arXiv subjects

Shivam Pandey

Publications and source records attributed to Shivam Pandey.

At least 19 recordsLinked to original sources

arXiv2026

Backlighting the Cosmic Web with Fast Radio Bursts: An Anthology of Dispersion Measure Cross-Correlations with Large-Scale Structure and Baryon Tracers

Fast Radio Bursts (FRBs) probe baryons permeating the cosmic web through their dispersion measures (DMs), which encode the integrated electron density along cosmological sightlines. Using 3,455 unique FRB sources from CHIME/FRB with $\sim 15$ arcmin localizations, we present an anthology of DM correlations with tracers of large-scale structure and baryonic matter at redshifts $z \lesssim 1.5$. We measure statistically significant correlations at $2.6-5\sigma$ with ten probes, including galaxies ($2.8\sigma$), weak gravitational lensing ($2.6\sigma$), cosmic infrared background ($4.0\sigma$), cosmic microwave background (CMB) lensing ($3.3\sigma$), thermal Sunyaev Zel'dovich (tSZ) effect ($3.8\sigma$), X-ray emission tracing galaxy clusters ($5.0\sigma$) and superclusters ($3.3\sigma$), soft X-ray background (SXRB, $4.1\sigma$), and radio continuum emission ($3.2\sigma$). These measurements reveal a consistent picture in which FRB sightlines intersecting overdense environments carry systematically larger DMs. Correlations with hot-gas tracers provide additional leverage on the strength of feedback, as they are strongly weighted towards the dense, bound gas. The measured amplitude of tSZ$\times$DM and SXRB$\times$DM correlations are consistent with theoretical predictions of baryon distribution from a DM-$z$ relation-inferred model with moderate feedback at $\sim 0.5\sigma$ level. Weaker feedback scenario is ruled out at $\sim 3.5\sigma$ by the SXRB$\times$DM correlation. Taken together, these measurements constitute a quantitative multi-tracer foundation for a new era in which FRBs from next generation facilities, such as BURSTT, CHORD, DSA, and SKA, in harmony with other probes, will map the baryon content of the full extent of the cosmic web.

astro-ph.CO↗

arXiv2026

Efficiently emulating distribution functions in gigaparsec volumes for varying cosmological parameters

We present a new method for emulating the halo mass function (HMF) and other distribution functions in large effective volumes, down to low halo masses, whilst simultaneously modifying large ranges of parameters, for a fraction of the cost of traditional periodic cosmological simulations. We demonstrate the method by selecting small regions, $V \sim (50 \,h^{-1}{\rm Mpc})^3$, with a range of overdensities from the Quijote suite, consisting of tens of thousands of $(1 \,h^{-1}{\rm Gpc})^3$ $N$-body simulation volumes run with varying $\Lambda$CDM parameters. We train a differentiable emulator, conditioned on the overdensity of the region and these global parameters, to reproduce the halo mass function in these regions. We then successfully recover the global distribution of halo masses of the entire box by integrating over the overdensity distribution. Our approach uses just $\sim\,$0.026% of the original simulation volume, and suggests that suites of targeted `zoom' simulations, extracted from low resolution parent volumes, can be used to emulate large volume simulations at a fraction of the computational cost, whilst simultaneously pushing the dynamic range to much lower masses than can be achieved in periodic simulations. We discuss emulation of other key dark matter and baryonic distribution functions, as well as higher order statistics, with implications for the interpretation of upcoming wide field surveys on observatories such as Euclid, Roman and Rubin.

astro-ph.CO↗

arXiv2026

Buzz Buzz: Haptic Cuing of Road Conditions in Autonomous Cars for Drivers Engaged in Secondary Tasks

Can drivers' situation awareness during automated driving be maintained using haptic cues that provide information about road and traffic scenarios while the drivers are engaged in a secondary task? And can this be done without disengaging them from the secondary task? Multiple Resource Theory predicts that using different sensory channels can improve multiple-task performance. Using haptics to provide information avoids the audio-visual channels likely occupied by the secondary task. An experiment was conducted to assess whether drivers' situation awareness could be maintained using haptic cues. Drivers played Fruit Ninja as the secondary task while seated in a driving simulator with a Level 4 autonomous system driving. A mixed design was used for the experiment with the presence of haptic cues and the presentation time of situation awareness questions as the between-subjects conditions. Five road and traffic scenarios comprised the within-subjects part of the design. Subjects who received haptic cues had a higher number of correct responses to the situation awareness questions and looked up at the simulator screen fewer times than those who were not provided cues. Subjects did not find the cues to be disruptive and gave good satisfaction scores to the haptic device. Additionally, subjects across all conditions seemed to have performed equally well in playing Fruit Ninja. It appears that haptic cuing can maintain drivers' situation awareness during automated driving while drivers are engaged in a secondary task. Practical implications of these findings for implementing haptic cues in autonomous vehicles are also discussed.

cs.HC↗

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.

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arXiv2025

Galactification: painting galaxies onto dark matter only simulations using a transformer-based model

Connecting the formation and evolution of galaxies to the large-scale structure is crucial for interpreting cosmological observations. While hydrodynamical simulations accurately model the correlated properties of galaxies, they are computationally prohibitive to run over volumes that match modern surveys. We address this by developing a framework to rapidly generate mock galaxy catalogs conditioned on inexpensive dark-matter-only simulations. We present a multi-modal, transformer-based model that takes 3D dark matter density and velocity fields as input, and outputs a corresponding point cloud of galaxies with their physical properties. We demonstrate that our trained model faithfully reproduces a variety of galaxy summary statistics and correctly captures their variation with changes in the underlying cosmological and astrophysical parameters, making it the first accelerated forward model to capture all the relevant galaxy properties, their full spatial distribution, and their conditional dependencies in hydrosimulations.

astro-ph.CO↗

arXiv2025

Symbolic Emulators for Cosmology: Accelerating Cosmological Analyses Without Sacrificing Precision

In cosmology, emulators play a crucial role by providing fast and accurate predictions of complex physical models, enabling efficient exploration of high-dimensional parameter spaces that would be computationally prohibitive with direct numerical simulations. Symbolic emulators have emerged as promising alternatives to numerical approaches, delivering comparable accuracy with significantly faster evaluation times. While previous symbolic emulators were limited to relatively narrow prior ranges, we expand these to cover the parameter space relevant for current cosmological analyses. We introduce approximations to hypergeometric functions used for the $\Lambda$CDM comoving distance and linear growth factor which are accurate to better than 0.001% and 0.05%, respectively, for all redshifts and for $\Omega_{\rm m} \in [0.1, 0.5]$. We show that integrating symbolic emulators into a Dark Energy Survey-like $3\times2$pt analysis produces cosmological constraints consistent with those obtained using standard numerical methods. Our symbolic emulators offer substantial improvements in speed and memory usage, demonstrating their practical potential for scalable, likelihood-based inference.

astro-ph.CO↗

arXiv2025

Comparison of Halo Model and Simulation Predictions for Projected-Field Kinematic Sunyaev-Zel'dovich Cross-Correlations

The kinematic Sunyaev-Zel'dovich (kSZ) effect in the cosmic microwave background (CMB) is a powerful probe of gas physics and large-scale structure (LSS) in our universe. We consider the "projected-field" kSZ estimator, which involves cross-correlating a foreground-cleaned, filtered, squared CMB temperature map with an LSS tracer, and requires no individual tracer redshifts. We compare $\verb|class_sz|$ halo model calculations of projected-field kSZ cross-correlations with measurements of these signals from the Websky numerical simulations. We cross-correlate halo density maps from Websky with various CMB secondary signals. We first validate our halo model by comparing its predictions for thermal SZ (tSZ) and patchy screening ($\tau$) cross-correlations to measurements of these signals from Websky. We consider three different halo redshift ranges in our comparisons. We also construct our own kSZ, tSZ, and $\tau$ maps to validate the form of the relevant profiles. Following the tSZ and $\tau$ validation, we compare projected-field kSZ calculations between the halo model and the simulations. We use filters constructed for $\textit{Planck}$ and the Simons Observatory (SO) to assess the accuracy of the halo-model kSZ predictions for experiments of differing sensitivity. Overall, we find good agreement, particularly at $\textit{Planck}$ sensitivity. However, we find an $\approx$ 20$\%$ difference between our halo model and the simulations for SO, which significantly exceeds the predicted error bars. We note that our halo model includes only the dominant expected term in the projected-field kSZ signal; the magnitude of the difference between our model and the simulations is consistent with previous predictions for terms arising from other contractions in the theory calculation. These terms will need to be included to obtain unbiased inference from upcoming projected-field kSZ measurements.

astro-ph.CO↗

arXiv2025

Testing halo models for constraining astrophysical feedback with multi-probe modeling: I. 3D Power spectra and mass fractions

Upcoming Stage-IV surveys will deliver measurements of distribution of matter with unprecedented precision, demanding highly accurate theoretical models for cosmological parameter inference. A major source of modeling uncertainty lies in astrophysical processes associated with galaxy formation and evolution, which remain poorly understood. Probes such as the thermal and kinematic Sunyaev-Zel'dovich effects, X-rays, and dispersion measure from fast radio bursts offer a promising avenue for mapping the distribution and thermal properties of cosmic baryons. A unified analytical framework capable of jointly modeling these observables is essential for fully harnessing the complementary information while mitigating probe-specific systematics. In this work, we present a detailed assessment of existing analytical models, which differ in their assumptions and prescriptions for simultaneously describing the distribution of matter and baryons in the universe. Using the Magneticum hydrodynamical simulation, we test these models by jointly analyzing the 3D auto- and cross-power spectra of the matter and baryonic fields that underpin the above probes. We find that all models can reproduce the power spectra at sub-percent to few-percent accuracy, depending on the tracer combination and number of free parameters. Their ability to recover underlying halo properties, such as the evolution of gas abundance and thermodynamic profiles with halo mass, varies considerably. Our results suggest that these models require further refinement and testing for reliable interpretation of multi-wavelength datasets.

astro-ph.CO↗

arXiv2025

CLASS_SZ II: Notes and Examples of Fast and Accurate Calculations of Halo Model, Large Scale Structure and Cosmic Microwave Background Observables

These notes are very much work-in-progress and simply intended to showcase, in various degrees of details (and rigour), some of the cosmology calculations that class_sz can do. We describe the class_sz code in C, Python and Jax. Based on the Boltzmann code class, it can compute a wide range of observables relevant to current and forthcoming CMB and Large Scale Structure surveys. This includes galaxy shear and clustering, CMB lensing, thermal and kinetic Sunyaev and Zeldovich observables, Cosmic Infrared Background, cross-correlations and three-point statistics. Calculations can be done either within the halo model or the linear bias model. For standard $\Lambda$CDM cosmology and extensions, class_sz uses high-accuracy cosmopower emulators of the CMB and matter power spectrum to accelerate calculations. With this, along with efficient numerical integration routines, most class_sz output can be obtained in less than 500 ms (CMB $C_\ell$'s or matter $P(k)$ take $\mathcal{O}(1\mathrm{ms})$), allowing for fast or ultra-fast parameter inference analyses. Parts of the calculations are "jaxified", so the software can be integrated into differentiable pipelines.

astro-ph.CO↗

arXiv2025

Fisher Score Matching for Simulation-Based Forecasting and Inference

We propose a method for estimating the Fisher score--the gradient of the log-likelihood with respect to model parameters--using score matching. By introducing a latent parameter model, we show that the Fisher score can be learned by training a neural network to predict latent scores via a mean squared error loss. We validate our approach on a toy linear Gaussian model and a cosmological example using a differentiable simulator. In both cases, the learned scores closely match ground truth for plausible data-parameter pairs. This method extends the ability to perform Fisher forecasts, and gradient-based Bayesian inference to simulation models, even when they are not differentiable; it therefore has broad potential for advancing cosmological analyses.

astro-ph.CO↗

arXiv2025

Deciphering Baryonic Feedback from ACT tSZ Galaxy Clusters

The next generation of cosmology surveys will probe the matter distribution of the universe to unparalleled precision. To match this level of precision in cosmological parameter estimation, we need to use information at small scales of $\sim$ 1 Mpc, which requires an accurate model of baryonic feedback. In this paper, we employ the Dark Matter + Baryon (DMB) model, a flexible halo model that is well-fit to various hydrodynamical simulations, to extract information on baryonic feedback from galaxy cluster observables. Using a sample of thermal Sunyaev-Zeldovich (tSZ) selected galaxy clusters from the Atacama Cosmology Telescope (ACT) - with masses calibrated via weak lensing from the Dark Energy Survey (DES) - we develop a robust end-to-end pipeline that directly models the calibrated observables. Our analysis demonstrates that the tSZ Y-M relation can constrain several DMB model parameters, providing key insights into baryonic feedback effects on cosmic shear at the several percent level. We find a preference for intermediate to strong levels of feedback, which is both consistent with several hydrodynamic simulations and competitive with similar analyses performed on complementary probes. Finally, we discuss the implications of our results in the context of current and upcoming cosmic shear surveys.

astro-ph.CO↗

arXiv2025

Minimizing Contaminant Leakage in Internal Linear Combination Maps Using a Data-Driven Approach

The thermal Sunyaev-Zel'dovich (tSZ) effect, the inverse-Compton scattering of cosmic microwave background (CMB) photons off high-energy electrons, is a powerful probe of hot, ionized gas in the Universe. It is often measured via cross-correlations of CMB data with large-scale structure (LSS) tracers to constrain gas physics and improve cosmological constraints. The largest source of bias to these measurements is the leakage of poorly understood thermal dust emission from star-forming galaxies -- the cosmic infrared background (CIB) -- into the tSZ maps. This CIB contamination is difficult to clean via multifrequency component separation methods, such as internal linear combination (ILC), due to uncertainty in its spectral energy distribution (SED), which exhibits spatial and line-of-sight variation and decorrelation. Thus, improved ILC-based techniques have been developed to null ("deproject") both the CIB and its first moment with respect to the emissivity index $\beta$ in order to robustly remove the CIB despite the lack of first-principles knowledge of its SED. While decreasing the bias, such procedures can significantly increase the noise in the resulting ILC maps. In this paper, we develop a data-driven algorithm for determining the optimal CIB SED to deproject when measuring a tSZ-LSS cross-correlation, obviating the need to deproject the first moment in the ILC map used for such a measurement. Our method gives an unbiased cross-correlation with increased signal-to-noise. We demonstrate its efficacy on simulations, finding a 60% improvement in the signal-to-noise ratio for an example tSZ cross-correlation with a halo sample at redshifts $0.8 < z < 1.8$, as compared to moment deprojection approaches. Though used here for CIB removal in tSZ cross-correlations, our method is broadly applicable to minimizing contaminant leakage in ILC maps. Our code is available in CIB-deproj.

astro-ph.CO↗

arXiv2025

The effect of intrinsic alignments on weak lensing statistics in hydrodynamical simulations

The next generation of weak gravitational lensing surveys has the potential to place stringent constraints on cosmological parameters. However, their analysis is limited by systematics such as the intrinsic alignments of galaxies, which alter weak lensing convergence and can lead to biases in cosmological parameter estimations. In this work, we investigate the impact of intrinsic alignments on non-Gaussian statistics of the weak lensing field using galaxy shapes derived from the IllustrisTNG hydrodynamical simulation. We create two catalogs of ray-traced convergence maps: one that includes the measured intrinsic shape of each galaxy and another where all galaxies are randomly rotated to eliminate intrinsic alignments. We compare an exhaustive list of weak lensing statistics between the two catalogs, including the shear-shear correlation function, the map-level angular power spectrum, one-point, peak count, minimum distribution functions, and Minkowski functionals. For each statistic, we assess the level of statistical distinguishability between catalogs for a set of future survey angular areas. Our results reveal strong small-scale correlation in the alignment of galaxies and statistically significant boosts in weak lensing convergence in both positive and negative directions for high-significance peaks and minimums, respectively. Weak lensing analyses utilizing non-Gaussian statistics must account for intrinsic alignments to avoid significantly compromised cosmological inferences.

astro-ph.CO↗

arXiv2024

syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy

Current and future large scale structure surveys aim to constrain the neutrino mass and the equation of state of dark energy. We aim to construct accurate and interpretable symbolic approximations to the linear and nonlinear matter power spectra as a function of cosmological parameters in extended $\Lambda$CDM models which contain massive neutrinos and non-constant equations of state for dark energy. This constitutes an extension of the syren-halofit emulators to incorporate these two effects, which we call syren-new (SYmbolic-Regression-ENhanced power spectrum emulator with NEutrinos and $W_0-w_a$). We also obtain a simple approximation to the derived parameter $\sigma_8$ as a function of the cosmological parameters for these models. Our results for the linear power spectrum are designed to emulate CLASS, whereas for the nonlinear case we aim to match the results of EuclidEmulator2. We compare our results to existing emulators and $N$-body simulations. Our analytic emulators for $\sigma_8$, the linear and nonlinear power spectra achieve root mean squared errors of 0.1%, 0.3% and 1.3%, respectively, across a wide range of cosmological parameters, redshifts and wavenumbers. We verify that emulator-related discrepancies are subdominant compared to observational errors and other modelling uncertainties when computing shear power spectra for LSST-like surveys. Our expressions have similar accuracy to existing (numerical) emulators, but are at least an order of magnitude faster, both on a CPU and GPU. Our work greatly improves the accuracy, speed and range of applicability of current symbolic approximations to the linear and nonlinear matter power spectra. We provide publicly available code for all symbolic approximations found.

astro-ph.CO↗

arXiv2024

Teaching dark matter simulations to speak the halo language

We develop a transformer-based conditional generative model for discrete point objects and their properties. We use it to build a model for populating cosmological simulations with gravitationally collapsed structures called dark matter halos. Specifically, we condition our model with dark matter distribution obtained from fast, approximate simulations to recover the correct three-dimensional positions and masses of individual halos. This leads to a first model that can recover the statistical properties of the halos at small scales to better than 3% level using an accelerated dark matter simulation. This trained model can then be applied to simulations with significantly larger volumes which would otherwise be computationally prohibitive with traditional simulations, and also provides a crucial missing link in making end-to-end differentiable cosmological simulations. The code, named GOTHAM (Generative cOnditional Transformer for Halo's Auto-regressive Modeling) is publicly available at \url{https://github.com/shivampcosmo/GOTHAM}.

astro-ph.CO↗

arXiv2024

Understanding posterior projection effects with normalizing flows

Many modern applications of Bayesian inference, such as in cosmology, are based on complicated forward models with high-dimensional parameter spaces. This considerably limits the sampling of posterior distributions conditioned on observed data. In turn, this reduces the interpretability of posteriors to their one- and two-dimensional marginal distributions, when more information is available in the full dimensional distributions. We show how to learn smooth and differentiable representations of posterior distributions from their samples using normalizing flows, which we train with an added evidence error loss term, to improve accuracy in multiple ways. Motivated by problems from cosmology, we implement a robust method to obtain one and two-dimensional posterior profiles. These are obtained by optimizing, instead of integrating, over other parameters, and are thus less prone than marginals to so-called projection effects. We also demonstrate how this representation provides an accurate estimator of the Bayesian evidence, with log error at the 0.2 level, allowing accurate model comparison. We test our method on multi-modal mixtures of Gaussians up to dimension 32 before applying it to simulated cosmology examples. Our code is publicly available at https://github.com/mraveri/tensiometer.

astro-ph.IM↗

arXiv2024

CHARM: Creating Halos with Auto-Regressive Multi-stage networks

To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations that evolve particles under gravity by estimating particle-particle interactions (N-body simulations) are computationally expensive and prohibitive to scale to the large volumes and resolutions necessary for the upcoming datasets. Moreover, modeling the distribution of galaxies typically involves identifying virialized dark matter halos, which is also a time- and memory-consuming process for large N-body simulations, further exacerbating the computational cost. In this study, we introduce CHARM, a novel method for creating mock halo catalogs by matching the spatial, mass, and velocity statistics of halos directly from the large-scale distribution of the dark matter density field. We develop multi-stage neural spline flow-based networks to learn this mapping at redshift z=0.5 directly with computationally cheaper low-resolution particle mesh simulations instead of relying on the high-resolution N-body simulations. We show that the mock halo catalogs and painted galaxy catalogs have the same statistical properties as obtained from $N$-body simulations in both real space and redshift space. Finally, we use these mock catalogs for cosmological inference using redshift-space galaxy power spectrum, bispectrum, and wavelet-based statistics using simulation-based inference, performing the first inference with accelerated forward model simulations and finding unbiased cosmological constraints with well-calibrated posteriors. The code was developed as part of the Simons Collaboration on Learning the Universe and is publicly available at \url{https://github.com/shivampcosmo/CHARM}.

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.

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