arXiv subjects

Dhayaa Anbajagane

Publications and source records attributed to Dhayaa Anbajagane.

33 records · Page 2Linked to original sources

arXiv2024

Baryonic Imprints on DM Halos: the concentration-mass relation and its dependence on halo and galaxy properties

The halo concentration-mass relation has ubiquitous use in modeling the matter field for cosmological and astrophysical analyses, and including the imprints from galaxy formation physics is tantamount to its robust usage. Many analyses, however, probe the matter around halos selected by a given halo/galaxy property -- rather than by halo mass -- and the imprints under each selection choice can be different. We employ the CAMELS simulation suite to quantify the astrophysics and cosmology dependence of the concentration-mass relation, $c_{\rm vir}-M_{\rm vir}$, when selected on five properties: (i) velocity dispersion, (ii) formation time, (iii) halo spin, (iv) stellar mass, and (v) gas mass. We construct simulation-informed nonlinear models for all properties as a function of halo mass, redshift, and six cosmological/astrophysical parameters, with a mass range $M_{\rm vir} \in [10^{11}, 10^{14.5}] M_\odot/h$. There are many mass-dependent imprints in all halo properties, with clear connections across different properties and non-linear couplings between the parameters. Finally, we extract the $c_{\rm vir}-M_{\rm vir}$ relation for subsamples of halos that have scattered above/below the mean property-$M_{\rm vir}$ relation for a chosen property. Selections on gas mass or stellar mass have a significant impact on the astrophysics/cosmology dependence of $c_{\rm vir}$, while those on any of the other three properties have a significant (mild) impact on the cosmology (astrophysics) dependence. We show that ignoring such selection effects can lead to errors of $\approx 25\%$ in baryon imprint modelling of $c_{\rm vir}$. Our nonlinear model for all properties is made publicly available.

astro-ph.GA↗

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

GODMAX: Modeling gas thermodynamics and matter distribution using JAX

We introduce GODMAX (Gas thermODynamics and Matter distribution using jAX), a novel code designed to calculate correlations between the cosmological matter distribution and various gas thermodynamic quantities. Utilizing the extensive ANTILLES suite of 200 hydrodynamical simulations with a diverse range of baryonic feedback strengths, we jointly fit the 3D profiles of total matter distribution, electron density, and electron pressure across various halo masses and redshifts. By accommodating significant variations in gas profiles expected due to baryonic feedback, solving exact hydrostatic equilibrium equation and offering flexible modeling of non-thermal pressure support, GODMAX has the capability to jointly fit all these profiles within the measurement uncertainties. This advancement enables, for the first time, robust joint analyses of multiple cosmic probes, including the kinetic and thermal Sunyaev-Zel'dovich effect, weak lensing, and X-ray observations. Furthermore, the model accurately captures correlations between the total matter power suppression due to baryonic feedback and local average thermodynamic quantities, such as the baryon fraction and integrated tSZ effect, in high-mass halos, aligning with observations from hydrodynamical simulations. Looking ahead, we forecast the expected constraints on cosmological and baryonic parameters from upcoming weak lensing catalogs from the LSST and tSZ maps from the Simons Observatory. This analysis underscores the importance of cross-correlations between weak lensing and tSZ in enhancing parameter constraints by resolving major systematic uncertainties due to baryonic physics. The GODMAX code leverages the JAX library, resulting in a fully differentiable halo model with native GPU compilation support.

astro-ph.CO↗

arXiv2024

Deciphering baryonic feedback with galaxy clusters

Upcoming cosmic shear analyses will precisely measure the cosmic matter distribution at low redshifts. At these redshifts, the matter distribution is affected by galaxy formation physics, primarily baryonic feedback from star formation and active galactic nuclei. Employing measurements from the Magneticum and IllustrisTNG simulations and a dark matter + baryon (DMB) halo model, this paper demonstrates that Sunyaev-Zel'dovich (SZ) effect observations of galaxy clusters, whose masses have been calibrated using weak gravitational lensing, can constrain the baryonic impact on cosmic shear with statistical and systematic errors subdominant to the measurement errors of DES-Y3 and LSST-Y1. We further dissect the contributions from different scales and halos with different masses to cosmic shear, highlighting the dominant role of SZ clusters at scales critical for cosmic shear analyses. These findings suggest a promising avenue for future joint analyses of Cosmic Microwave Background (CMB) and lensing surveys.

astro-ph.CO↗

arXiv2023

Merger Response of Halo Anisotropy Properties

Anisotropy properties -- halo spin, shape, position offset, velocity offset, and orientation -- are an important family of dark matter halo properties that indicate the level of directional variation of the internal structures of haloes. These properties reflect the dynamical state of haloes, which in turn depends on the mass assembly history. In this work, we study the evolution of anisotropy properties in response to merger activity using the IllustrisTNG simulations. We find that the response trajectories of the anisotropy properties significantly deviate from secular evolution. These trajectories have the same qualitative features and timescales across a wide range of merger and host properties. We propose explanations for the behaviour of these properties and connect their evolution to the relevant stages of merger dynamics. We measure the relevant dynamical timescales. We also explore the dependence of the strength of the response on time of merger, merger ratio, and mass of the main halo. These results provide insight into the physics of halo mergers and their effects on the statistical behaviour of halo properties. This study paves the way towards a physical understanding of scaling relations, particularly to how systematics in their scatter are connected to the mass assembly histories of haloes.

astro-ph.CO↗

arXiv2023

Baryonic Imprints on DM Halos: The concentration-mass relation in the CAMELS simulations

The physics of baryons in halos, and their subsequent influence on the total matter phase space, has a rich phenomenology and must be well understood in order to pursue a vast set of questions in both cosmology and astrophysics. We use the CAMELS simulation suite to quantify the impact of four different galaxy formation parameters/processes (as well as two cosmological parameters) on the concentration-mass relation, $c_{\rm vir} - M_{\rm vir}$. We construct a simulation-informed nonlinear model for concentration as a function of halo mass, redshift, and 6 cosmological/astrophysical parameters. This is done for two galaxy formation models, IllustrisTNG and SIMBA, using 1000 simulations of each. We extract the imprints of galaxy formation across a wide range in mass $M_{\rm vir} \in [10^{11}, 10^{14.5}] M_{\rm \odot}/h$ and in redshift $z \in [0,6]$ finding many strong mass- and redshift-dependent features. Comparisons between the IllustrisTNG and SIMBA results show the astrophysical model choices cause significant differences in the mass and redshift dependence of these baryon imprints. Finally, we use existing observational measurements of $c_{\rm vir} - M_{\rm vir}$ to provide rough limits on the four astrophysical parameters. Our nonlinear model is made publicly available and can be used to include CAMELS-based baryon imprints in any halo model-based analysis.

astro-ph.CO↗

arXiv2022

A multi-simulation study of relativistic SZ temperature scalings in galaxy clusters and groups

The Sunyaev-Zeldovich (SZ) effect is a powerful tool in modern cosmology. With future observations promising ever improving SZ measurements, the relativistic corrections to the SZ signals from galaxy groups and clusters are increasingly relevant. As such, it is important to understand the differences between three temperature measures: (a) the average relativistic SZ (rSZ) temperature, (b) the mass-weighted temperature relevant for the thermal SZ (tSZ) effect, and (c) the X-ray spectroscopic temperature. In this work, we compare these cluster temperatures, as predicted by the {\sc Bahamas} \& {\sc Macsis}, {\sc Illustris-TNG}, {\sc Magneticum}, and {\sc The Three Hundred Project} simulations. Despite the wide range of simulation parameters, we find the SZ temperatures are consistent across the simulations. We estimate a $\simeq 10\%$ level correction from rSZ to clusters with $Y\simeq10^{-4}$~Mpc$^{-2}$. Our analysis confirms a systematic offset between the three temperature measures; with the rSZ temperature $\simeq 20\%$ larger than the other measures, and diverging further at higher redshifts. We demonstrate that these measures depart from simple self-similar evolution and explore how they vary with the defined radius of haloes. We investigate how different feedback prescriptions and resolution affect the observed temperatures, and discover the SZ temperatures are rather insensitive to these details. The agreement between simulations indicates an exciting avenue for observational and theoretical exploration, determining the extent of relativistic SZ corrections. We provide multiple simulation-based fits to the scaling relations for use in future SZ modelling.

astro-ph.CO↗

arXiv2022

The scatter in the galaxy-halo connection: a machine learning analysis

We apply machine learning, a powerful method for uncovering complex correlations in high-dimensional data, to the galaxy-halo connection of cosmological hydrodynamical simulations. The mapping between galaxy and halo variables is stochastic in the absence of perfect information, but conventional machine learning models are deterministic and hence cannot capture its intrinsic scatter. To overcome this limitation, we design an ensemble of neural networks with a Gaussian loss function that predict probability distributions, allowing us to model statistical uncertainties in the galaxy-halo connection as well as its best-fit trends. We extract a number of galaxy and halo variables from the Horizon-AGN and IllustrisTNG100-1 simulations and quantify the extent to which knowledge of some subset of one enables prediction of the other. This allows us to identify the key features of the galaxy-halo connection and investigate the origin of its scatter in various projections. We find that while halo properties beyond mass account for up to 50 per cent of the scatter in the halo-to-stellar mass relation, the prediction of stellar half-mass radius or total gas mass is not substantially improved by adding further halo properties. We also use these results to investigate semi-analytic models for galaxy size in the two simulations, finding that assumptions relating galaxy size to halo size or spin are not successful.

astro-ph.GA↗

arXiv2022

\textsc{The Three Hundred} project: The \textsc{Gizmo-Simba} run

We introduce \textsc{Gizmo-Simba}, a new suite of galaxy cluster simulations within \textsc{The Three Hundred} project. \textsc{The Three Hundred} consists of zoom re-simulations of 324 clusters with $M_{200}\gtrsim 10^{14.8}M_\odot$ drawn from the MultiDark-Planck $N$-body simulation, run using several hydrodynamic and semi-analytic codes. The \textsc{Gizmo-Simba} suite adds a state-of-the-art galaxy formation model based on the highly successful {\sc Simba} simulation, mildly re-calibrated to match $z=0$ cluster stellar properties. Comparing to \textsc{The Three Hundred} zooms run with \textsc{Gadget-X}, we find intrinsic differences in the evolution of the stellar and gas mass fractions, BCG ages, and galaxy colour-magnitude diagrams, with \textsc{Gizmo-Simba} generally providing a good match to available data at $z \approx 0$. \textsc{Gizmo-Simba}'s unique black hole growth and feedback model yields agreement with the observed BH scaling relations at the intermediate-mass range and predicts a slightly different slope at high masses where few observations currently lie. \textsc{Gizmo-Simba} provides a new and novel platform to elucidate the co-evolution of galaxies, gas, and black holes within the densest cosmic environments.

astro-ph.GA↗

arXiv2022

Correlations of Dark Matter, Gas and Stellar Profiles in Dark Matter Halos

Halos of similar mass and redshift exhibit a large degree of variability in their differential properties, such as dark matter, hot gas, and stellar mass density profiles. This variability is an indicator of diversity in the formation history of these dark matter halos that is reflected in the coupling of scatters about the mean relations. In this work, we show that the strength of this coupling depends on the scale at which halo profiles are measured. By analyzing the outputs of the IllustrisTNG hydrodynamical cosmological simulations we report the radial- and mass-dependent couplings between the dark matter, hot gas, and stellar mass radial density profiles utilizing the population diversity in dark matter halos. We find that for the same mass halos the scatters in the density of baryons and dark matter are strongly coupled at large scales ($r>R_{200}$); but the coupling between gas and dark matter density profiles fades near the core of halos ($r < 0.3 R_{200}$). We then show that the correlation between halo profile and integrated quantities induces a radius-dependent additive bias in the profile observables of halos when halos are selected on properties other than their mass. We discuss the impact of this effect on cluster abundance and cross-correlations cosmology with multi-wavelength cosmological surveys.

astro-ph.CO↗

arXiv2022

KLLR: A scale-dependent, multivariate model class for regression analysis

The underlying physics of astronomical systems governs the relation between their measurable properties. Consequently, quantifying the statistical relationships between system-level observable properties of a population offers insights into the astrophysical drivers of that class of systems. While purely linear models capture behavior over a limited range of system scale, the fact that astrophysics is ultimately scale-dependent implies the need for a more flexible approach to describing population statistics over a wide dynamic range. For such applications, we introduce and implement a class of Kernel-Localized Linear Regression (KLLR) models. KLLR is a natural extension to the commonly-used linear models that allows the parameters of the linear model -- normalization, slope, and covariance matrix -- to be scale-dependent. KLLR performs inference in two steps: (1) it estimates the mean relation between a set of independent variables and a dependent variable and; (2) it estimates the conditional covariance of the dependent variables given a set of independent variables. We demonstrate the model's performance in a simulated setting and showcase an application of the proposed model in analyzing the baryonic content of dark matter halos. As a part of this work, we publicly release a Python implementation of the KLLR method.

astro-ph.IM↗

arXiv2021

Galaxy Velocity Bias in Cosmological Simulations: Towards Percent-level Calibration

Galaxy cluster masses, rich with cosmological information, can be estimated from internal dark matter (DM) velocity dispersions, which in turn can be observationally inferred from satellite galaxy velocities. However, galaxies are biased tracers of the DM, and the bias can vary over host halo and galaxy properties as well as time. We precisely calibrate the velocity bias, b_v -- defined as the ratio of galaxy and DM velocity dispersions -- as a function of redshift, host halo mass, and galaxy stellar mass threshold (Mstarsat), for massive halos (M200c > 1e13.5 msun) from five cosmological simulations: IllustrisTNG, Magneticum, Bahamas + Macsis, The Three Hundred Project, and MultiDark Planck-2. We first compare scaling relations for galaxy and DM velocity dispersion across simulations; the former is estimated using a new ensemble velocity likelihood method that is unbiased for low galaxy counts per halo, while the latter uses a local linear regression. The simulations show consistent trends of b_v increasing with M200c and decreasing with redshift and Mstarsat. The ensemble-estimated theoretical uncertainty in b_v is 2-3% but becomes percent-level when considering only the three highest resolution simulations. We update the mass-richness normalization previously estimated by Farahi et al. (2016) for an SDSS redMaPPer cluster sample. The improved accuracy of our b_v estimates reduces the mass normalization uncertainty from 22% to 8%, demonstrating that dynamical estimation techniques can be competitive with weak lensing in calibrating population mean masses. We discuss necessary steps for further improving this precision. Our estimates for b_v(M200c, Mstarsat, z) are made publicly available.

astro-ph.CO↗

arXiv2021

A Test of the Standard Cosmological Model with Geometry and Growth

We perform a general test of the $Λ{\rm CDM}$ and $w {\rm CDM}$ cosmological models by comparing constraints on the geometry of the expansion history to those on the growth of structure. Specifically, we split the total matter energy density, $Ω_M$, and (for $w {\rm CDM}$) dark energy equation of state, $w$, into two parameters each: one that captures the geometry, and another that captures the growth. We constrain our split models using current cosmological data, including type Ia supernovae, baryon acoustic oscillations, redshift space distortions, gravitational lensing, and cosmic microwave background (CMB) anisotropies. We focus on two tasks: (i) constraining deviations from the standard model, captured by the parameters $ΔΩ_M \equiv Ω_M^{\rm grow}-Ω_M^{\rm geom}$ and $Δw \equiv w^{\rm grow}-w^{\rm geom}$, and (ii) investigating whether the $S_8$ tension between the CMB and weak lensing can be translated into a tension between geometry and growth, i.e. $ΔΩ_M \neq 0$, $Δw \neq 0$. In both the split $Λ{\rm CDM}$ and $w {\rm CDM}$ cases, our results from combining all data are consistent with $ΔΩ_M = 0$ and $Δw = 0$. If we omit BAO/RSD data and constrain the split $w {\rm CDM}$ cosmology, we find the data prefers $Δw<0$ at $3.6σ$ significance and $ΔΩ_M>0$ at $4.2σ$ evidence. We also find that for both CMB and weak lensing, $ΔΩ_M$ and $S_8$ are correlated, with CMB showing a slightly stronger correlation. The general broadening of the contours in our extended model does alleviate the $S_8$ tension, but the allowed nonzero values of $ΔΩ_M$ do not encompass the $S_8$ values that would point toward a mismatch between geometry and growth as the origin of the tension.

astro-ph.CO↗

arXiv2021

Baryonic Imprints on DM Halos: Population Statistics from Dwarf Galaxies to Galaxy Clusters

In a purely cold dark matter universe, the initial matter power spectrum and its subsequent gravitational growth contain no special mass- or time-scales, and so neither do the emergent population statistics of internal dark matter (DM) halo properties. Using 1.5 million halos from three IllustrisTNG realizations of a LambdaCDM universe, we show that galaxy formation physics drives non-monotonic features ("wiggles") into DM property statistics across six decades in halo mass, from dwarf galaxies to galaxy clusters. We characterize these features by extracting the halo mass-dependent statistics of five DM halo properties -- velocity dispersion, NFW concentration, density- and velocity-space shapes, and formation time -- using kernel-localized linear regression (KLLR). Comparing precise estimates of normalizations, slopes, and covariances between realizations with and without galaxy formation, we find systematic deviations across all mass-scales, with maximum deviations of 25% at the Milky-Way mass of 1e12 Msun. The mass-dependence of the wiggles is set by the interplay between different cooling and feedback mechanisms, and we discuss its observational implications. The property covariances depend strongly on halo mass and physics treatment, but the correlations are mostly robust. Using multivariate KLLR and interpretable machine learning, we show the halo concentration and velocity-space shape are principal contributors, at different mass, to the velocity dispersion variance. Statistics of mass accretion rate and DM surface pressure energy are provided in an appendix. We publicly release halo property catalogs and KLLR parameters for the TNG runs at twenty epochs up to z = 12.

astro-ph.CO↗

arXiv2020

Stellar Property Statistics of Massive Halos from Cosmological Hydrodynamics Simulations: Common Kernel Shapes

We study stellar property statistics, including satellite galaxy occupation, of massive halo populations realized by three cosmological hydrodynamics simulations: BAHAMAS + MACSIS, TNG300 of the IllustrisTNG suite, and Magneticum Pathfinder. The simulations incorporate independent sub-grid methods for astrophysical processes with spatial resolutions ranging from $1.5$ to $6$ kpc, and each generates samples of $1000$ or more halos with $M_{\rm halo}> 10^{13.5} M_{\odot}$ at redshift $z=0$. Applying localized, linear regression (LLR), we extract halo mass-conditioned statistics (normalizations, slopes, and intrinsic covariance) for a three-element stellar property vector consisting of: i) $N_{sat}$, the number of satellite galaxies with stellar mass, $M_{\star, \rm sat} > 10^{10} M_{\odot}$ within radius $R_{200c}$ of the halo; ii) $M_{\star,\rm tot}$, the total stellar mass within that radius, and; iii) $M_{\star,\rm BCG}$, the gravitationally-bound stellar mass of the central galaxy within a $100 \, \rm kpc$ radius. Scaling parameters for the three properties with halo mass show mild differences among the simulations, in part due to numerical resolution, but there is qualitative agreement on property correlations, with halos having smaller than average central galaxies tending to also have smaller total stellar mass and a larger number of satellite galaxies. Marginalizing over total halo mass, we find the satellite galaxy kernel, $p(\ln N_{sat}\,|\,M_{\rm halo},z)$ to be consistently skewed left, with skewness parameter $γ= -0.91 \pm 0.02$, while that of $\ln M_{\star,\rm tot}$ is closer to log-normal, in all three simulations. The highest resolution simulations find $γ\simeq -0.8$ for the $z=0$ shape of $p(\ln M_{\star,\rm BCG}\,|\,M_{\rm halo},z)$ and also that the fractional scatter in total stellar mass is below $10\%$ in halos more massive than $10^{14.3} M_{\odot}$.

astro-ph.GA↗