arXiv subjects

Markus M. Rau

Publications and source records attributed to Markus M. Rau.

13 recordsLinked to original sources

arXiv2026

Redshift Assessment Infrastructure Layers (RAIL): Rubin-era photometric redshift stress-testing and at-scale production

Virtually all extragalactic use cases of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) require the use of galaxy redshift information, yet the vast majority of its sample of tens of billions of galaxies will lack high-fidelity spectroscopic measurements thereof, instead relying on photometric redshifts (photo-$z$) subject to systematic imprecision and inaccuracy best encapsulated by photo-$z$ probability density functions (PDFs). We present the version 1 release of Redshift Assessment Infrastructure Layers (RAIL), an open source Python library for at-scale probabilistic photo-$z$ estimation, initiated by the LSST Dark Energy Science Collaboration (DESC) with contributions from the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) Frameworks team. RAIL's three subpackages provide modular tools for end-to-end stress-testing, including a forward modeling suite to generate realistically complex photometry, a unified API for estimating per-galaxy and ensemble redshift PDFs by an extensible set of algorithms, and built-in metrics of both photo-$z$ PDFs and point estimates. RAIL serves as a flexible toolkit enabling the derivation and optimization of photo-$z$ data products at scale for a variety of science goals and is not specific to LSST data. We thus describe to the extragalactic science community, including and beyond Rubin the design and functionality of the RAIL software library so that any researcher may have access to its wide array of photo-$z$ characterization and assessment tools.

astro-ph.IM↗

arXiv2025

Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference

The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subhalos through their gravitational interactions with stellar streams. In this study, we apply Neural Posterior Estimation (NPE) to constrain subhalo interaction parameters, including mass, scale radius, velocity, and encounter geometry, from stellar stream kinematics. We generate particle spray simulations based on the Lagrange Cloud stripping technique, focusing on the ATLAS-Aliqa Uma stream as a test case. We train multiple NPE models across multiple observational scenarios, quantifying how kinematic completeness affects inference and forecasting constraints from upcoming surveys including LSST, 4MOST, and 10-year Gaia data. Our results demonstrate that NPE can produce accurate and well-calibrated posteriors. In the idealized case with full 6D coordinates, we achieve subhalo mass uncertainties of 15-20% for a $10^7 \, \mathrm{M_\odot}$ subhalo, with 5D coordinates (excluding radial velocities) achieving similar performance. Under realistic observational conditions, mass uncertainties range from 50% (present-day) to 20-40% (future scenarios), with comparable performance between the photometric-only LSST sample and a smaller sample that includes Gaia proper motions and 4MOST radial velocities. Most notably, we find that velocity bimodality emerges when phase space is poorly sampled, whether due to missing kinematic information or limited stellar tracers. Combining large photometric samples with targeted spectroscopic follow-up can effectively resolves this degeneracy. These results demonstrate the power of implicit likelihood inference for optimizing stellar stream observational strategies and forecasting DM subhalo constraints from upcoming surveys.

astro-ph.GA↗

arXiv2025

Modelling Galaxy Clustering and Tomographic Galaxy-Galaxy Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model and Redshift Self-Calibration

The combination of galaxy-galaxy weak lensing and galaxy clustering is a powerful probe of the cosmological model, and exploration of how to best model and extract this information from the signals is essential. We present the measurement of the galaxy-galaxy weak lensing signals using the SDSS DR11 spectroscopic galaxies as lens galaxies, and the HSC Y3 shear catalog as source galaxies, binned into four tomographic bins by their photometric redshift. The SDSS DR11 galaxies, with a redshift range $0.15<z<0.7$, are binned into three redshift bins, each as a probe for measuring the projected correlation function, $w_p(R_p)$. We measure the galaxy-galaxy lensing signal $ΔΣ(R_p)$ in 12 lens-source bin pairs and show that there is no evidence for significant systematic biases in the measurement with null testing. We combine our $w_p(R_p)$ and $ΔΣ(R_p)$ ($2\times2$pt) data vectors and perform likelihood inference with a flat $Λ$CDM model. For $ΔΣ(R_p)$, we extend the lower limit of the scale cut compared to previous HSC Y3 analyses to $2 h^{-1}$Mpc by including a point-mass correction term in addition to the minimal bias model. We present various tests to validate our model and provide extended consistency tests. In the $Λ$CDM context, our fiducial model yields $S_8 = 0.804^{+0.051}_{-0.051}$. The $2\times2$pt data vector provides redshift parameter constraints for the third and fourth redshift bins $Δz_3 = -0.079^{+0.074}_{-0.084}$, and $Δz_4 = -0.203^{+0.167}_{-0.206}$, which is consistent with results from the previous tomographic cosmic shear studies, and serves as the foundation for a future $3\times 2$pt analysis.

astro-ph.CO↗

arXiv2025

Cosmology and Source Redshift Constraints from Galaxy Clustering and Tomographic Weak Lensing with HSC Y3 and SDSS using the Point-Mass Correction Model

The combination of galaxy clustering and weak lensing is a powerful probe of the cosmology model. We present a joint analysis of galaxy clustering and weak lensing cosmology using SDSS data as the tracer of dark matter (lens sample) and the HSC Y3 dataset as source galaxies. The analysis divides HSC Y3 galaxies into four tomographic bins for both galaxy-galaxy lensing and cosmic shear measurements, and employs a point-mass correction model to utilize galaxy-galaxy lensing signals down to 2$h^{-1}$Mpc, extending up to 70$h^{-1}$Mpc. These strategies enhance the signal-to-noise ratio of the galaxy-galaxy lensing data vector. Using a flat $Λ$CDM model, we find $S_8 = 0.780^{+0.029}_{-0.030}$, and using a $w$CDM model, we obtain $S_8 = 0.756^{+0.038}_{-0.036}$ with $w = -1.176^{+0.310}_{-0.346}$. We apply uninformative priors on the redshift mean-shift parameters for the third and fourth tomographic bins. Leveraging the self-calibration power of tomographic weak lensing, we measure $Δz_3 = -0.112^{+0.046}_{-0.049}$ and $Δz_4 = -0.185^{+0.071}_{-0.081}$, in agreement with previous HSC Y3 results. This demonstrates that weak lensing self-calibration can achieve redshift constraints comparable to other methods such as photometric and clustering redshift calibration.

astro-ph.CO↗

arXiv2025

Weak lensing mass-richness relation of redMaPPer clusters in the LSST DESC DC2 simulations

Cluster scaling relations are key ingredients in cluster abundance-based cosmological studies. In optical cluster cosmology, where clusters are detected through their richness, cluster-weak gravitational lensing has proven to be a powerful tool to constrain the cluster mass-richness relation. This work is conducted as part of the Dark Energy Science Collaboration (DESC), which aims to analyze the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory, starting in 2026. Weak lensing-inferred cluster properties, such as mass, suffer from several sources of bias. We constrain the mass-richness relation of 3,600 clusters detected by the redMaPPer algorithm in the cosmoDC2 extra-galactic mock catalog of the LSST DESC DC2 simulation, covering 440 square degrees, using number count measurements and either stacked weak lensing profiles or mean cluster masses in intervals of richness ($20 < λ< 200$) and redshift ($0.2 < z < 1$). We find that, for an LSST-like source galaxy density, our constraints are robust to changes in the concentration-mass relation and dark matter density profile modeling choices, when source redshifts and shapes are perfectly known. We find that photometric redshift uncertainties can introduce bias at the 1$σ$ level, which can be mitigated by an overall correction factor, fitted jointly with the scaling parameters. We find that including positive shear-richness covariance in the fit shifts the results by up to 0.5$σ$. Our constraints also compare fairly to a fiducial mass-richness relation, obtained from matching cosmoDC2 halo masses to redMaPPer-detected cluster richnesses.

astro-ph.CO↗

arXiv2025

Joint Modelling of Astrophysical Systematics for Cosmology with LSST Cosmic Shear

We present a novel framework for jointly modelling the weak lensing source galaxy redshift distribution and the intrinsic alignment of galaxies via a shared luminosity function (LF). Considering this framework within the context of a Rubin Observatory's Legacy Survey of Space and Time (LSST) Year 1 and Year 10 cosmic shear analysis, we first demonstrate the substantial impact of the LF on both source galaxy redshift distributions and the intrinsic alignment contamination. We establish how the individual parameters of a Schechter LF model impact the redshift distribution of a magnitude-limited sample, and we demonstrate the effect of marginalising over the LF parameters as incorporated in the intrinsic alignment modelling of a standard cosmic shear analysis set-up. We forecast the impact of our joint modelling framework on cosmological parameter constraints. Our preliminary results are promising, indicating that this framework can yield cosmological constraints consistent with those expected from standard analyses, enhanced by the flexibility of not fixing LF parameters. We plan to further validate these findings with comprehensive Markov chain Monte Carlo simulations to robustly quantify bias avoidance and underscore the framework's efficacy. Taking advantage of our forecasting results and the parameter degeneracies, we identify the specific impact of the shape of the LF of source galaxies on the cosmic shear data vector. We also discuss the potential of this method in providing a way to model generic selection functions in redshift distribution estimation, as well as its possibilities for extension to a 3x2pt analysis, particularly with respect to incorporating galaxy bias in this luminosity-function-based framework. Although we consider the context of LSST cosmic shear in this work, the proposed joint modelling framework is generically applicable to weak lensing surveys.

astro-ph.CO↗

arXiv2025

Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: I. Cluster Catalog, Selection Function and Mass--Observable Relation

We present the first step toward deriving cosmological constraints through the abundances of galaxy clusters selected in a $510\,\mathrm{deg}^2$ weak-lensing aperture mass map, constructed with the Year-Three shear catalog from the Hyper Suprime-Cam Subaru Strategic Program. We adopt a conservative source galaxy selection to construct a sample of $129$ weak-lensing peaks with a signal-to-noise ratio above $4.7$. We use semi-analytical injection simulations to derive the selection function and the mass--observable relation of our sample. These results take into account complicated uncertainties associated with weak-lensing measurements, such as the non-uniform survey depth and the complex survey geometry, projection effects from uncorrelated large-scale structures, and the intrinsic alignment of source galaxies. We also propose a novel modeling framework to make parts of the mass--observable relation insensitive to assumed cosmological parameters. Such a framework not only offers a great computational advantage to cosmological studies, but can also benefit future astrophysical studies using shear-selected clusters. Our results are an important step toward utilizing these cluster samples that are constructed nearly independent of any baryonic assumptions in upcoming deep-and-wide lensing surveys from the Vera Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope.

astro-ph.CO↗

arXiv2024

Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: II. Cosmological Constraints from the Cluster Abundance

We present cosmological constraints using the abundance of weak-lensing shear-selected galaxy clusters in the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The clusters are selected on the mass maps constructed using the three-year (Y3) weak-lensing data with an area of $\approx500~$deg$^2$, resulting in a sample size of $129$ clusters with high signal-to-noise ratios $ν$ of $ν\geq4.7$. Owing to the deep, wide-field, and uniform imaging of the HSC survey, this is by far the largest sample of shear-selected clusters, in which the selection solely depends on gravity and is free from any assumptions about the dynamical state. Informed by the optical counterparts, the shear-selected clusters span a redshift range of $z\lesssim0.7$ with a median of $z\approx0.3$. The lensing sources are securely selected at $z\gtrsim0.7$ with a median of $z\approx1.3$, leading to nearly zero cluster member contamination. We carefully account for (1) the bias in the photometric redshift of sources, (2) the bias and scatter in the weak-lensing mass using a simulation-based calibration, and (3) the measurement uncertainty that is directly estimated on the mass maps using an injection-based method developed in a companion paper (Chen et al. submitted). In a blind analysis, the fully marginalized posteriors of the cosmological parameters are obtained as $Ω_{\mathrm{m}} = 0.50^{+0.28}_{-0.24}$, $σ_8 = 0.685^{+0.161}_{-0.088}$, $\hat{S}_{8}\equivσ_8\left(Ω_{\mathrm{m}}/0.3\right)^{0.25} = 0.835^{+0.041}_{-0.044}$, and $σ_8\left(Ω_{\mathrm{m}}/0.3\right)^{0.5} = 0.993^{+0.084}_{-0.126}$ in a flat $Λ$CDM model. We compare our cosmological constraints with other studies, including those based on cluster abundances, galaxy-galaxy lensing and clustering, and Cosmic Microwave Background observed by $Planck$, and find good agreement at levels of $\lesssim2σ$. [abridged]

astro-ph.CO↗

arXiv2023

Hyper Suprime-Cam Year 3 Results: Cosmology from Galaxy Clustering and Weak Lensing with HSC and SDSS using the Minimal Bias Model

We present cosmological parameter constraints from a blind joint analysis of three two-point correlation functions measured from the Year 3 Hyper Suprime-Cam (HSC-Y3) imaging data, covering 416 deg$^2$, and the SDSS DR11 spectroscopic galaxies spanning the redshift range $[0.15, 0.70]$. We subdivide the SDSS galaxies into three volume-limited samples separated in redshift, each of which acts as a large-scale structure tracer characterized by the measurement of the projected correlation function, $w_{\rm p}(R)$. We also use the measurements of the galaxy-galaxy weak lensing signal $ΔΣ(R)$ for each of these SDSS samples which act as lenses for a secure sample of source galaxies selected from the HSC-Y3 shape catalog based on their photometric redshifts. We combine these measurements with the cosmic shear correlation functions, $ξ_{\pm}(\vartheta)$, measured for our HSC source sample. We model these observables with the minimal bias model of the galaxy clustering observables in the context of a flat $Λ$CDM cosmology. We use conservative scale cuts, $R>12$ and $8~h^{-1}$Mpc, for $ΔΣ$ and $w_{\rm p}$, respectively, where the minimal bias model is valid, in addition to conservative prior on the residual bias in the mean redshift of the HSC photometric source galaxies. Our baseline analysis yields $S_8=0.775^{+0.043}_{-0.038}$ (68% C.I.) for the $Λ$CDM model, after marginalizing over uncertainties in other parameters. Our value of $S_8$ is consistent with that from the Planck 2018 data, but the credible interval of our result is still relatively large. Our results are statistically consistent with those of a companion paper, which extends this analysis to smaller scales with an emulator-based halo model.

astro-ph.CO↗

arXiv2023

Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Two-point Correlation Functions

We perform a blinded cosmology analysis with cosmic shear two-point correlation functions (2PCFs) measured from more than 25 million galaxies in the Hyper Suprime-Cam three-year shear catalog in four tomographic redshift bins ranging from 0.3 to 1.5. After conservative masking and galaxy selection, the survey covers 416 deg$^2$ of the northern sky with an effective galaxy number density of 15 arcmin$^{-2}$ over the four redshift bins. The 2PCFs adopted for cosmology analysis are measured in the angular range: $7.1 < θ/{\rm arcmin} < 56.6$ for $ξ_+$ and $31.2 <θ/{\rm arcmin} < 248$ for $ξ_-$, with a total signal-to-noise ratio of 26.6. We apply a conservative, wide, flat prior on the photometric redshift errors on the last two tomographic bins, and the relative magnitudes of the cosmic shear amplitude across four redshift bins allow us to calibrate the photometric redshift errors. With this flat prior on redshift errors, we find $Ω_{\rm m}=0.256_{-0.044}^{+0.056}$ and $S_8\equiv σ_8 \sqrt{Ω_{\rm m}/0.3}=0.769_{-0.034}^{+0.031}$ (both 68\% CI) for a flat $Λ$ cold dark matter cosmology. We find, after unblinding, that our constraint on $S_8$ is consistent with the Fourier space cosmic shear and the 3$\times$2pt analyses on the same HSC dataset. We carefully study the potential systematics from astrophysical and systematic model uncertainties in our fiducial analysis using synthetic data, and report no biases (including projection bias in the posterior space) greater than $0.5σ$ in the estimation of $S_8$. Our analysis hints that the mean redshifts of the two highest tomographic bins are higher than initially estimated. In addition, a number of consistency tests are conducted to assess the robustness of our analysis. Comparing our result with Planck-2018 cosmic microwave background observations, we find a ~$2σ$ tension for the $Λ$CDM model.

astro-ph.CO↗

arXiv2023

Hyper Suprime-Cam Year 3 Results: Cosmology from Galaxy Clustering and Weak Lensing with HSC and SDSS using the Emulator Based Halo Model

We present cosmology results from a blinded joint analysis of cosmic shear, $ξ_{\pm}(\vartheta)$, galaxy-galaxy weak lensing, $Δ\!Σ(R)$, and projected galaxy clustering, $w_{\rm p}(R)$, measured from the Hyper Suprime-Cam three-year (HSC-Y3) shape catalog and the Sloan Digital Sky Survey (SDSS) DR11 spectroscopic galaxy catalog - a 3$\times$2pt cosmology analysis. We define luminosity-cut samples of SDSS galaxies to serve as the tracers of $w_{\rm p}$ and as the lens samples for $Δ\!Σ$ in three spectroscopic redshift bins spanning the range $0.15<z<0.7$. For the $ξ_{\pm}$ and $Δ\!Σ$ measurements, we use a single source sample over 416 deg$^2$, selected from HSC-Y3 based on having photometric redshifts (photo-$z$) greater than 0.75. For cosmological parameter inference, we use Dark Emulator combined with a halo occupation distribution prescription to model $w_{\rm p}$ and $Δ\!Σ$ down to quasi-nonlinear scales. In our baseline analysis we employ an uninformative flat prior of the residual photo-$z$ error to model a residual bias in the mean redshift of HSC source galaxies. We obtain a robust constraint on the cosmological parameters for the flat $Λ$CDM model: $S_8=σ_8(Ω_{\rm m}/0.3)^{0.5}=0.763^{+0.040}_{-0.036}$ (68% C.I.), or the best-constrained parameter given by $S'_8=σ_8(Ω_{\rm m}/0.3)^{0.22}=0.721\pm 0.028$, determined with about 4% fractional precision. Our HSC-Y3 data exhibits about 2.5$σ$ tension with the Planck inferred $S_8$ value for the $Λ$CDM model, and hints at a non-zero residual photo-$z$ bias implying that the true mean redshift of the HSC galaxies at $z\gtrsim 0.75$ is higher than that implied by the original photo-$z$ estimates.

astro-ph.CO↗

arXiv2023

Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Power Spectra

We measure weak lensing cosmic shear power spectra from the three-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers $416 \ \mathrm{deg}^2$ of the northern sky, with a mean $i$-band seeing of 0.59 arcsec and an effective galaxy number density of 15 $\mathrm{arcmin}^{-2}$ within our adopted redshift range. With an $i$-band magnitude limit of 24.5 mag, and four tomographic redshift bins spanning $0.3 \leq z_{\mathrm{ph}} \leq 1.5$ based on photometric redshifts, we obtain a high-significance measurement of the cosmic shear power spectra, with a signal-to-noise ratio of approximately 26.4 in the multipole range $300<\ell<1800$. The accuracy of our power spectrum measurement is tested against realistic mock shear catalogs, and we use these catalogs to get a reliable measurement of the covariance of the power spectrum measurements. We use a robust blinding procedure to avoid confirmation bias, and model various uncertainties and sources of bias in our analysis, including point spread function systematics, redshift distribution uncertainties, the intrinsic alignment of galaxies and the modeling of the matter power spectrum. For a flat $Λ$CDM model, we find $S_8 \equiv σ_8 (Ω_m/0.3)^{0.5} =0.776^{+0.032}_{-0.033}$, which is in excellent agreement with the constraints from the other HSC Year 3 cosmology analyses, as well as those from a number of other cosmic shear experiments. This result implies a $\sim$$2σ$-level tension with the Planck 2018 cosmology. We study the effect that various systematic errors and modeling choices could have on this value, and find that they can shift the best-fit value of $S_8$ by no more than $\sim$$0.5σ$, indicating that our result is robust to such systematics.

astro-ph.CO↗

arXiv2021

Debiased Galaxy Cluster Pressure Profiles from X-ray Observations and Simulations

We present an updated model for the average cluster pressure profile, adjusted for hydrostatic mass bias by combining results from X-ray observations with cosmological simulations. Our model estimates this bias by fitting a power-law to the relation between the "true" halo mass and X-ray cluster mass in hydrodynamic simulations (IllustrisTNG, BAHAMAS, and MACSIS). As an example application, we consider the REXCESS X-ray cluster sample and the Universal Pressure Profile (UPP) derived from scaled and stacked pressure profiles. We find adjusted masses, $M_\mathrm{500c},$ that are $\lesssim$15% higher and scaled pressures $P/P_\mathrm{500c}$ that have $\lesssim$35% lower normalization than previously inferred. Our Debiased Pressure Profile (DPP) is well-fit by a Generalized Navarro-Frenk-White (GNFW) function, with parameters $[P_0,c_{500},α,β,γ]=[5.048,1.217,1.192,5.490,0.433]$ and does not require a mass-dependent correction term. When the DPP is used to model the Sunyaev-Zel'dovich (SZ) effect, we find that the integrated Compton $Y-M$ relation has only minor deviations from self-similar scaling. The thermal SZ angular power spectrum is lower in amplitude by approximately 30%, assuming nominal cosmological parameters (e.g. $Ω_\text{m}=0.3$, $σ_8 = 0.8$), and is broadly consistent with recent Planck results without requiring additional bias corrections.

astro-ph.CO↗