Search

Environment plays a critical role in shaping the assembly of low-mass galaxies. Here, we use the UniverseMachine (UM) galaxy-halo connection framework and the Data Release 3 of the Satellites Around Galactic Analogs (SAGA) Survey to place dwarf galaxy star formation and quenching into a cosmological context. UM is a data-driven forward model that flexibly parameterizes galaxy star formation rates (SFR) using only halo mass and assembly history. We add a new quenching model to UM, tailored for galaxies with stellar masses $\lesssim 10^9$ solar masses, and constrain the model down to a stellar mass $\gtrsim 10^7$ solar masses using new SAGA observations of 101 satellite systems around Milky Way (MW)-mass hosts and a sample of isolated field galaxies in a similar mass range from the Sloan Digital Sky Survey (SDSS). The new best-fit model, 'UM-SAGA,' reproduces the satellite stellar mass functions, average SFRs, and quenched fractions in SAGA satellites while keeping isolated dwarfs mostly star forming. The enhanced quenching in satellites relative to isolated field galaxies leads the model to maximally rely on halo assembly to explain the observed environmental quenching. Extrapolating the model down to a stellar mass $\sim 10^{6.5}$ solar masses yields a quenched fraction of $\gtrsim$ 30% for isolated field galaxies and $\gtrsim$ 80% for satellites of MW-mass hosts at this stellar mass. This specific prediction can soon be tested by spectroscopic surveys to reveal the relative importance of internal feedback, cessation of mass and gas accretion, satellite-specific gas processes, and reionization for the evolution of faint low-mass galaxies., Comment: 33 pages, 14 figures, 2 tables. This paper is part of the SAGA Survey Data Release 3. Survey website: https://sagasurvey.org

We present the star-forming properties of 378 satellite galaxies around 101 Milky Way analogs in the Satellites Around Galactic Analogs (SAGA) Survey, focusing on the environmental processes that suppress or quench star formation. In the SAGA stellar mass range of 10^6 to 10^10 solar masses, we present quenched fractions, star-forming rates, gas-phase metallicities, and gas content. The fraction of SAGA satellites that are quenched increases with decreasing stellar mass and shows significant system-to-system scatter. SAGA satellite quenched fractions are highest in the central 100 kpc of their hosts and decline out to the virial radius. Splitting by specific star formation rate (sSFR), the least star-forming satellite quartile follows the radial trend of the quenched population. The median sSFR of star-forming satellites increases with decreasing stellar mass and is roughly constant with projected radius. Star-forming SAGA satellites are consistent with the star formation rate--stellar mass relationship determined in the Local Volume, while the median gas-phase metallicity is higher and median HI gas mass is lower at all stellar masses. We investigate the dependence of the satellite quenched fraction on host properties. Quenched fractions are higher in systems with larger host halo mass, but this trend is only seen in the inner 100 kpc; we do not see significant trends with host color or star formation rate. Our results suggest that lower mass satellites and satellites inside 100 kpc are more efficiently quenched in a Milky Way-like environment, with these processes acting sufficiently slowly to preserve a population of star-forming satellites at all stellar masses and projected radii., Comment: 25 pages, 13 figures, 2 tables. Accepted by ApJ. This paper is part of the SAGA Survey Data Release 3. Data and notebooks are available on the survey website: https://sagasurvey.org

We present the third Data Release (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified across 101 MW-mass systems in the distance range 25-40.75 Mpc, and an accompanying redshift catalog of background galaxies (including about 46,000 taken by SAGA) in the SAGA footprint of 84.7 sq. deg. The number of confirmed satellites per system ranges from zero to 13, in the stellar mass range 10^6 to 10^10 solar masses. Based on a detailed completeness model, this sample accounts for 94% of the true satellite population down to a stellar mass of 10^7.5 solar masses. We find that the mass of the most massive satellite in SAGA systems is the strongest predictor of satellite abundance; one-third of the SAGA systems contain LMC-mass satellites, and they tend to have more satellites than the MW. The SAGA satellite radial distribution is less concentrated than the MW, and the SAGA quenched fraction below 10^8.5 solar masses is lower than the MW, but in both cases, the MW is within 1 sigma of SAGA system-to-system scatter. SAGA satellites do not exhibit a clear corotating signal as has been suggested in the MW/M31 satellite systems. Although the MW differs in many respects from the typical SAGA system, these differences can be reconciled if the MW is an older, slightly less massive host with a recently accreted LMC/SMC system., Comment: 38 pages, 23 figures, 7 tables. Accepted by ApJ. This paper is part of the SAGA Survey Data Release 3. Data and notebooks will be available on the survey website: https://sagasurvey.org

We present Milky Way-est, a suite of 20 cosmological cold-dark-matter-only zoom-in simulations of Milky Way (MW)-like host halos. Milky Way-est hosts are selected such that they (i) are consistent with the MW's measured halo mass and concentration, (ii) accrete a Large Magellanic Cloud (LMC)-like ($\approx 10^{11}~M_{\odot}$) subhalo within the last $2~\mathrm{Gyr}$ on a realistic orbit, placing them near $50~\mathrm{kpc}$ from the host center at $z\approx 0$, and (iii) undergo a $>$1:5 sub-to-host halo mass ratio merger with a Gaia-Sausage-Enceladus (GSE)-like system at early times ($0.67

Measuring the relation between star formation and galactic winds is observationally difficult. In this work we make an indirect measurement of the mass loading factor (the ratio between mass outflow rate and star formation rate) in low-mass galaxies using a differential approach to modeling the low-redshift evolution of the star-forming main sequence and mass-metallicity relation. We use the SAGA (Satellites Around Galactic Analogs) background galaxies, those spectra observed by the SAGA survey that are not associated with the main SAGA host galaxies, to construct a sample of 11925 spectroscopically confirmed low-mass galaxies from $0.01\lesssim z \leq 0.21$ and measure a auroral line metallicity for 120 galaxies. The crux of the method is to use the lowest redshift galaxies as the boundary condition of our model, and to infer a mass-loading factor for the sample by comparing the expected evolution of the low redshift reference sample in stellar mass, gas-phase metallicity, and star formation rate against the observed properties of the sample at higher redshift. We infer a mass-loading factor of $\eta_{\rm m}=0.92^{+1.76}_{-0.74}$, which is in line with direct measurements of the mass-loading factor from the literature despite the drastically different set of assumptions needed for each approach. While our estimate of the mass-loading factor is in good agreement with recent galaxy simulations that focus on resolving the dynamics of the interstellar medium, it is smaller by over an order of magnitude than the mass-loading factor produced by many contemporary cosmological simulations., Comment: 37 pages, 19 figures, accepted to ApJ

The abundance of faint dwarf galaxies is determined by the underlying population of low-mass dark matter (DM) halos and the efficiency of galaxy formation in these systems. Here, we quantify potential galaxy formation and DM constraints from future dwarf satellite galaxy surveys. We generate satellite populations using a suite of Milky Way (MW)--mass cosmological zoom-in simulations and an empirical galaxy--halo connection model, and assess sensitivity to galaxy formation and DM signals when marginalizing over galaxy--halo connection uncertainties. We find that a survey of all satellites around one MW-mass host can constrain a galaxy formation cutoff at peak virial masses of $M_{50}=10^8~M_{\mathrm{\odot}}$ at the $1\sigma$ level; however, a tail toward low $M_{50}$ prevents a $2\sigma$ measurement. In this scenario, combining hosts with differing bright satellite abundances significantly reduces uncertainties on $M_{50}$ at the $1\sigma$ level, but the $2\sigma$ tail toward low $M_{50}$ persists. We project that observations of one (two) complete satellite populations can constrain warm DM models with $m_{\mathrm{WDM}}\approx 10~\mathrm{keV}$ ($20~\mathrm{keV}$). Subhalo mass function (SHMF) suppression can be constrained to $\approx 70\%$, $60\%$, and $50\%$ that in cold dark matter (CDM) at peak virial masses of $10^8$, $10^9$, and $10^{10}~M_{\mathrm{\odot}}$, respectively; SHMF enhancement constraints are weaker ($\approx 20$, $4$, and $2$ times that in CDM, respectively) due to galaxy--halo connection degeneracies. These results motivate searches for faint dwarf galaxies beyond the MW and indicate that ongoing missions like Euclid and upcoming facilities including the Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope will probe new galaxy formation and DM physics., Comment: 38 pages, 23 figures, 2 tables. Updated to published version

We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterise their stellar mass and redshift distributions with a spectroscopic calibration sample. Using the ${\sim}5000\mathrm{deg}^2$ multi-band photometry from Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs (SAGA) survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z{<}0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log_{10}(M_*/M_{\odot})= [8.52^{+0.57}_{-0.76}, 9.02^{+0.50}_ {-0.64}, 9.49^{+0.50}_{-0.58}]$. We measure the stacked excess surface mass density profiles, $\Delta\Sigma(R)$, of these galaxies using galaxy--galaxy lensing with a signal-to-noise of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log_{10}(M_{\rm halo}/M_{\odot})$ = [$10.67\substack{+0.2\\-0.4}$, $11.01\substack{+0.14 \\ -0.27}$,$11.40\substack{+0.08\\-0.15}$]. The CDM profiles are consistent with NFW profiles over scales ${\lesssim}0.15 \rm{h}^{-1}$Mpc. We find that ${\sim}20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower-mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data., Comment: Measurements available at: https://github.com/aamon/Dwarf-Lensing ; 22 pages, 16 figures

We report the discovery of two ultra-faint dwarf galaxies, Leo M and Leo K, that lie outside the halo of the Milky Way. Using Hubble Space Telescope imaging of the resolved stars, we create color-magnitude diagrams reaching the old main sequence turn-off of each system and (i) fit for structural parameters of the galaxies; (ii) measure their distances using the luminosity of the Horizontal Branch stars; (iii) estimate integrated magnitudes and stellar masses; and (iv) reconstruct the star formation histories. Based on their location in the Local Group, neither galaxy is currently a satellite of the Milky Way, although Leo K is located ~26 kpc from the low-mass galaxy Leo T and these two systems may have had a past interaction. Leo M and Leo K have stellar masses of 1.8 (+0.3/-0.2) x 10^4 Msun and 1.2+/-0.2 x 10^4 Msun, and were quenched 10.6 (+2.2/-1.1) Gyr and 12.8 (+0.1/-4.2) Gyr ago, respectively. Given that the galaxies are not satellites of the MW, it is unlikely that they were quenched by environmental processing. Instead, given their low stellar masses, their early quenching timescales are consistent with the scenario that a combination of reionization and stellar feedback shut-down star formation at early cosmic times., Comment: 12 pages, 9 figures, 1 table

Within the $\Lambda$CDM cosmology, dark matter haloes are comprised of both a smooth component and a population of smaller, gravitationally bound subhaloes. These components are often treated as a single halo when halo properties, such as density profiles, are extracted from simulations. Recent work has shown that density profiles change substantially when subhalo mass is excluded. In this paper, we expand on this result by analysing the change in three specific host halo properties -- concentration ($c_{\rm{NFW}}$), spin ($\lambda_{\rm Bullock}$), and shape ($c/a$), -- when calculated only from the smooth component of the halo. This analysis is performed on both Milky Way-mass haloes and cluster-mass haloes in high-resolution, zoom-in, $N$-body simulations. We find that when subhaloes are excluded the median value of (1) $c_{\rm{NFW}}$ is enhanced by $\approx 38 \pm 12\%$ and $\approx 88 \pm 7.7\%$ for Milky Way mass ($10^{12.1}\,\text{M}_\odot$) and cluster mass ($10^{14.8}\,\text{M}_\odot$) haloes respectively, (2) $\lambda_{\rm Bullock}$ is reduced for Milky Way mass by $\approx 16 \pm 6.8\%$ and cluster mass haloes by $\approx 32 \pm 8.9\%$. Additionally, with the removal of subhaloes, cluster mass haloes tend to become more spherical as the ratio of minor-to-major axis, $c/a$, increases by $\approx 12 \pm 4\%$, whereas Milky Way mass haloes remain approximately the same shape with $c/a$ changed by $\approx 1.2 \pm 5.6\%$. The fractional change of each of these properties depends primarily on the amount of mass that is removed from the halo system and, to a lesser extent, mass accretion history. Our findings demonstrate that the properties of the smooth components of dark matter haloes are biased relative to the total mass of the halo including subhaloes., Comment: Accepted to MNRAS 09/26/2023

We report the discovery of an ultrafaint dwarf (UFD) galaxy, Pegasus W, located on the far side of the Milky Way-M31 system and outside the virial radius of M31. The distance to the galaxy is 915 (+60/-91) kpc, measured using the luminosity of horizontal branch (HB) stars identified in Hubble Space Telescope optical imaging. The galaxy has a half-light radius (r_h) of 100 (+11/-13) pc, M_V = -7.20 (+0.17/-0.16) mag, and a present-day stellar mass of 6.5 (+1.1/-1.4) x 10^4 Msun. We identify sources in the color-magnitude diagram (CMD) that may be younger than ~500 Myr suggesting late-time star formation in the UFD galaxy, although further study is needed to confirm these are bona fide young stars in the galaxy. Based on fitting the CMD with stellar evolution libraries, Pegasus W shows an extended star formation history (SFH). Using the tau_90 metric (defined as the timescale by which the galaxy formed 90% of its stellar mass), the galaxy was quenched only 7.4 (+2.2/-2.6) Gyr ago, which is similar to the quenching timescale of a number of UFD satellites of M31 but significantly more recent than the UFD satellites of the Milky Way. Such late-time quenching is inconsistent with the more rapid timescale expected by reionization and suggests that, while not currently a satellite of M31, Pegasus W was nonetheless slowly quenched by environmental processes., Comment: 15 pages, 10 figures, 2 tables

We introduce the DESI LOW-Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine learning methods, to target low-redshift dwarf galaxies ($z$ < 0.03) between $19 < r < 21$ with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW-Z survey has already obtained over 22,000 redshifts of dwarf galaxies (M$_* < 10^9$ M$_\odot$), comparable to the number of dwarf galaxies discovered in SDSS-DR8 and GAMA. As a spare fiber survey, LOW-Z currently receives fiber allocation for just ~50% of its targets. However, we estimate that our selection is highly complete: for galaxies at $z < 0.03$ within our magnitude limits, we achieve better than 95% completeness with ~1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections $z<0.03$ galaxies from the photometric cuts subsample at least ten times more efficiently while maintaining high completeness. The full five-year DESI program will expand the LOW-Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys., Comment: 24 pages, 14 figures, data to reproduce figures: https://zenodo.org/record/7422591

Cosmological and astrophysical observations currently provide the only robust, positive evidence for dark matter. Cosmic probes of dark matter, which seek to determine the fundamental properties of dark matter through observations of the cosmos, have emerged as a promising means to reveal the nature of dark matter. This report summarizes the current status and future potential of cosmic probes to inform our understanding of the fundamental nature of dark matter in the coming decade., Comment: Report of the CF3 Topical Group for Snowmass 2021; 35 pages, 10 figures, many references. V3 updates Fig 3-2 and the author list

We present Symphony, a compilation of $262$ cosmological, cold-dark-matter-only zoom-in simulations spanning four decades of host halo mass, from $10^{11}$$-$$10^{15}~M_{\mathrm{\odot}}$. This compilation includes three existing simulation suites at the cluster and Milky Way$-$mass scales, and two new suites: $39$ Large Magellanic Cloud-mass ($10^{11}~M_{\mathrm{\odot}}$) and $49$ strong-lens-analog ($10^{13}~M_{\mathrm{\odot}}$) group-mass hosts. Across the entire host halo mass range, the highest-resolution regions in these simulations are resolved with a dark matter particle mass of $\approx 3\times 10^{-7}$ times the host virial mass and a Plummer-equivalent gravitational softening length of $\approx 9\times 10^{-4}$ times the host virial radius, on average. We measure correlations between subhalo abundance and host concentration, formation time, and maximum subhalo mass, all of which peak at the Milky Way host halo mass scale. Subhalo abundances are $\approx 50\%$ higher in clusters than in lower-mass hosts at fixed sub-to-host halo mass ratios. Subhalo radial distributions are approximately self-similar as a function of host mass and are less concentrated than hosts' underlying dark matter distributions. We compare our results to the semianalytic model $\mathrm{\texttt{Galacticus}}$, which predicts subhalo mass functions with a higher normalization at the low-mass end and radial distributions that are slightly more concentrated than Symphony. We use $\mathrm{\texttt{UniverseMachine}}$ to model halo and subhalo star formation histories in Symphony, and we demonstrate that these predictions resolve the formation histories of the halos that host nearly all currently observable satellite galaxies in the universe. To promote open use of Symphony, data products are publicly available at http://web.stanford.edu/group/gfc/symphony., Comment: 39 pages, 20 figures, 2 tables. Updated to published version

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science., Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" workshop

We present observational constraints on the galaxy-halo connection, focusing particularly on galaxy assembly bias, from a novel combination of counts-in-cylinders statistics, $P(N_{\rm{CIC}})$, with the standard measurements of the projected two-point correlation function, $w_{\rm{p}}(r_{\rm{p}})$, and number density, $n_{\rm{gal}}$, of galaxies. We measure $n_{\rm{gal}}$, $w_{\rm{p}}(r_{\rm{p}})$ and $P(N_{\rm{CIC}})$ for volume-limited, luminosity-threshold samples of galaxies selected from SDSS DR7, and use them to constrain halo occupation distribution (HOD) models, including a model in which galaxy occupation depends upon a secondary halo property, namely halo concentration. We detect significant positive central assembly bias for the $M_r<-20.0$ and $M_r<-19.5$ samples. Central galaxies preferentially reside within haloes of high concentration at fixed mass. Positive central assembly bias is also favoured in the $M_r<-20.5$ and $M_r<-19.0$ samples. We find no evidence of central assembly bias in the $M_r<-21.0$ sample. We observe only a marginal preference for negative satellite assembly bias in the $M_r<-20.0$ and $M_r<-19.0$ samples, and non-zero satellite assembly bias is not indicated in other samples. Our findings underscore the necessity of accounting for galaxy assembly bias when interpreting galaxy survey data, and demonstrate the potential of count statistics in extracting information from the spatial distribution of galaxies, which could be applied to both galaxy-halo connection studies and cosmological analyses., Comment: 16+5 pages, 9+3 figures, 5+2 tables, Fig. 6 shows the main result. To be submitted to MNRAS, comments welcome

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of $0.1\sim60~h^{-1}$Mpc. Although our simulations are based on $w$CDM with general relativity (GR), we include a scaling parameter of the halo velocity field, $\gamma_f$, defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find $f\sigma_{8}(z=0.25) = 0.413\pm0.031$, $f\sigma_{8}(z=0.4) = 0.470\pm0.026$ and $f\sigma_{8}(z=0.55) = 0.396\pm0.022$. Compared with Planck observations using a flat $\Lambda$CDM model, our results are lower by $1.9\sigma$, $0.3\sigma$ and $3.4\sigma$ respectively. These results are consistent with other recent simulation-based results at non-linear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of $\gamma_f^{1/2}\sigma_8\approx 0.75$. We note, however, that the BOSS data is well fit assuming GR, i.e. $\gamma_f=1$. We cannot rule out an unknown systematic error in the galaxy bias model at non-linear scales, but near-future data and modeling will enhance our understanding of the galaxy--halo connection, and provide a strong test of new physics beyond the standard model., Comment: 30 pages, 23 figures and 4 tables; ApJ accepted, updated to the match the accepted version

Despite efforts over several decades, direct-detection experiments have not yet led to the discovery of the dark matter (DM) particle. This has led to increasing interest in alternatives to the Lambda CDM (LCDM) paradigm and alternative DM scenarios (including fuzzy DM, warm DM, self-interacting DM, etc.). In many of these scenarios, DM particles cannot be detected directly and constraints on their properties can ONLY be arrived at using astrophysical observations. The Dark Energy Spectroscopic Instrument (DESI) is currently one of the most powerful instruments for wide-field surveys. The synergy of DESI with ESA's Gaia satellite and future observing facilities will yield datasets of unprecedented size and coverage that will enable constraints on DM over a wide range of physical and mass scales and across redshifts. DESI will obtain spectra of the Lyman-alpha forest out to z~5 by detecting about 1 million QSO spectra that will put constraints on clustering of the low-density intergalactic gas and DM halos at high redshift. DESI will obtain radial velocities of 10 million stars in the Milky Way (MW) and Local Group satellites enabling us to constrain their global DM distributions, as well as the DM distribution on smaller scales. The paradigm of cosmological structure formation has been extensively tested with simulations. However, the majority of simulations to date have focused on collisionless CDM. Simulations with alternatives to CDM have recently been gaining ground but are still in their infancy. While there are numerous publicly available large-box and zoom-in simulations in the LCDM framework, there are no comparable publicly available WDM, SIDM, FDM simulations. DOE support for a public simulation suite will enable a more cohesive community effort to compare observations from DESI (and other surveys) with numerical predictions and will greatly impact DM science., Comment: Contributed white paper to Snowmass 2021, CF03; minor revisions

The non-linear process of cosmic structure formation produces gravitationally bound overdensities of dark matter known as halos. The abundances, density profiles, ellipticities, and spins of these halos can be tied to the underlying fundamental particle physics that governs dark matter at microscopic scales. Thus, macroscopic measurements of dark matter halos offer a unique opportunity to determine the underlying properties of dark matter across the vast landscape of dark matter theories. This white paper summarizes the ongoing rapid development of theoretical and experimental methods, as well as new opportunities, to use dark matter halo measurements as a pillar of dark matter physics., Comment: White paper submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021). 88 pages, 9 figures. Comments welcome

Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities., Comment: Contribution to Snowmass 2021

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

Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on $ugriz$ images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of $\sim$400,000 Sloan Digital Sky Survey (SDSS) galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets ($r\leq17.8$ and $z_{\mathrm{spec}}\leq0.4$) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a 2-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g., size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g., magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1 ., Comment: 22 pages, 12 figures. Published in MNRAS

We present "Extending the Satellites Around Galactic Analogs Survey" (xSAGA), a method for identifying low-$z$ galaxies on the basis of optical imaging, and results on the spatial distributions of xSAGA satellites around host galaxies. Using spectroscopic redshift catalogs from the SAGA Survey as a training data set, we have optimized a convolutional neural network (CNN) to identify $z < 0.03$ galaxies from more distant objects using image cutouts from the DESI Legacy Imaging Surveys. From the sample of $> 100,000$ CNN-selected low-$z$ galaxies, we identify $>20,000$ probable satellites located between 36-300 projected kpc from NASA-Sloan Atlas central galaxies in the stellar mass range $9.5 < \log(M_\star/M_\odot) < 11$. We characterize the incompleteness and contamination for CNN-selected samples, and apply corrections in order to estimate the true number of satellites as a function of projected radial distance from their hosts. Satellite richness depends strongly on host stellar mass, such that more massive host galaxies have more satellites, and on host morphology, such that elliptical hosts have more satellites than disky hosts with comparable stellar masses. We also find a strong inverse correlation between satellite richness and the magnitude gap between a host and its brightest satellite. The normalized satellite radial distribution between 36-300 kpc does not depend strongly on host stellar mass, morphology, or magnitude gap. The satellite abundances and radial distributions we measure are in reasonable agreement with predictions from hydrodynamic simulations. Our results deliver unprecedented statistical power for studying satellite galaxy populations, and highlight the promise of using machine learning for extending galaxy samples of wide-area surveys., Comment: 27 pages, 18 figures, 1 table. Accepted to ApJ. Code available at https://github.com/jwuphysics/xsaga

Large simulation efforts are required to provide synthetic galaxy catalogs for ongoing and upcoming cosmology surveys. These extragalactic catalogs are being used for many diverse purposes covering a wide range of scientific topics. In order to be useful, they must offer realistically complex information about the galaxies they contain. Hence, it is critical to implement a rigorous validation procedure that ensures that the simulated galaxy properties faithfully capture observations and delivers an assessment of the level of realism attained by the catalog. We present here a suite of validation tests that have been developed by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). We discuss how the inclusion of each test is driven by the scientific targets for static ground-based dark energy science and by the availability of suitable validation data. The validation criteria that are used to assess the performance of a catalog are flexible and depend on the science goals. We illustrate the utility of this suite by showing examples for the validation of cosmoDC2, the extragalactic catalog recently released for the LSST DESC second Data Challenge., Comment: 46 pages, 33 figures

Given recent developments in our understanding of the Large Magellanic Cloud's (LMC) impact on the Milky Way's (MW) dark matter subhalo population, we compare the signatures of dark matter and baryonic physics on subhalos in MW systems with realistic LMC analogs. In particular, we study the effects of self-interacting dark matter (SIDM), warm dark matter (WDM), and the Galactic disk on the peak maximum circular velocity ($V_{\mathrm{peak}}$) function, radial distribution, and spatial distribution of MW and LMC-associated subhalos using cosmological dark matter-only zoom-in simulations of MW+LMC systems. For a fixed abundance of subhalos expected to host dwarf galaxies ($V_{\mathrm{peak}}\gtrsim 20\ \mathrm{km\ s}^{-1}$), SIDM and WDM can produce a similar mass-dependent suppression of the subhalo $V_{\mathrm{peak}}$ function, while disk disruption is mass independent. Subhalos in the inner regions of the MW are preferentially disrupted by both self-interactions and the disk, while suppression in WDM is radially independent. The relative abundance of LMC-associated subhalos is not strongly affected by disk disruption or WDM, but is significantly suppressed in SIDM due to self-interactions with the LMC at early times and with the MW during LMC infall at late times, erasing spatial anisotropy in the MW subhalo population. These results provide avenues to distinguish dark matter and baryonic physics by combining properties of the MW and LMC subhalo populations probed by upcoming observations of satellite galaxies and stellar streams., Comment: 9 pages, 2 figures, 1 table. Updated to published version

This paper presents the results of the Rubin Observatory Dark Energy Science Collaboration (DESC) 3x2pt tomography challenge, which served as a first step toward optimizing the tomographic binning strategy for the main DESC analysis. The task of choosing an optimal tomographic binning scheme for a photometric survey is made particularly delicate in the context of a metacalibrated lensing catalogue, as only the photometry from the bands included in the metacalibration process (usually riz and potentially g) can be used in sample definition. The goal of the challenge was to collect and compare bin assignment strategies under various metrics of a standard 3x2pt cosmology analysis in a highly idealized setting to establish a baseline for realistically complex follow-up studies; in this preliminary study, we used two sets of cosmological simulations of galaxy redshifts and photometry under a simple noise model neglecting photometric outliers and variation in observing conditions, and contributed algorithms were provided with a representative and complete training set. We review and evaluate the entries to the challenge, finding that even from this limited photometry information, multiple algorithms can separate tomographic bins reasonably well, reaching figures-of-merit scores close to the attainable maximum. We further find that adding the g band to riz photometry improves metric performance by ~15% and that the optimal bin assignment strategy depends strongly on the science case: which figure-of-merit is to be optimized, and which observables (clustering, lensing, or both) are included., Comment: 30 pages (incl. 12 in appendix), 12 figures. Version accepted for publication in the Open Journal of Astrophysics

We apply the empirical galaxy--halo connection model UniverseMachine to dark matter-only zoom-in simulations of isolated Milky Way (MW)--mass halos along with their parent cosmological simulations. This application extends \textsc{UniverseMachine} predictions into the ultra-faint dwarf galaxy regime ($ 10^{2}\,\mathrm{M_{\odot}} \leqslant M_{\ast} \leqslant 10^{5}\,\mathrm{M_{\odot}}$) and yields a well-resolved stellar mass--halo mass (SMHM) relation over the peak halo mass range $10^8\,\mathrm{M_{\odot}}$ to $10^{15}\,\mathrm{M_{\odot}}$. The extensive dynamic range provided by the zoom-in simulations allows us to assess specific aspects of dwarf galaxy evolution predicted by \textsc{UniverseMachine}. In particular, although UniverseMachine is not constrained for dwarf galaxies with $M_* \lesssim 10^{8}\,\mathrm{M_{\odot}}$, our predicted SMHM relation is consistent with that inferred for MW satellite galaxies at $z=0$ using abundance matching. However, UniverseMachine predicts that nearly all galaxies are actively star forming below $M_{\ast}\sim 10^{7}\,\mathrm{M_{\odot}}$ and that these systems typically form more than half of their stars at $z\lesssim 4$, which is discrepant with the star formation histories of Local Group dwarf galaxies that favor early quenching. This indicates that the current UniverseMachine model does not fully capture galaxy quenching physics at the low-mass end. We highlight specific improvements necessary to incorporate environmental and reionization-driven quenching for dwarf galaxies, and provide a new tool to connect dark matter accretion to star formation over the full dynamic range that hosts galaxies., Comment: Accepted for publication in ApJ. 21 pages, 8 figures, 1 table. Minor edits to v1. Added discussion of reionization contribution of ultra-faint dwarfs in sections 4.4 and 5

In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg$^2$ simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository., Comment: 25 pages, 3 figures; 9 tables. A detailed changelog can be found in Appendix A. To obtain data, visit the DESC Data Portal at https://data.lsstdesc.org/

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology., Comment: 39 pages, 19 figures, version accepted for publication in ApJS

We present the Stage II results from the ongoing Satellites Around Galactic Analogs (SAGA) Survey. Upon completion, the SAGA Survey will spectroscopically identify satellite galaxies brighter than $ M_{r,o} = -12.3 $ around 100 Milky Way (MW) analogs at $ z \sim 0.01 $. In Stage II, we have more than quadrupled the sample size of Stage I, delivering results from 127 satellites around 36 MW analogs with an improved target selection strategy and deep photometric imaging catalogs from the Dark Energy Survey and the Legacy Surveys. We have obtained 25,372 galaxy redshifts, peaking around $ z = 0.2 $. These data significantly increase spectroscopic coverage for very low redshift objects in $ 17 < r_o < 20.75 $ around SAGA hosts, creating a unique data set that places the Local Group in a wider context. The number of confirmed satellites per system ranges from zero to nine, and correlates with host galaxy and brightest satellite luminosities. We find that the number and the luminosities of MW satellites are consistent with being drawn from the same underlying distribution as SAGA systems. The majority of confirmed SAGA satellites are star forming, and the quenched fraction increases as satellite stellar mass and projected radius from the host galaxy decrease. Overall, the satellite quenched fraction among SAGA systems is lower than that in the Local Group. We compare the luminosity functions and radial distributions of SAGA satellites with theoretical predictions based on cold dark matter simulations and an empirical galaxy-halo connection model and find that the results are broadly in agreement., Comment: 42 pages, 22 figures, 3 tables. See Sec. 9 (p.28) for summary and figure index. Main results are shown in Sec. 6-8 (Fig. 8-18). Accepted by ApJ. Data available on survey website: https://sagasurvey.org

Cold dark matter haloes consist of a relatively smooth dark matter component as well as a system of bound subhaloes. It is the prevailing practice to include all halo mass, including mass in subhaloes, in studies of halo density profiles. However, often in observational studies satellites are treated as having their own distinct dark matter density profiles in addition to the profile of the host. This difference makes comparisons between theoretical and observed results difficult. In this work we investigate density profiles of the smooth components of host haloes by excluding mass contained within subhaloes. We find that the density profiles of the smooth halo component (without subhaloes) differs substantially from the conventional halo density profile. Smooth profiles decline more rapidly at large radii and are not well characterised by the standard NFW profile. We also find that concentrations derived from smooth density profiles exhibit less scatter at fixed mass and a weaker mass dependence than standard concentrations. Both smooth and standard halo profiles can be described by a generalised Einasto profile, an Einasto profile with a modified central slope, with smaller residuals than either an NFW or Einasto profile. These results hold for both Milky Way-mass and cluster-mass haloes. This new characterisation of smooth halo profiles can be useful for many analyses, such as lensing and dark matter annihilation, in which the smooth and clumpy components of a halo should be accounted for separately., Comment: 19 pages, 9 figures, appendices, submitted to MNRAS

The concentration parameter is a key characteristic of a dark matter halo that conveniently connects the halo's present-day structure with its assembly history. Using 'Dark Sky', a suite of cosmological $N$-body simulations, we investigate how halo concentration evolves with time and emerges from the mass assembly history. We also explore the origin of the scatter in the relation between concentration and assembly history. We show that the evolution of halo concentration has two primary modes: (1) smooth increase due to pseudo-evolution; and (2) intense responses to physical merger events. Merger events induce lasting and substantial changes in halo structures, and we observe a universal response in the concentration parameter. We argue that merger events are a major contributor to the uncertainty in halo concentration at fixed halo mass and formation time. In fact, even haloes that are typically classified as having quiescent formation histories experience multiple minor mergers. These minor mergers drive small deviations from pseudo-evolution, which cause fluctuations in the concentration parameters and result in effectively irreducible scatter in the relation between concentration and assembly history. Hence, caution should be taken when using present-day halo concentration parameter as a proxy for the halo assembly history, especially if the recent merger history is unknown., Comment: 15 pages, 7 + 1 figures, accepted for publication in MNRAS, comments welcome

We explore the impact of elastic, anisotropic, velocity-dependent dark matter (DM) self-interactions on the host halo and subhalos of Milky Way (MW)--mass systems. We consider a generic self-interacting dark matter (SIDM) model parameterized by the masses of a light mediator and the DM particle. The ratio of these masses, $w$, sets the velocity scale above which momentum transfer due to DM self-interactions becomes inefficient. We perform high-resolution zoom-in simulations of an MW-mass halo for values of $w$ that span scenarios in which self-interactions either between the host and its subhalos or only within subhalos efficiently transfer momentum, and we study the effects of self-interactions on the host halo and on the abundance, radial distribution, orbital dynamics, and density profiles of subhalos in each case. The abundance and properties of surviving subhalos are consistent with being determined primarily by subhalo--host halo interactions. In particular, subhalos on radial orbits in models with larger values of the cross section at the host halo velocity scale are more susceptible to tidal disruption owing to mass loss from ram pressure stripping caused by self-interactions with the host. This mechanism suppresses the abundance of surviving subhalos relative to collisionless DM simulations, with stronger suppression for larger values of $w$. Thus, probes of subhalo abundance around MW-mass hosts can be used to place upper limits on the self-interaction cross section at velocity scales of $\sim 200\ \rm{km\ s}^{-1}$, and combining these measurements with the orbital properties and internal dynamics of subhalos may break degeneracies among velocity-dependent SIDM models., Comment: 19 pages, 10 figures, 1 table. Updated to published version

We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging dataset, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of $0.4 < z < 0.9$ over 5655 deg$^2$. We have developed new photometric redshift (photo-$z$) estimates using the Legacy Survey DECam and WISE photometry, with $\sigma_{\mathrm{NMAD}} = 0.02$ precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalog, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N-body catalogs, and present a new technique for finding best-fit parameters in this situation. Accompanying this paper we have released the Photometric Redshifts for the Legacy Surveys (PRLS) catalog of photo-$z$'s obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 dataset. This catalog provides accurate photometric redshifts for objects with $z < 21$ over more than 16,000 deg$^2$ of sky., Comment: 24 pages, 25 figures, published in MNRAS

We demonstrate how the total luminosity in satellite galaxies is a powerful probe of dark matter halos around central galaxies. The method cross-correlates central galaxies in spectroscopic galaxy samples with fainter galaxies detected in photometric surveys. After background subtraction, the excess galaxies around the central galaxies represent faint satellite galaxies within the dark matter halo. Using abundance matching models, we show that the the total galaxy luminosity, L_sat, scales linearly with host halo mass, making L_sat an excellent proxy for M_h. L_sat is also sensitive to the formation time of the halo, as younger halos have more substructure at fixed M_h. We demonstrate that probes of galaxy large-scale environment can break this degeneracy. Although this is an indirect probe of the halo, it can yield a high-S/N measurement for galaxies expected to occupy halos at $<10^{12}$ M_sol, where other methods suffer from larger errors. In this paper we focus on observational and theoretical systematics in the L_sat method. We test the robustness of our method of finding central galaxies and our methods of estimating the number of background galaxies. We implement this method on central galaxies in SDSS data, with satellites identified in faint imaging from the DESI Legacy Imaging Surveys. We find excellent agreement between our theoretical predictions and the observational measurements. Finally, we compare our L_sat measurements to weak lensing estimates of M_h for red and blue subsamples. In the stellar mass range where the measurements overlap, we find consistent results, where red galaxies live in larger halos. However, the L_sat approach allows us to probe significantly lower mass galaxies. At these masses, the L_sat values are equivalent. This example shows the potential of L_sat as a probe of dark halos. (Abridged), Comment: 21 pages, submitted to MNRAS

We develop and implement two new methods for constraining the scatter in the relationship between galaxies and dark matter halos. These new techniques are sensitive to the scatter at low halo masses, making them complementary to previous constraints that are dependent on clustering amplitudes or rich galaxy groups, both of which are only sensitive to more massive halos. In both of our methods, we use a galaxy group finder to locate central galaxies in the SDSS main galaxy sample. Our first technique uses the small-scale cross-correlation of central galaxies with all lower mass galaxies. This quantity is sensitive to the satellite fraction of low-mass galaxies, which is in turn driven by the scatter between halos and galaxies. The second technique uses the kurtosis of the distribution of line-of-sight velocities between central galaxies and neighboring galaxies. This quantity is sensitive to the distribution of halo masses that contain the central galaxies at fixed stellar mass. Theoretical models are constructed using peak halo circular velocity, $V_{\rm peak}$, as our property to connect galaxies to halos. The cross-correlation technique yields a constraint of $\sigma[ M_\ast|V_{\rm peak}]=0.27\pm 0.05$ dex, corresponding to a scatter in $\log M_\ast$ at fixed $M_h$ of $\sigma[ M_\ast|M_h]=0.38\pm 0.06$ dex at $M_h=10^{11.8}$ Msun. The kurtosis technique yields $\sigma[ M_\ast|V_{\rm peak}]=0.30\pm0.03$, corresponding to $\sigma[ M_\ast|M_h]=0.34\pm 0.04$ at $M_h=10^{12.2}$ Msun. The values of $\sigma[ M_\ast|M_h]$ are significantly larger than the constraints at higher masses, in agreement with the results of hydrodynamic simulations. This increase is only partly due to the scatter between $V_{\rm peak}$ and $M_h$, and it represents an increase of nearly a factor of two relative to the values inferred from clustering and group studies at high masses., Comment: 14 pages, 13 figures, submitted to MNRAS

This paper introduces cosmoDC2, a large synthetic galaxy catalog designed to support precision dark energy science with the Large Synoptic Survey Telescope (LSST). CosmoDC2 is the starting point for the second data challenge (DC2) carried out by the LSST Dark Energy Science Collaboration (LSST DESC). The catalog is based on a trillion-particle, 4.225 Gpc^3 box cosmological N-body simulation, the `Outer Rim' run. It covers 440 deg^2 of sky area to a redshift of z=3 and is complete to a magnitude depth of 28 in the r-band. Each galaxy is characterized by a multitude of properties including stellar mass, morphology, spectral energy distributions, broadband filter magnitudes, host halo information and weak lensing shear. The size and complexity of cosmoDC2 requires an efficient catalog generation methodology; our approach is based on a new hybrid technique that combines data-driven empirical approaches with semi-analytic galaxy modeling. A wide range of observation-based validation tests has been implemented to ensure that cosmoDC2 enables the science goals of the planned LSST DESC DC2 analyses. This paper also represents the official release of the cosmoDC2 data set, including an efficient reader that facilitates interaction with the data., Comment: 27 pages, 17 figures, submitted to APJS

(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

Most models for the connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than mass, a phenomenon known as galaxy assembly bias. Yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy--halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function $w_{\mathrm{p}}(r_{\mathrm{p}})$, the galaxy--galaxy lensing signal $\Delta \Sigma(r_{\mathrm{p}})$, the void probability function $\mathrm{VPF}(r)$, the distributions of counts-in-cylinders $P(N_{\mathrm{CIC}})$, and counts-in-annuli $P(N_{\mathrm{CIA}})$, and the distribution of the ratio of counts in cylinders of different sizes $P(N_2/N_5)$. We find that despite the frequent use of the combination $w_{\mathrm{p}}(r_{\mathrm{p}})+\Delta \Sigma(r_{\mathrm{p}})$ in interpreting galaxy data, the count statistics, $P(N_{\mathrm{CIC}})$ and $P(N_{\mathrm{CIA}})$, are generally more efficient in constraining galaxy assembly bias when combined with $w_{\mathrm{p}}(r_{\mathrm{p}})$. Constraints based upon $w_{\mathrm{p}}(r_{\mathrm{p}})$ and $\Delta \Sigma(r_{\mathrm{p}})$ share common degeneracy directions in the parameter space, while combinations of $w_{\mathrm{p}}(r_{\mathrm{p}})$ with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy--halo connection., Comment: Figures 3 and 4 show the main results. Published in Monthly Notices of the Royal Astronomical Society

Over the past decade, empirical constraints on the galaxy-dark matter halo connection have significantly advanced our understanding of galaxy evolution. Past techniques have focused on connections between halo properties and galaxy stellar mass and/or star formation rates. Empirical techniques in the next decade will link halo assembly histories with galaxies' circumgalactic media, supermassive black holes, morphologies, kinematics, sizes, colors, metallicities, and transient rates. Uncovering these links will resolve many critical uncertainties in galaxy formation and will enable much higher-fidelity mock catalogs essential for interpreting observations. Achieving these results will require broader and deeper spectroscopic coverage of galaxies and their circumgalactic media; survey teams will also need to meet several criteria (cross-comparisons, public access, and covariance matrices) to facilitate combining data across different surveys. Acting on these recommendations will continue enabling dramatic progress in both empirical modeling and galaxy evolution for the next decade., Comment: Science white paper submitted to the Astro2020 Decadal Survey

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 develop a comprehensive and flexible model for the connection between satellite galaxies and dark matter subhalos in dark matter-only zoom-in simulations of Milky Way (MW)--mass host halos. We systematically identify the physical and numerical uncertainties in the galaxy--halo connection and simulations underlying our method, including (i) the influence of host halo properties; (ii) the relationship between satellite luminosities and subhalo properties, including the effects of reionization; (iii) the relationship between satellite and subhalo locations; (iv) the relationship between satellite sizes and subhalo properties, including the effects of tidal stripping; (v) satellite and subhalo disruption due to baryonic effects; and (vi) artificial subhalo disruption and orphan satellites. To illustrate our approach, we fit this model to the luminosity distribution of both classical MW satellites and those discovered in the Sloan Digital Sky Survey by performing realistic mock observations that depend on the luminosity, size, and distance of our predicted satellites, and we infer the total satellite population that will be probed by upcoming surveys. We argue that galaxy size and surface brightness modeling will play a key role in interpreting current and future observations, as the expected number of observable satellites depends sensitively on their surface brightness distribution., Comment: 21 pages, 10 figures. Updated to published version. Code available at https://github.com/eonadler/subhalo_satellite_connection

On small scales there have been a number of claims of discrepancies between the standard Cold Dark Matter (CDM) model and observations. The 'missing satellites problem' infamously describes the overabundance of subhalos from CDM simulations compared to the number of satellites observed in the Milky Way. A variety of solutions to this discrepancy have been proposed; however, the impact of the specific properties of the Milky Way halo relative to the typical halo of its mass have yet to be explored. Motivated by recent studies that identified ways in which the Milky Way is atypical (e.g., Licquia et al. 2015), we investigate how the properties of dark matter halos with mass comparable to our Galaxy's --- including concentration, spin, shape, and scale factor of the last major merger --- correlate with the subhalo abundance. Using zoom-in simulations of Milky Way-like halos, we build two models of subhalo abundance as functions of host halo properties and conclude that the Milky Way should be expected to have 22%-44% fewer subhalos with low maximum rotation velocities ($V_{\rm max}^{\rm sat} \sim 10$kms$^{-1}$) at the 95% confidence level and up to 72% fewer than average subhalos with high rotation velocities ($V_{\rm max}^{\rm sat} \gtrsim 30$kms$^{-1}$, comparable to the Magellanic Clouds) than would be expected for a typical halo of the Milky Way's mass. Concentration is the most informative single parameter for predicting subhalo abundance. Our results imply that models tuned to explain the missing satellites problem assuming typical subhalo abundances for our Galaxy will be over-correcting., Comment: 21 pages, 11 figures, submitted to Monthly Notices of the Royal Astronomical Society

Using the N-body simulations of the AEMULUS Project, we construct an emulator for the non-linear clustering of galaxies in real and redshift space. We construct our model of galaxy bias using the halo occupation framework, accounting for possible velocity bias. The model includes 15 parameters, including both cosmological and galaxy bias parameters. We demonstrate that our emulator achieves ~ 1% precision at the scales of interest, 0.1

The rapidly growing statistical precision of galaxy surveys has lead to a need for ever-more precise predictions of the observables used to constrain cosmological and galaxy formation models. The primary avenue through which such predictions will be obtained is suites of numerical simulations. These simulations must span the relevant model parameter spaces, be large enough to obtain the precision demanded by upcoming data, and be thoroughly validated in order to ensure accuracy. In this paper we present one such suite of simulations, forming the basis for the AEMULUS Project, a collaboration devoted to precision emulation of galaxy survey observables. We have run a set of 75 (1.05 h^-1 Gpc)^3 simulations with mass resolution and force softening of 3.51\times 10^10 (Omega_m / 0.3) ~ h^-1 M_sun and 20 ~ h^-1 kpc respectively in 47 different wCDM cosmologies spanning the range of parameter space allowed by the combination of recent Cosmic Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae results. We present convergence tests of several observables including spherical overdensity halo mass functions, galaxy projected correlation functions, galaxy clustering in redshift space, and matter and halo correlation functions and power spectra. We show that these statistics are converged to 1% (2%) for halos with more than 500 (200) particles respectively and scales of r>200 ~ h^-1 kpc in real space or k ~ 3 h Mpc^-1 in harmonic space for z\le 1. We find that the dominant source of uncertainty comes from varying the particle loading of the simulations. This leads to large systematic errors for statistics using halos with fewer than 200 particles and scales smaller than k ~ 4 h^-1 Mpc. We provide the halo catalogs and snapshots detailed in this work to the community at https://AemulusProject.github.io., Comment: 16 pages, 12 figures, 3 Tables Project website: https://aemulusproject.github.io/