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The DREAMS Project: A New Suite of 1,024 Simulations to Contextualize the Milky Way and Assess Physics Uncertainties
Authors:
Jonah C. Rose,
Mariangela Lisanti,
Paul Torrey,
Francisco Villaescusa-Navarro,
Alex M. Garcia,
Arya Farahi,
Carrie Filion,
Alyson M. Brooks,
Nitya Kallivayalil,
Kassidy E. Kollmann,
Ethan Lilie,
Bonny Y. Wang,
Akaxia Cruz,
Sandip Roy,
Andrew B. Pace,
Niusha Ahvazi,
Stephanie O'Neil,
Cian Roche,
Xuejian Shen,
Mark Vogelsberger
Abstract:
We introduce a new suite of 1,024 cosmological and hydrodynamical zoom-in simulations of Milky Way-mass halos, run with Cold Dark Matter, as part of the DREAMS Project. Each simulation in the suite has a unique set of initial conditions and combination of cosmological and astrophysical parameters. The suite is designed to quantify theoretical uncertainties from halo-to-halo variance, as well as st…
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We introduce a new suite of 1,024 cosmological and hydrodynamical zoom-in simulations of Milky Way-mass halos, run with Cold Dark Matter, as part of the DREAMS Project. Each simulation in the suite has a unique set of initial conditions and combination of cosmological and astrophysical parameters. The suite is designed to quantify theoretical uncertainties from halo-to-halo variance, as well as stellar and black hole feedback. We develop a novel weighting scheme that prioritizes regions of the input parameter space, yielding galaxies consistent with the observed present-day stellar mass--halo mass relation. The resulting galaxy population exhibits a wide diversity in structural properties that encompasses those of the actual Milky Way, providing a powerful statistical sample for galactic archaeology. To demonstrate the suite's scientific utility, we investigate the connection between a galaxy's merger history, focusing on Gaia-Sausage-Enceladus~(GSE) analogs, and its present-day properties. We find that galaxies with a GSE analog have lower star formation rates, more compact disks, and more spherical stellar halos. Crucially, significant halo-to-halo scatter remains, demonstrating that matching more than the most significant events in the Milky Way's past is necessary to recover its present-day properties. Our results highlight the necessity for large statistical samples to disentangle the stochastic nature of galaxy formation and robustly model the Milky Way's unique history.
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Submitted 28 November, 2025;
originally announced December 2025.
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A Novel Density Profile for Isothermal Cores of Dark Matter Halos
Authors:
Vinh Tran,
Xuejian Shen,
Mark Vogelsberger,
Daniel Gilman,
Stephanie O'Neil,
Cian Roche,
Oliver Zier,
Jiarun Gao
Abstract:
We present a novel analytic density profile for halos in self-interacting dark matter (SIDM) models, which accurately captures the isothermal-core configuration, i.e. where both the density and velocity dispersion profiles exhibit central plateaus in the halo innermost region. Importantly, the profile retains a simple and tractable functional form. We demonstrate analytically how our density profi…
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We present a novel analytic density profile for halos in self-interacting dark matter (SIDM) models, which accurately captures the isothermal-core configuration, i.e. where both the density and velocity dispersion profiles exhibit central plateaus in the halo innermost region. Importantly, the profile retains a simple and tractable functional form. We demonstrate analytically how our density profile satisfies the aforementioned conditions, with comparisons to other contemporary functional choices. We further validate the profile using idealized N-body simulations, showing that it provides excellent representations of both the density and velocity dispersion profiles across a broad range of evolutionary stages, from the early thermalization phase to the late core-collapse regime. As a result of its accuracy and simplicity, the proposed profile offers a robust framework for analyzing halo evolution in a variety of SIDM scenarios. It also holds practical utility in reducing simulation needs and in generating initial conditions for simulations targeting the deep core-collapse regime.
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Submitted 18 November, 2025; v1 submitted 18 November, 2024;
originally announced November 2024.
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How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds
Authors:
Tri Nguyen,
Francisco Villaescusa-Navarro,
Siddharth Mishra-Sharma,
Carolina Cuesta-Lazaro,
Paul Torrey,
Arya Farahi,
Alex M. Garcia,
Jonah C. Rose,
Stephanie O'Neil,
Mark Vogelsberger,
Xuejian Shen,
Cian Roche,
Daniel Anglés-Alcázar,
Nitya Kallivayalil,
Julian B. Muñoz,
Francis-Yan Cyr-Racine,
Sandip Roy,
Lina Necib,
Kassidy E. Kollmann
Abstract:
The connection between galaxies and their host dark matter (DM) halos is critical to our understanding of cosmology, galaxy formation, and DM physics. To maximize the return of upcoming cosmological surveys, we need an accurate way to model this complex relationship. Many techniques have been developed to model this connection, from Halo Occupation Distribution (HOD) to empirical and semi-analytic…
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The connection between galaxies and their host dark matter (DM) halos is critical to our understanding of cosmology, galaxy formation, and DM physics. To maximize the return of upcoming cosmological surveys, we need an accurate way to model this complex relationship. Many techniques have been developed to model this connection, from Halo Occupation Distribution (HOD) to empirical and semi-analytic models to hydrodynamic. Hydrodynamic simulations can incorporate more detailed astrophysical processes but are computationally expensive; HODs, on the other hand, are computationally cheap but have limited accuracy. In this work, we present NeHOD, a generative framework based on variational diffusion model and Transformer, for painting galaxies/subhalos on top of DM with an accuracy of hydrodynamic simulations but at a computational cost similar to HOD. By modeling galaxies/subhalos as point clouds, instead of binning or voxelization, we can resolve small spatial scales down to the resolution of the simulations. For each halo, NeHOD predicts the positions, velocities, masses, and concentrations of its central and satellite galaxies. We train NeHOD on the TNG-Warm DM suite of the DREAMS project, which consists of 1024 high-resolution zoom-in hydrodynamic simulations of Milky Way-mass halos with varying warm DM mass and astrophysical parameters. We show that our model captures the complex relationships between subhalo properties as a function of the simulation parameters, including the mass functions, stellar-halo mass relations, concentration-mass relations, and spatial clustering. Our method can be used for a large variety of downstream applications, from galaxy clustering to strong lensing studies.
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Submitted 4 September, 2024;
originally announced September 2024.
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Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine learning and Simulations
Authors:
Jonah C. Rose,
Paul Torrey,
Francisco Villaescusa-Navarro,
Mariangela Lisanti,
Tri Nguyen,
Sandip Roy,
Kassidy E. Kollmann,
Mark Vogelsberger,
Francis-Yan Cyr-Racine,
Mikhail V. Medvedev,
Shy Genel,
Daniel Anglés-Alcázar,
Nitya Kallivayalil,
Bonny Y. Wang,
Belén Costanza,
Stephanie O'Neil,
Cian Roche,
Soumyodipta Karmakar,
Alex M. Garcia,
Ryan Low,
Shurui Lin,
Olivia Mostow,
Akaxia Cruz,
Andrea Caputo,
Arya Farahi
, et al. (5 additional authors not shown)
Abstract:
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 -- f…
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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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Submitted 1 May, 2024;
originally announced May 2024.
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Brightest Cluster Galaxy Offsets in Cold Dark Matter
Authors:
Cian Roche,
Michael McDonald,
Josh Borrow,
Mark Vogelsberger,
Xuejian Shen,
Volker Springel,
Lars Hernquist,
Ruediger Pakmor,
Sownak Bose,
Rahul Kannan
Abstract:
The distribution of offsets between the brightest cluster galaxies of galaxy clusters and the centroid of their dark matter distributions is a promising probe of the underlying dark matter physics. In particular, since this distribution is sensitive to the shape of the potential in galaxy cluster cores, it constitutes a test of dark matter self-interaction on the largest mass scales in the univers…
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The distribution of offsets between the brightest cluster galaxies of galaxy clusters and the centroid of their dark matter distributions is a promising probe of the underlying dark matter physics. In particular, since this distribution is sensitive to the shape of the potential in galaxy cluster cores, it constitutes a test of dark matter self-interaction on the largest mass scales in the universe. We examine these offsets in three suites of modern cosmological simulations; IllustrisTNG, MillenniumTNG and BAHAMAS. For clusters above $10^{14}\rm{M_\odot}$, we examine the dependence of the offset distribution on gravitational softening length, the method used to identify centroids, redshift, mass, baryonic physics, and establish the stability of our results with respect to various nuisance parameter choices. We find that offsets are overwhelmingly measured to be smaller than the minimum converged length scale in each simulation, with a median offset of $\sim1\rm{kpc}$ in the highest resolution simulation considered, TNG300-1, which uses a gravitational softening length of $1.48\rm{kpc}$. We also find that centroids identified via source extraction on smoothed dark matter and stellar particle data are consistent with the potential minimum, but that observationally relevant methods sensitive to cluster strong gravitational lensing scales, or those using gas as a tracer for the potential can overestimate offsets by factors of $\sim10$ and $\sim30$, respectively. This has the potential to reduce tensions with existing offset measurements which have served as evidence for a nonzero dark matter self-interaction cross section.
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Submitted 5 August, 2024; v1 submitted 1 February, 2024;
originally announced February 2024.
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The Escape Velocity Profile of the Milky Way from Gaia DR3
Authors:
Cian Roche,
Lina Necib,
Tongyan Lin,
Xiaowei Ou,
Tri Nguyen
Abstract:
The escape velocity profile of the Milky Way offers a crucial and independent measurement of its underlying mass distribution and dark matter properties. Using a sample of stars from Gaia DR3 with 6D kinematics and strict quality cuts, we obtain an escape velocity profile of the Milky Way from 4 kpc to 11 kpc in Galactocentric radius. To infer the escape velocity in radial bins, we model the tail…
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The escape velocity profile of the Milky Way offers a crucial and independent measurement of its underlying mass distribution and dark matter properties. Using a sample of stars from Gaia DR3 with 6D kinematics and strict quality cuts, we obtain an escape velocity profile of the Milky Way from 4 kpc to 11 kpc in Galactocentric radius. To infer the escape velocity in radial bins, we model the tail of the stellar speed distribution with both traditional power law models and a new functional form that we introduce. While power law models tend to rely on extrapolation to high speeds, we find our new functional form gives the most faithful representation of the observed distribution. Using this for the escape velocity profile, we constrain the properties of the Milky Way's dark matter halo modeled as a Navarro-Frenck-White profile. Combined with constraints from the circular velocity at the solar position, we obtain a concentration and mass of $c_{200\rm{c}}^{\rm{DM}} = 13.9^{+6.2}_{-4.3}$ and $\rm{M}_{200\rm{c}}^{\rm{DM}} = 0.55^{+0.15}_{-0.14}\times 10^{12} M_\odot$. This corresponds to a total Milky Way mass of $\rm{M}_{200\rm{c}} = 0.64^{+0.15}_{-0.14}\times 10^{12} M_\odot$, which is on the low end of the historic range of the Galaxy's mass, but in line with other recent estimates.
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Submitted 31 January, 2024;
originally announced February 2024.
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Testing Progenitor Models Using the Late-Time Light Curve of Supernova 1992A
Authors:
Cian Roche,
Peter Garnavich
Abstract:
The dominant radioactive energy source powering Type Ia supernova light curves is expected to switch from the decay of $^{56}$Co to $^{57}$Co at very late epochs. We use archival HST images of SN1992A obtained more than 900 days after explosion to constrain its cobalt isotopic abundance ratio and compare it to the well-studied event SN2011fe. We confirm the $^{57}$Co / $^{56}$Co ratio for SN2011fe…
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The dominant radioactive energy source powering Type Ia supernova light curves is expected to switch from the decay of $^{56}$Co to $^{57}$Co at very late epochs. We use archival HST images of SN1992A obtained more than 900 days after explosion to constrain its cobalt isotopic abundance ratio and compare it to the well-studied event SN2011fe. We confirm the $^{57}$Co / $^{56}$Co ratio for SN2011fe of $0.026\pm 0.004$ found by arXiv:1608.01155, consistent with a "double degenerate" progenitor scenario. For SN1992A, we find a ratio of $0.034\pm 0.010$, but the large uncertainty does not allow us to differentiate between progenitor models
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Submitted 18 November, 2020;
originally announced November 2020.