See Change survey additionally tested the feasibility of maintaining, or further increasing, the efficiency at yet higher redshifts, where we have less detailed information on the expected cluster masses and star-formation rates. We find that the resulting number of SNe Ia per orbit is a factor of $\sim 8$ higher than for a field search, and 45% of our orbits contained an active SN Ia within 22 rest-frame days of peak, with one of the clusters by itself yielding 6 of the SNe Ia. We present the survey design, pipeline, and SN discoveries. Novel features include fully blinded SN searches, the first random forest candidate classifier for undersampled IR data (with a 50% detection threshold within 0.05 magnitudes of human searchers), real-time forward-modeling photometry of candidates, and semi-automated photometric classifications and follow-up forecasts. We also describe the spectroscopic follow-up, instrumental in measuring host-galaxy redshifts. The cosmology analysis of our sample will be presented in a companion paper.

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arXiv2021

The Phase Space Structure of Dark Matter Halos

The phase space structure of dark matter halos can be used to measure the mass of the halo, infer mass accretion rates, and probe the effects of modified gravity. Previous studies showed that the splashback radius can be measured in position space using the slope of the density profile. Using N-body simulations, we show that the phase space structure of the dark matter halo does not end at this splashback radius. Instead, there exists a region where infalling, splashback, and virialized halos are mixed spatially. We model the distribution of the three kinematically distinct populations and show that there exists an "edge radius" beyond which a dark matter halo has no orbiting substructures. This radius is a fixed multiple of the splashback radius as defined in previous works, and can be interpreted as a radius which contains a fixed fraction of the apocenters of dark matter particles. Our results provide a firm theoretical foundation to the satellite galaxy model adopted in the companion paper by Tomooka et al., where we analyzed the phase space distribution of SDSS redMaPPer clusters.

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arXiv2020

RedMaPPer: Evolution and Mass Dependence of the Conditional Luminosity Functions of Red Galaxies in Galaxy Clusters

We characterize the luminosity distribution, halo mass dependence, and redshift evolution of red galaxies in galaxy clusters using the SDSS Data Release 8 RedMaPPer cluster sample. We propose a simple prescription for the relationship between the luminosity of both central and satellite galaxies and the mass of their host halos, and show that this model is well-fit by the data. Using a larger galaxy cluster sample than previously employed in the literature, we find that the luminosities of central galaxies scale as $\langle \log L \rangle \propto A_L \log (M_{200b})$, with $A_L=0.39\pm0.04$, and that the scatter of the central--galaxy luminosity at fixed $M_{200b}$ ( $σ_{\log L|M}$) is $0.23 ^{+0.05}_{-0.04}$ dex, with the error bar including systematics due to miscentering of the cluster finder, photometry, and photometric redshift estimation. Our data prefers a positive correlation between the luminosity of central galaxies and the observed richness of clusters at a fixed halo mass, with an effective correlation coefficient $d_{\rm{eff}}=0.36^{+0.17}_{-0.16}$. The characteristic luminosity of satellites becomes dimmer from $z=0.3$ to $z=0.1$ by $\sim 20\%$ after accounting for passive evolution. We estimate the fraction of galaxy clusters where the brightest galaxy is not the central to be $P_{\rm{BNC}} \sim 20\%$. We discuss implications of these findings in the context of galaxy evolution and the galaxy--halo connection.

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arXiv2020

Measuring Cosmological Distances Using Cluster Edges as a Standard Ruler

The line-of-sight velocity dispersion profile of galaxy clusters exhibits a "kink" corresponding to the spatial extent of orbiting galaxies. Because the spatial extent of a cluster is correlated with the amplitude of the velocity dispersion profile, we can utilise this feature as a gravity-calibrated standard ruler. Specifically, the amplitude of the velocity dispersion data allows us to infer the physical cluster size. Consequently, observations of the angular scale of the "kink" in the profile can be translated into a distance measurement to the cluster. Assuming the relation between cluster radius and cluster velocity dispersion can be calibrated from simulations, we forecast that with existing data from the Sloan Digital Sky Survey (SDSS) we will be able to measure the Hubble constant with $3\%$ precision. Implementing our method with data from the Dark Energy Spectroscopic Instrument (DESI) will result in a $1.3\%$ measurement of the Hubble constant. Adding cosmological supernova data improves the uncertainty of the DESI measurement to $0.7\%$.

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arXiv2020

Probing galaxy evolution in massive clusters using ACT and DES: splashback as a cosmic clock

We measure the projected number density profiles of galaxies and the splashback feature in clusters selected by the Sunyaev--Zeldovich (SZ) effect from the Advanced Atacama Cosmology Telescope (AdvACT) survey using galaxies observed by the Dark Energy Survey (DES). The splashback radius for the complete galaxy sample is consistent with theoretical measurements from CDM-only simulations, and is located at $2.4^{+0.3}_{-0.4}$ Mpc $h^{-1}$. We split the sample based on galaxy color and find significant differences in the profile shapes. Red galaxies and those in the green valley show a splashback-like minimum in their slope profile consistent with theoretical predictions, while the bluest galaxies show a weak feature that appears at a smaller radius. We develop a mapping of galaxies to subhalos in $N$-body simulations by splitting subhalos based on infall time onto the cluster halos. We find that the location of the steepest slope and differences in the shapes of the profiles can be mapped to differences in the average time of infall of galaxies of different colors. The minima of the slope in the galaxy profiles trace a discontinuity in the phase space of dark matter halos. By relating spatial profiles to infall time for galaxies of different colours, we can use splashback as a clock to understand galaxy quenching. We find that red galaxies have on average been in their clusters for over $3.2 ~\rm Gyrs$, green galaxies about $2.2 ~\rm Gyrs$, while blue galaxies have been accreted most recently and have not reached apocenter. Using the information from the complete radial profiles, we fit a simple quenching model and find that the onset of galaxy quenching in clusters occurs after a delay of about a gigayear, and that galaxies quench rapidly thereafter with an exponential timescale of $0.6$ Gyr.

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arXiv2020

A Redefinition of the Halo Boundary Leads to a Simple yet Accurate Halo Model of Large Scale Structure

We present a model for the halo--mass correlation function that explicitly incorporates halo exclusion. We assume that halos trace mass in a way that can be described using a single scale-independent bias parameter. However, our model exhibits scale dependent biasing due to the impact of halo-exclusion, the use of a ``soft'' (i.e. not infinitely sharp) halo boundary, and differences in the one halo term contributions to $ξ_{\rm hm}$ and $ξ_{\rm mm}$. These features naturally lead us to a redefinition of the halo boundary that lies at the ``by eye'' transition radius from the one--halo to the two--halo term in the halo--mass correlation function. When adopting our proposed definition, our model succeeds in describing the halo--mass correlation function with $\approx 2\%$ residuals over the radial range $0.1\ h^{-1}{\rm Mpc} < r < 80\ h^{-1}{\rm Mpc}$, and for halo masses in the range $10^{13}\ h^{-1}{\rm M}_{\odot} < M < 10^{15}\ h^{-1}{\rm M}_{\odot}$. Our proposed halo boundary is related to the splashback radius by a roughly constant multiplicative factor. Taking the 87-percentile as reference we find $r_{\rm t}/R_{\rm sp} \approx 1.3$. Surprisingly, our proposed definition results in halo abundances that are well described by the Press-Schechter mass function with $δ_{\rm sc}=1.449\pm 0.004$. The clustering bias parameter is offset from the standard background-split prediction by $\approx 10\%-15\%$. This level of agreement is comparable to that achieved with more standard halo definitions.

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arXiv2020

Localizing Transformations of the Galaxy-Galaxy Lensing Observable

Modern cosmological analyses of galaxy-galaxy lensing face a theoretical systematic effect arising from the non-locality of the observed galaxy-galaxy lensing signal. Because the predicted tangential shear signal at a given separation depends on the physical modeling on all scales internal to that separation, systematic uncertainties in the modeling of non-linear small scales are propagated outwards to larger scales. Even in the absence of other limiting factors, this systematic effect alone can necessitate conservative small-scale cuts, resulting in significant losses of information in the tangential shear data vector. We construct a simple linear transformation of the observable that removes this non-locality, enabling more aggressive small-scale cuts for a given theoretical model. Our modified galaxy-galaxy lensing observable makes it possible to include observations on significantly smaller scales than those under the standard approach in cosmological analyses. More importantly, it ensures that the cosmological signal contained within the observable is exclusively drawn from well-understood physical scales.

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arXiv2020

Cosmology with the Wide-Field Infrared Survey Telescope -- Multi-Probe Strategies

We simulate the scientific performance of the Wide-Field Infrared Survey Telescope (WFIRST) High Latitude Survey (HLS) on dark energy and modified gravity. The 1.6 year HLS Reference survey is currently envisioned to image 2000 deg$^2$ in multiple bands to a depth of $\sim$26.5 in Y, J, H and to cover the same area with slit-less spectroscopy beyond z=3. The combination of deep, multi-band photometry and deep spectroscopy will allow scientists to measure the growth and geometry of the Universe through a variety of cosmological probes (e.g., weak lensing, galaxy clusters, galaxy clustering, BAO, Type Ia supernova) and, equally, it will allow an exquisite control of observational and astrophysical systematic effects. In this paper we explore multi-probe strategies that can be implemented given WFIRST's instrument capabilities. We model cosmological probes individually and jointly and account for correlated systematics and statistical uncertainties due to the higher order moments of the density field. We explore different levels of observational systematics for the WFIRST survey (photo-z and shear calibration) and ultimately run a joint likelihood analysis in N-dim parameter space. We find that the WFIRST reference survey alone (no external data sets) can achieve a standard dark energy FoM of >300 when including all probes. This assumes no information from external data sets and realistic assumptions for systematics. Our study of the HLS reference survey should be seen as part of a future community driven effort to simulate and optimize the science return of WFIRST.

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arXiv2020

Cosmology with the Wide-Field Infrared Survey Telescope -- Synergies with the Rubin Observatory Legacy Survey of Space and Time

We explore synergies between the space-based Wide-Field Infrared Survey Telescope (WFIRST) and the ground-based Rubin Observatory Legacy Survey of Space and Time (LSST). In particular, we consider a scenario where the currently envisioned survey strategy for WFIRST's High Latitude Survey (HLS), i.e., 2000 square degrees in four narrow photometric bands is altered in favor of a strategy that combines rapid coverage of the LSST area (to full LSST depth) in one band. We find that a 5-month WFIRST survey in the W-band can cover the full LSST survey area providing high-resolution imaging for >95% of the LSST Year 10 gold galaxy sample. We explore a second, more ambitious scenario where WFIRST spends 1.5 years covering the LSST area. For this second scenario we quantify the constraining power on dark energy equation of state parameters from a joint weak lensing and galaxy clustering analysis, and compare it to an LSST-only survey and to the Reference WFIRST HLS survey. Our survey simulations are based on the WFIRST exposure time calculator and redshift distributions from the CANDELS catalog. Our statistical uncertainties account for higher-order correlations of the density field, and we include a wide range of systematic effects, such as uncertainties in shape and redshift measurements, and modeling uncertainties of astrophysical systematics, such as galaxy bias, intrinsic galaxy alignment, and baryonic physics. Assuming the 5-month WFIRST wide scenario, we find a significant increase in constraining power for the joint LSST+WFIRST wide survey compared to LSST Y10 (FoM(Wwide)= 2.4 FoM(LSST)) and compared to LSST+WFIRST HLS (FoM(Wwide)= 5.5 FoM(HLS)).

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arXiv2020

Clusters Have Edges: The Projected Phase SpaceStructure of SDSS redMaPPer Clusters

We study the distribution of line-of-sight velocities of galaxies in the vicinity of SDSS redMaPPer galaxy clusters. Based on their velocities, galaxies can be split into two categories: galaxies that are dynamically associated with the cluster, and random line-of-sight projections. Both the fraction of galaxies associated with the galaxy clusters, and the velocity dispersion of the same, exhibit a sharp feature as a function of radius. The feature occurs at a radial scale $R_{\rm edge} \approx 2.2R_{\rmλ}$, where $R_{\rmλ}$ is the cluster radius assigned by redMaPPer. We refer to $R_{\rm edge}$ as the "edge radius." These results are naturally explained by a model that further splits the galaxies dynamically associated with a galaxy cluster into a component of galaxies orbiting the halo and an infalling galaxy component. The edge radius $R_{\rm edge}$ constitutes a true "cluster edge", in the sense that no orbiting structures exist past this radius. A companion paper (Aung et al. 2020) tests whether the "halo edge" hypothesis holds when investigating the full three-dimensional phase space distribution of dark matter substructures in numerical simulations, and demonstrates that this radius coincides with a suitably defined splashback radius.

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