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ABSTRACT The dark matter (DM) distribution in dwarf galaxies provides crucial insights into both structure formation and the particle nature of DM. GraphNPE (Graph Neural Posterior Estimator), first introduced in Nguyen et al. (2023), is a novel simulation-based inference framework that combines graph neural networks and normalizing flows to infer the DM density profile from line-of-sight stellar velocities. Here, we apply GraphNPE to satellite dwarf galaxies in the FIRE-2 Latte simulation suite of Milky Way-mass haloes, testing it against both Cold and Self-Interacting DM scenarios. Our method demonstrates superior precision compared to conventional Jeans-based approaches, recovering DM density profiles to within the 95 per cent confidence level even in systems with as few as 30 tracers. Moreover, we present the first evaluation of mass modelling methods in constraining two key parameters from realistic simulations: the peak circular velocity, $$V_\mathrm{max}$$, and the peak virial mass, $$M_\mathrm{200m}^\mathrm{peak}$$. Using only line-of-sight velocities, GraphNPE can reliably recover both $$V_\mathrm{max}$$ and $$M_\mathrm{200m}^\mathrm{peak}$$ within our quoted uncertainties, including those experiencing tidal effects ($$\gtrsim 63~{{\rm per\ cent}}$$ of systems are recovered within our 68 per cent confidence intervals and $$\gtrsim 92~{{\rm per\ cent}}$$ within our 95 per cent confidence intervals). The method achieves $$10-20~{{\rm per\ cent}}$$ accuracy in $$V_\mathrm{max}$$ recovery, while $$M_\mathrm{200m}^\mathrm{peak}$$ is recovered to $$0.1-0.4 \, \mathrm{dex}$$ accuracy. This work establishes GraphNPE as a robust tool for inferring DM density profiles in dwarf galaxies, offering promising avenues for constraining DM models. The framework’s potential extends beyond this study, as it can be adapted to non-spherical and disequilibrium models, showcasing the broader utility of simulation-based inference and graph-based learning in astrophysics. 

Abstract We utilize the cosmological volume simulation FIREbox to investigate how a galaxy’s environment influences its size and dark matter content. Our study focuses on approximately 1200 galaxies (886 central and 332 satellite halos) in the low-mass regime, with stellar masses between 10⁶and 10⁹M_⊙. We analyze the size–mass relation (r₅₀–M_⋆), the inner dark matter mass–stellar mass ( $M_{\mathrm{DM}}^{50}$–M_⋆) relation, and the halo mass–stellar mass (M_halo–M_⋆) relation. At fixed stellar mass, we find that galaxies experiencing stronger tidal influences, indicated by higher Perturbation Indices (PI > 1) are generally larger and have lower halo masses relative to their counterparts with lower Perturbation Indices (PI < 1). Applying a Random Forest regression model, we show that both the environment (PI) and halo mass (M_halo) are significant predictors of a galaxy’s relative size and dark matter content. Notably, becauseM_halois also strongly affected by the environment, our findings indicate that environmental conditions not only influence galactic sizes and relative inner dark matter content directly, but also indirectly, through their impact on halo mass. Our results highlight a critical interplay between environmental factors and halo mass in shaping galaxy properties, affirming the environment as a fundamental driver in galaxy formation and evolution. 

Abstract Measurements of the accelerations of stars enabled by time-series extreme-precision spectroscopic observations, pulsar timing, and eclipsing binary stars in the solar neighborhood offer insights into the mass distribution of the Milky Way that do not rely on traditional equilibrium modeling. Given the measured accelerations, we can determine a total mass density and infer the amount of dark matter (DM) by accounting for the mass in stars, gas, and dust. Leveraging FIRE-2 simulations of Milky Way–mass galaxies we compare vertical acceleration profiles between cold DM (CDM) and self-interacting DM (SIDM) with a constant cross section of 1 cm²g⁻¹across three halos with diverse assembly histories. Notably, significant asymmetries in vertical acceleration profiles near the midplane at fixed radii are observed in both CDM and SIDM, particularly in halos recently affected by mergers with satellites of Sagittarius/SMC-like masses or greater. These asymmetries offer a unique window into exploring the merger history of a galaxy. We show that SIDM halos manifest a more oblate shape and consistently exhibit higher local stellar and DM densities and steeper vertical acceleration gradients, up to 10%–30% steeper near the solar neighborhood. However, similar magnitude changes can arise from azimuthal variations in the baryonic components at a fixed radius and external influences like mergers, making it difficult to distinguish between CDM and SIDM using acceleration measurements in a single galaxy. 

Abstract We analyze the first cosmological baryonic zoom-in simulations of galaxies in dissipative self-interacting dark matter (dSIDM). The simulations utilize the FIRE-2 galaxy formation physics with the inclusion of dissipative dark matter self-interactions modeled as a constant fractional energy dissipation (f_diss= 0.75). In this paper, we examine the properties of dwarf galaxies withM_*∼ 10⁵–10⁹M_⊙in both isolation and within Milky Way–mass hosts. For isolated dwarfs, we find more compact galaxy sizes and promotion of disk formation in dSIDM with (σ/m) ≤ 1 cm²g⁻¹. On the contrary, models with (σ/m) = 10 cm²g⁻¹produce puffier stellar distributions that are in tension with the observed size–mass relation. In addition, owing to the steeper central density profiles, the subkiloparsec circular velocities of isolated dwarfs when (σ/m) ≥ 0.1 cm²g⁻¹are enhanced by about a factor of 2, which are still consistent with the kinematic measurements of Local Group dwarfs but in tension with the Hirotation curves of more massive field dwarfs. Meanwhile, for satellites of Milky Way–mass hosts, the median circular velocity profiles are marginally affected by dSIDM physics, but dSIDM may help promote the structural diversity of dwarf satellites. The number of satellites is slightly enhanced in dSIDM, but the differences are small compared with the large host-to-host variations. In conclusion, the dSIDM models with (σ/m) ≳ 0.1 cm²g⁻¹,f_diss= 0.75 are in tension in massive dwarfs (M_halo∼ 10¹¹M_⊙) due to circular velocity constraints. However, models with lower effective cross sections (at this halo mass/velocity scale) are still viable and can produce nontrivial observable signatures. 

Abstract We introduce the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) project, an innovative approach to understanding the astrophysical implications of alternative dark matter (DM) models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over DM 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 (WDM), each comprising 1024 simulations generated using thearepocode. One suite consists of uniform-box simulations covering a ${\left(25h^{-1}\mathrm{Mpc}\right)}^3$volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the WDM 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 DM and baryonic physics on galactic properties. The DREAMS project can be extended further to include different DM 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 DM on these scales. 

ABSTRACT In this paper, we construct the circular velocity curve of the Milky Way out to ∼30 kpc, providing an updated model of the dark matter density profile. We derive precise parallaxes for 120 309 stars with a data-driven model, using APOGEE DR17 spectra combined with GaiaDR3, 2MASS, and WISE photometry. At outer galactic radii up to 30 kpc, we find a significantly faster decline in the circular velocity curve compared to the inner parts. This decline is better fit with a cored Einasto profile with a slope parameter $$0.91^{+0.04}_{-0.05}$$ than a generalized Navarro–Frenk–White (NFW) profile. The virial mass of the best-fitting dark matter halo profile is only $$1.81^{+0.06}_{-0.05}\times 10^{11}$$ M⊙, significantly lower than what a generalized NFW profile delivers. We present a study of the potential systematics, affecting mainly large radii. Such a low mass for the Galaxy is driven by the functional forms tested, given that it probes beyond our measurements. It is found to be in tension with mass measurements from globular clusters, dwarf satellites, and streams. Our best-fitting profile also lowers the expected dark matter annihilation signal flux from the galactic centre by more than an order of magnitude, compared to an NFW profile-fit. In future work, we will explore profiles with more flexible functional forms to more fully leverage the circular velocity curve and observationally constrain the properties of the Milky Way’s dark matter halo. 

Abstract The third data release (DR3) of Gaia has provided a fivefold increase in the number of radial velocity measurements of stars, as well as a stark improvement in parallax and proper motion measurements. To help with studies that seek to test models and interpret Gaia DR3, we present nine Gaia synthetic surveys, based on three solar positions in three Milky Way-mass galaxies of theLattesuite of theFire-2 cosmological simulations. These synthetic surveys match the selection function, radial velocity measurements, and photometry of Gaia DR3, adapting the code baseAnanke, previously used to match the Gaia DR2 release by Sanderson et al. The synthetic surveys are publicly available and can be found athttp://ananke.hub.yt/. Similarly to the previous release ofAnanke, these surveys are based on cosmological simulations and thus are able to model nonequilibrium dynamical effects, making them a useful tool in testing and interpreting Gaia DR3. 

Abstract The Hercules ultrafaint dwarf galaxy (UFD) has long been hypothesized to be tidally disrupting, yet no conclusive evidence has been found for tidal disruption owing partly to difficulties in identifying Hercules member stars. In this work, we present a homogeneous reanalysis of new and existing observations of Hercules, including the detection of a new potential member star located ∼1° (∼1.7 kpc) west of the center of the system. In addition to measuring the line-of-sight velocity gradient, we compare predictions from dynamical models of stream formation to these observations. We report an updated velocity dispersion measurement based on 28 stars, ${1.9}_{-0.6}^{+0.6}$km s⁻¹, which is significantly lower than previous measurements. We find that the line-of-sight velocity gradient is ${1.8}_{-1.8}^{+1.8}$km s⁻¹kpc along the major axis of Hercules, consistent with zero within 1σ. Our dynamical models of stream formation, on the other hand, can reproduce the morphology of the Hercules UFD, specifically the misalignment between the elongation and the orbital motion direction. Additionally, these dynamical models indicate that any radial velocity gradient from tidal disruption would be too small, ${0.00}_{-0.91}^{+0.97}$km s⁻¹kpc, to be detectable with current sample sizes. Combined with our analysis of the tidal radius evolution of the system as a function of its orbital phase, we argue that it is likely that Hercules is indeed currently undergoing tidal disruption in its extended stellar halo with a line-of-sight velocity gradient too small to be detected with current observational data sets. 

ABSTRACT Understanding local stellar kinematic substructures in the solar neighbourhood helps build a complete picture of the formation of the Milky Way, as well as an empirical phase space distribution of dark matter that would inform detection experiments. We apply the clustering algorithm hdbscan on the Gaia early third data release to identify a list of stable clusters in velocity space and action-angle space by taking into account the measurement uncertainties and studying the stability of the clustering results. We find 1405 (497) stars in 23 (6) robust clusters in velocity space (action-angle space) that are consistently not associated with noise. We discuss the kinematic properties of these structures and study whether many of the small clusters belong to a similar larger cluster based on their chemical abundances. They are attributed to the known structures: the Gaia Sausage-Enceladus, the Helmi Stream, and globular cluster NGC 3201 are found in both spaces, while NGC 104 and the thick disc (Sequoia) are identified in velocity space (action-angle space). Although we do not identify any new structures, we find that the hdbscan member selection of already known structures is unstable to input kinematics of the stars when resampled within their uncertainties. We therefore present the stable subset of local kinematic structures, which are consistently identified by the clustering algorithm, and emphasize the need to take into account error propagation during both the manual and automated identification of stellar structures, both for existing ones as well as future discoveries.