arXiv subjects

Katrin Heitmann

Publications and source records attributed to Katrin Heitmann.

At least 19 recordsLinked to original sources

arXiv2026

Investigating The Effects of Early Dark Energy on Large-scale Structure Within the EDENS Suite

Early Dark Energy (EDE) models have been suggested as a possible solution to the so-called Hubble Tension, a discrepancy of the measurement of the Hubble constant at early and late times. In this paper, we investigate the effects of EDE on large-scale structure probes of cosmology via the EDENS (Early Dark Energy N-body Simulations) suite. The EDENS suite extends the reach of available EDE simulations considerably by adding volume and resolution. We derive several key metrics, such as the halo mass function, the nonlinear power spectrum, and the concentration-mass relation. Furthermore, we implement a halo occupation distribution model to populate the simulations with synthetic galaxies. This allows us to measure the galaxy-galaxy correlation function and galaxy bias. We choose an EDE model that is consistent with observations across several probes and allows for the increase of the present day value of the Hubble constant to resolve the Hubble tension. This model adds three more parameters to the standard $\Lambda$CDM model. Additionally, it requires small shifts in the best-fit $\Lambda$CDM cosmological parameters to accommodate existing observational constraints. We find significant differences between the standard $\Lambda$CDM model and the EDE model, suggesting that some of our chosen metrics may allow us to distinguish EDE from $\Lambda$CDM, and future observations should help further constrain possible cosmological models. We release outputs from our simulations via the OpenCosmo data portal.

astro-ph.CO↗

arXiv2026

OpenCosmo: Community Portal and Analysis Framework for Flagship Cosmological Simulations

Cosmology is a precision observational science, and large simulations are necessary components of many analyses. These simulations are computationally expensive and produce massive, complex datasets; sharing them widely -- to enable further explorations, comparison with observations, and communication with general audiences -- is crucial to realizing their scientific value. In this paper, we introduce the OpenCosmo project, which provides flexible access to, and analysis of, flagship cosmological simulations performed with HACC. A web-based portal (https://opencosmo.science) serves custom subsets -- halo catalogs, profiles, particles, galaxy catalogs, and lightcone catalogs and maps -- from simulations including the two-trillion-particle Frontier-E gravity-only run, Last Journey, Discovery, and a 64-member hydrodynamic suite. A companion Python toolkit analyzes the returned data and scales without modification from laptop-sized subsets to full simulations on supercomputers. OpenCosmo supports multiple levels of interaction, from browser-based search and download to programmatic and AI-agent-driven workflows, by integrating with existing high-performance computing and data infrastructure. Its architecture, built on Globus services, provides a scalable and adaptable framework that can be extended to other scientific domains seeking to couple data sharing with computational capability.

astro-ph.IM↗

arXiv2026

$4\times3$ Point Correlation Functions in Galaxy Surveys: Impact of Baryonic Feedback

We investigate the impact of baryonic feedback on two-point and three-point correlation functions (2PCFs and 3PCFs hereafter, respectively) involving galaxy density fields (g) and weak lensing shear fields (G), from simulated photometric catalogs of galaxies. Specifically, we baryonify high-resolution simulation using a baryonic correction model (BCM) and explore the consequences down to sub-arcminute (arcmin) scales, varying two model parameters with the largest impact on our probes: $M_{\rm c}$, which governs the amount of gas expelled beyond the halo boundary, and $\theta_{\rm ej}$, which encodes the maximal ejection radius relative to halo boundary. We create lensing maps and galaxy catalogs assuming survey properties of the upcoming Year-10 data for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), and investigate the impact of baryonic feedback on the observed correlations, including the galaxy--galaxy--shear (ggG) and the galaxy--shear--shear (gGG) 3PCFs, which are measured, for the first time from simulations, with \textsc{TreeCorr}. Focusing on equilateral 3PCFs, we find that small scales are more heavily affected by baryonic effects than the corresponding 2PCFs, by up to 90 percent depending on the probe, redshift and BCM model. The galaxy--galaxy--galaxy (ggg) 3PCF is significantly affected at scales smaller than about 4 arcmin; a similar effect occurs at 10 arcmin for the ggG 3PCF, at 40 arcmin for the gGG 3PCF, and at about a degree for the shear--shear--shear (GGG) 3PCF. These four three-point statistics, which are collectively referred to as the $4\times3$PCFs, can be used at large scales to robustly constrain cosmological parameters. At smaller scales, their enhanced sensitivity to baryonic effects provides valuable leverage for constraining the BCM parameters and supplying informative priors. [Abridged]

astro-ph.CO↗

arXiv2026

Preserving Clusters in Error-Bounded Lossy Compression of Scientific Particle Data

Scientific particle simulations in cosmology, molecular dynamics, and fluid dynamics produce large-scale datasets whose storage, movement, and analysis increasingly rely on lossy compression. However, existing compressors typically bound only pointwise position errors, providing no guarantee on the fidelity of structures derived from particle coordinates, such as single-linkage clustering (also known as Friends-of-Friends algorithm), where clusters are connected components of a proximity graph formed by linking particle pairs within a distance threshold. Even small coordinate perturbations near this threshold can break true links or create false links, thereby splitting or merging entire clusters. We propose a compressor-independent correction technique for preserving single-linkage cluster membership under lossy compression. Our method operates on reconstructed outputs from off-the-shelf compressors such as SZ3, ZFP, Draco, and LCP, and stores a compact corrective edit stream. Our key observation is that cluster-membership queries depend on connected components rather than the complete set of proximity links. Based on this observation, we introduce three constraint-selection modes, vulnerable-pair, safe-component, and halo-forest, that progressively reduce the constraints enforced during correction. Projected gradient descent then corrects the reconstructed coordinates to eliminate the selected violations while respecting the original pointwise error bound. Experiments on cosmology, molecular dynamics, and fluid dynamics datasets with single-GPU and distributed-memory implementations show that our method preserves cluster membership while improving compression ratio by up to 4$\times$ and maintains competitive end-to-end throughput compared to the same base compressors configured with sufficiently tight error bounds to preserve clustering.

cs.LG↗

arXiv2026

Emulator-Based Inference of Cosmological Subgrid Models

The formation of structure in the Universe at large scales is dominated by gravity, with baryonic physics becoming significant at $\sim{\rm Mpc}$ scales. To capture the impact of baryonic physics, cosmological simulations must model gas dynamics and a host of relevant astrophysical processes. A recent extension of the Hardware/Hybrid Accelerated Cosmology Code (HACC) couples its gravity solver with a modern smoothed particle hydrodynamics method. This extension incorporates sub-resolution models for chemical enrichment, black hole and star formation, AGN kinetic and thermal feedback, supernova-driven feedback, galactic winds, and metal-line cooling. We present an inference framework based on high-fidelity emulators to aid in model calibration against observational targets, e.g., the galaxy stellar mass function, radial gas density profiles, and the cluster gas fraction. The emulators are trained on simulation suites comprising 64 boxes with side-length $128\,h^{-1}$Mpc and 16 boxes with side-length $256\,h^{-1}$Mpc with $2\times 512^3$ and $2\times 1024^3$ particles, respectively. Our analysis reveals two distinct AGN kinetic feedback modes -- a low-feedback mode yielding strong agreement with the observed radial gas density profiles of massive X-ray clusters, and a high-feedback mode providing a better fit to cluster gas fraction data, but systematically underestimating gas densities in inner regions.

astro-ph.GA↗

arXiv2025

Modeling Galaxy Formation in Cosmological Simulations with CRK-HACC

Self-consistently modeling baryonic effects in survey-scale cosmological simulations has become increasingly important as the diversity, precision, and statistical reach of modern observations continue to improve. The advent of exascale computing now enables a new generation of simulations that couple these physical processes across full-sky volumes with excellent statistical sampling of large-scale structure tracers such as galaxies, groups, and clusters. To support these efforts, we extend the CRK-HACC framework, a GPU-accelerated cosmological hydrodynamics code, with a suite of astrophysical subgrid models that simulate radiative cooling, star formation, stellar evolution, and AGN feedback within a numerically robust formulation optimized for scalability on modern exascale architectures. The models were selected and calibrated to reproduce observed galaxy stellar mass functions over the redshift range $0 < z < 2$ and cluster populations probed by cosmological surveys, capturing the large-scale baryonic evolution relevant for multi-wavelength, cross-correlated analyses. We describe the implementation and calibration of these models and demonstrate their consistency with observed galaxy population statistics and modern hydrodynamic simulations, establishing the baseline for exascale efforts that extend this framework to survey-scale volumes.

astro-ph.CO↗

arXiv2025

Benchmarking AI-evolved cosmological structure formation

The potential of deep learning-based image-to-image translations has recently attracted significant attention. One possible application of such a framework is as a fast, approximate alternative to cosmological simulations, which would be particularly useful in various contexts, including covariance studies, investigations of systematics, and cosmological parameter inference. To investigate different aspects of learning-based cosmological mappings, we choose two approaches for generating suitable cosmological matter fields as datasets: a simple analytical prescription provided by the Zel'dovich approximation, and a numerical N-body method using the Particle-Mesh approach. The evolution of structure formation is modeled using U-Net, a widely employed convolutional image translation framework. Because of the lack of a controlled methodology, validation of these learned mappings requires multiple benchmarks beyond simple visual comparisons and summary statistics. A comprehensive list of metrics is considered, including higher-order correlation functions, conservation laws, topological indicators, and statistical independence of density fields. We find that the U-Net approach performs well only for some of these physical metrics, and accuracy is worse at increasingly smaller scales, where the dynamic range in density is large. By introducing a custom density-weighted loss function during training, we demonstrate a significant improvement in the U-Net results at smaller scales. This study provides an example of how a family of physically motivated benchmarks can, in turn, be used to fine-tune optimization schemes -- such as the density-weighted loss used here -- to significantly enhance the accuracy of scientific machine learning approaches by focusing attention on relevant features.

astro-ph.CO↗

arXiv2025

Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability

Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific partnership, detailed gas dynamics, along with a host of astrophysical effects, must be treated self-consistently with gravity for end-to-end modeling of structure formation. As an important step on this roadmap, exascale computing enables simulations that span survey-scale volumes while incorporating key subgrid processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for the extreme scalability requirements set by modern cosmological surveys. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACC executed Frontier-E: a four trillion particle full-sky simulation, over an order of magnitude larger than previous efforts. The run achieved 513.1 PFLOPs peak performance, processing 46.6 billion particles per second and writing more than 100 PB of data in just over one week of runtime.

cs.DC↗

arXiv2025

Bayesian Deep Gaussian Processes for Correlated Functional Data: A Case Study in Cosmological Matter Power Spectra

Understanding the structure of our universe and the distribution of matter is an area of active research. As cosmological surveys grow in complexity, the development of emulators to efficiently and effectively predict matter power spectra is essential. We are particularly motivated by the Mira-Titan Universe simulation suite that, for a specified cosmological parameterization (termed a "cosmology"), provides multiple response curves of various fidelities, including correlated functional realizations. Our objective is two-fold. First, we estimate the underlying matter power spectra, with appropriate uncertainty quantification (UQ), from all of the provided curves. To this end, we propose a novel Bayesian deep Gaussian process (DGP) hierarchical model which synthesizes all the simulation information to estimate the underlying matter power spectra while providing effective UQ. Our model extends previous work on Bayesian DGPs from scalar responses to correlated functional outputs. Second, we leverage our predicted power spectra from various cosmologies in order to accurately predict the entire matter power spectra for an unobserved cosmology. For this task, we use basis function representations of the functional spectra to train a separate Gaussian process emulator. Our method performs well in synthetic exercises and against the benchmark cosmological emulator (Cosmic Emu).

stat.AP↗

arXiv2025

Illuminating the Physics of Dark Energy with the Discovery Simulations

In this paper, we present the Discovery simulations: a new pair of high-resolution N-body simulations motivated by the DESI Y1 BAO cosmological constraints on dark energy. The Discovery simulations were run with identical initial conditions, and differ only in their cosmological parameters. The first simulation is based on a flat $\Lambda\mathrm{CDM}$ cosmology, while the second is based on a $w_0 w_a\mathrm{CDM}$ cosmology, with particular parameter values chosen based on the DESI analysis which includes constraints from BAO with CMB priors. Both simulations evolve $6720^3$ particles in a box with a side length of $L_\mathrm{box} = 1.5$ Gpc, leading to a mass resolution of $\sim4 \times 10^8$ $\mathrm{M}_{\odot}$ in each simulation. In this work we demonstrate the impact of the $w_0 w_a\mathrm{CDM}$ cosmology on the matter power spectrum, halo mass function, and halo mass accretion rate. We also populate halos with galaxies using a novel forward model for in-situ star formation, and examine the way in which changes to cosmology manifest as changes in star formation history. The Discovery simulations provide a testbed for alternative cosmological probes that may offer additional constraining power beyond BAO, such as higher-order summary statistics and observables in the nonlinear regime. Halo catalogs from the Discovery simulations are publicly available and can be downloaded from the HACC Simulation Data Portal.

astro-ph.CO↗

arXiv2024

Bayesian "Deep" Process Convolutions: An Application in Cosmology

The nonlinear matter power spectrum in cosmology describes how matter density fluctuations vary with scale in the universe, providing critical insights into large-scale structure formation. The matter power spectrum includes both smooth regions and highly oscillatory features. Cosmologists rely on noisy, multi-resolution realizations of large N-body simulations to study these phenomena, which require appropriate smoothing techniques to learn about underlying structures. We introduce a Bayesian Deep Process Convolution (DPC) model that flexibly adapts its smoothness parameter across the input space, enabling it to capture both smooth and variable structure within a single framework. The DPC model leverages common patterns across related functions to improve estimation in regions with sparse data. Compared to existing methods, the DPC model offers superior accuracy and uncertainty quantification in simulated data, and qualitatively superior performance with the cosmological data. This methodology will be useful in cosmology and other fields requiring flexible modeling of smooth nonstationary surfaces.

astro-ph.CO↗

arXiv2024

Exploring the Core-galaxy Connection

Halo core tracking is a novel concept designed to efficiently follow halo substructure in large simulations. We have recently developed this concept in gravity-only simulations to investigate the galaxy-halo connection in the context of empirical and semi-analytic models. Here, we incorporate information from hydrodynamics simulations, with an emphasis on establishing a connection between cores and galaxies. We compare cores across gravity-only, adiabatic hydrodynamics, and subgrid hydrodynamics simulations with the same initial phases. We demonstrate that cores are stable entities whose halo-centric radial profiles match across the simulations. We further develop a methodology that uses merging and infall mass cuts to group cores in the hydrodynamics simulation, creating on average, a one-to-one match to corresponding galaxies. We apply this methodology to cores from the gravity-only simulation, thus creating a proxy for galaxies which approximate the populations from the hydrodynamics simulation. Our results pave the way to incorporate inputs from smaller-scale hydrodynamics simulations directly into large-scale gravity-only runs in a principled manner.

astro-ph.CO↗

arXiv2024

The New Worlds Simulations: Large-scale Simulations across Three Cosmologies

In this paper we describe the set of ``New Worlds Simulations'', three very large cosmology simulations, Qo'noS, Vulcan, and Ferenginar, that were carried out on the Summit supercomputer with the Hardware/Hybrid Cosmology Code, HACC. The gravity-only simulations follow the evolution of structure in the Universe by each employing 12,288^3 particles in (3 Gpc/h)^3 volumes, leading to a mass resolution of m_p~10^9 Msun/h. The simulations cover three different cosmologies, one LambdaCDM model, consistent with measurements from Planck, one simulation with massive neutrinos, and one simulation with a varying dark energy equation of state. All simulations have the same phases to allow a detailed comparison of the results and the investigation of the impact of different cosmological parameters. We present measurements of some basic statistics, such as matter power spectra, correlation function, halo mass function and concentration-mass relation and investigate the differences due to the varying cosmologies. Given the large volume and high resolution, these simulations provide excellent bases for creating synthetic skies. A subset of the data is made publicly available as part of this paper.

astro-ph.CO↗

arXiv2024

SPHEREx: NASA's Near-Infrared Spectrophotmetric All-Sky Survey

SPHEREx, the Spectro-Photometer for the History of the Universe, Epoch of Reionization, and ices Explorer, is a NASA MIDEX mission planned for launch in 2024. SPHEREx will carry out the first all-sky spectral survey at wavelengths between 0.75 micron and 5 micron with spectral resolving power ~40 between 0.75 and 3.8 micron and ~120 between 3.8 and 5 micron At the end of its two-year mission, SPHEREx will provide 0.75-to-5 micron spectra of each 6.2"x6.2" pixel on the sky - 14 billion spectra in all. This paper updates an earlier description of SPHEREx presenting changes made during the mission's Preliminary Design Phase, including a discussion of instrument integration and test and a summary of the data processing, analysis, and distribution plans.

astro-ph.IM↗

arXiv2023

Simulating image coaddition with the Nancy Grace Roman Space Telescope: II. Analysis of the simulated images and implications for weak lensing

One challenge for applying current weak lensing analysis tools to the Nancy Grace Roman Space Telescope is that individual images will be undersampled. Our companion paper presented an initial application of Imcom - an algorithm that builds an optimal mapping from input to output pixels to reconstruct a fully sampled combined image - on the Roman image simulations. In this paper, we measure the output noise power spectra, identify the sources of the major features in the power spectra, and show that simple analytic models that ignore sampling effects underestimate the power spectra of the coadded noise images. We compute the moments of both idealized injected stars and fully simulated stars in the coadded images, and their 1- and 2-point statistics. We show that the idealized injected stars have root-mean-square ellipticity errors (1 - 6) x 10-4 per component depending on the band; the correlation functions are >= 2 orders of magnitude below requirements, indicating that the image combination step itself is using a small fraction of the overall Roman 2nd moment error budget, although the 4th moments are larger and warrant further investigation. The stars in the simulated sky images, which include blending and chromaticity effects, have correlation functions near the requirement level (and below the requirement level in a wide-band image constructed by stacking all 4 filters). We evaluate the noise-induced biases in the ellipticities of injected stars, and explain the resulting trends with an analytical model. We conclude by enumerating the next steps in developing an image coaddition pipeline for Roman.

astro-ph.IM↗

arXiv2023

Simulating image coaddition with the Nancy Grace Roman Space Telescope: I. Simulation methodology and general results

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as Imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired "target" point spread function (PSF). We present here an initial application of Imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that Imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the "leakage"), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moir\'e patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper ("Paper II") explores the implications for weak lensing analyses.

astro-ph.IM↗

arXiv2023

Galaxy Clustering in the Mira-Titan Universe I: Emulators for the redshift space galaxy correlation function and galaxy-galaxy lensing

We construct accurate emulators for the projected and redshift space galaxy correlation functions and excess surface density as measured by galaxy-galaxy lensing, based on Halo Occupation Distribution (HOD) modeling. Using the complete Mira-Titan suite of 111 $N$-body simulations, our emulators vary over eight cosmological parameters and include the effects of neutrino mass and dynamical dark energy. We demonstrate that our emulators are sufficiently accurate for the analysis of the BOSS DR12 CMASS galaxy sample over the range 0.5 < r < 50 Mpc/h. Furthermore, we show that our emulators are capable of recovering unbiased cosmological constraints from realistic mock catalogs over the same range. Our mock catalog tests show the efficacy of combining small scale galaxy-galaxy lensing with redshift space clustering and that we can constrain the growth rate and \sigma_8 to 7% and 4.5% respectively for a CMASS-like sample using only the measurements covered by our emulator. With the inclusion of a CMB prior on H_0, this reduces to a 2% measurement on the growth rate.

astro-ph.CO↗

arXiv2023

Modeling the Galaxy Distribution in Clusters using Halo Cores

The galaxy distribution in dark matter-dominated halos is expected to approximately trace the details of the underlying dark matter substructure. In this paper we introduce halo `core-tracking' as a way to efficiently follow the small-scale substructure in cosmological simulations and apply the technique to model the galaxy distribution in observed clusters. The method relies on explicitly tracking the set of particles identified as belonging to a halo's central density core, once a halo has attained a certain threshold mass. The halo cores are then followed throughout the entire evolution of the simulation. The aim of core-tracking is to simplify substructure analysis tasks by avoiding the use of subhalos and, at the same time, to more easily account for the so-called ``orphan'' galaxies, which have lost substantial dark mass due to tidal stripping. We show that simple models based on halo cores can reproduce the number and spatial distribution of galaxies found in optically-selected clusters in the Sloan Digital Sky Survey. We also discuss future applications of the core-tracking methodology in studying the galaxy-halo connection.

astro-ph.CO↗