arXiv subjects

Romain Teyssier

Publications and source records attributed to Romain Teyssier.

At least 37 records · Page 2Linked to original sources

arXiv2025

Numerical Cosmology

In these lecture notes, we describe the current state-of-the-art for numerical simulations of large-scale structure and galaxy formation. Numerical simulations play a central role in the preparation and the exploitation of large-scale galaxy surveys, in which galaxies are the fundamental observational objects. We first describe basic methods for collisionless N-body dynamics that enable us to model dark matter accurately by solving the Vlasov-Poisson equations. We then discuss simple methods to populate dark matter halos with galaxies, such as Halo and Sub-halo Abundance Matching techniques and baryonification techniques for capturing baryonic effects on the matter distribution. We finally describe how to model the gas component by solving the Euler-Poisson equations, focusing on the foundational assumptions behind these equations, namely local thermo-dynamical equilibrium, and the nature of the truncation errors of the numerical scheme, namely numerical diffusion. We show a few examples of simulations of a Milky-Way-like halo without cooling, with cooling and with star formation. We finally describe different subgrid prescriptions recently developed to model star formation, supernovae feedback and active galactic nuclei and how they impact cosmological simulations.

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arXiv2025

Comparing subgrid models for cosmic ray diffusion in a magnetized isolated galaxy simulation

Galactic cosmic rays (CRs) play a crucial role in galaxy formation and evolution by altering gas dynamics and chemistry across multiple scales. Typical numerical simulations of CR transport assume a constant diffusion coefficient for the entire galaxy, despite both numerical and theoretical studies showing that it can change by orders of magnitude depending on the phase of the interstellar medium. Only a few simulations exist that self-consistently calculate CR transport with diffusion, streaming, and advection by the background gas. In this study we explore three subgrid models for CR diffusion, based on popular theories of CR transport. We post-process an isolated, star-forming MHD galactic disk simulated using the RAMSES code. The resulting diffusion coefficients depend solely on the subgrid turbulent kinetic energy and the MHD state variables of the plasma. We use these models to calculate coefficients for vertical transport. We find that they depend critically on the local magnetic field tilt angle. Across models, our resulting diffusion coefficients range from $10^{26}~\rm cm^2s^{-1}$ to $10^{31}~\rm cm^2s^{-1}$, and yield CR energy densities at the midplane from $1$ to $100 ~\rm eV cm^{-3}$, suggesting varied degrees of backreaction on their environment. Using simple approximations, we show that the gamma ray luminosity of the galaxy depends primarily on the gas surface density and the turbulent confinement of CRs by the galactic corona.

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arXiv2025

Much Ado About Nothing: Galaxy Formation and Galactic Outflows in Cosmic Voids

We present a theoretical framework for calculating the volume filling fraction of galactic outflows in cosmic voids by integrating analytical models for the halo mass function (HMF), the halo occupation fraction, the stellar mass-halo mass relation, and outflow sizes. Using RAMSES, we perform a hydrodynamical zoom-in simulation of the central 25 cMpc/h region of a spherical void, identified as the lowest-density region among 1,000 random spheres in a parent 1 Gpc box simulation. This void has a diameter of 120 cMpc/h and a density contrast of $δ\simeq -0.8$. We find that the properties of void galaxies remain stable when expanding the zoom-in region to 50 cMpc/h, though our relatively low mass resolution impacts the results. Our higher-resolution simulation aligns with the analytical HMF that accounts for the void's underdensity and size. While higher resolution improves stellar mass estimates for low-mass halos, computational constraints necessitate a theoretical framework that enables extrapolation to infinite resolution. Our analytical model, calibrated to our simulations, enables extrapolation down to the filtering mass of star-forming halos. To compare galaxy properties in this void with those in the field, we conduct a companion field simulation of the same box size. At infinite resolution, we predict wind volume filling fractions of $18.6\%$ in the field and $3.1\%$ in our void, with values dependent on cosmic variance, void size, and underdensity. Dwarf galaxies contribute minimally, and resolving halos to $M_{\rm h}=10^{10} M_\odot$ suffices for robust estimates. Applying our framework to the Local Group void ($δ\simeq -0.5$, $R=20\ \mathrm{cMpc}$), we predict a wind volume filling fraction of $9.6\%\pm3.3\%$.

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arXiv2025

Field-Level Comparison and Robustness Analysis of Cosmological N-body Simulations

We present the first field-level comparison of cosmological N-body simulations, considering various widely used codes: Abacus, CUBEP$^3$M, Enzo, Gadget, Gizmo, PKDGrav, and Ramses. Unlike previous comparisons focused on summary statistics, we conduct a comprehensive field-level analysis: evaluating statistical similarity, quantifying implications for cosmological parameter inference, and identifying the regimes in which simulations are consistent. We begin with a traditional comparison using the power spectrum, cross-correlation coefficient, and visual inspection of the matter field. We follow this with a statistical out-of-distribution (OOD) analysis to quantify distributional differences between simulations, revealing insights not captured by the traditional metrics. We then perform field-level simulation-based inference (SBI) using convolutional neural networks (CNNs), training on one simulation and testing on others, including a full hydrodynamic simulation for comparison. We identify several causes of OOD behavior and biased inference, finding that resolution effects, such as those arising from adaptive mesh refinement (AMR), have a significant impact. Models trained on non-AMR simulations fail catastrophically when evaluated on AMR simulations, introducing larger biases than those from hydrodynamic effects. Differences in resolution, even when using the same N-body code, likewise lead to biased inference. We attribute these failures to a CNN's sensitivity to small-scale fluctuations, particularly in voids and filaments, and demonstrate that appropriate smoothing brings the simulations into statistical agreement. Our findings motivate the need for careful data filtering and the use of field-level OOD metrics, such as PQMass, to ensure robust inference.

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arXiv2025

Dust-UV offsets in high-redshift galaxies in the Cosmic Dawn III simulation

Recent observations have revealed puzzling spatial disparities between ALMA dust continuum and UV emission as seen by HST and JWST in galaxies at $z=5-7$ (e.g. ALPINE and REBELS surveys), compelling us to propose a physical interpretation of such offsets. We investigate these offsets using the Cosmic Dawn III (CoDa III) simulation, a state-of-the-art fully coupled radiation-hydrodynamics cosmological simulation, which incorporates a dynamical dust model. First of all, we find that our simulated dust masses, while calibrated to match observed ones, yield unrealistically large UV attenuations. In fact, the bright-end galaxy UV Luminosity function is best reproduced using only 7.5\% of the dust content of CoDa III galaxies. With this recalibration, we obtain populations of massive galaxies matching ALPINE and REBELS magnitudes and UV slopes, but with smaller dust masses than observed. In this framework, we also find significant dust-UV offsets in massive, UV-bright galaxies ($\mathrm{M}_\mathrm{DM}> 10^{11.5}$ M$_\odot$, M$_*>10^{10}$ M$_\odot$, M$_{\rm AB1600}<-21.5$), reaching up to $\sim 2$ pkpc for the most massive systems. Our analysis reveals that these offsets primarily result from severe dust extinction in galactic centers rather than a misalignment between dust and stellar mass distributions. At the spatial resolution of CoDa III (1.65 pkpc at z=6), the dust remains in majority well-aligned with the bulk stellar component, and we predict the dust continuum should therefore align well with the stellar rest-frame NIR component, less affected by dust attenuation. This study highlights the importance of dust in shaping the appearance of early galaxies at UV wavelengths, even as early as in the Epoch of Reionization.

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arXiv2025

Baryonification II: Constraining feedback with X-ray and kinematic Sunyaev-Zel'dovich observations

Baryonic feedback alters the matter distribution on small and intermediate scales, posing a challenge for precision cosmology. The new, component-wise baryonification (BFC) approach provides a self-consistent framework to model feedback effects for different observables. In this paper we use this framework to fit kinematic Sunyaev-Zel'dovich (kSZ) observations from the Atacama Cosmology Telescope (ACT) alongside halo X-ray gas fractions from eROSITA, investigating baryonic feedback in a cosmological context. We first show that the kSZ data from ACT is consistent with the gas fractions from eROSITA, both suggesting a feedback model that is stronger than what is assumed in most hydrodynamical simulations. This finding is in contrast to older, pre-eROSITA gas fraction measurements that point towards weaker feedback in tension with the kSZ results. We suspect these discrepancies to be due to selection bias in the pre-eROSITA sample, or differences in halo mass estimation between the two data sets. In a further step, we use the BFC model to predict the baryonic suppression of the matter power spectrum. Based on our combined fit to data from ACT and eROSITA, we find a power spectrum suppression that exceeds the percent-level at modes above $k=0.3-0.6 \,h\,\mathrm{Mpc}^{-1}$, growing to 2-8 percent at $k=1\,h\,\mathrm{Mpc}^{-1}$, and to 20-25 percent at $k=5\,h\,\mathrm{Mpc}^{-1}$, consistent with strong-feedback hydrodynamical simulations. Finally, we compare our best-fitting model to the observed gas density and pressure profiles of massive galaxy clusters from the X-COP sample, finding excellent agreement. These results show that BFC provides a self-consistent picture of feedback across mass- and length scales as well as different cosmological observables, thus making it promising for applications to multiwavelength studies to jointly constrain cosmology and baryonic effects.

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arXiv2025

On the Origin of the High Star-Formation Efficiency in Massive Galaxies at Cosmic Dawn

Motivated by the early excess of bright galaxies seen by JWST, we run zoom-in cosmological simulations of a massive galaxy at Cosmic Dawn, in a halo of $10^{11} M_\odot$ at $z = 9$, using the hydro-gravitational code RAMSES at an effective resolution $\sim 10~{\rm pc}$. We investigate physical mechanisms that enhance the star-formation efficiencies (SFEs) at the high gas densities of the star-forming regions in this galaxy ($\sim 3\times 10^3~{\rm cm^{-3}}$, $\sim 10^4~M_\odot/{\rm pc^2}$). Our fiducial star formation recipe uses a physically-motivated, turbulence-based, multi-freefall model, avoiding ad hoc extrapolation from lower redshifts. By $z = 9$, our simulated galaxy is a clumpy, thick, rotating disc with a high stellar mass $\sim 3\times 10^9~M_\odot$ and high star formation rate $\sim 50~M_\odot/{\rm yr}$. The high gas density makes supernova (SN) feedback less efficient, producing a high local SFE $\gtrsim 10\%$. The global SFE is set by feedback-driven outflows and only weakly correlated with the local SFE. Photoionization heating makes SN feedback more efficient, but the integrated SFE always remains high. Intense accretion at Cosmic Dawn seeds turbulence which reduces local SFE, but this only weakly affects the global SFE. The star formation histories of our simulated galaxies are similar to observed massive galaxies at Cosmic Dawn, despite our limited resolution. We set the stage for future simulations which treat radiation self-consistently and use a higher effective resolution $\sim 1~{\rm pc}$ that captures the physics of star-forming clouds.

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arXiv2025

Cosmic ray and plasma coupling for isothermal supersonic turbulence in the magnetized interstellar medium

Cosmic rays (CRs) are an integral part of the non-thermal pressure budget in the interstellar medium (ISM) and are the leading-order ionization mechanism in cold molecular clouds. We study the impacts that different microphysical CR diffusion coefficients and streaming speeds have on the evolution of isothermal, magnetized, turbulent plasmas, relevant to the cold ISM. We utilized a two-moment CR magnetohydrodynamic (CRMHD) model, allowing us to dynamically evolve both CR energy and flux densities with contributions from Alfvénic streaming and anisotropic diffusion. We identify $\textit{coupled}$ and $\textit{decoupled}$ regimes, and define dimensionless Prandtl numbers $\rm{Pm_c}$ and $\rm{Pm_s}$, which quantify whether the plasma falls within these two regimes. In the coupled regime -- characteristic of slow streaming ($\rm{Pm_s} < 1$) and low diffusion ($\rm{Pm_c} < 1$) -- the CR fluid imprints upon the plasma a mixed equation of state between $P_{\rm{c}} \propto ρ^{4/3}$ (relativistic fluid) and $P_{\rm{c}} \propto ρ^{2/3}$ (streaming), where $P_{\rm{c}}$ is the CR pressure, and $ρ$ is the plasma density. By modifying the sound speed, the coupling reduces the turbulent Mach number, and hence the amplitude of the density fluctuations, whilst supporting secular heating of the CR fluid. In contrast, in the decoupled regime ($\rm{Pm_s} > 1$ or $\rm{Pm_c} > 1$) the CR fluid and the plasma have negligible interactions. We further show that CR heating is enabled by coherent structures within the compressible velocity field, with no impact on the turbulence spectrum of incompressible modes.

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arXiv2025

Line Intensity Mapping Prediction from the Cosmic Dawn (CoDa) III Simulation for H$α$ from Galaxies and the Intergalactic Medium during the Epoch of Reionization

The evolution of large-scale structure, galaxies and the intergalactic medium (IGM) during the Epoch of Reionization (EoR) can be probed by upcoming Line Intensity Mapping (LIM) experiments, which sample in redshift and direction without needing to resolve individual galaxies. We predict the intensity and sources of hydrogen H$α$ emission, dominated by radiative recombination following ionization by UV from the same massive stars that caused reionization, down to redshift 4.6, using the largest fully-coupled, radiation-hydro simulation of galaxy formation and reionization to date, Cosmic Dawn (CoDa) III. We compute the mean intensity and Voxel Intensity Distribution (VID) vs. redshift, including the relative contributions of galaxies and IGM. This will provide mock data to guide and interpret LIM experiments such as NASA's SPHEREx and proposed Cosmic Dawn Intensity Mapper (CDIM).

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arXiv2025

Synergising semi-analytical models and hydrodynamical simulations to interpret JWST data from the first billion years

The field of high redshift galaxy formation has been revolutionised by JWST, which is yielding unprecedented insights on galaxy assembly at early times. Our key aim is to study the physical mechanisms that can explain the unexpected abundance of bright galaxies at $z \geq 11$, as well as their metal enrichment and spectral properties. We also use recent data to determine the key sources of reionisation. To do so, we implement cold gas fractions and star formation efficiencies derived from the SPHINX20 high-resolution radiation-hydrodynamics simulation into DELPHI, a semi-analytic model that tracks the assembly of dark matter halos and their baryonic components from $z \sim 4.5-40$. In addition, we explore two different methodologies to boost galaxy luminosities at $z \geq 11$: a stellar initial mass function (IMF) that becomes increasingly top-heavy with decreasing metallicity and increasing redshift (eIMF model), and star formation efficiencies that increase with increasing redshift (eSFE model). Our key findings are: (i) both the eIMF and eSFE models can explain the abundance of bright galaxies at $z \geq 11$; (ii) dust attenuation plays an important role for the bright-end of the UV LF at $z \leq 11$; (iii) the mass-metallicity relation is in place as early as $z \sim 17$ in all models although its slope is model-dependent; (iv) within the spread of both models and observations, all of our models are in good agreement with current estimates of $β$ slopes at $z \sim 5-17$ and Balmer break strengths at $z \sim 6-10$; (v) in the eIMF model, galaxies at $z\geq12$ or with $\rm{M_{UV}}\geq-18$ show values of $ξ_{\rm{ion}} \sim 10^{25.55}~{\rm [Hz~erg^{-1}]}$, twice larger than in other models; (vi) star formation in galaxies below $10^{9}\rm{M_{\odot}}$ is the key driver of reionisation, providing the bulk ($\sim 85\%$) of ionising photons down to its midpoint at $z \sim 7$.

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arXiv2025

Constraining Reionization with Lyα Damping-Wing Absorption in Galaxy Spectra: A Machine Learning Model Based on Reionization Simulations

Recently, NIRSpec PRISM/CLEAR observations by JWST have begun providing rest-frame UV continuum measurements of galaxies at $z\gtrsim7$, revealing signatures of Ly$α$ damping-wing (DW) absorption by the intergalactic medium (IGM). We develop a methodology to constrain the global ionization fraction of the IGM $(Q_{\rm HII})$ using low-resolution spectra, employing the random forest classification (RFC) method. We construct mock spectra using the simulated galaxies and the IGM from the Cosmic Dawn II simulation and train RFC models to estimate $Q_{\rm HII}$ at the redshift of the source and to detect the presence of a damped Ly$α$ absorber (DLA). We find that individual galaxy spectra with spectral bins between 1220 and 1270 Å and with signal-to-noise ratios greater than 20 can place tight constraints on $Q_{\rm HII}$, provided the UV continuum is accurately modeled. This method is particularly effective for the early phase of reionization ($Q_{\rm HII}<50\%$), when the IGM opacity is high in the DW. As a demonstration, we apply our model to existing NIRSpec PRISM/CLEAR spectra, placing upper bounds of $Q_{\rm HII}=59.6\%$, $5.6\%$, and $18.5\%$ at $z=7.7,~9.4,$ and $10.6$, respectively, with $68\%$ confidence, though several modeling uncertainties remain to be discussed. These constraints favor late-starting reionization models, where $\gtrsim 80\%$ of the IGM is ionized after $z=8$. We conclude that high-SNR observations of carefully selected targets around $z\sim7-9$ can effectively constrain reionization models.

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arXiv2025

Constructing Merger Trees of Density Peaks Using Phase-Space Watershed Segmentation Algorithm

Structure identification in cosmological simulations plays an important role in analysing simulation outputs. The definition of these structures directly impacts the inferred properties derived from these simulations. This paper proposes a more straightforward definition and model of structure by focusing on density peaks rather than halos and clumps. It introduces a new watershed algorithm that uses phase-space analysis to identify structures, especially in complex environments where traditional methods may struggle due to spatially overlapping structures. Additionally, a merger tree code is introduced to track density peaks across timesteps, making use of the boosted potential for identifying the most bound particles for each peak.

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arXiv2024

Impact of star formation models on the growth of simulated galaxies at high redshifts

Star formation is a key process that governs the baryon cycle within galaxies, however, the question of how it controls their growth remains elusive due to modeling uncertainties. To understand the impact of star formation models on galaxy evolution, we performed cosmological zoom-in radiation-hydrodynamic simulations of a dwarf dark matter halo, with a virial mass of $M_{\rm vir} \sim 10^9\, M_\odot$ at $z=6$. We compared two different star formation models: a multi-freefall model combined with a local gravo-thermo-turbulent condition and a more self-consistent model based on a sink particle algorithm, where gas accretion and star formation are directly controlled by the gas kinematics. As the first study in this series, we used cosmological zoom-in simulations with different spatial resolutions and found that star formation is more bursty in the runs with the sink algorithm, generating stronger outflows than in the runs with the gravo-thermo-turbulent model. The main reason for the increased burstiness is that the gas accretion rates on the sinks are high enough to form stars on very short timescales, leading to more clustered star formation. As a result, the star-forming clumps are disrupted more quickly in the sink run due to more coherent radiation and supernova feedback. The difference in burstiness between the two star formation models becomes even more pronounced when the supernova explosion energy is artificially increased. Our results suggest that improving the modeling of star formation on small, sub-molecular cloud scales can significantly impact the global properties of simulated galaxies.

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arXiv2024

Dispersion Measures of Fast Radio Bursts through the Epoch of Reionization

Dispersion measures (DM) of fast radio bursts (FRBs) probe the density of electrons in the intergalactic medium (IGM) along their lines-of-sight, including the average density versus distance to the source and its variations in direction. While previous study focused on low-redshift, FRBs are potentially detectable out to high redshift, where their DMs can, in principle, probe the epoch of reionization (EOR) and its patchiness. We present the first predictions from large-scale, radiation-hydrodynamical simulation of fully-coupled galaxy formation and reionization, using Cosmic Dawn (``CoDa")~II to model the density and ionization fields of the universe down to redshifts through the end of the EOR at $z_{re}\approx6.1$. Combining this with an N-body simulation CoDa~II--Dark Matter of the fully-ionized epoch from the EOR to the present, we calculate the mean and standard deviation of FRB DMs as functions of their source redshift. The mean and standard deviation of DM increase with redshift, reaching a plateau by $z(x_{HII}\lesssim0.25)\gtrsim8$, i.e. well above $z_{re}$. The mean-DM asymptote $\mathcal{DM}_{max} \approx 5900~\mathrm{pc\, cm^{-3}}$ reflects the end of the EOR and its duration. The standard deviation there is $σ_{DM, max}\approx497 ~\mathrm{pc\, cm^{-3}}$, reflecting inhomogeneities of both patchy reionization and density. Inhomogeneities in ionization during the EOR contribute $\mathcal{O}(1$ per cent) of this value of $σ_{DM,max}$ from FRBs at redshifts $z\gtrsim 8$. Current estimates of FRB rates suggest this may be detectable within a few years of observation.

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arXiv2024

Nexus: A framework for conrolled simulations of idealised galaxies

Motivated by the need for realistic, dynamically self-consistent, evolving galaxy models that avoid the complexity of full, and zoom-in, cosmological simulations, we have developed NEXUS, an integral framework to create and evolve synthetic galaxies made of collisionless and gaseous components. NEXUS leverages the power of publicly available, tried-and-tested packages: the stellar-dynamics, action-based library AGAMA; and the adaptive mesh refinement, N-body/hydrodynamical code RAMSES, modified to meet our needs. In addition, we make use of a proprietary module to account for galaxy formation physics, including gas cooling and heating, star formation, stellar feedback, and chemical enrichment. NEXUS' basic functionality consists in the generation of bespoke initial conditions (ICs) for a diversity of galaxy models, which are advanced in time to simulate the galaxy's evolution. The fully self-consistent ICs are generated with a distribution-function based approach, as implemented in the galaxy modelling module of AGAMA -- up to now restricted to collisionless components, extended in this work to treat two types of gaseous configurations: hot halos and gas discs. NEXUS allows constructing equilibrium models with disc gas fractions $0~\leq~f_{\rm gas}~\leq~1$, appropriate to model both low- and high-redshift galaxies. Similarly, the framework is ideally suited to the study of galactic ecology, i.e. the dynamical interplay between stars and gas over billions of years. As a validation and illustration of our framework, we reproduce several isolated galaxy model setups reported in earlier studies, and present a new, `nested bar' galaxy simulation. Future upgrades of NEXUS will include magneto-hydrodynamics and highly energetic particle (`cosmic ray') heating.

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arXiv2024

Towards Implementation of the Pressure-Regulated, Feedback-Modulated Model of Star Formation in Cosmological Simulations: Methods and Application to TNG

Traditional star formation subgrid models implemented in cosmological galaxy formation simulations, such as that of Springel & Hernquist (2003, hereafter SH03), employ adjustable parameters to satisfy constraints measured in the local Universe. In recent years, however, theory and spatially-resolved simulations of the turbulent, multiphase, star-forming ISM have begun to produce new first-principles models, which when fully developed can replace traditional subgrid prescriptions. This approach has advantages of being physically motivated and predictive rather than empirically tuned, and allowing for varying environmental conditions rather than being tied to local Universe conditions. As a prototype of this new approach, by combining calibrations from the TIGRESS numerical framework with the Pressure-Regulated Feedback-Modulated (PRFM) theory, simple formulae can be obtained for both the gas depletion time and an effective equation of state. Considering galaxies in TNG50, we compare the "native" simulation outputs with post-processed predictions from PRFM. At TNG50 resolution, the total midplane pressure is nearly equal to the total ISM weight, indicating that galaxies in TNG50 are close to satisfying vertical equilibrium. The measured gas scale height is also close to theoretical equilibrium predictions. The slopes of the effective equations of states are similar, but with effective velocity dispersion normalization from SH03 slightly larger than that from current TIGRESS simulations. Because of this and the decrease in PRFM feedback yield at high pressure, the PRFM model predicts shorter gas depletion times than the SH03 model at high densities and redshift. Our results represent a first step towards implementing new, numerically calibrated subgrid algorithms in cosmological galaxy formation simulations.

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arXiv2024

Dust dynamics in RAMSES -- II. Equilibrium drift velocity distributions of charged dust grains

We investigate the gas-grain relative drift velocity distributions of charged astrophysical dust grains in MHD turbulence. We do this using a range of MHD-PIC simulations spanning different plasma-$β$, sonic/Alfvén Mach number, and with grains of varying size and charge-to-mass ratio. We find that the root-mean-square drift velocity is a strong function of the grain size, following a power law with a 1/2 slope. The r.m.s. value has only a very weak dependence on the charge-to-mass ratio. On the other hand, the shape of the distribution is a strong function of the grain charge-to-mass ratio, and in compressible turbulence, also the grain size. We then compare these results to simple analytic models based upon time-domain quasi-linear theory and solutions to the Fokker-Planck equation. These models explain qualitatively the r.m.s. drift velocity's lack of charge-to-mass ratio dependence, as well as why the shape of the distribution changes as the charge-to-mass ratio increases. Finally we scale our results to astrophysical conditions. As an example, at a length scale of one parsec in the cold neutral medium, 0.1 $μ$m grains should be drifting at roughly 40% of the turbulent velocity dispersion. These findings may serve as a basis for a model for grain velocities in the context of grain-grain collisions, non-thermal sputtering, and accretion of metals. These findings also have implications for the transport of grains through the galaxy, suggesting that grains may have non-negligible random motions at length-scales that many modern galaxy simulations approach.

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arXiv2024

Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine learning and Simulations

We introduce the DREAMS project, an innovative approach to understanding the astrophysical implications of alternative dark matter models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over dark matter physics, astrophysics, and cosmology in modeling a range of systems -- from galaxy clusters to ultra-faint satellites. Such extensive simulation suites can provide adequate training sets for machine-learning-based analyses. This paper introduces two new cosmological hydrodynamical suites of Warm Dark Matter, each comprised of 1024 simulations generated using the Arepo code. One suite consists of uniform-box simulations covering a $(25~h^{-1}~{\rm M}_\odot)^3$ volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the Warm Dark Matter particle mass is varied along with the initial density field and several parameters controlling the strength of baryonic feedback within the IllustrisTNG model. We provide two examples, separately utilizing emulators and Convolutional Neural Networks, to demonstrate how such simulation suites can be used to disentangle the effects of dark matter and baryonic physics on galactic properties. The DREAMS project can be extended further to include different dark matter models, galaxy formation physics, and astrophysical targets. In this way, it will provide an unparalleled opportunity to characterize uncertainties on predictions for small-scale observables, leading to robust predictions for testing the particle physics nature of dark matter on these scales.

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