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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 ($r_{\rm apo} \gtrsim 200$ kpc) and pericentres ($r_{\rm peri} \gtrsim 50$ 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., Comment: 16 pages, 10 figures, 1 table, submitted to MNRAS

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, stellar stream-like 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 stream-like debris on low-energy orbits, consistent with those observed around the Milky Way. However, we find a preference for stream-like 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., Comment: 18+6 pages, 10+2 figures, code publicly available on GitHub

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., Comment: Submitted to ApJ; 30 + 6 pages; 11 + 4 figures; Comments welcomed

Observations of the Milky Way's stellar halo find that it is predominantly comprised of a radially-biased population of stars, dubbed the Gaia Sausage--Enceladus, or GSE. These stars are thought to be debris from dwarf galaxy accretion early in the Milky Way's history. Though typically considered to be from a single merger, it is possible that the GSE debris has multiple sources. To investigate this possibility, we use the IllustrisTNG50 simulation to identify stellar accretion histories in 98 Milky Way analogues -- the largest sample for which such an identification has been performed -- and find GSE-like debris in 32, with two-merger GSEs accounting for a third of these cases. Distinguishing single-merger GSEs from two-merger GSEs is difficult in common kinematic spaces, but differences are more evident through chemical abundances and star formation histories. This is because single-merger GSEs are typically accreted more recently than the galaxies in two-merger GSEs: the median infall times (with 16th and 84th percentiles) are $5.9^{+3.3}_{-2.0}$ and $10.7^{+1.2}_{-3.7}$ Gyr ago for these scenarios, respectively. The systematic shifts in abundances and ages which occur as a result suggest that efforts in modeling these aspects of the stellar halo prove ever-important in understanding its assembly., Comment: 20 pages, 9 figures; 39 pages of appendices with 38 supplementary figures. Comments welcome!

Measurements of the accelerations of stars enabled by time-series extreme-precision spectroscopic observations, from pulsar timing, and from 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 from this, by accounting for the mass in stars, gas, and dust, we can infer the amount of dark matter. Leveraging the FIRE-2 simulations of Milky Way-mass galaxies, we compare vertical acceleration profiles between cold dark matter (CDM) and self-interacting dark matter (SIDM) with constant cross-section of 1 cm$^2$ g$^{-1}$ across 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 consistently exhibit higher local stellar and dark matter densities and steeper vertical acceleration gradients, up to 30% steeper near the Solar Neighborhood. SIDM halos also manifest a more oblate halo shape in the Solar Neighborhood. Furthermore, enhanced precision in acceleration measurements and larger datasets promise to provide better constraints on the local dark matter density, complementing our understanding from kinematic analysis of their distribution within galaxies., Comment: 14 pages, 5 figures, and 2 tables. Submitted to APJ

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., Comment: 28 pages, 8 figures, DREAMS website: https://www.dreams-project.org

While galaxy rotation curves provide one of the most powerful methods for measuring dark matter profiles in the inner regions of rotation-supported galaxies, at the dwarf scale there are factors that can complicate this analysis. Given the expectation of a universal profile in dark matter-only simulations, the diversity of observed rotation curves has become an often-discussed issue in Lambda Cold Dark Matter cosmology on galactic scales. We analyze a suite of Feedback in Realistic Environments (FIRE) simulations of $10^{10}-10^{12}$ $M_\odot$ halos with standard cold dark matter, and compare the true circular velocity to rotation curve reconstructions. We find that, for galaxies with well-ordered gaseous disks, the measured rotation curve may deviate from true circular velocity by at most 10% within the radius of the disk. However, non-equilibrium behavior, non-circular motions, and non-thermal and non-kinetic stresses may cause much larger discrepancies of 50% or more. Most rotation curve reconstructions underestimate the true circular velocity, while some reconstructions transiently over-estimate it in the central few kiloparsecs due to dynamical phenomena. We further demonstrate that the features that contribute to these failures are not always visibly obvious in HI observations. If such dwarf galaxies are included in galaxy catalogs, they may give rise to the appearance of "artificial" rotation curve diversity that does not reflect the true variation in underlying dark matter profiles., Comment: 20 pages, 10 figures

The Hercules ultra-faint 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 re-analysis of new and existing observations of Hercules, including the detection of a new potential member star located $\sim$1 $^{\circ}$ ($\sim1.7$ 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$^{\rm -1}$, 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$^{\rm -1}$ kpc$^{\rm -1}$ along the major axis of Hercules, consistent with zero within 1 $\sigma$. 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, $0.00^{+0.97}_{-0.91}$ km s$^{\rm -1}$ kpc$^{\rm -1}$, 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 datasets., Comment: 21 pages, 11 figures. Accepted for publication in ApJ

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., Comment: 25 pages, 13 figures, comments welcome

Observational studies are finding stars believed to be relics of the earliest stages of hierarchical mass assembly of the Milky Way (i.e., proto-Galaxy). In this work, we contextualize these findings by studying the masses, ages, spatial distributions, morphology, kinematics, and chemical compositions of proto-galaxy populations from the 13 Milky Way (MW)-mass galaxies from the FIRE-2 cosmological zoom-in simulations. Our findings indicate that proto-Milky Way populations: i) can have a stellar mass range between $1\times10^{8}<\mathrm{M}_{\star}<2\times10^{10}[\mathrm{M}_{\odot}]$, a virial mass range between $3\times10^{10}<\mathrm{M}_{\star}<6\times10^{11}[\mathrm{M}_{\odot}]$, and be as young as $8 \lesssim \mathrm{Age} \lesssim 12.8$ [Gyr] ($1\lesssim z \lesssim 6$); ii) are predominantly centrally concentrated, with $\sim50\%$ of the stars contained within $5-10$ kpc; iii) on average show weak but systematic net rotation in the plane of the host's disc at $z=0$ (i.e., $0.25\lesssim\langle\kappa/\kappa_{\mathrm{disc}}\rangle\lesssim0.8$); iv) present [$\alpha$/Fe]-[Fe/H] compositions that overlap with the metal-poor tail of the host's old disc; v) tend to assemble slightly earlier in Local Group-like environments than in systems in isolation. Interestingly, we find that ~60% of the proto-Milky Way galaxies are comprised by 1 dominant system ($1/5\lesssim$M$_{\star}$/M$_{\star,\mathrm{proto-Milky Way}}$$\lesssim4/5$) and 4-5 lower mass systems (M$_{\star}$/M$_{\star,\mathrm{proto-Milky Way}}$$\lesssim1/10$); the other ~40% are comprised by 2 dominant systems and 3-4 lower mass systems. These massive/dominant proto-Milky Way fragments can be distinguished from the lower mass ones in chemical-kinematic samples, but appear (qualitatively) indistinguishable from one another. Our results could help observational studies disentangle if the Milky Way formed from one or two dominant systems., Comment: Accepted in MNRAS. 16 pages, 12 figures and 3 tables

We present the results of a survey meant to assess the opinion of the high-energy physics theory (HET) community on the January 7th postdoc acceptance deadline - specifically, whether there is a preference to shift the deadline to later in January or February. This survey, which served for information-gathering purpose only, is part of a community conversation on the optimal timing of an acceptance deadline and whether the community would be better served by a later date. In addition, we present an analysis of data from the postdoc Rumor Mill, which gives a picture of the current hiring landscape in the field. We emphasize the importance of preserving a universal deadline, and the current results of our survey show broad support for a shift to a later date. A link to the survey, frequently asked questions, a running list of supporters, and next steps can be found on our companion web page., Comment: 13 pages, 8 figures and 2 tables webpage: https://het-postdoc-accord.github.io/information/

The third data release (DR3) of Gaia has provided a five-fold 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 the Latte suite of the Fire-2 cosmological simulations. These synthetic surveys match the selection function, radial velocity measurements, and photometry of Gaia DR3, adapting the code base Ananke, previously used to match the Gaia DR2 release in Sanderson et al. 2020. The synthetic surveys are publicly available and can be found at http://ananke.hub.yt/. Similarly to the previous release of Ananke, these surveys are based on cosmological simulations and thus able to model non-equilibrium dynamical effects, making them a useful tool in testing and interpreting Gaia DR3., Comment: 17 pages, 7 tables, 6 figures

In this paper, we construct the circular velocity curve of the Milky Way out to $\sim 30$ 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 Gaia DR3, 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-fit dark matter halo profile is only $1.81^{+0.06}_{-0.05}\times10^{11}$ $M_{\odot}$, 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-fit 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., Comment: 17 pages, 11 figures. Fixed typos, updated values, and included additional analyses

We present an update to Via Machinae, an automated stellar stream-finding algorithm based on the deep learning anomaly detector ANODE. Via Machinae identifies stellar streams within Gaia, using only angular positions, proper motions, and photometry, without reference to a model of the Milky Way potential for orbit integration or stellar distances. This new version, Via Machinae 2.0, includes many improvements and refinements to nearly every step of the algorithm, that altogether result in more robust and visually distinct stream candidates than our original formulation. In this work, we also provide a quantitative estimate of the false positive rate of Via Machinae 2.0 by applying it to a simulated Gaia-mock catalog based on Galaxia, a smooth model of the Milky Way that does not contain substructure or stellar streams. Finally, we perform the first full-sky search for stellar streams with Via Machinae 2.0, identifying 102 streams at high significance within the Gaia Data Release 2, of which only 10 have been previously identified. While follow-up observations for further confirmation are required, taking into account the false positive rate presented in this work, we expect approximately 90 of these stream candidates to correspond to real stellar structures., Comment: 22 pages, 24 figures

In the $\Lambda$-Cold Dark Matter model of the Universe, galaxies form in part through accreting satellite systems. Previous work have built an understanding of the signatures of these processes contained within galactic stellar halos. This work revisits that picture using seven Milky Way-like galaxies in the \textit{Latte} suite of FIRE-2 cosmological simulations. The resolution of these simulations allows a comparison of contributions from satellites above M$_{*}$$\gtrsim$10$\times$$^{7}$M$_{\odot}$, enabling the analysis of observable properties for disrupted satellites in a fully self-consistent and cosmological context. Our results show that, the time of accretion and the stellar mass of an accreted satellite are fundamental parameters that in partnership dictate the resulting spatial distribution, orbital energy, and [$\alpha$/Fe]-[Fe/H] compositions of the stellar debris of such mergers $at$ $present$ $day$. These parameters also govern the resulting dynamical state of an accreted galaxy at $z=0$, leading to the expectation that the inner regions of the stellar halo (R$_{\mathrm{GC}}$ $\lesssim$30 kpc) should contain fully phase-mixed debris from both lower and higher mass satellites. In addition, we find that a significant fraction of the lower mass satellites accreted at early times deposit debris in the outer halo (R$_{\mathrm{GC}}$ $>$50 kpc) that are $not$ fully phased-mixed, indicating that they could be identified in kinematic surveys. Our results suggest that, as future surveys become increasingly able to map the outer halo of our Galaxy, they may reveal the remnants of long-dead dwarf galaxies whose counterparts are too faint to be seen $in$ $situ$ in higher redshift surveys., Comment: Submitted for publication in ApJ

Nyx is a nearby, prograde, and high-eccentricity stellar stream physically contained in the thick disk but with an unknown origin. Nyx could be the remnant of a disrupted dwarf galaxy, in which case the associated dark matter substructure could affect terrestrial dark matter direct detection experiments. Alternatively, Nyx could be a signature of the Milky Way's disk formation and evolution. To determine the origin of Nyx, we obtained high-resolution spectroscopy of 34 Nyx stars using Keck/HIRES and Magellan/MIKE. A differential chemical abundance analysis shows that most Nyx stars reside in a metal-rich ($\mbox{[Fe/H]} > -1$) high-$\alpha$ component that is chemically indistinguishable from the thick disk. This rules out an originally suggested scenario that Nyx is the remnant of a single massive dwarf galaxy merger. However, we also identify five substantially more metal-poor stars ($\mbox{[Fe/H]} \sim -2.0$) that have chemical abundances similar to the metal-weak thick disk. It remains unclear how stars chemically identical to the thick disk can be on such prograde, high-eccentricity orbits. We suggest two most likely scenarios: that Nyx is the result of an early minor dwarf galaxy merger or that it is a record of the early spin-up of the Milky Way disk -- although neither perfectly reproduces the chemodynamic observations. The most likely formation scenarios suggest that future spectroscopic surveys should find Nyx-like structures outside of the Solar Neighborhood., Comment: 25 pages, 6 figures, Appendix by Shuyu Wang, accepted by the Astrophysical Journal on July 29, 2023

Dwarf galaxies are small, dark matter-dominated galaxies, some of which are embedded within the Milky Way. Their lack of baryonic matter (e.g., stars and gas) makes them perfect test beds for probing the properties of dark matter -- understanding the spatial dark matter distribution in these systems can be used to constrain microphysical dark matter interactions that influence the formation and evolution of structures in our Universe. We introduce a new method that leverages simulation-based inference and graph-based machine learning in order to infer the dark matter density profiles of dwarf galaxies from observable kinematics of stars gravitationally bound to these systems. Our approach aims to address some of the limitations of established methods based on dynamical Jeans modeling. We show that this novel method can place stronger constraints on dark matter profiles and, consequently, has the potential to weigh in on some of the ongoing puzzles associated with the small-scale structure of dark matter halos, such as the core-cusp discrepancy., Comment: 9 + 11 pages, 4 + 9 figures

We present the first detailed study comparing the populations of stellar streams in cosmological simulations to observed Milky Way dwarf galaxy streams. In particular, we compare streams identified around Milky Way analogs in the FIRE-2 simulations to stellar streams observed by the Southern Stellar Stream Spectroscopic Survey (S5). For an accurate comparison between the stream populations, we produce mock Dark Energy Survey (DES) observations of the FIRE streams and estimate the detectability of their tidal tails and progenitors. The number and stellar mass distributions of detectable stellar streams is consistent between observations and simulations. However, there are discrepancies in the distributions of pericenters and apocenters, with the detectable FIRE streams, on average, forming at larger pericenters (out to > 110 kpc) and surviving only at larger apocenters (> 40 kpc) than those observed in the Milky Way. We find that the population of high-stellar mass dwarf galaxy streams in the Milky Way is incomplete. Interestingly, a large fraction of the FIRE streams would only be detected as satellites in DES-like observations, since their tidal tails are too low-surface brightness to be detectable. We thus predict a population of yet-undetected tidal tails around Milky Way satellites, as well as a population of fully undetected low surface brightness stellar streams, and estimate their detectability with the Rubin Observatory. Finally, we discuss the causes and implications of the discrepancies between the stream populations in FIRE and the Milky Way, and explore future avenues for tests of satellite disruption in cosmological simulations., Comment: 24 pages, 13 figures, 3 tables, submitted to ApJ

We apply the clustering algorithm HDBSCAN on the Gaia early third data release astrometry combined with the Gaia second data release radial velocity measurements of almost 5.5 million stars to identify the local stellar kinematic substructures in the solar neighborhood. Understanding these structures helps build a more 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. The main goal of this study is to provide a list of the most stable clusters, by taking into account the measurement uncertainties and studying the stability of the clustering results. We apply the clustering algorithm in two spaces, in velocity space in order to study recently accreted structures, and in action-angle space to find phase-mixed structures. We find 23 (6) robust clusters in velocity space (action-angle space) that are consistently not associated with noise. 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 disk (Sequoia) are identified in velocity space (action-angle space). 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. 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 most 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. (abridged), Comment: 35 pages, 16 figures. Comments are welcome

We analyze the first set of 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 modelled as a constant fractional energy dissipation ($f_{\rm diss}=0.5$). In this paper, we examine the properties of dwarf galaxies with $M_{\ast} \sim 10^{5}\operatorname{-}10^{9}\,{\rm M}_{\odot}$ in both isolation and within Milky Way-mass hosts. For isolated dwarfs, we find more compact galaxy sizes and promotion of stellar/neutral gas disk formation in dSIDM with $(\sigma/m)\leq 1\,{\rm cm^2\,g^{-1}}$ but they are still consistent with observed galaxy sizes and masses. In addition, as a result of the steeper central density profiles developed in dSIDM, the sub-kpc circular velocities of isolated dwarfs in models with $(\sigma/m)\geq 0.1\,{\rm cm^2\,g^{-1}}$ are enhanced by about a factor of two, which are still consistent with the measured stellar velocity dispersions of Local Group dwarfs but in tension with the HI rotation curves of more massive field dwarfs. Meanwhile, for satellites of the simulated Milky Way-mass hosts, the median circular velocity profiles are marginally affected by dSIDM physics, but dSIDM may help address the missing compact dwarf satellites in CDM. 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 constant cross-section $(\sigma/m) \gtrsim 0.1\,{\rm cm^2\,g^{-1}}$ (assuming $f_{\rm diss}=0.5$) are effectively ruled out in bright dwarfs ($M_{\rm halo}\sim 10^{11}\,{\rm M}_{\odot}$) by circular velocity constraints. However, models with lower effective cross-sections (at this halo mass/velocity scale) are still viable and can give rise to non-trivial observable signatures., Comment: To be submitted to MNRAS. 18 pages, 12 figures

Little is known about the origin of the fastest stars in the Galaxy. Our understanding of the Milky Way and surrounding dwarf galaxies chemical evolution history allows us to use the chemical composition of a star to investigate its origin, and say whether a star was formed in-situ or was accreted. However, the fastest stars, the hypervelocity stars, are young and massive and their chemical composition has not yet been analyzed. Though it is difficult to analyze the chemical composition of a massive young star, we are well versed in the analysis of late-type stars. We have used high-resolution ARCES/3.5m Apache Point Observatory, MIKE/Magellan spectra to study the chemical details of 15 late-type hypervelocity stars candidates. With Gaia EDR3 astrometry and spectroscopically determined radial velocities we found total velocities with a range of $274$ - $520$ km s$^{-1}$ and mean value of $381$ km s$^{-1}$. Therefore, our sample stars are not fast enough to be classified as Hypervelocity stars, and are what is known as extreme-velocity stars. Our sample has a wide iron abundance range of $-2.5 \le \mathrm{[Fe/H]} \le -0.9$. Their chemistry indicate that at least 50\% of them are accreted extragalactic stars, with iron-peak elements consistent with prior sub-Chandrasekhar mass type Ia supernova enrichment. Without indication of binary companions, their chemical abundances and orbital parameters are indicative that they are the accelerated tidal debris of disrupted dwarf galaxies., Comment: Accepted for publication at AJ; 23 pages; 6 Figures; 4 Tables

Over the past several decades, unexpected astronomical discoveries have been fueling a new wave of particle model building and are inspiring the next generation of ever-more-sophisticated simulations to reveal the nature of Dark Matter (DM). This coincides with the advent of new observing facilities coming online, including JWST, the Rubin Observatory, the Nancy Grace Roman Space Telescope, and CMB-S4. The time is now to build a novel simulation program to interpret observations so that we can identify novel signatures of DM microphysics across a large dynamic range of length scales and cosmic time. This white paper identifies the key elements that are needed for such a simulation program. We identify areas of growth on both the particle theory side as well as the simulation algorithm and implementation side, so that we can robustly simulate the cosmic evolution of DM for well-motivated models. We recommend that simulations include a fully calibrated and well-tested treatment of baryonic physics, and that outputs should connect with observations in the space of observables. We identify the tools and methods currently available to make predictions and the path forward for building more of these tools. A strong cosmic DM simulation program is key to translating cosmological observations to robust constraints on DM fundamental physics, and provides a connection to lab-based probes of DM physics., Comment: Contribution to Snowmass 2021

This whitepaper focuses on the astrophysical systematics which are encountered in dark matter searches. Oftentimes in indirect and also in direct dark matter searches, astrophysical systematics are a major limiting factor to sensitivity to dark matter. Just as there are many forms of dark matter searches, there are many forms of backgrounds. We attempt to cover the major systematics arising in dark matter searches using photons -- radio and gamma rays -- to cosmic rays, neutrinos and gravitational waves. Examples include astrophysical sources of cosmic messengers and their interactions which can mimic dark matter signatures. In turn, these depend on commensurate studies in understanding the cosmic environment -- gas distributions, magnetic field configurations -- as well as relevant nuclear astrophysics. We also cover the astrophysics governing celestial bodies and galaxies used to probe dark matter, from black holes to dwarf galaxies. Finally, we cover astrophysical backgrounds related to probing the dark matter distribution and kinematics, which impact a wide range of dark matter studies. In the future, the rise of multi-messenger astronomy, and novel analysis methods to exploit it for dark matter, will offer various strategic ways to continue to enhance our understanding of astrophysical backgrounds to deliver improved sensitivity to dark matter., Comment: contribution to Snowmass 2021

Increasingly, uncertainties in predictions from galaxy formation simulations (at sub-Milky Way masses) are dominated by uncertainties in stellar evolution inputs. In this paper, we present the full set of updates from the FIRE-2 version of the Feedback In Realistic Environments (FIRE) project code, to the next version, FIRE-3. While the transition from FIRE-1 to FIRE-2 focused on improving numerical methods, here we update the stellar evolution tracks used to determine stellar feedback inputs, e.g. stellar mass-loss (O/B and AGB), spectra (luminosities and ionization rates), and supernova rates (core-collapse and Ia), as well as detailed mass-dependent yields. We also update the low-temperature cooling and chemistry, to enable improved accuracy at $T \lesssim 10^{4}\,$K and densities $n\gg 1\,{\rm cm^{-3}}$, and the meta-galactic ionizing background. All of these synthesize newer empirical constraints on these quantities and updated stellar evolution and yield models from a number of groups, addressing different aspects of stellar evolution. To make the updated models as accessible as possible, we provide fitting functions for all of the relevant updated tracks, yields, etc, in a form specifically designed so they can be directly 'plugged in' to existing galaxy formation simulations. We also summarize the default FIRE-3 implementations of 'optional' physics, including spectrally-resolved cosmic rays and supermassive black hole growth and feedback., Comment: 26 pages, 12 figures. Submitted to MNRAS. Comments welcome

We use FIRE-2 zoom cosmological simulations of Milky Way size galaxy halos to calculate astrophysical J-factors for dark matter annihilation and indirect detection studies. In addition to velocity-independent (s-wave) annihilation cross sections $\sigma_v$, we also calculate effective J-factors for velocity-dependent models, where the annihilation cross section is either either p-wave ($\propto v^2/c^2$) or d-wave ($\propto v^4/c^4$). We use 12 pairs of simulations, each run with dark-matter-only (DMO) physics and FIRE-2 physics. We observe FIRE runs produce central dark matter velocity dispersions that are systematically larger than in DMO runs by factors of $\sim 2.5-4$. They also have a larger range of central ($\sim 400$ pc) dark matter densities than the DMO runs ($\rho_{\rm FIRE}/\rho_{\rm DMO} \simeq 0.5 - 3$) owing to the competing effects of baryonic contraction and feedback. At 3 degrees from the Galactic Center, FIRE J-factors are $5-50$ (p-wave) and $15-500$ (d-wave) times higher than in the DMO runs. The change in s-wave signal at 3 degrees is more modest and can be higher or lower ($\sim 0.3-6$), though the shape of the emission profile is flatter (less peaked towards the Galactic Center) and more circular on the sky in FIRE runs. Our results for s-wave are broadly consistent with the range of assumptions in most indirect detection studies. We observe p-wave J-factors that are significantly enhanced compared to most past estimates. We find that thermal models with p-wave annihilation may be within range of detection in the near future., Comment: 15 pages, 9 figures, submitted to MNRAS

We develop a new machine learning algorithm, Via Machinae, to identify cold stellar streams in data from the Gaia telescope. Via Machinae is based on ANODE, a general method that uses conditional density estimation and sideband interpolation to detect local overdensities in the data in a model agnostic way. By applying ANODE to the positions, proper motions, and photometry of stars observed by Gaia, Via Machinae obtains a collection of those stars deemed most likely to belong to a stellar stream. We further apply an automated line-finding method based on the Hough transform to search for line-like features in patches of the sky. In this paper, we describe the Via Machinae algorithm in detail and demonstrate our approach on the prominent stream GD-1. Though some parts of the algorithm are tuned to increase sensitivity to cold streams, the Via Machinae technique itself does not rely on astrophysical assumptions, such as the potential of the Milky Way or stellar isochrones. This flexibility suggests that it may have further applications in identifying other anomalous structures within the Gaia dataset, for example debris flow and globular clusters., Comment: 17 pages, 17 figures, v2: references added, minor corrections, v3: published version

We present the first set of cosmological baryonic zoom-in simulations of galaxies including dissipative self-interacting dark matter (dSIDM). These simulations utilize the Feedback In Realistic Environments (FIRE-2) galaxy formation physics, but allow the dark matter to have dissipative self-interactions analogous to Standard Model forces, parameterized by the self-interaction cross-section per unit mass, $(\sigma/m)$, and the dimensionless degree of dissipation, $0

Measuring the escape velocity of the Milky Way is critical in obtaining the mass of the Milky Way, understanding the dark matter velocity distribution, and building the dark matter density profile. In Necib $\&$ Lin (2021), we introduced a strategy to robustly measure the escape velocity. Our approach takes into account the presence of kinematic substructures by modeling the tail of the stellar distribution with multiple components, including the stellar halo and the debris flow called the Gaia Sausage (Enceladus). In doing so, we can test the robustness of the escape velocity measurement for different definitions of the "tail" of the velocity distribution, and the consistency of the data with different underlying models. In this paper, we apply this method to the second data release of Gaia and find that a model with at least two components is preferred. Based on a fit with three bound components to account for the disk, relaxed halo, and the Gaia Sausage, we find the escape velocity of the Milky Way at the solar position to be $v_{\rm{esc}}= 484.6^{+17.8}_{-7.4}$ km/s. Assuming a Navarro-Frenck-White dark matter profile, and taken in conjunction with a recent measurement of the circular velocity at the solar position of $v_c = 230 \pm 10$ km/s, we find a Milky Way concentration of $c_{200} = 13.8^{+6.0}_{-4.3}$ and a mass of $M_{200} = 7.0^{+1.9}_{-1.2} \times 10^{11} M_{\odot}$, which is considerably lighter than previous measurements., Comment: 10+7 pages, 7+7 figures

The local escape velocity provides valuable inputs to the mass profile of the Galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard $\&$ Tremaine (1990), various works have since modeled the tail of the stellar speed distribution as $\propto (v_{\rm{esc}} -v)^k$, where $v_{\rm{esc}}$ is the escape velocity, and $k$ is the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed on $k$ in order to constrain $v_{\rm{esc}}$. Furthermore, the validity of the power law form is likely to break down in the presence of multiple kinematic substructures. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws without imposing strong priors. Using mock data, we show the robustness of this method in the presence of kinematic structure that is similar to the recently-discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia DR2 data., Comment: 17+13 pages, 13+14 figures

The Milky Way is surrounded by dozens of ultra-faint (< $10^5$ solar luminosities) dwarf satellite galaxies. They are the surviving remnants of the earliest galaxies, as confirmed by their ancient (~13 billion years old) and chemically primitive stars. Simulations suggest that these systems formed within extended dark matter halos and experienced early galaxy mergers and supernova feedback. However, the signatures of these events would lie outside their core regions (>2 half-light radii), which are spectroscopically unstudied due to the sparseness of their distant stars. Here we identify members of the Tucana II ultra-faint dwarf galaxy in its outer region (up to 9 half-light radii), demonstrating the system to be dramatically more spatially extended and chemically primitive than previously found. These distant stars are extremely metal-poor (<[Fe/H]>=-3.02; less than ~1/1000th of the solar iron abundance), affirming Tucana II as the most metal-poor known galaxy. We observationally establish, for the first time, an extended dark matter halo surrounding an ultra-faint dwarf galaxy out to one kiloparsec, with a total mass of >$10^7$ solar masses. This measurement is consistent with the expected ~2x$10^7$ solar masses using a generalized NFW density profile. The extended nature of Tucana II suggests that it may have undergone strong bursty feedback or been the product of an early galactic merger. We demonstrate that spatially extended stellar populations, which other ultra-faint dwarfs hint at hosting as well, are observable in principle and open the possibility for detailed studies of the stellar halos of relic galaxies., Comment: Published in Nature Astronomy on February 1, 2021 at https://www.nature.com/articles/s41550-020-01285-w. Free read-only access at https://rdcu.be/cezEm

The distribution of dark matter in dwarf galaxies can have important implications on our understanding of galaxy formation as well as the particle physics properties of dark matter. However, accurately characterizing the dark matter content of dwarf galaxies is challenging due to limited data and complex dynamics that are difficult to accurately model. In this paper, we apply spherical Jeans modeling to simulated stellar kinematic data of spherical, isotropic dwarf galaxies with the goal of identifying the future observational directions that can improve the accuracy of the inferred dark matter distributions in the Milky Way dwarf galaxies. We explore how the dark matter inference is affected by the location and number of observed stars as well as the line-of-sight velocity measurement errors. We use mock observation to demonstrate the difficulty in constraining the inner core/cusp of the dark matter distribution with datasets of fewer than 10,000 stars. We also demonstrate the need for additional measurements to make robust estimates of the expected dark matter annihilation signal strength. For the purpose of deriving robust indirect detection constraints, we identify Ursa Major II, Ursa Minor, and Draco as the systems that would most benefit from additional stars being observed., Comment: 27+16 pages, 12+17 figures

Boosted dark matter (BDM) is a well-motivated class of dark matter (DM) candidates in which a small component of DM is relativistic at the present time. We lay the foundation for BDM searches via hadronic interactions in large liquid-argon time-projection chambers (LArTPCs), such as DUNE. We investigate BDM-nucleus scattering in detail by developing new event generation techniques with a parameterized detector simulation. We study the discovery potential in a DUNE-like experiment using the low threshold and directionality of hadron detection in LArTPCs and compare with other experiments., Comment: 14 pages, 4 figures

In previous work, we developed a deep neural network classifier that only relies on phase-space information to obtain a catalog of accreted stars based on the second data release of Gaia (DR2). In this paper, we apply two clustering algorithms to identify velocity substructure within this catalog. We focus on the subset of stars with line-of-sight velocity measurements that fall in the range of Galactocentric radii $r \in [6.5, 9.5]$ kpc and vertical distances $|z| < 3$ kpc. Known structures such as Gaia Enceladus and the Helmi stream are identified. The largest previously-unknown structure, Nyx, is a vast stream consisting of at least 90 stars in the region of interest. This study displays the power of the machine learning approach by not only successfully identifying known features, but also discovering new kinematic structures that may shed light on the merger history of the Milky Way., Comment: 15 + 13 pages, 9 + 15 figures. v2: Minor changes in calculating probabilities to belong to a kinematic structure. Conclusions unchanged

Massive dwarf galaxies that merge with the Milky Way on prograde orbits can be dragged into the disk plane before being completely disrupted. Such mergers can contribute to an accreted stellar disk and a dark matter disk. We present evidence for Nyx, a vast new stellar stream in the vicinity of the Sun, that may provide the first indication that such an event occurred in the Milky Way. We identify about 500 stars that have coherent radial and prograde motion in this stream using a catalog of accreted stars built by applying deep learning methods to the second Gaia data release. Nyx is concentrated within $\pm 2$ kpc of the Galactic midplane and spans the full radial range studied (6.5-9.5 kpc). The kinematics of Nyx stars are distinct from those of both the thin and thick disk. In particular, its rotational speed lags the disk by $\sim 80$ km/s and its stars follow more eccentric orbits. A small number of Nyx stars have chemical abundances or inferred ages; from these, we deduce that Nyx stars have a peak metallicity of [Fe/H] $\sim -0.5$ and ages $\sim $10-13 Gyr. Taken together with the kinematic observations, these results strongly favor the interpretation that Nyx is the remnant of a disrupted dwarf galaxy. To further justify this interpretation, we explicitly demonstrate that metal-rich, prograde streams like Nyx can be found in the disk plane of Milky Way-like galaxies using the FIRE hydrodynamic simulations. Future spectroscopic studies will be able to validate whether Nyx stars originate from a single progenitor., Comment: 8+5 pages, 4+7 figures. Nyx star sample updated with a modified probability calculation, conclusions unchanged. Stellar IDs can be found here https://linoush.github.io/nyx_stream/

The goal of this study is to present the development of a machine learning based approach that utilizes phase space alone to separate the Gaia DR2 stars into two categories: those accreted onto the Milky Way from those that are in situ. Traditional selection methods that have been used to identify accreted stars typically rely on full 3D velocity, metallicity information, or both, which significantly reduces the number of classifiable stars. The approach advocated here is applicable to a much larger portion of Gaia DR2. A method known as "transfer learning" is shown to be effective through extensive testing on a set of mock Gaia catalogs that are based on the FIRE cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies. The machine is first trained on simulated data using only 5D kinematics as inputs and is then further trained on a cross-matched Gaia/RAVE data set, which improves sensitivity to properties of the real Milky Way. The result is a catalog that identifies around 767,000 accreted stars within Gaia DR2. This catalog can yield empirical insights into the merger history of the Milky Way and could be used to infer properties of the dark matter distribution., Comment: v1: 24 pages and 13 Figures + 4 appendices, v2: Journal version, fixed bug resulting in incorrect final catalog scores, updated plots, conclusions unchanged

(Abridged) The Maunakea Spectroscopic Explorer (MSE) is an end-to-end science platform for the design, execution and scientific exploitation of spectroscopic surveys. It will unveil the composition and dynamics of the faint Universe and impact nearly every field of astrophysics across all spatial scales, from individual stars to the largest scale structures in the Universe. Major pillars in the science program for MSE include (i) the ultimate Gaia follow-up facility for understanding the chemistry and dynamics of the distant Milky Way, including the outer disk and faint stellar halo at high spectral resolution (ii) galaxy formation and evolution at cosmic noon, via the type of revolutionary surveys that have occurred in the nearby Universe, but now conducted at the peak of the star formation history of the Universe (iii) derivation of the mass of the neutrino and insights into inflationary physics through a cosmological redshift survey that probes a large volume of the Universe with a high galaxy density. MSE is positioned to become a critical hub in the emerging international network of front-line astronomical facilities, with scientific capabilities that naturally complement and extend the scientific power of Gaia, the Large Synoptic Survey Telescope, the Square Kilometer Array, Euclid, WFIRST, the 30m telescopes and many more., Comment: 9 chapters, 301 pages, 100 figures. This version of the DSC is a comprehensive update of the original version, released in 2016, which can be downloaded at arXiv:1606.00043. A detailed summary of the design of MSE is available in the MSE Book 2018, available at arXiv:1810.08695

Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter., Comment: 11 pages, 2 figures, Science Whitepaper for Astro 2020, more information at https://lsstdarkmatter.github.io

We discuss how astrophysical observations with the Maunakea Spectroscopic Explorer (MSE), a high-multiplexity (about 4300 fibers), wide field-of-view (1.5 square degree), large telescope aperture (11.25 m) facility, can probe the particle nature of dark matter. MSE will conduct a suite of surveys that will provide critical input for determinations of the mass function, phase-space distribution, and internal density profiles of dark matter halos across all mass scales. N-body and hydrodynamical simulations of cold, warm, fuzzy and self-interacting dark matter suggest that non-trivial dynamics in the dark sector could have left an imprint on structure formation. Analysed within these frameworks, the extensive and unprecedented datasets produced by MSE will be used to search for deviations away from cold and collisionless dark matter model. MSE will provide an improved estimate of the local density of dark matter, critical for direct detection experiments, and will improve estimates of the J-factor for indirect searches through self-annihilation or decay into Standard Model particles. MSE will determine the impact of low mass substructures on the dynamics of Milky Way stellar streams in velocity space, and will allow for estimates of the density profiles of the dark matter halos of Milky Way dwarf galaxies using more than an order of magnitude more tracers. In the low redshift Universe, MSE will provide critical redshifts to pin down the luminosity functions of vast numbers of satellite systems, and MSE will be an essential component of future strong lensing measurements to constrain the halo mass function. Across nearly all mass scales, the improvements offered by MSE, in comparison to other facilities, are such that the relevant analyses are limited by systematics rather than statistics., Comment: 44 pages, 19 figures. To appear as a chapter for "The Detailed Science Case for the Maunakea Spectroscopic Explorer, 2019"

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/ ., Comment: 96 pages, 22 figures, 1 table

We briefly comment on the paper "On the correlation between the local dark matter and stellar velocities" (Bozorgnia et al. 2018), which purports to test our previous claims regarding the correlation of stellar and dark matter kinematics (Herzog-Arbeitman et al. 2017; Necib et al. 2018). The conclusions of these papers are not accurately presented in Bozorgnia et al. (2018), and we thus clarify them here., Comment: 1 page

The Gaia era opens new possibilities for discovering the remnants of disrupted satellite galaxies in the Solar neighborhood. If the population of local accreted stars is correlated with the dark matter sourced by the same mergers, one can then map the dark matter distribution directly. Using two cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies from the Latte suite of Fire-2 simulations, we find a strong correlation between the velocity distribution of stars and dark matter at the solar circle that were accreted from luminous satellites. This correspondence holds for dark matter that is either relaxed or in kinematic substructure called debris flow, and is consistent between two simulated hosts with different merger histories. The correspondence is more problematic for streams because of possible spatial offsets between the dark matter and stars. We demonstrate how to reconstruct the dark matter velocity distribution from the observed properties of the accreted stellar population by properly accounting for the ratio of stars to dark matter contributed by individual mergers. After demonstrating this method using the Fire-2 simulations, we apply it to the Milky Way and use it to recover the dark matter velocity distribution associated with the recently discovered stellar debris field in the Solar neighborhood. Based on results from Gaia, we estimate that $42 ^{+26}_{-22}\%$ of the local dark matter that is accreted from luminous mergers is in debris flow., Comment: 18+5 pages, 12+5 figures. Supplementary Data can be found here https://linoush.github.io/DM_Velocity_Distribution/

We use the distribution of accreted stars in SDSS-Gaia DR2 to demonstrate that a non-trivial fraction of the dark matter halo within Galactocentric radii of 7.5-10 kpc and $|z| > 2.5$ kpc is in substructure, and thus may not be in equilibrium. Using a mixture likelihood analysis, we separate the contributions of an old, isotropic stellar halo and a younger anisotropic population. The latter dominates and is uniform within the region studied. It can be explained as the tidal debris of a disrupted massive satellite on a highly radial orbit, and is consistent with mounting evidence from recent studies. Simulations that track the tidal debris from such mergers find that the dark matter traces the kinematics of its stellar counterpart. If so, our results indicate that a component of the nearby dark matter halo that is sourced by luminous satellites is in kinematic substructure referred to as debris flow. These results challenge the Standard Halo Model, which is discrepant with the distribution recovered from the stellar data, and have important ramifications for the interpretation of direct detection experiments., Comment: 17 + 4 pages, 10 + 5 figures. Supplementary Data can be found here: https://linoush.github.io/DM_Velocity_Distribution/ v2: Title updated, small modifications of discussions, results unchanged. Version published in ApJ

We introduce a new jet substructure technique called Recursive Soft Drop, which generalizes the Soft Drop algorithm to have multiple grooming layers. Like the original Soft Drop method, this new recursive variant traverses a jet clustering tree to remove soft wide-angle contamination. By enforcing the Soft Drop condition N times, Recursive Soft Drop improves the jet mass resolution for boosted hadronic objects like W bosons, top quarks, and Higgs bosons. We further show that this improvement in mass resolution persists when including the effects of pileup, up to large pileup multiplicities. In the limit that N goes to infinity, the resulting groomed jets formally have zero catchment area. As an alternative approach, we present a bottom-up version of Recursive Soft Drop which, in its local form, is similar to Recursive Soft Drop and which, in its global form, can be used to perform event-wide grooming., Comment: 20+14 pages, 17 figures, v2 updated to match published version

The local velocity distribution of dark matter plays an integral role in interpreting the results from direct detection experiments. We previously showed that metal-poor halo stars serve as excellent tracers of the virialized dark matter velocity distribution using a high-resolution hydrodynamic simulation of a Milky Way--like halo. In this paper, we take advantage of the first \textit{Gaia} data release, coupled with spectroscopic measurements from the RAdial Velocity Experiment (RAVE), to study the kinematics of stars belonging to the metal-poor halo within an average distance of $\sim 5$ kpc of the Sun. We study stars with iron abundances [Fe/H]$ < -1.5$ and $-1.8$ that are located more than $1.5$ kpc from the Galactic plane. Using a Gaussian mixture model analysis, we identify the stars that belong to the halo population, as well as some kinematic outliers. We find that both metallicity samples have similar velocity distributions for the halo component, within uncertainties. Assuming that the stellar halo velocities adequately trace the virialized dark matter, we study the implications for direct detection experiments. The Standard Halo Model, which is typically assumed for dark matter, is discrepant with the empirical distribution by $\sim6\sigma$ and predicts fewer high-speed particles. As a result, the Standard Halo Model overpredicts the nuclear scattering rate for dark matter masses below $\sim 10$ GeV. The kinematic outliers that we identify may potentially be correlated with dark matter substructure, though further study is needed to establish this correspondence., Comment: v1: 12 pages, 5 figures + Appendix. Supplementary Data can be found here: https://linoush.github.io/DM_Velocity_Distribution/ v2: Version appeared in JCAP, minor updates to the text, Fig 5 updated, conclusions unchanged

In this thesis, I study the expected direct and indirect detection signals of dark matter. More precisely, I study three aspects of dark matter; I use hydrodynamic simulations to extract properties of weakly interacting dark matter that are relevant for both direct and indirect detection signals, and construct viable dark matter models with interesting experimental signatures. First, I analyze the full scale Illustris simulation, and find that Galactic indirect detection signals are expected to be largely symmetric, while extragalactic signals are not, due to recent mergers and the presence of substructure. Second, through the study of the high resolution Milky Way simulation Eris, I find that metal-poor halo stars can be used as tracers for the dark matter velocity distribution. I use the Sloan Digital Sky Survey to obtain the first empirical velocity distribution of dark matter, which weakens the expected direct detection limits by up to an order of magnitude at masses $\lesssim 10$ GeV. Finally, I expand the weakly interacting dark matter paradigm by proposing a new dark matter model called boosted dark matter. This novel scenario contains a relativistic component with interesting hybrid direct and indirect detection signatures at neutrino experiments. I propose two search strategies for boosted dark matter, at Cherenkov-based experiments and future liquid-argon neutrino detectors., Comment: PhD Thesis, MIT, May 2017. 178 Pages, 40 Figures

Cold, ultralight ($\ll$ eV) bosonic dark matter with a misalignment abundance can induce temporal variation in the masses and couplings of Standard Model particles. We find that fast variations in neutrino oscillation parameters can lead to significantly distorted neutrino oscillations (DiNOs) and yield striking signatures at long baseline experiments. We study several representative observables to demonstrate this effect and find that current and future experiments including DUNE and JUNO are sensitive to a wide range of viable scalar parameters over many decades in mass reach., Comment: 5+2 pages, 4 figures , 2 appendices