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DOE OSTI2024

CTA and SWGO can discover Higgsino dark matter annihilation

Thermal Higgsino dark matter (DM), with a mass near 1.1 TeV, is one of the most well-motivated and untested DM candidates. Leveraging recent hydrodynamic cosmological simulations that give DM density profiles in Milky Way analog galaxies we show that the linelike gamma-ray signal predicted from Higgsino annihilation in the Galactic Center could be detected at high significance with the upcoming Cherenkov Telescope Array (CTA) and Southern Wide-field Gamma-ray Observatory (SWGO) for all but the most pessimistic DM profiles. We perform the most sensitive search to-date for the linelike signal using 15 years of data from the Fermi Large Area Telescope, coming within an order one factor of the necessary sensitivity to detect the Higgsino for some Milky Way analog DM density profiles. We show that H.E.S.S. has subleading sensitivity relative to Fermi for the Higgsino at present. In contrast, we analyze H.E.S.S. inner Galaxy data for the thermal wino model with a mass near 2.8 TeV; we find no evidence for a DM signal and exclude the wino by over a factor of two in cross section for all DM profiles considered. In the process, we identify and attempt to correct what appears to be an inconsistency in previous H.E.S.S. inner Galaxy analyses for DM annihilation related to the analysis effective area, which may weaken the DM cross-section sensitivity claimed in those works by around an order of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Observed Evolution of the Stellar Mass–Halo Mass Relation for Brightest Central Galaxies

We quantify evolution in the cluster-scale stellar mass–halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range 0.03 ≤ z ≤ 0.60. The precision on the inferred SMHM parameters is improved by including the magnitude gap (m gap ) between the BCG and fourth-brightest cluster member (M14) as a third parameter in the SMHM relation. At fixed halo mass, accounting for m gap , through a stretch parameter, reduces the SMHM relation's intrinsic scatter. To explore this redshift range, we use clusters, BCGs, and cluster members identified using the Sloan Digital Sky Survey C4 and redMaPPer cluster catalogs and the Dark Energy Survey redMaPPer catalog. Through this joint analysis, we detect no systematic differences in BCG stellar mass, m gap , and cluster mass (inferred from richness) between the data sets. We utilize the Pareto function to quantify each parameter's evolution. We confirm prior findings of negative evolution in the SMHM relation's slope (3.5σ), and detect negative evolution in the stretch parameter (4.0σ) and positive evolution in the offset parameter (5.8σ). This observed evolution, combined with the absence of BCG growth, when stellar mass is measured within 50 kpc, suggests that this evolution results from changes in the cluster's m gap . For this to occur, late-term growth must be in the intracluster light surrounding the BCG. We also compare the observed results to IllustrisTNG 300-1 cosmological hydrodynamic simulations and find modest qualitative agreement. However, the simulations lack the evolutionary features detected in the real data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Inferring the Thermal History of the Intergalactic Medium from the Properties of the Hydrogen and Helium Lyα Forest

The filamentary network of intergalactic medium (IGM) gas that gives origin to the Lyα forest in the spectra of distant quasars encodes information on the physics of structure formation and the early thermodynamics of diffuse baryonic material. Here we use a massive suite of more than 400 high-resolution cosmological hydrodynamical simulations run with the Graphics Processing Unit–accelerated code Cholla to study the IGM at high spatial resolution maintained over the entire computational volume. The simulations capture a wide range of possible IGM thermal histories by varying the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei. A statistical comparison of synthetic spectra with the observed 1D flux power spectra of hydrogen at redshifts 2.2 ≤ z ≤ 5.0 and with the helium Lyα opacity at redshifts 2.4 < z < 2.9 tightly constrains the photoionization and photoheating history of the IGM. By leveraging the constraining power of the available Lyα forest data to break model degeneracies, we find that the IGM experienced two main reheating events over 1.2 Gyr of cosmic time. For our best-fit model, hydrogen reionization completes by z R ≈ 6.0 with a first IGM temperature peak of T 0 ≃ 1.3 × 10 4 K and is followed by the reionization of He ii that completes by z R ≈ 3.0 and yields a second temperature peak of T 0 ≃ 1.4 × 10 4 K. We discuss how our results can be used to obtain information on the timing and the sources of hydrogen and helium reionization.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Improved Measurements of Galaxy Star Formation Stochasticity from the Intrinsic Scatter of Burst Indicators

Abstract Measurements of short-timescale star formation variations (i.e., “burstiness” or star formation stochasticity) are integral to our understanding of star formation feedback mechanisms and the assembly of stellar populations in galaxies. We expand upon the work of Broussard et al. by introducing a new analysis of galaxy star formation burstiness that accounts for variations in the Q sg = E B − V stars / E B − V gas distribution, a major confounding factor. We use Balmer decrements from the MOSFIRE Deep Evolution Field (MOSDEF) survey to measure Q sg , which we use to construct mock catalogs from the Santa Cruz Semi-Analytic Models and Mufasa cosmological hydrodynamical simulation based on 3D-HST, Fiber Multi-Object Spectrograph (FMOS)-COSMOS, and MOSDEF galaxies with H α detections. The results of the mock catalogs are compared against observations using the burst indicator η = log 10 ( SFR H α / SFR NUV ) , with the standard deviation of the η distribution indicating burstiness. We find decent agreement between mock and observed η distribution shapes; however, the FMOS-COSMOS and MOSDEF mocks show a systematically low median and scatter in η in comparison to the observations. This work also presents the novel approach of analytically deriving the relationship between the intrinsic scatter in η , scatter added by measurement uncertainties, and observed scatter, resulting in an intrinsic burstiness measurement of 0.06–0.16 dex.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

SAGAbg. II. The Low-mass Star-forming Sequence Evolves Significantly between 0.05 < z < 0.21

The redshift-dependent relation between galaxy stellar mass and star formation rate (SFR), known as the star-forming sequence (SFS), is a key observational yardstick for galaxy assembly. We use the SAGAbg-A sample of background galaxies from the Satellites Around Galactic Analogs (SAGA) Survey to model the low-redshift evolution of the low-mass SFS. The sample is comprised of 23,258 galaxies with Hα-based SFRs spanning 6 < log 10 (M * /[M ⊙ ]) < 10 and z < 0.21 (t < 2.5 Gyr). Although it is common to bin or stack galaxies at z ≲ 0.2 for galaxy population studies, the difference in lookback time between z = 0 and z = 0.21 is comparable to the time between z = 1 and z = 2. We develop a model to account for both the physical evolution of low-mass SFS and the selection function of the SAGA Survey, allowing us to disentangle redshift evolution from redshift-dependent selection effects across the SAGAbg-A redshift range. Our findings indicate significant evolution in the SFS over the last ∼2.5 Gyr, with a rising normalization: $\langle$SRF(M * = 10 8.5 M ⊙ )$\rangle$ (z) = 1.24$^{+0.25}_{–0.23}$z – 1.47$^{+0.03}_{–0.03}$. We also identify the redshift limit at which a static SFS is ruled out at the 95% confidence level, which is z = 0.05 based on the precision of the SAGAbg-A sample. Comparison with cosmological hydrodynamic simulations reveals that some contemporary simulations underpredict the recent evolution of the low-mass SFS. This demonstrates that the recent evolution of the low-mass SFS can provide new constraints on the assembly of the low-mass Universe and highlights the need for improved models in this regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Dwarf Galaxy Number Counts within 25 Mpc: Predictions from Local Group Analogs in TNG50

The modern generation of wide-field galaxy surveys, such as LSST, Euclid, and Roman, will enable studies of dwarf galaxies (10 6 ≤ M * /M ⊙ ≤ 10 9 ) beyond the Local Group (LG) in unprecedented detail. Improved theoretical understanding of this population is necessary to guide these observations, since predictions in this regime are generally limited to specific environments like the LG. We present predictions for the population of dwarf galaxies from the TNG50 run of the IllustrisTNG suite of cosmological hydrodynamical simulations, focusing on the environments within 1 < D/Mpc < 25 of LG analogs at z = 0. In the simulated sample, there are ∼1000 and ∼12,000 dwarf galaxies within 10 and 25 Mpc, respectively. We compare our results with the 50 Mpc Galaxy Catalog and estimate that current observations are highly incomplete at low masses: for 10 6 ≤ M * /M ⊙ ≤ 10 7 (−13 ≲ M r ≲ −10), we find completeness fractions of ∼23% within 10 Mpc and ∼4% within 25 Mpc. The simulated galaxies below the completeness limits of the observations exist in a range of environments, with notable populations of field dwarfs at all distances and satellites around centrals with masses 10 8 ≲ M * /M ⊙ ≲ 10 11 within 10–25 Mpc. We find that there are ∼8 times more quiescent dwarf galaxies in the TNG50 sample than are currently cataloged. Our results suggest that upcoming observations should uncover a substantial population of dwarf galaxies, and that ≳15% of these will be red, currently quenched galaxies in the field.

Shread, Evangela E. [California Institute of Techn↗
DOE OSTI2026

ODIN: Characterizing the Three-dimensional Structure of Two Protocluster Complexes at z = 3.1

We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at z = 3.1. These protocluster "complexes," designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of z = 3.1 Lyα emitters (LAEs) identified in the COSMOS field by the One-hundred-deg$^{2}$ DECam Imaging in Narrowbands survey. These protocluster complexes have been followed up with extensive spectroscopy from Keck, Gemini, and DESI. Using a probabilistic method that combines photometrically selected and spectroscopically confirmed LAEs, we reconstruct the 3D structure of these complexes on scales of ≈50 cMpc. We validate our reconstruction method using the IllustrisTNG300-1 cosmological hydrodynamical simulation and show that it consistently outperforms approaches relying solely on spectroscopic data. The resulting 3D maps reveal that both complexes are irregular and elongated along a single axis, emphasizing the impact of sightline on our perception of structure morphology. The complexes consist of multiple density peaks, 10 in COSMOS-z3.1-A and 4 in COSMOS-z3.1-C. The former is confirmed to be a proto-supercluster, similar to Hyperion at z = 2.4 but observed at an even earlier epoch. Multiple "tails" connected to the cores of the density peaks are seen, likely representing cosmic filaments feeding into these extremely overdense regions. The 3D reconstructions further provide strong evidence that Lyα blobs preferentially reside in the outskirts of the highest density regions. Descendant mass estimates of the density peaks suggest that COSMOS-z3.1-A and COSMOS-z3.1-C will evolve to become ultramassive structures by z = 0, with total masses log ( M / M ,⊙ ,) ≳ 15.3 , exceeding that of Coma.

Ramakrishnan, Vandana [Purdue U., West Lafayette] ↗
DOE OSTI2025

Wino and Real Minimal Dark Matter Excluded by Fermi Gamma-Ray Observations

We show that minimal, fermionic dark matter (DM) models in the $n$-dimensional representation of the weak force with zero hypercharge that make up 100% of the DM under the standard cosmological history are strongly excluded for $n < 9$. This includes the thermal wino, which we show is ruled out even allowing for DM core sizes up to $\sim$6.7 kpc with the preferred local DM density or $\sim$3.7 kpc in addition to the local DM density being half the preferred value, at less than $0.2$ GeV/cm$^3$. We reach these conclusions through dedicated searches with 14 years of Fermi gamma-ray data in the inner Galaxy between 30 GeV and 2 TeV for the continuum gamma-rays produced in the decays of unstable particles produced in DM annihilation and bound-state formation processes. We consider a variety of Milky Way DM profiles in our analyses, including those motivated by modern hydrodynamic cosmological simulations, and show that all the $n < 9$ minimal DM models are disfavored even under the most conservative assumptions for these density profiles. While wino, quintuplet ($n=5$), and $n = 7$ DM models are strongly disfavored by our analyses under the standard cosmology, we discuss how non-standard cosmological histories or DM sub-fractions could still allow for these particles to be realized in nature, with discovery opportunities at next-generation particle colliders and gamma-ray telescopes.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
DOE OSTI2026

Lyman-$α$ forest holography: 3D predictions from 1D measurements

Cosmological analyses of Lyman-$α$ forest clustering rely on either one-dimensional correlations along individual sightlines or three-dimensional correlations between different sightlines. Because these observables probe the matter distribution on very different scales, they have traditionally been analyzed independently. In this work, we bridge this gap using ForestFlow, an emulator trained on a suite of cosmological hydrodynamical simulations that provides a unified description of Lyman-$α$ forest clustering from linear to nonlinear scales. This framework enables us to determine the range of three-dimensional clustering models compatible with the DESI one-dimensional flux power spectrum ($P_{\rm 1D}$). The resulting predictions successfully reproduce the large-scale clustering measured by the DESI BAO analysis and provide physically motivated priors on nonlinear clustering that are used in a companion paper presenting the full-shape analysis of the DESI DR2 Lyman-$α$ forest. We validate our methodology using the large-volume, high-resolution hydrodynamical simulation ACCEL-2, demonstrating excellent agreement across the full range of scales considered. Finally, we combine constraints from the $P_{\rm 1D}$ and BAO analyses on the parameter combinations $b_δσ_8$ and $b_ηf σ_8$, finding that the two probes provide comparable constraining power while exhibiting complementary parameter degeneracies. Our results establish a direct connection between one- and three-dimensional Lyman-$α$ forest measurements through ForestFlow, an approach we term Lyman-$α$ holography by analogy with the reconstruction of higher-dimensional structure from lower-dimensional information.

Chaves-Montero, J. [Barcelona, IFAE] (ORCID:000000↗
DOE OSTI2022

HYPHY: Deep Generative Conditional Posterior Mapping of Hydrodynamical Physics

Generating large-volume hydrodynamical simulations for cosmological observables is a computationally demanding task necessary for next-generation observations. In this work, we construct a novel fully convolutional variational autoencoder (VAE) to synthesize hydrodynamic fields conditioned on dark matter fields from N -body simulations. After training the model on a single hydrodynamical simulation, we are able to probabilistically map new dark-matter-only simulations to corresponding full hydrodynamical outputs. By sampling over the latent space of our VAE, we can generate posterior samples and study the variance of the mapping. We find that our reconstructed field provides an accurate representation of the target hydrodynamical fields as well as reasonable variance estimates. This approach has promise for the rapid generation of mocks as well as for implementation in a full inverse model of observed data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Galaxy mergers in eagle do not induce a significant amount of black hole growth yet do increase the rate of luminous AGN

ABSTRACT We investigate the connection between galaxy–galaxy mergers and enhanced black hole (BH) growth using the cosmological hydrodynamical eagle simulation. We do this via three methods of analysis, investigating: the merger fraction of AGN, the AGN fraction of merging systems, and the AGN fraction of galaxies with close companions. In each case, we find an increased abundance of AGN within merging systems relative to control samples of inactive or isolated galaxies (by up to a factor of ≈3 depending on the analysis method used), confirming that mergers are enhancing BH accretion rates for at least a subset of the galaxy population. The greatest excess of AGN triggered via a merger are found in lower mass (M* ∼ 1010 M⊙) gas rich (fgas > 0.2) central galaxies with lower mass BHs (MBH ∼ 107 M⊙) at lower redshifts (z < 1). We find no enhancement of AGN triggered via mergers in more massive galaxies (M* ≳ 1011 M⊙). The enhancement of AGN is not uniform throughout the phases of a merger, and instead peaks within the early remnants of merging systems (typically lagging ≈300 Myr post-coalescence of the two galaxies at z = 0.5). We argue that neither major ($M_{\mathrm{*,1}} / M_{\mathrm{*,2}} \ge \frac{1}{4}$) nor minor mergers ($\frac{1}{10} \lt M_{\mathrm{*,1}} / M_{\mathrm{*,2}} \lt \frac{1}{4}$) are statistically relevant for enhancing BH masses globally. Whilst at all redshifts the galaxies experiencing a merger have accretion rates that are on average 2–3 times that of isolated galaxies, the majority of mass that is accreted on to BHs occurs outside the periods of a merger. We compute that on average no more than 15 per cent of a BHs final day mass comes from the enhanced accretion rates triggered via a merger.

McAlpine, Stuart↗
DOE OSTI2021

Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian deep learning

The goal of generative models is to learn the intricate relations between the data to create new simulated data, but current approaches fail in very high dimensions. When the true data-generating process is based on physical processes, these impose symmetries and constraints, and the generative model can be created by learning an effective description of the underlying physics, which enables scaling of the generative model to very high dimensions. In this work, we propose Lagrangian deep learning (LDL) for this purpose, applying it to learn outputs of cosmological hydrodynamical simulations. The model uses layers of Lagrangian displacements of particles describing the observables to learn the effective physical laws. The displacements are modeled as the gradient of an effective potential, which explicitly satisfies the translational and rotational invariance. The total number of learned parameters is only of order 10, and they can be viewed as effective theory parameters. Further, we combine N-body solver fast particle mesh (FastPM) with LDL and apply it to a wide range of cosmological outputs, from the dark matter to the stellar maps, gas density, and temperature. The computational cost of LDL is nearly four orders of magnitude lower than that of the full hydrodynamical simulations, yet it outperforms them at the same resolution. We achieve this with only of order 10 layers from the initial conditions to the final output, in contrast to typical cosmological simulations with thousands of time steps. This opens up the possibility of analyzing cosmological observations entirely within this framework, without the need for large dark-matter simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

High-precision Galaxy Clustering Predictions from Small-volume Hydrodynamical Simulations via Control Variates

Abstract Cosmological simulations of galaxy formation are an invaluable tool for understanding galaxy formation and its impact on cosmological parameter inference from large-scale structures. However, their high computational cost is a significant obstacle for running simulations that probe cosmological volumes comparable to those analyzed by contemporary large-scale structure experiments. In this work, we explore the possibility of obtaining high-precision galaxy clustering predictions from small-volume hydrodynamical simulations such as MillenniumTNG and FLAMINGO via control variates. In this approach, the hydrodynamical full-physics simulation is paired with a matched low-resolution gravity-only simulation. By learning the galaxy–halo connection from the hydrodynamical simulation and applying it to the gravity-only counterpart, one obtains a galaxy population that closely mimics the one in the more expensive simulation. One can then construct an estimator of galaxy clustering that combines the clustering amplitudes in the small-volume hydrodynamical and gravity-only simulations with clustering amplitudes in a large-volume gravity-only simulation. Depending on the galaxy sample, clustering statistic, and scale, this galaxy clustering estimator can have an effective volume of up to around 100 times the volume of the original hydrodynamical simulation in the nonlinear regime. With this approach, we can construct galaxy clustering predictions from existing simulations that are precise enough for mock analyses of next-generation large-scale structure surveys such as the Dark Energy Spectroscopic Instrument and the Legacy Survey of Space and Time.

Doytcheva, Alexandra (ORCID:0009000111254888)↗
DOE OSTI2026

Cosmological analysis of the DESI DR1 Lyα 1D power spectrum

We present the cosmological analysis of the one-dimensional Lyman-α flux power spectrum from the first data release of the Dark Energy Spectroscopic Instrument (DESI). We capture the dependence of the signal on cosmology and intergalactic medium physics using an emulator trained on a cosmological suite of hydrodynamical simulations, and we correct its predictions for the impact of astrophysical contaminants and systematics, many of these not considered in previous analyses. We employ this framework to constrain the amplitude and logarithmic slope of the linear matter power spectrum at k ★ = 0.009 km -1 s and redshift z = 3, obtaining Δ 2 ★ = 0.379 ± 0.032 and n ★ = -2.309 ± 0.019 https://github.com/igmhub/cobaya_lya_p1d. The robustness of these constraints is validated through the analysis of mocks and a large number of alternative data analysis variations, with cosmological parameters kept blinded throughout the validation process. We then combine our results with constraints from DESI BAO and temperature, polarization, and lensing measurements from Planck, ACT, and SPT-3G to set constraints on ΛCDM extensions. While our measurements do not significantly tighten the limits on the sum of neutrino masses from the combination of these probes, they sharpen the constraints on the effective number of relativistic species, N eff = 3.02 ± 0.10, the running of the spectral index, α s = 0.0014 ± 0.0041, and the running of the running, β s = -0.0006 ± 0.0048, by a factor of 1.18, 1.27, and 1.90, respectively. We conclude by outlining the improvements needed to fully reach the level of confidence implied by these uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Filaments in and between galaxy clusters at low and mid-frequency with the SKA

Context. Understanding the magnetised Universe is a major challenge in modern astrophysics, and cosmic magnetism has been acknowledged as one of the key scientific drivers of the most ambitious radio instrument ever planned, the Square Kilometre Array. Aims. With this work, we aim to investigate the potential of the Square Kilometre Array and its precursors and pathfinders in the study of magnetic fields in galaxy clusters and filaments through diffuse synchrotron radio emission. Galaxy clusters and filaments of the cosmic web are indeed unique laboratories in which to investigate turbulent fluid motions and large-scale magnetic fields in action, and much of what is known about magnetic fields in galaxy clusters comes from sensitive radio observations. Methods. Based on cosmological magneto-hydrodynamic simulations, we predict radio properties (total intensity and polarisation) of a pair of galaxy clusters connected by a cosmic-web filament. Results. We use our theoretical expectations to explore the potential of polarimetric observations to study large-scale structure magnetic fields in the frequency ranges 50–350 MHz and 950–1760 MHz. We also present predictions for galaxy cluster polarimetric observations with the Square Kilometre Array precursors and pathfinders, such as the LOw frequency ARray 2.0 and the MeerKAT+ telescope. Conclusions. Our findings point out that polarisation observations are particularly powerful for the study of large-scale magnetic fields, since they are not significantly affected by confusion noise. The unprecedented sensitivity and spatial resolution of the intermediatefrequency radio telescopes make them the favourite instruments for the study of these sources through polarimetric data, potentially allowing us to understand if the energy density of relativistic electrons is in equipartition with the magnetic field or rather coupled with the thermal gas density. Our results show that low-frequency instruments also represent a precious tool to study diffuse synchrotron emission in total intensity and polarisation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Stellar migration and chemical enrichment in the milky way disc: a hybrid model

ABSTRACT We develop a hybrid model of galactic chemical evolution that combines a multiring computation of chemical enrichment with a prescription for stellar migration and the vertical distribution of stellar populations informed by a cosmological hydrodynamic disc galaxy simulation. Our fiducial model adopts empirically motivated forms of the star formation law and star formation history, with a gradient in outflow mass loading tuned to reproduce the observed metallicity gradient. With this approach, the model reproduces many of the striking qualitative features of the Milky Way disc’s abundance structure: (i) the dependence of the [O/Fe]–[Fe/H] distribution on radius Rgal and mid-plane distance |z|; (ii) the changing shapes of the [O/H] and [Fe/H] distributions with Rgal and |z|; (iii) a broad distribution of [O/Fe] at sub-solar metallicity and changes in the [O/Fe] distribution with Rgal, |z|, and [Fe/H]; (iv) a tight correlation between [O/Fe] and stellar age for [O/Fe] > 0.1; (v) a population of young and intermediate-age α-enhanced stars caused by migration-induced variability in the Type Ia supernova rate; (vi) non-monotonic age–[O/H] and age–[Fe/H] relations, with large scatter and a median age of ∼4 Gyr near solar metallicity. Observationally motivated models with an enhanced star formation rate ∼2 Gyr ago improve agreement with the observed age–[Fe/H] and age–[O/H] relations, but worsen agreement with the observed age–[O/Fe] relation. None of our models predict an [O/Fe] distribution with the distinct bimodality seen in the observations, suggesting that more dramatic evolutionary pathways are required. All code and tables used for our models are publicly available through the Versatile Integrator for Chemical Evolution (VICE; https://pypi.org/project/vice).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Nyx: A Massively Parallel AMR Code for Computational Cosmology

Nyx is a highly parallel, adaptive mesh, finite-volume N-body compressible hydrodynamics solver for cosmological simulations. It has been used to simulate different cosmological scenarios with a recent focus on the intergalactic medium and Lyman alpha forest. Together, Nyx, the compressible astrophysical simulation code, Castro, and the low Mach number code MAESTROeX, make up the AMReX-Astrophysics Suite of open-source, adaptive mesh, performance-portable astrophysical simulation codes. Other examples of cosmological simulation research codes include Enzo, Enzo-P/Cello, RAMSES, ART, FLASH, Cholla, as well as Gadget, Gasoline, Arepo, Gizmo, and SWIFT.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Revealing the Galaxy–Halo Connection through Machine Learning

Abstract Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of star formation, feedback from supernovae, and the radiative transfer of ionizing photons can capture the processes relevant for establishing these connections. The complexity of these physics can prove difficult to disentangle and obfuscate how mass-dependent trends in the galaxy population originate. Here, we train a machine-learning method called Explainable Boosting Machines (EBMs) to infer how the stellar mass and star formation rate of nearly 6 million galaxies simulated by the Cosmic Reionization on Computers project depend on the physical properties of halo mass, the peak circular velocity of the galaxy during its formation history v peak , cosmic environment, and redshift. The resulting EBM models reveal the relative importance of these properties in setting galaxy stellar mass and star formation rate, with v peak providing the most dominant contribution. Environmental properties provide substantial improvements for modeling the stellar mass and star formation rate in only ≲10% of the simulated galaxies. We also provide alternative formulations of EBM models that enable low-resolution simulations, which cannot track the interior structure of dark matter halos, to predict the stellar mass and star formation rate of galaxies computed by high-resolution simulations with detailed baryonic physics.

79 ASTRONOMY AND ASTROPHYSICS↗