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Chihway Chang

Publications and source records attributed to Chihway Chang.

At least 19 recordsLinked to original sources
arXiv2026

Extracting intrinsic alignments in the Dark Energy Survey's year 1 data, using the self-calibration method and LSST-DESC tools

We present the implementation of a Self-Calibration of Intrinsic Alignments of galaxies as an extension to the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC)'s weak lensing 3x2pt pipeline (TXPipe). As a demonstration, we have run this pipeline on the Dark Energy Survey (DES) year one data set. We find indications of a non-zero intrinsic alignment signal in the higher redshift bins, while in the lower bins our results look more uncertain. We believe this is caused by known issues with the individual galaxies photo-z estimation. This effect is particularly harmful for the self-calibration method, since it has high requirements for reliable estimation of the photo-$z$s, and the need for individual galaxy point estimates and tomographic binning to match. We show how different methods of recreating the redshift probability distribution can affect the detection of intrinsic alignment.

astro-ph.CO↗
arXiv2026

Extending SOMPZ beyond Spectroscopic Coverage for Roman Weak Lensing

Precision weak lensing cosmology requires accurate galaxy redshift distributions. However, the spectroscopic samples used to characterize these distributions do not fully span the magnitude--color--redshift space of weak lensing source galaxies, necessitating extrapolation. This challenge will be critical at the depth of the Roman Space Telescope's High Latitude Imaging Survey (Roman HLIS). Using simulated LSST Year 4 and Roman HLIS photometry from the Cardinal simulations, we quantify how spectroscopic incompleteness biases photometric-redshift (photo-z) calibration and cosmological constraints. We find that the standard Self-Organizing Map p(z) (SOMPZ) method produces substantial tomographic bin overlaps and biased source redshift distributions. To address these limitations, we develop Roman-SOMPZ, which uses dedicated individual-galaxy photo-z estimators to supply redshift references for tomographic binning and redshift estimation. For the latter, we introduce UMAP-flow-z, an estimator that uses a UMAP embedding of deep-field galaxy colors to infer redshifts for phenotypes lacking spectroscopic representation. Compared with the standard pipeline, Roman-SOMPZ produces better-separated tomographic bins and lower absolute mean-redshift biases in eight of nine bins. Propagating the estimated redshift distributions into cosmological inference, we find that existing spectroscopy is adequate for early-stage weak lensing analyses in the Roman deep fields. Conversely, full medium-tier cosmology will require further improvements in redshift characterization.

astro-ph.CO↗
arXiv2026

Combining Rubin and Roman photometry and its implications for photometric redshift estimation

We perform a joint Roman--Rubin photometry analysis using the LSST Science Pipelines (LSP) on simulated images, by using the Roman F158 band as the reference band and applying forced photometry on the other bands. We find that the LSP CModel photometry for Roman bands is on average unbiased, but with a bright-end systematic uncertainty floor of 7-8%. The pgauss photometry as part of the Metadetection weak-lensing shape measurement pipeline also exhibits a similar floor despite a substantially different flux-bias behavior. However, this systematic uncertainty floor becomes negligible for the color residuals and both algorithms recover unbiased colors for Roman as well as Rubin. We also show that not accounting for correlated pixel noise in Roman IMCOM coadded images results in underestimation of flux errors by a factor of ~4. Based on the measured photometry, we build a machine-learning algorithm that maps the true galaxy properties to empirical flux errors, providing a convenient method to reproduce realistic photometry errors without having to rerun expensive image simulations and photometry pipelines. We apply this empirical error model to a new mock galaxy catalog with improved realism to investigate the impact of different survey depths and configurations on photometric redshift (photo-z) estimation performance. We find that 1) Rubin survey depth significantly impacts the photo-$z$ precision, 2) additional systematic uncertainties on photometry could significantly degrade the photo-z performance especially towards high redshifts, therefore eroding the Roman--Rubin synergy, and 3) Roman photometry becomes important above z~1.5 while adding Rubin photometry to that of Roman improves photo-z performance across all redshifts. Our results provide a foundation for understanding how realistic uncertainties in galaxy photometry may propagate into the Roman--Rubin synergy in photo-z analyses.

astro-ph.IM↗
arXiv2026

Robust Photometry for Roman High-Latitude Imaging Survey Cosmology Using Roman and Rubin Imaging

Accurate and precise photometry is essential for Roman cosmology because it affects photometric-redshift performance, galaxy and cluster selection, tomographic binning, and redshift-distribution characterization. Achieving robust photometry is challenging because Roman's depth leads to substantial source blending, particularly in joint Roman--Rubin analyses, where the two surveys have different spatial resolutions. In this work, we develop and validate slimfarmer, a model-fitting photometry pipeline designed for Roman High-Latitude Imaging Survey (HLIS) cosmological analyses. Building on The Farmer, slimfarmer introduces treatments of the correlated noise present in Roman images and of astronomical shot noise, together with model-fitting configurations tuned for Roman imaging. We validate the pipeline using Roman coadded simulated images and perform forced photometry on matched Rubin image simulations. We find that slimfarmer recovers galaxy colors with the mode of the color residuals within 20 millimag for Roman-based colors and within 70 millimag for Rubin-based colors. Properly accounting for correlated noise is essential for uncertainty quantification, as photometric uncertainties are otherwise underestimated by up to a factor of ~3. We also find that applying multi-object fitting consistently to both Roman and Rubin imaging substantially mitigates blending-induced color systematics. In crowded regions, single-object fitting produces environment-dependent color biases of up to ~0.5 mag, leading to environment-dependent degradation of photometric-redshift performance. Together, these results establish slimfarmer as a prototype photometric pipeline for Roman HLIS cosmology applications and identify the correlated-noise corrections, astronomical shot-noise treatment, and joint Roman--Rubin multi-object fitting required for robust photometric-redshift characterization.

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arXiv2026

Joint inference of weak lensing convergence map and cosmology with diffusion models

We present a method for joint inference of cosmological parameters and convergence maps from weak lensing observations, targeting the full posterior conditioned on the observed shear field. Our approach uses implicit inference with diffusion models, learning the joint distribution from simulations, without the need to have an explicit and differentiable forward model for gradient-based MCMC sampling. We introduce a transformer-based architecture that operates in pixel space and treats cosmological parameters as additional tokens in a unified sequence, enabling efficient multimodal processing within a single network. At inference time, the trained model generates posterior samples of joint convergence maps and cosmological parameters conditioned on observed noisy shear fields. We demonstrate the method on simulated weak lensing data generated from log-normal fields in a wcdm cosmology. The model accurately reconstructs convergence maps and recovers cosmological posteriors that agree with traditional MCMC, while remaining well calibrated across the prior, with a MIRA calibration score of $0.635 \pm 0.017$ on the joint posterior (where $0.667$ is optimal). The inferred fields reproduce the correct two-point statistics as well as non-Gaussian statistics such as the one-point distribution. This work establishes diffusion-based implicit inference as a viable route toward full field-level cosmological analyses, paving the way for applications to more realistic, non-differentiable simulators.

astro-ph.CO↗
arXiv2026

Accurate modeling for 3$\times$2pt analyses in Roman and Rubin: a study of model approximations

One of the pillars of modern cosmology is the use of galaxy imaging surveys to extract information from the large-scale structure. In recent surveys, this measurement is typically performed through a 3$\times$2pt analysis, which combines auto- and cross-correlations between galaxy density and galaxy weak lensing. In this paper, we carry out a systematic study of three modeling approximations commonly used in such analyses: 1) applying the Limber approximation, 2) neglecting redshift-space distortions, and 3) using less accurate models for the nonlinear matter power spectrum. We carry out the study in the context of the final data from two major Stage-IV galaxy imaging surveys: the Nancy Grace Roman Space Telescope's High Latitude Imaging Survey and the Vera C. Rubin Observatory's Legacy Survey of Space and Time. To do this, we first validate our modeling pipeline, implemented in the software package CoCoA, against an established code base, CCL. Next, we perform a simulated likelihood analysis to assess the impact of these approximations on the cosmological constraints. We find all three effects to be important; neglecting any of them can induce biases in cosmological constraints approaching or exceeding $1σ$, and exceeding $2σ$ for Rubin in several cases. Moreover, we explore how the lens-galaxy sample configuration and scale-cut choice can influence the constraints.

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arXiv2026

Towards Practical Field-Level Inference for Weak Lensing

Nonlinear structure growth generates higher-order correlations and morphological features in the cosmic density field that cannot be fully characterized by two-point statistics. Upcoming surveys will measure these features with greater precision, making it essential to develop methods capable of extracting as much cosmological information as possible from them. Field-level inference (FLI) is one such approach, in which cosmological parameters are constrained by comparing observed maps to forward-modeled maps, either directly or through learned summaries that retain map-level information. In this work, we compare FLI with power-spectrum-based inference using the same forward-modeling pipeline for generating weak lensing maps, with the goal of quantifying the gain from map-level analysis relative to two-point statistics. We perform this comparison with both implicit and explicit inference methods, using 8-million-parameter forward models based on Lagrangian perturbation theory and particle-mesh (PM) N-body evolution. The two FLI approaches yield closely consistent posteriors; this agreement, together with coverage tests confirming the calibration of the implicit analyses, gives us confidence in the recovered field-level constraints. Relative to the power-spectrum-based analyses, these results show significant gains in cosmological information, especially when small scales are included in the PM-based forward model. We then discuss the remaining challenges that must be addressed before PM-based explicit FLI can be applied to observational datasets.

astro-ph.CO↗
arXiv2026

Brightest Cluster Galaxy ellipticity as proxy for halo shape: Orientation bias, assembly bias, and potential selection effects in SZ-selected clusters

The orientation of triaxial galaxy clusters with respect to the line-of-sight is expected to be one of the prime sources of scatter and potential bias in optical observables (e.g., richness and weak-lensing signal) of galaxy clusters. In this work, we use the observed shape of the central Brightest Cluster Galaxy (BCG) as proxy for the orientation along the line-of-sight for clusters selected via the Sunyaev-Zel'dovich (SZ) effect from the South Pole Telescope (SPT) and Atacama Cosmology Telescope (ACT) surveys, matched to optically selected clusters from the Dark Energy Survey Year 3 (DES). We construct two samples of clusters that are designed to be identical in SZ mass estimate and redshift but with the roundest vs. the most elliptical BCGs, which we expect to correspond to BCGs (and clusters) with major axes aligned along the line-of-sight vs. in the plane of the sky, respectively. We find that the optical richness of round-BCG clusters is $\sim 10$\% larger than that of elliptical-BCG clusters, in agreement with the expectation from projection effects and presenting the first such detection in data. The density profiles, however, are not in agreement with the expectation from projection effects: the 1-halo term (below $6~h^{-1}\rm{Mpc}$) of both the weak-lensing and galaxy density profiles are the same for the subsamples, contrary to previous studies based on X-ray selected clusters. In the 2-halo regime (above $6~h^{-1}\rm{Mpc}$), we find a significant excess of the elliptical-BCG cluster profiles compared to the round-BCG cluster profiles, which is the opposite of the expectation from numerical simulations. We hypothesize that the intrinsic shape of the BCG reflects not just the orientation angle, but also intrinsic properties of the cluster which can affect both the SZ signal and the amplitude of the 2-halo term.

astro-ph.CO↗
arXiv2026

The Vera C. Rubin Observatory Data Preview 1

We present Rubin Data Preview 1 DP1, the first data from the NSF DOE Vera C Rubin Observatory, comprising raw and calibrated single epoch images, coadds, difference images, detection catalogs, and ancillary data products. DP1 is based on 1792 optical near infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera LSSTComCam on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón Chile in late 2024. DP1 covers $\sim$15 deg$^2$ distributed across seven roughly equal-sized non-contiguous fields, each independently observed in six broad photometric bands $ugrizy$. The median FWHM of the point spread function across all bands is approximately 1.14 arcseconds, with the sharpest images reaching about 0.58 arcseconds. The 5$σ$ point source depths for coadded images in the deepest field the Extended Chandra Deep Field South are $u$ = 24.55, $g$ = 26.18, $r$ = 25.96, $i$ = 25.71, $z$ = 25.07, $y$ = 23.1. Other fields are no more than 2.2 magnitudes shallower in any band where they have nonzero coverage. DP1 contains approximately 2.3 million distinct astrophysical objects, of which 1.6 million are extended in at least one band in coadds and 431 solar system objects of which 93 are new discoveries. DP1 is approximately 3.5 TB in size and is available to Rubin data rights holders via the Rubin Science Platform a cloud based environment for the analysis of petascale astronomical data. While small compared to future LSST releases its high quality and diversity of data support a broad range of early science investigations ahead of full operations in 2026.

astro-ph.IM↗
arXiv2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

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arXiv2025

A DECADE of dwarfs: first detection of weak lensing around spectroscopically confirmed low-mass galaxies

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5σ$ lower than $Λ$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $Λ$CDM predictions.

astro-ph.GA↗
arXiv2025

Reanalysis of Stage-III cosmic shear surveys: A comprehensive study of shear diagnostic tests

In recent years, shear catalogs have been released by various Stage-III weak lensing surveys including the Kilo-Degree Survey, the Dark Energy Survey, and the Hyper Suprime-Cam Subaru Strategic Program. These shear catalogs have undergone rigorous validation tests to ensure that the residual shear systematic effects in the catalogs are subdominant relative to the statistical uncertainties, such that the resulting cosmological constraints are unbiased. While there exists a generic set of tests that are designed to probe certain systematic effects, the implementations differ slightly across the individual surveys, making it difficult to make direct comparisons. In this paper, we use the TXPipe package to conduct a series of predefined diagnostic tests across three public shear catalogs -- the 1,000 deg$^2$ KiDS-1000 shear catalog, the Year 3 DES-Y3 shear catalog, and the Year 3 HSC-Y3 shear catalog. We attempt to reproduce the published results when possible and perform key tests uniformly across the surveys. While all surveys pass most of the null tests in this study, we find two tests where some of the surveys fail. Namely, we find that when measuring the tangential ellipticity around bright and faint star samples, KiDS-1000 fails with a $χ^2$/dof of 121.1/16 and 257.7/16 for bins 4 and 5 for faint, weighted stars. We also find that DES-Y3 and HSC-Y3 fail the $B$-mode test when estimated with the Hybrid-$E$/$B$ method, with a $χ^2$/dof of 37.9/10 and 36.0/8 for the fourth and third autocorrelation bins. We assess the impacts on the $Ω_{\rm m}$ - S$_{8}$ parameter space by comparing the posteriors of a simulated data vector with and without PSF contamination -- we find negligible effects in all cases. Finally, we propose strategies for performing these tests on future surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

astro-ph.CO↗
arXiv2025

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the $300\,$deg$^2$ DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3$σ$ on scales below approximately $10'$, but large scales are unaffected. We fit $Ω_{\rm m}$ and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

astro-ph.CO↗
arXiv2025

Uniting the Observed Dynamical Dark Energy Preference with the Discrepancies in $Ω_m$ and $H_0$ Across Cosmological Probes

Recent results from Type Ia Supernovae (SNe), baryon acoustic oscillations (BAO), and the cosmic microwave background (CMB) indicate 1) potentially discrepant measurements of the matter density $Ω_m$ and Hubble constant $ H_0 $ in $Λ$CDM model when analyzed individually, and 2) hints of dynamical dark energy in a $w_0w_a$CDM model when data are combined in a joint analysis. We examine whether underlying dynamical dark energy cosmologies favored by data would result in biases in $Ω_m$ and $ H_0 $ for each probe when analyzed individually under $Λ$CDM. We generate mock datasets in $w_0w_a$CDM cosmologies, fit the individual probes under the $Λ$CDM model, and find expected biases in $Ω_m$ are $\sim 0.03$. Notably, the $Ω_m$ differences between probes are consistent with values observed in real datasets. We also observe that mock DESI-BAO datasets generated in the $w_0w_a$CDM cosmologies will lead to a biased measurement of $H_0$ higher by ($\sim1.2$km/s/Mpc) when fitted under $Λ$CDM, appearing to mildly improve the Hubble tension, but as the true underlying $H_0$ is lower, the tension is in fact worsened. We find that the $Ω_m$ discrepancies, the high BAO $ H_0 $ relative to CMB, and the joint dynamical dark energy signal are all related effects that could be explained \textit{simultaneously} with either new physics or new systematics. While it is possible to unite many of the discrepancies seen in recent analyses along a single axis, our results underscore the importance of understanding systematic differences in datasets, as they have unique impacts in different cosmological parameter spaces.

astro-ph.CO↗
arXiv2025

Dark Energy Survey: Modeling strategy for multiprobe cluster cosmology and validation for the Full Six-year Dataset

We introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3x2pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (1) identification of modeling and parameterization choices and impact studies using simulated analyses with each possible model misspecification (2) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3x2pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy--galaxy lensing and cosmic shear two-point statistics) and the CL+3x2pt+BAO+SN (combination of CL+3x2pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

astro-ph.CO↗
arXiv2024

Map-level baryonification: Efficient modelling of higher-order correlations in the weak lensing and thermal Sunyaev-Zeldovich fields

Semi-analytic methods can generate baryon-corrected fields from N-body simulations (``baryonification'') and are rapidly becoming a ubiquitous tool in modeling structure formation on non-linear scales. We extend this formalism to consistently model the weak lensing and thermal Sunyaev-Zeldovich (tSZ) fields directly on the full-sky, with an emphasis on higher-order correlations. We use the auto- and cross- $N$th-order moments, with $N \in \{2, 3, 4\}$, as a summary statistic of the lensing and tSZ fields, and show that our model can jointly fit these statistics measured in IllustrisTNG to within measurement uncertainties, for scales above $\gtrsim 1 {\rm Mpc}$ and across multiple redshifts. The model predictions change only minimally when including additional information from secondary halo properties, such as halo concentration and ellipticity. Each individual moment is dependent on halos of different mass ranges and has different sensitivities to the model parameters. A simulation-based forecast on the ULAGAM simulation suite shows that the combination of all moments, measured from current and upcoming lensing and tSZ surveys, can jointly constrain cosmology and baryons to high precision. The lensing and tSZ field are sensitive to different combinations of the baryonification parameters, with degeneracy directions that are often orthogonal, and the combination of the two fields leads to significantly better constraints on both cosmology and astrophysics. Our pipeline for map-level baryonification is publicly available at https://github.com/DhayaaAnbajagane/BaryonForge.

astro-ph.CO↗
arXiv2024

Primordial non-Gaussianities with weak lensing: Information on non-linear scales in the Ulagam full-sky simulations

Primordial non-Gaussianities (PNGs) are signatures in the density field that encode particle physics processes from the inflationary epoch. Such signatures have been extensively studied using the Cosmic Microwave Background, through constraining the amplitudes, $f^{X}_{\rm NL}$, with future improvements expected from large-scale structure surveys; specifically, the galaxy correlation functions. We show that weak lensing fields can be used to achieve competitive and complementary constraints. This is shown via the new Ulagam suite of N-body simulations, a subset of which evolves primordial fields with four types of PNGs. We create full-sky lensing maps and estimate the Fisher information from three summary statistics measured on the maps: the moments, the cumulative distribution function, and the 3-point correlation function. We find that the year 10 sample from the Rubin Observatory Legacy Survey of Space and Time (LSST) can constrain PNGs to $σ(f^{\rm\,eq}_{\rm NL}) \approx 110$, $σ(f^{\rm\,or,lss}_{\rm NL}) \approx 120$, $σ(f^{\rm\,loc}_{\rm NL}) \approx 40$. For the former two, this is better than or comparable to expected galaxy clustering-based constraints from the Dark Energy Spectroscopic Instrument (DESI). The PNG information in lensing fields is on non-linear scales and at low redshifts ($z \lesssim 1.25$), with a clear origin in the evolution history of massive halos. The constraining power degrades by $\sim\!\!60\%$ under scale cuts of $\gtrsim 20{\,\rm Mpc}$, showing there is still significant information on scales mostly insensitive to small-scale systematic effects (e.g. baryons). We publicly release the Ulagam suite to enable more survey-focused analyses.

astro-ph.CO↗
arXiv2024

Late Time Modification of Structure Growth and the S8 Tension

The $S_8$ tension between low-redshift galaxy surveys and the primary CMB signals a possible breakdown of the $Λ$CDM model. Recently differing results have been obtained using low-redshift galaxy surveys and the higher redshifts probed by CMB lensing, motivating a possible time-dependent modification to the growth of structure. We investigate a simple phenomenological model in which the growth of structure deviates from the $Λ$CDM prediction at late times, in particular as a simple function of the dark energy density. Fitting to galaxy lensing, CMB lensing, BAO, and Supernovae datasets, we find significant evidence - 2.5 - 3$σ$, depending on analysis choices - for a non-zero value of the parameter quantifying a deviation from $Λ$CDM. The preferred model, which has a slower growth of structure below $z\sim 1$, improves the joint fit to the data over $Λ$CDM. While the overall fit is improved, there is weak evidence for galaxy and CMB lensing favoring different changes in the growth of structure.

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