Search for: All records

Abstract In this work, we study how the abundance and dynamics of populations of disrupting satellite galaxies change systematically as a function of host galaxy properties. We apply a theoretical model of the phase-mixing process to classify intact satellite galaxies and stellar streamlike and shell-like debris in ∼1500 Milky Way–mass systems generated by a semi-analytic galaxy formation code,SatGen. In particular, we test the effect of host galaxy halo mass, disk mass, ratio of disk scale height to length, and stellar feedback model on disrupting satellite populations. We find that the counts of tidal debris are consistent across all host galaxy models, within a given host mass range, and that all models can have streamlike debris on low-energy orbits, consistent with that observed around the Milky Way. However, we find a preference for streamlike debris on lower-energy orbits in models with a thicker (lower-density) host disk or on higher-energy orbits in models with a more massive host disk. Importantly, we observe significant halo-to-halo variance across all models. These results highlight the importance of simulating and observing large samples of Milky Way–mass galaxies and accounting for variations in host properties when using disrupting satellites in studies of near-field cosmology. 

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 Galaxies like the Milky Way are surrounded by complex populations of satellites at all stages of tidal disruption. In this paper, we present a dynamical study of the disrupting satellite galaxies in the Auriga simulations that are orbiting 28 distinct Milky Way-mass hosts across three resolutions. We find that the satellite galaxy populations are highly disrupted. The majority of satellites that remain fully intact at present day were accreted recently without experiencing more than one pericentre ($$n_{\rm peri} \lesssim 1$$) and have large apocentres ($$r_{\rm apo} \gtrsim 200 \mathrm{\, kpc}$$) and pericentres ($$r_{\rm peri} \gtrsim 50 \mathrm{\, kpc}$$). The remaining satellites have experienced significant tidal disruption and, given full knowledge of the system, would be classified as stellar streams. We find stellar streams in Auriga across the range of pericentres and apocentres of the known Milky Way dwarf galaxy streams and, interestingly, overlapping significantly with the Milky Way intact satellite population. We find no significant change in satellite orbital distributions across resolution. However, we do see substantial halo-to-halo variance of $$(r_\text{peri}, r_\text{apo})$$ distributions across host galaxies, as well as a dependence of satellite orbits on host halo mass–systems disrupt at larger pericentres and apocentres in more massive hosts. Our results suggest that either cosmological simulations (including, but not limited to, Auriga) are disrupting satellites far too readily, or that the Milky Way’s satellites are more disrupted than current imaging surveys have revealed. Future observing facilities and careful mock observations of these systems will be key to revealing the nature of this apparent discrepancy. 

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.