arXiv subjects

Florian Kéruzoré

Publications and source records attributed to Florian Kéruzoré.

9 recordsLinked to original sources

arXiv2026

Diffhalos: A Generative Model of Cosmological Lightcones of Dark Matter Halos

We present a generative model of cosmological lightcones of dark matter halos, Diffhalos. In our model, we draw Monte Carlo samples of the halo mass function in a lightcone with a JAX-based implementation of the halo model, Halox, and we generate samples of subhalos by drawing from a model for the conditional subhalo mass function. We generate mass assembly histories (MAHs) using a normalizing flow trained on merger trees in cosmological N-body simulations. We show that Diffhalos can generate samples of halos, subhalos, and their MAHs with a statistical distribution that accurately approximates populations in simulated lightcones. As an example application, we use Diffhalos to calculate gradients of the halo and subhalo mass functions with respect to cosmological parameters. We conclude with a discussion of ongoing work using Diffhalos together with models of the galaxy--halo connection to make theoretical predictions for cosmological populations of galaxies, and to generate mock galaxy catalogs.

astro-ph.GA↗

arXiv2026

Reducing Model Error Using Optimised Galaxy Selection: Weak Lensing Cluster Mass Estimation

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory's Legacy Survey of Space and Time are expected to revolutionise the field, by enabling the analysis of cluster samples of unprecedented size and quality. To reach this era of high-precision cluster cosmology, the mitigation of sources of systematic error is crucial. A particularly important challenge is bias in cluster mass measurements induced by the mismodelling of photometric redshift estimates of source galaxies. This work proposes a method to optimise the source sample selection in cluster weak lensing analyses drawn from wide-field survey lensing catalogs to reduce the bias on reconstructed cluster masses. We use a combinatorial optimisation scheme and methods from variational inference to select galaxies in latent space to produce a probabilistic galaxy source sample catalog for highly accurate cluster mass estimation. We show that our method reduces the critical surface mass density $Σ_{\rm crit}$ relative modelling bias on the 60-70% level, while maintaining up to 90\% of galaxies. We highlight that our methodology has applications beyond cluster mass estimation as an approach to jointly combine galaxy selection and model inference under sources of systematics.

astro-ph.CO↗

arXiv2026

halox: Dark matter halo properties and large-scale structure calculations using JAX

Dark matter halos are fundamental structures in cosmology, forming the gravitational potential wells hosting galaxies and clusters of galaxies. Their properties and statistical distribution (including the halo mass function) are invaluable tools to infer the fundamental properties of the Universe. The \texttt{halox} package is a JAX-powered Python library enabling differentiable and accelerated computations of key properties of dark matter halos, and of the halo mass function. The automatic differentiation capabilities of \texttt{halox} enable its usage in gradient-based workflows, e.g. in efficient Hamiltonian Monte Carlo sampling or machine learning applications.

astro-ph.IM↗

arXiv2026

Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models

Deep generative models (DGMs) compress high-dimensional data but often entangle distinct physical factors in their latent spaces. We present an auxiliary-variable-guided framework for disentangling representations of thermal Sunyaev-Zel'dovich (tSZ) maps of dark matter halos. We introduce halo mass and concentration as auxiliary variables and apply a lightweight alignment penalty to encourage latent dimensions to reflect these physical quantities. To generate sharp and realistic samples, we extend latent conditional flow matching (LCFM), a state-of-the-art generative model, to enforce disentanglement in the latent space. Our Disentangled Latent-CFM (DL-CFM) model recovers the established mass-concentration scaling relation and identifies latent space outliers that may correspond to unusual halo formation histories. By linking latent coordinates to interpretable astrophysical properties, our method transforms the latent space into a diagnostic tool for cosmological structure. This work demonstrates that auxiliary guidance preserves generative flexibility while yielding physically meaningful, disentangled embeddings, providing a generalizable pathway for uncovering independent factors in complex astronomical datasets.

stat.ML↗

arXiv2026

Unified and consistent structure growth measurements from joint ACT, SPT and \textit{Planck} CMB lensing

We present the tightest cosmic microwave background (CMB) lensing constraints to date on the growth of structure by combining CMB lensing measurements from the Atacama Cosmology Telescope (ACT), the South Pole Telescope (SPT) and \textit{Planck}. Each of these surveys individually provides lensing measurements with similarly high statistical power, achieving signal-to-noise ratios of approximately 40. The combined lensing bandpowers represent the most precise CMB lensing power spectrum measurement to date with a signal-to-noise ratio of 61 and an amplitude of $A_\mathrm{lens}^\mathrm{recon} = 1.025 \pm 0.017$ with respect to the theory prediction from the best-fit CMB \textit{Planck}-ACT cosmology. The bandpowers from all three lensing datasets, analyzed jointly, yield a $1.6\%$ measurement of the parameter combination $S_8^\mathrm{CMBL} \equiv σ_8\,(Ω_m/0.3)^{0.25} = 0.825^{+0.015}_{-0.013}$. Including Dark Energy Spectroscopic Instrument (DESI) Baryon Acoustic Oscillation (BAO) data improves the constraint on the amplitude of matter fluctuations to $σ_8 = 0.829 \pm 0.009$ (a $1.1\%$ determination). When combining with uncalibrated supernovae from \texttt{Pantheon+}, we present a $4\%$ sound-horizon-independent estimate of $H_0=66.4\pm2.5\,\mathrm{km\,s^{-1}\,Mpc^{-1}} $. The joint lensing constraints on structure growth and present-day Hubble rate are fully consistent with a $Λ$CDM model fit to the primary CMB data from \textit{Planck} and ACT. While the precise upper limit is sensitive to the choice of data and underlying model assumptions, when varying the neutrino mass sum within the $Λ\mathrm{CDM}$ cosmological model, the combination of primary CMB, BAO and CMB lensing drives the probable upper limit for the mass sum towards lower values, comparable to the minimum mass prior required by neutrino oscillation experiments.

astro-ph.CO↗

arXiv2025

Constraints on Non-Thermal Pressure at galaxy cluster outskirts from a Joint SPT and XMM-Newton Analysis

We present joint South Pole Telescope (SPT) and XMM-Newton observations of 8 massive galaxy clusters (0.8--1.7$\times$10$^{15}$ M$_{\odot}$) spanning a redshift range of 0.16 to 0.35. Employing a novel SZ+X-ray fitting technique, we effectively constrain the thermodynamic properties of these clusters out to the virial radius. The resulting best-fit electron density, deprojected temperature, and deprojected pressure profiles are in good agreement with previous observations of massive clusters. For the majority of the cluster sample (5 out of 8 clusters), the entropy profiles exhibit a self-similar behavior near the virial radius. We further derive hydrostatic mass, gas mass, and gas fraction profiles for all clusters up to the virial radius. Comparing the enclosed gas fraction profiles with the universal gas fraction profile, we obtain non-thermal pressure fraction profiles for our cluster sample at $>$$R_{500}$, demonstrating a steeper increase between $R_{500}$ and $R_{200}$ that is consistent with the hydrodynamical simulations. Our analysis yields non-thermal pressure fraction ranges of 8--28% (median: 15 $\pm$ 11%) at $R_{500}$ and 21--35% (median: 27 $\pm$ 12%) at $R_{200}$. Notably, weak-lensing mass measurements are available for only four clusters in our sample, and our recovered total cluster masses, after accounting for non-thermal pressure, are consistent with these measurements.

astro-ph.GA↗

arXiv2021

PANCO2: a new software to measure pressure profiles from resolved thermal SZ observations

We have developed a new software to perform the measurement of galaxy cluster pressure profiles from high angular resolution thermal SZ observations. The code allows the user to take into account various features of millimeter observations, such as point spread function (PSF) convolution, pipeline filtering, correlated residual noise, and point source contamination, in a forward modeling approach. One of the key advantages of the code is the possibility to use binned, non-parametric pressure profiles, enabling the detection of pressure features better than smooth functions such as the traditionally used generalized Navarro-Frenk-White profile. Another major upside is the performance of the software, enabling the extraction of the pressure profile and associated confidence intervals via MCMC sampling in times as short as a few minutes. We present the code and its validation on various realistic synthetic maps, of ideal spherical clusters, as well as of realistic, hydrodynamically simulated objects. We plan to publicly release the software in the coming months.

astro-ph.IM↗

arXiv2021

Forecasting the $Y_{500}-M_{500}$ scaling relation from the NIKA2 SZ Large Program

One of the key elements needed to perform the cosmological exploitation of a cluster survey is the relation between the survey observable and the cluster masses. Among these observables, the integrated Compton parameter $Y$ is a measurable quantity in Sunyaev-Zeldovich (SZ) surveys, which tightly correlates with cluster mass. The calibration of the relation between the Compton parameter $Y_{500}$ and the mass $M_{500}$ enclosed within radius $R_{500}$ is one of the scientific goals of the NIKA2 SZ Large Program (LPSZ). We present an ongoing study to forecast the constraining power of this program, using mock simulated datasets that mimic the large program sample, selection function, and typical uncertainties on $Y_{500}$ and $M_{500}$. We use a Bayesian hierarchical modeling that enables taking into account a large panel of systematic effects. Our results show that the LPSZ can yield unbiased estimates of the scaling relation parameters for realistic input parameter values. The relative uncertainties on these parameters is $\sim 10\%$ for the intercept and slope of the scaling relation, and $\sim 34\%$ for its intrinsic scatter, foreshadowing precise estimates to be delivered by the LPSZ.

astro-ph.CO↗

arXiv2021

Exploring the hydrostatic mass bias in MUSIC clusters: application to the NIKA2 mock sample

Clusters of galaxies are useful tools to constrain cosmological parameters, only if their masses can be correctly inferred from observations. In particular, X-ray and Sunyaev-Zeldovich (SZ) effect observations can be used to derive masses within the framework of the hydrostatic equilibrium. Therefore, it is crucial to have a good control of the possible mass biases that can be introduced when this hypothesis is not valid. In this work, we analyzed a set of 260 synthetic clusters from the MUSIC simulation project, at redshifts $0 \leq z \leq 0.82$. We estimate the hydrostatic mass of the MUSIC clusters from X-ray only (temperature and density) and from X-ray and SZ (density and pressure). Then, we compare them with the true 3D dynamical mass. The biases are of the order of 20%. We find that using the temperature instead of the pressure leads to a smaller bias, although the two values are compatible within 1$σ$. Non-thermal contributions to the total pressure support, arising from bulk motion and turbulence of the gas, are also computed and show that they are sufficient to account for this bias. We also present a study of the correlation between the mass bias and the dynamical state of the clusters. A clear correlation is shown between the relaxation state of the clusters and the bias factor. We applied the same analysis on a subsample of 32 objects, already selected for supporting the NIKA2 SZ Large Program.

astro-ph.CO↗