Search

Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1+z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes., Comment: Updated to match the version accepted by the MNRAS, 23 pages, 9 figures, 2 tables

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

We introduce the Southern Stellar Stream Spectroscopy Survey (${S}^5$), an on-going program to map the kinematics and chemistry of stellar streams in the Southern Hemisphere. The initial focus of ${S}^5$ has been spectroscopic observations of recently identified streams within the footprint of the Dark Energy Survey (DES), with the eventual goal of surveying streams across the entire southern sky. Stellar streams are composed of material that has been tidally striped from dwarf galaxies and globular clusters and hence are excellent dynamical probes of the gravitational potential of the Milky Way, as well as providing a detailed snapshot of its accretion history. Observing with the 3.9-m Anglo-Australian Telescope's 2-degree-Field fibre positioner and AAOmega spectrograph, and combining the precise photometry of DES DR1 with the superb proper motions from $Gaia$ DR2, allows us to conduct an efficient spectroscopic survey to map these stellar streams. So far ${S}^5$ has mapped 9 DES streams and 3 streams outside of DES; the former are the first spectroscopic observations of these recently discovered streams. In addition to the stream survey, we use spare fibres to undertake a Milky Way halo survey and a low-redshift galaxy survey. This paper presents an overview of the ${S}^5$ program, describing the scientific motivation for the survey, target selection, observation strategy, data reduction and survey validation. Finally, we describe early science results on stellar streams and Milky Way halo stars drawn from the survey. Updates on ${S}^5$, including future public data release, can be found at \url{http://s5collab.github.io}., Comment: 25 pages, 14 figures (1 in appendix), 3 tables (1 in appendix). Published on MNRAS. See also paper from Shipp et al. 2019, which measures the proper motion of the DES streams

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

Nadler, Ethan O, et al. DES Collaboration, We perform a comprehensive study of Milky Way (MW) satellite galaxies to constrain the fundamental properties of dark matter (DM). This analysis fully incorporates inhomogeneities in the spatial distribution and detectability of MW satellites and marginalizes over uncertainties in the mapping between galaxies and DM halos, the properties of the MW system, and the disruption of subhalos by the MW disk. Our results are consistent with the cold, collisionless DM paradigm and yield the strongest cosmological constraints to date on particle models of warm, interacting, and fuzzy dark matter. At 95% confidence, we report limits on (i) the mass of thermal relic warm DM, mWDM>6.5 keV (free-streaming length, λfs≲10h-1 kpc), (ii) the velocity-independent DM-proton scattering cross section, σ02.9×10-21 eV (de Broglie wavelength, λdB≲0.5 kpc). These constraints are complementary to other observational and laboratory constraints on DM properties., The DES participants from Spanish institutions are partially supported by MICINN under Grants No. ESP2017-89838, No. PGC2018-094773, No. PGC2018-102021, No. SEV-2016-0588, No. SEV-2016-0597, and No. MDM-2015-0509, some of which include ERDF funds from the European Union. I. F. A. E. is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC Grant Agreements No. 240672, No. 291329, and No. 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) e-Universe (CNPq Grant No. 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.

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., 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

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

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., 27 pages, 18 figures, 1 table. Accepted to ApJ. Code available at https://github.com/jwuphysics/xsaga

We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging data set, 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 deg2. We have developed new photometric redshift (photo-z) estimates using the Legacy Survey DECam and WISE photometry, with σNMAD = 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 catalogue, 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 catalogues, and present a new technique for finding best-fitting parameters in this situation. Accompanying this paper, we have released the Photometric Redshifts for the Legacy Surveys catalogue of photo-z's obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 data set. This catalogue provides accurate photometric redshifts for objects with z < 21 over more than 16 000 deg2 of sky. © 2020 The Author(s), Published by Oxford University Press on behalf of Royal Astronomical Society, The authors would like to thank Hee-Jong Seo, Jeremy Tinker, and Gustavo Niz for their feedback on the draft and useful discussions. RZ and JANwere supported by the U.S. Department of Energy Office of Science, Office of High Energy Physics via grant DE-SC0007914. RZalso is supported by the Director, Office of Science, Office ofHigh Energy Physics of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123. Support for YYM was provided by the Pittsburgh Particle Physics, Astrophysics and Cosmology Center through the Samuel P. Langley PITT PACC Postdoctoral Fellowship, and by NASA through the NASA Hubble Fellowship grant no. HST-HF2-51441.001 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. JM gratefully acknowledges support from NSF grant AST-1616414 and DOE grant DE-SC0020086. ADM was supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0019022. ARZ was funded by the US National Science Foundation (NSF) through grants AST 1516266 and AST 1517563. DYT thanks Prof. Steve Ahlen for his mentorship and support and acknowledges the generous support by U.S. Department of Energy Office of Science, grant No. DE-SC0015628. This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences underContract No. AST-0950945 to the National Optical Astronomy Observatory; the Science and Technologies Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic EnergyCommission (CEA); the National Council of Science and Technology of Mexico, and by the DESI Member Institutions. The authors are honoured to be permitted to conduct astronomical research on Iolkam Du'ag (Kitt Peak), a mountain with particular significance to the Tohono O'odham Nation. The Legacy Surveys consist of three individual and complementary projects: the Dark Energy Camera Legacy Survey (DECaLS; NOAO Proposal ID #2014B-0404; PIs: David Schlegel and Arjun Dey), the Beijing-Arizona Sky Survey (BASS; NOAO Proposal ID #2015A-0801; PIs: Zhou Xu and Xiaohui Fan), and theMayall z-band Legacy Survey (MzLS; NOAOProposal ID #2016A-0453; PI: Arjun Dey). DECaLS, BASS, and MzLS together include data obtained, respectively, at the Blanco telescope, Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory (NOAO); the Bok telescope, Steward Observatory, University of Arizona; and the Mayall telescope, Kitt Peak National Observatory, NOAO. The Legacy Surveys project is honoured to be permitted to conduct astronomical research on Iolkam Du'ag (Kitt Peak), a mountain with particular significance to the Tohono O'odham Nation. This project used data obtained with the Dark Energy Camera (DECam), which was constructed by the Dark Energy Survey (DES) collaboration. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at UrbanaChampaign, the Kavli Institute of Cosmological Physics at the University of Chicago, Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and the Ministerio da Ciencia, Tecnologia e Inovacao, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenossische Technische Hochschule (ETH) Zurich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciencies de l'Espai (IEEC/CSIC), the Institut de Fisica d'Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universitat Munchen and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, the Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, and Texas A&M University. BASS is a key project of the Telescope Access Program (TAP), which has been funded by the National Astronomical Observatories of China, the Chinese Academy of Sciences (the Strategic Priority Research Program 'The Emergence of Cosmological Structures' Grant #XDB09000000), and the Special Fund for Astronomy from the Ministry of Finance. The BASS is also supported by the External Cooperation Program of Chinese Academy of Sciences (Grant #114A11KYSB20160057), and National Natural Science Foundation of China (Grant #11433005). The Legacy Survey team makes use of data products from the Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE), which is a project of the Jet Propulsion Laboratory/California Institute of Technology. NEOWISE is funded by the National Aeronautics and Space Administration. The Legacy Surveys imaging of the DESI footprint is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123, by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; and by the U.S. National Science Foundation, Division of Astronomical Sciences under Contract No. AST-0950945 to NOAO. Funding for the DEEP2 Galaxy Redshift Survey has been provided by NSF grants AST-95-09298, AST-0071048, AST-0507428, and AST-0507483 as well as NASA LTSA grant NNG04GC89G. Funding for the DEEP3 Galaxy Redshift Survey has been provided by NSF grants AST-0808133, AST-0807630, and AST-0806732. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, theU.S. Department ofEnergy, theNational Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy Office of Science. Funding for the SloanDigital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. GAMA is a joint European-Australasian project based around a spectroscopic campaign using the Anglo-Australian Telescope. The GAMA input catalogue is based on data taken from the Sloan Digital Sky Survey and the UKIRT Infrared Deep Sky Survey. Complementary imaging of the GAMA regions is being obtained by a number of independent survey programmes including GALEX MIS, VST KiDS, VISTA VIKING, WISE, Herschel-ATLAS, GMRT and ASKAP providing UV to radio coverage. GAMA is funded by the STFC (UK), the ARC (Australia), the AAO, and the participating institutions. The GAMA website is http://www.gama-survey.org/.This paper uses data from the VIMOS Public Extragalactic Redshift Survey (VIPERS). VIPERS has been performed using the ESO Very Large Telescope, under the `Large Programme' 182.A-0886. The participating institutions and funding agencies are listed at http://vipers.inaf.it.This research uses data from the VIMOS VLT Deep Survey, obtained from the VVDS database operated by Cesam, Laboratoire d'Astrophysique de Marseille, France., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709.

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., 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., 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., 19 pages, 10 figures, 1 table. Updated to published version

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., 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

We measure how the properties of star-forming central galaxies correlate with large-scale environment, $\delta$, measured on $10$Mpc/h scales. We use group catalogs to isolate a robust sample of central galaxies with high purity and completeness. The properties we investigate are star formation rate (SFR), exponential disk scale length $R_{\rm exp}$, and Sersic index of the light profile, $n$. We find that, at all stellar masses, there is an inverse correlation between SFR and $\delta$, meaning that above-average star forming centrals live in underdense regions. For $n$ and $R_{\rm exp}$, there is no correlation with $\delta$ at $M_{\rm star}\lesssim 10^{10.5}$ $M_\odot$, but at higher masses there are positive correlations; a weak correlation with $R_{\rm exp}$ and a strong correlation with $n$. These data are evidence of assembly bias within the star-forming population. The results for SFR are consistent with a model in which SFR correlates with present-day halo accretion rate, $\dot{M}_h$. In this model, galaxies are assigned to halos using the abundance matching ansatz, which maps galaxy stellar mass onto halo mass. At fixed halo mass, SFR is assigned to galaxies using the same approach,but $\dot{M}_h$ is used to map onto SFR. The best-fit model requires some scatter in the $\dot{M}_h$-SFR relation. The $R_{\rm exp}$ and $n$ measurements are consistent with a model in which these quantities are correlated with the spin parameter of the halo, $\lambda$. Halo spin does not correlate with $\delta$ at low halo masses, but for higher mass halos, high-spin halos live in higher density environments at fixed $M_h$. Put together with the earlier installments of this series, these data demonstrate that quenching processes have limited correlation with halo formation history, but the growth of active galaxies, as well as other detailed properties, are influenced by the details of halo assembly., Comment: 13 pages, submitted to MNRAS

We test whether halo age and galaxy age are correlated at fixed halo and galaxy mass. The formation histories, and thus ages, of dark matter halos correlate with their large-scale density $\rho$, an effect known as assembly bias. We test whether this correlation extends to galaxies by measuring the dependence of galaxy stellar age on $\rho$. To clarify the comparison between theory and observation, and to remove the strong environmental effects on satellites, we use galaxy group catalogs to identify central galaxies and measure their quenched fraction, $f_Q$, as a function of large-scale environment. Models that match halo age to central galaxy age predict a strong positive correlation between $f_Q$ and $\rho$. However, we show that the amplitude of this effect depends on the definition of halo age: assembly bias is significantly reduced when removing the effects of splashback halos---those halos that are central but have passed through a larger halo or experienced strong tidal encounters. Defining age using halo mass at its peak value rather than current mass removes these effects. In SDSS data, at M$_{\rm gal}\gtrsim 10^{10.0}$ M_sol/h$^2$, there is a $\sim 5\%$ increase in $f_Q$ from low to high densities, which is in agreement with predictions of dark matter halos using peak halo mass. At lower stellar mass there is little to no correlation of $f_Q$ with $\rho$. For these galaxies, age-matching is inconsistent with the data across the wide range the halo formation metrics that we tested. This implies that halo formation history has a small but statistically significant impact on quenching of star formation at high masses, while the quenching process in low-mass central galaxies is uncorrelated with halo formation history., Comment: 13 pages, 12 figures, submitted to 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 $, 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

94 pages, 22 figures, 1 table; 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/ .

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

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

Existing models for the dependence of the halo mass function on cosmological parameters will become a limiting source of systematic uncertainty for cluster cosmology in the near future. We present a halo mass function emulator and demonstrate improved accuracy relative to state-of-the-art analytic models. In this work, mass is defined using an overdensity criteria of 200 relative to the mean background density. Our emulator is constructed from the AEMULUS simulations, a suite of 40 N-body simulations with snapshots from z=3 to z=0. These simulations cover the flat wCDM parameter space allowed by recent Cosmic Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae results, varying the parameters w, Omega_m, Omega_b, sigma_8, N_{eff}, n_s, and H_0. We validate our emulator using five realizations of seven different cosmologies, for a total of 35 test simulations. These test simulations were not used in constructing the emulator, and were run with fully independent initial conditions. We use our test simulations to characterize the modeling uncertainty of the emulator, and introduce a novel way of marginalizing over the associated systematic uncertainty. We confirm non-universality in our halo mass function emulator as a function of both cosmological parameters and redshift. Our emulator achieves better than 1% precision over much of the relevant parameter space, and we demonstrate that the systematic uncertainty in our emulator will remain a negligible source of error for cluster abundance studies through at least the LSST Year 1 data set., Comment: https://aemulusproject.github.io/

Galaxy clustering on small scales is significantly under-predicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, $M_{\rm peak}$. SHAM models based on the peak maximum circular velocity, $V_{\rm peak}$, have had much better success. The primary reason $M_{\rm peak}$ based models fail is the relatively low abundance of satellite galaxies produced in these models compared to those based on $V_{\rm peak}$. Despite success in predicting clustering, a simple $V_{\rm peak}$ based SHAM model results in predictions for galaxy growth that are at odds with observations. We evaluate three possible remedies that could "save" mass-based SHAM: (1) SHAM models require a significant population of "orphan" galaxies as a result of artificial disruption/merging of sub-haloes in modern high resolution dark matter simulations; (2) satellites must grow significantly after their accretion; and (3) stellar mass is significantly affected by halo assembly history. No solution is entirely satisfactory. However, regardless of the particulars, we show that popular SHAM models based on $M_{\rm peak}$ cannot be complete physical models as presented. Either $V_{\rm peak}$ truly is a better predictor of stellar mass at $z\sim 0$ and it remains to be seen how the correlation between stellar mass and $V_{\rm peak}$ comes about, or SHAM models are missing vital component(s) that significantly affect galaxy clustering., 25 pages, 22 figures, submitted to MNRAS, comments welcome

A strong correlation has been measured between the observed centripetal accelerations in galaxies and the accelerations implied by the baryonic components of galaxies. This empirical radial acceleration relation must be accounted for in any viable model of galaxy formation. We measure and compare the radial accelerations contributed by baryons and by dark matter in disk galaxies in the MassiveBlack-II hydrodynamic galaxy formation simulation. The sample of 1594 galaxies spans three orders of magnitude in luminosity and four in surface brightness, comparable to the observed sample from the Spitzer Photometry & Accurate Rotation Curves (SPARC) dataset used by McGaugh et al. (2016). We find that radial accelerations contributed by baryonic matter only and by total matter are highly correlated, with only small scatter around their mean or median relation, despite the wide ranges of galaxy luminosity and surface brightness. We further find that the radial acceleration relation in this simulation differs from that of the SPARC sample, and can be described by a simple power law in the acceleration range we are probing., 7 pages, 4 figures

The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys. The catalogs have diverse applications, such as investigating signatures of fundamental physics in cosmological observables, understanding the effect of systematic uncertainties on measured signals and testing mitigation strategies for reducing these uncertainties, aiding analysis pipeline development and testing, and survey strategy optimization. The list of applications is growing with improvements in the quality of the catalogs and the details that they can provide. Given the importance of simulated catalogs, it is critical to provide rigorous validation protocols that enable both catalog providers and users to assess the quality of the catalogs in a straightforward and comprehensive way. For this purpose, we have developed the DESCQA framework for the Large Synoptic Survey Telescope Dark Energy Science Collaboration as well as for the broader community. The goal of DESCQA is to enable the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. In this paper, we present the design concept and first implementation of DESCQA. In order to establish and demonstrate its full functionality we use a set of interim catalogs and validation tests. We highlight several important aspects, both technical and scientific, that require thoughtful consideration when designing a validation framework, including validation metrics and how these metrics impose requirements on the synthetic sky catalogs., La lista completa de autores se encuentra en el documento., Instituto de Astrofísica de La Plata, Facultad de Ciencias Astronómicas y Geofísicas

Secondary halo bias, commonly known as 'assembly bias,' is the dependence of halo clustering on a halo property other than mass. This prediction of the Lambda-Cold Dark Matter cosmology is essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property., Comment: 14+1 pages, 9+1 figures. Figures 2 and 8 highlight the main results. Accepted by MNRAS. Fig 9 updated; main result unchanged

Merger tree codes are routinely used to follow the growth and merger of dark matter haloes in simulations of cosmic structure formation. Whereas in Srisawat et. al. we compared the trees built using a wide variety of such codes here we study the influence of the underlying halo catalogue upon the resulting trees. We observe that the specifics of halo finding itself greatly influences the constructed merger trees. We find that the choices made to define the halo mass are of prime importance. For instance, amongst many potential options different finders select self-bound objects or spherical regions of defined overdensity, decide whether or not to include substructures within the mass returned and vary in their initial particle selection. The impact of these decisions is seen in tree length (the period of time a particularly halo can be traced back through the simulation), branching ratio (essentially the merger rate of \subhalos) and mass evolution. We therefore conclude that the choice of the underlying halo finder is more relevant to the process of building merger trees than the tree builder itself. We also report on some built-in features of specific merger tree codes that (sometimes) help to improve the quality of the merger trees produced., Accepted in MNRAS. 15 pages, 10 figures, 1 table

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., 16 pages, 12 figures, 3 Tables Project website: https://aemulusproject.github.io/

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, Comment: 14 pages, 8 figures, 1 table; submitted to ApJ; the project webpage is available at https://aemulusproject.github.io ; typo in Figure 7 and caption updated, results unchanged

Merger trees follow the growth and merger of dark-matter haloes over cosmic history. As well as giving important insights into the growth of cosmic structure in their own right, they provide an essential backbone to semi-analytic models of galaxy formation. This paper is the first in a series to arise from the SUSSING MERGER TREES Workshop in which ten different tree-building algorithms were applied to the same set of halo catalogues and their results compared. Although many of these codes were similar in nature, all algorithms produced distinct results. Our main conclusions are that a useful merger-tree code should possess the following features: (i) the use of particle IDs to match haloes between snapshots; (ii) the ability to skip at least one, and preferably more, snapshots in order to recover subhaloes that are temporarily lost during merging; (iii) the ability to cope with (and ideally smooth out) large, temporary flucuations in halo mass. Finally, to enable different groups to communicate effectively, we defined a common terminology that we used when discussing merger trees and we encourage others to adopt the same language. We also specified a minimal output format to record the results., Comment: 14 pages,11 figures

Many properties of the Milky Way's dark matter halo, including its mass assembly history, concentration, and subhalo population, remain poorly constrained. We explore the connection between these properties of the Milky Way and its satellite galaxy population, especially the implication of the presence of the Magellanic Clouds for the properties of the Milky Way halo. Using a suite of high-resolution $N$-body simulations of Milky Way-mass halos with a fixed final Mvir ~ 10^{12.1}Msun, we find that the presence of Magellanic Cloud-like satellites strongly correlates with the assembly history, concentration, and subhalo population of the host halo, such that Milky Way-mass systems with Magellanic Clouds have lower concentration, more rapid recent accretion, and more massive subhalos than typical halos of the same mass. Using a flexible semi-analytic galaxy formation model that is tuned to reproduce the stellar mass function of the classical dwarf galaxies of the Milky Way with Markov-Chain Monte-Carlo, we show that adopting host halos with different mass-assembly histories and concentrations can lead to different best-fit models for galaxy-formation physics, especially for the strength of feedback. These biases arise because the presence of the Magellanic Clouds boosts the overall population of high-mass subhalos, thus requiring a different stellar-mass-to-halo-mass ratio to match the data. These biases also lead to significant differences in the mass--metallicity relation, the kinematics of low-mass satellites, the number counts of small satellites associated with the Magellanic Clouds, and the stellar mass of Milky Way itself. Observations of these galaxy properties can thus provide useful constraints on the properties of the Milky Way halo., Comment: 20 pages, 12 figures, accepted for publication in ApJ. A new section on the effect of host halo mass-assembly history on the central galaxy stellar mass is added

We present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies starting from a catalog of dark matter halos obtained from a cosmological simulation. The package supports many of the common forms used to describe galaxy-halo models: the halo occupation distribution (HOD), the conditional luminosity function (CLF), abundance matching, and alternatives to these models that include effects such as environmental quenching or variable galaxy assembly bias. Satellite galaxies can be modeled to live in subhalos, or to follow custom number density profiles within their halos, including spatial and/or velocity bias with respect to the dark matter profile. The package has an optimized toolkit to make mock observations on a synthetic galaxy population, including galaxy clustering, galaxy-galaxy lensing, galaxy group identification, RSD multipoles, void statistics, pairwise velocities and others, allowing direct comparison to observations. Halotools is object-oriented, enabling complex models to be built from a set of simple, interchangeable components, including those of your own creation. Halotools has an automated testing suite and is exhaustively documented on http://halotools.readthedocs.io, which includes quickstart guides, source code notes and a large collection of tutorials. The documentation is effectively an online textbook on how to build and study empirical models of galaxy formation with Python., Revisions match version accepted for publication in AAS

We study the mass spectrum of destroyed dwarfs that contribute to the accreted stellar mass of Milky Way (MW) mass M_vir ~ 10^12.1 M_sun) halos using a suite of 45 zoom-in, dissipationless simulations. Empirical models are employed to relate (peak) subhalo mass to dwarf stellar mass, and we use constraints from z=0 observations and hydrodynamical simulations to estimate the metallicity distribution of the accreted stellar material. The dominant contributors to the accreted stellar mass are relatively massive dwarfs with M_star ~ 10^8-10^10 M_sun. Halos with more quiescent accretion histories tend to have lower mass progenitors (10^8-10^9 M_sun), and lower overall accreted stellar masses. Ultra-faint mass (M_star < 10^5 M_sun) dwarfs contribute a negligible amount (<< 1%) to the accreted stellar mass and, despite having low average metallicities, supply a small fraction (~2-5 %) of the very metal-poor stars with [Fe/H] < -2. Dwarfs with masses 10^5 < M_star/M_sun < 10^8 provide a substantial amount of the very metal-poor stellar material (~40-80 %), and even relatively metal-rich dwarfs with M_star > 10^8 M_sun can contribute a considerable fraction (~20-60 %) of metal-poor stars if their metallicity distributions have significant metal-poor tails. Finally, we find that the generic assumption of a quiescent assembly history for the MW halo seems to be in tension with the mass spectrum of its surviving dwarfs. We suggest that the MW could be a "transient fossil"; a quiescent halo with a recent accretion event(s) that disguises the preceding formation history of the halo., 12 pages, 10 figures. Accepted by ApJ

Empirical methods for connecting galaxies to their dark matter halos have become essential for interpreting measurements of the spatial statistics of galaxies. In this work, we present a novel approach for parameterizing the degree of concentration dependence in the abundance matching method. This new parameterization provides a smooth interpolation between two commonly used matching proxies: the peak halo mass and the peak halo maximal circular velocity. This parameterization controls the amount of dependence of galaxy luminosity on halo concentration at a fixed halo mass. Effectively this interpolation scheme enables abundance matching models to have adjustable assembly bias in the resulting galaxy catalogs. With the new 400 Mpc/h DarkSky Simulation, whose larger volume provides lower sample variance, we further show that low-redshift two-point clustering and satellite fraction measurements from SDSS can already provide a joint constraint on this concentration dependence and the scatter within the abundance matching framework., 15 pages, 11 figures. APJ in press. Matched published version

Merging haloes with similar masses (i.e., major mergers) pose significant challenges for halo finders. We compare five halo finding algorithms' (AHF, HBT, Rockstar, SubFind, and VELOCIraptor) recovery of halo properties for both isolated and cosmological major mergers. We find that halo positions and velocities are often robust, but mass biases exist for every technique. The algorithms also show strong disagreement in the prevalence and duration of major mergers, especially at high redshifts (z>1). This raises significant uncertainties for theoretical models that require major mergers for, e.g., galaxy morphology changes, size changes, or black hole growth, as well as for finding Bullet Cluster analogues. All finders not using temporal information also show host halo and subhalo relationship swaps over successive timesteps, requiring careful merger tree construction to avoid problematic mass accretion histories. We suggest that future algorithms should combine phase-space and temporal information to avoid the issues presented., Figs. 2, 4, and 7 show the main issues. This project was initiated at the Subhaloes Going Notts conference (http://popia.ft.uam.es/SubhaloesGoingNotts/Home.html). MNRAS submitted

Hierarchical structure formation implies that the number of subhalos within a dark matter halo depends not only on halo mass, but also on the formation history of the halo. This dependence on the formation history, which is highly correlated with halo concentration, can account for the super-Poissonian scatter in subhalo occupation at a fixed halo mass that has been previously measured in simulations. Here we propose a model to predict the subhalo abundance function for individual host halos, that incorporates both halo mass and concentration. We combine results of cosmological simulations with a new suite of zoom-in simulations of Milky Way-mass halos to calibrate our model. We show the model can successfully reproduce the mean and the scatter of subhalo occupation in these simulations. The implications of this correlation between subhalo abundance and halo concentration are further investigated. We also discuss cases in which inferences about halo properties can be affected if this correlation between subhalo abundance and halo concentration is ignored; in these cases our model would give a more accurate inference. We propose that with future deep surveys, satellite occupation in the low-mass regime can be used to verify the existence of halo assembly bias., Comment: ApJ in print. Updated to match publication version. 13 pages, 14 figures

We report the discovery of eight new ultra-faint dwarf galaxy candidates in the second year of optical imaging data from the Dark Energy Survey (DES). Six of these candidates are detected at high confidence, while two lower-confidence candidates are identified in regions of non-uniform survey coverage. The new stellar systems are found by three independent automated search techniques and are identified as overdensities of stars, consistent with the isochrone and luminosity function of an old and metal-poor simple stellar population. The new systems are faint (Mv > -4.7 mag) and span a range of physical sizes (17 pc < $r_{1/2}$ < 181 pc) and heliocentric distances (25 kpc < D < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultra-faint dwarf galaxies (��< 27.5 mag arcsec$^{-2}$). Roughly half of the DES candidates are more distant, less luminous, and/or have lower surface brightnesses than previously known Milky Way satellite galaxies. Most of the candidates are found in the southern part of the DES footprint close to the Magellanic Clouds. We find that the DES data alone exclude (p < 0.001) a spatially isotropic distribution of Milky Way satellites and that the observed distribution can be well, though not uniquely, described by an association between several of the DES satellites and the Magellanic system. Our model predicts that the full sky may hold ~100 ultra-faint galaxies with physical properties comparable to the DES satellites and that 20-30% of these would be spatially associated with the Magellanic Clouds., 46 pages, 16 figures, 4 tables; Update to matched published version. Note that the name of DES J2038-4609/Indus II has been changed to disambiguate it from Kim 2/DES J2108.8-5109/Indus I

A halo merger tree forms the essential backbone of a semi-analytic model for galaxy formation and evolution. Recent studies have pointed out that extracting merger trees from numerical simulations of structure formation is non-trivial; different tree building algorithms can give differing merger histories. These differences should be carefully understood before merger trees are used as input for models of galaxy formation. We investigate the impact of different halo merger trees on a semi-analytic model. We find that the z=0 galaxy properties in our model show differences between trees when using a common parameter set. The star formation history of the Universe and the properties of satellite galaxies can show marked differences between trees with different construction methods. Independently calibrating the semi-analytic model for each tree can reduce the discrepancies between the z=0 global galaxy properties, at the cost of increasing the differences in the evolutionary histories of galaxies. Furthermore, the underlying physics implied can vary, resulting in key quantities such as the supernova feedback efficiency differing by factors of 2. Such a change alters the regimes where star formation is primarily suppressed by supernovae. Therefore, halo merger trees extracted from a common halo catalogue using different, but reliable, algorithms can result in a difference in the semi-analytic model. Given the uncertainties in galaxy formation physics, however, these differences may not necessarily be viewed as significant., Comment: 15 pages, 18 figures, accepted for publication in MNRAS

We examine the Velocity Distribution Function (VDF) in dark matter halos from Milky Way to cluster mass scales. We identify an empirical model for the VDF with a wider peak and a steeper tail than a Maxwell--Boltzmann distribution, and discuss physical explanations. We quantify sources of scatter in the VDF of cosmological halos and their implication for direct detection of dark matter. Given modern simulations and observations, we find that the most significant uncertainty in the VDF of the Milky Way arises from the unknown radial position of the solar system relative to the dark matter halo scale radius., Comment: Accepted to ApJ. Figure 3 and 5 and Section 4 newly added. 6 pages, 6 figures, typeset using emulateapj

We discuss the properties of subhalos in cluster-size halos, using a high-resolution statistical sample: the Rhapsody simulations introduced in Wu et al. (2012). We demonstrate that the criteria applied to select subhalos have significant impact on the inferred properties of the sample, including the scatter in the number of subhalos, the correlation between the subhalo number and formation time, and the shape of subhalos' spatial distribution and velocity structure. We find that the number of subhalos, when selected using the peak maximum circular velocity in their histories (a property expected to be closely related to the galaxy luminosity), is uncorrelated with the formation time of the main halo. This is in contrast to the previously reported correlation from studies where subhalos are selected by the current maximum circular velocity; we show that this difference is a result of the tidal stripping of the subhalos. We also find that the dominance of the main halo and the subhalo mass fraction are strongly correlated with halo concentration and formation history. These correlations are important to take into account when interpreting results from cluster samples selected with different criteria. Our sample also includes a fossil cluster, which is presented separately and placed in the context of the rest of the sample., Comment: 15 pages, 10 figures; Paper I: arXiv:1209.3309; replaced to match published version

We present the first results from the Rhapsody cluster re-simulation project: a sample of 96 "zoom-in" simulations of dark matter halos of 10^14.8 +- 0.05 Msun/h, selected from a 1 (Gpc/h)^3 volume. This simulation suite is the first to resolve this many halos with ~5x10^6 particles per halo in the cluster-mass regime, allowing us to statistically characterize the distribution of and correlation between halo properties at fixed mass. We focus on the properties of the main halos and how they are affected by formation history, which we track back to z=12, over five decades in mass. We give particular attention to the impact of the formation history on the density profiles of the halos. We find that the deviations from the Navarro-Frenk-White (NFW) model and the Einasto model depend on formation time. Late-forming halos tend to have considerable deviations from both models, partly due to the presence of massive subhalos, while early-forming halos deviate less but still significantly from the NFW model and are better described by the Einasto model. We find that the halo shapes depend only moderately on formation time. Departure from spherical symmetry impacts the density profiles through the anisotropic distribution of massive subhalos. Further evidence of the impact of subhalos is provided by analyzing the phase-space structure. A detailed analysis of the properties of the subhalo population in Rhapsody is presented in a companion paper., 20 pages, 13 figures, replaced to match published version

Determining the positions of halo centres in large-scale structure surveys is crucial for many cosmological studies. A common assumption is that halo centres correspond to the location of their brightest member galaxies. In this paper, we study the dynamics of brightest galaxies with respect to other halo members in the Sloan Digital Sky Survey DR7. Specifically, we look at the line-of-sight velocity and spatial offsets between brightest galaxies and their neighbours. We compare those to detailed mock catalogues, constructed from high-resolution, dark-matter-only $N$-body simulations, in which it is assumed that satellite galaxies trace dark matter subhaloes. This allows us to place constraints on the fraction $f_{\rm BNC}$ of haloes in which the brightest galaxy is not the central. Compared to previous studies we explicitly take into account the unrelaxed state of the host haloes, velocity offsets of halo cores and correlations between $f_{\rm BNC}$ and the satellite occupation. We find that $f_{\rm BNC}$ strongly decreases with the luminosity of the brightest galaxy and increases with the mass of the host halo. Overall, in the halo mass range $10^{13} - 10^{14.5} h^{-1} M_\odot$ we find $f_{\rm BNC} \sim 30\%$, in good agreement with a previous study by Skibba et al. We discuss the implications of these findings for studies inferring the galaxy--halo connection from satellite kinematics, models of the conditional luminosity function and galaxy formation in general., Comment: 24 pages, 15 figures. Accepted for publication in MNRAS

Dwarf galaxies are known to have remarkably low star formation efficiency due to strong feedback. Adopting the dwarf galaxies of the Milky Way as a laboratory, we explore a flexible semi-analytic galaxy formation model to understand how the feedback processes shape the satellite galaxies of the Milky Way. Using Markov-Chain Monte-Carlo, we exhaustively search a large parameter space of the model and rigorously show that the general wisdom of strong outflows as the primary feedback mechanism cannot simultaneously explain the stellar mass function and the mass--metallicity relation of the Milky Way satellites. An extended model that assumes that a fraction of baryons is prevented from collapsing into low-mass halos in the first place can be accurately constrained to simultaneously reproduce those observations. The inference suggests that two different physical mechanisms are needed to explain the two different data sets. In particular, moderate outflows with weak halo mass dependence are needed to explain the mass--metallicity relation, and prevention of baryons falling into shallow gravitational potentials of low-mass halos (e.g. "pre-heating") is needed to explain the low stellar mass fraction for a given subhalo mass., 14 pages, 4 figures, accepted for publication in ApJ

We identify subhalos in dark matter-only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)-mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion, and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an $85\%$ out-of-bag classification score. We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations., Comment: 20 pages, 14 figures. Updated to published version. Code available at https://github.com/ollienad/subhalo_randomforest

Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by spherical overdensity parameter, $\Delta$. We summarize the strength of concentration-, shape-, and spin-dependent halo clustering as a function of halo mass and halo definition. Concentration-dependent clustering depends strongly on mass at all $\Delta$. For conventional halo definitions ($\Delta \sim 200\mathrm{m}-600\mathrm{m}$), concentration-dependent clustering at low mass is driven by a population of haloes that is altered through interactions with neighbouring haloes. Concentration-dependent clustering can be greatly reduced through a mass-dependent halo definition with $\Delta \sim 20\mathrm{m}-40\mathrm{m}$ for haloes with $M_{200\mathrm{m}} \lesssim 10^{12}\, h^{-1}\mathrm{M}_{\odot}$. Smaller $\Delta$ implies larger radii and mitigates assembly bias at low mass by subsuming altered, so-called backsplash haloes into now larger host haloes. At higher masses ($M_{200\mathrm{m}} \gtrsim 10^{13}\, h^{-1}\mathrm{M}_{\odot}$) larger overdensities, $\Delta \gtrsim 600\mathrm{m}$, are necessary. Shape- and spin-dependent clustering are significant for all halo definitions that we explore and exhibit a relatively weaker mass dependence. Generally, both the strength and the sense of assembly bias depend on halo definition, varying significantly even among common definitions. We identify no halo definition that mitigates all manifestations of assembly bias. A halo definition that mitigates assembly bias based on one halo property (e.g., concentration) must be mass dependent. The halo definitions that best mitigate concentration-dependent halo clustering do not coincide with the expected average splashback radii at fixed halo mass., Comment: 19 pages, 13 figures. Updated to published version. Main result summarized in Figure 10

Using group catalogs from the SDSS DR7, we attempt to measure galactic conformity in the local universe. We measure the quenched fraction of neighbor galaxies around isolated primary galaxies, dividing the isolated sample into star-forming and quiescent objects. We restrict our measurements to scales $>1$ Mpc to probe the correlations between the formation histories of distinct halos. Over the stellar mass range $10^{9.7} \le M_\ast/M_\odot \le 10^{10.9}$, we find minimal statistical evidence for conformity. We further compare these data to predictions of the halo age-matching model, in which the oldest galaxies are associated with the oldest halos at fixed $M_\ast$. For models with strong correlations between halo and stellar age, the conformity signal is too large to be consistent with the data. For weaker implementations of age-matching, galactic conformity is not a sensitive diagnostic of halo assembly bias, and would not produce a detectable signal in SDSS data. We reproduce the results of Kauffmann et al 2013, in which the star formation rates of neighbor galaxies are significantly reduced around primary galaxies when the primaries are themselves low star formers. However, we find this result is mainly driven by contamination in the isolation criterion, when using our group catalog to remove the small fraction of satellite galaxies in the sample, the conformity signal largely goes away. Lastly, we show that small conformity signals, i.e., 2-5% differences in the quenched fractions of neighbor galaxies, can be produced by mechanisms other than halo assembly bias. For example, if passive galaxies occupy more massive halos than star forming galaxies of the same stellar mass, a conformity signal that is consistent with recent measurements from PRIMUS (Berti et al 2016) can be produced., 13 pages, 7 figures, submitted to MNRAS

We present the survey strategy and early results of the "Satellites Around Galactic Analogs" (SAGA) Survey. The SAGA Survey's goal is to measure the distribution of satellite galaxies around 100 systems analogous to the Milky Way down to the luminosity of the Leo I dwarf galaxy ($ M_r < -12.3 $). We define a Milky Way analog based on $K$-band luminosity and local environment. Here, we present satellite luminosity functions for 8 Milky Way analog galaxies between 20 to 40 Mpc. These systems have nearly complete spectroscopic coverage of candidate satellites within the projected host virial radius down to $ r_o < 20.75 $ using low redshift $gri$ color criteria. We have discovered a total of 25 new satellite galaxies: 14 new satellite galaxies meet our formal criteria around our complete host systems, plus 11 additional satellites in either incompletely surveyed hosts or below our formal magnitude limit. Combined with 13 previously known satellites, there are a total of 27 satellites around 8 complete Milky Way analog hosts. We find a wide distribution in the number of satellites per host, from 1 to 9, in the luminosity range for which there are five Milky Way satellites. Standard abundance matching extrapolated from higher luminosities predicts less scatter between hosts and a steeper luminosity function slope than observed. We find that the majority of satellites (26 of 27) are star-forming. These early results indicate that the Milky Way has a different satellite population than typical in our sample, potentially changing the physical interpretation of measurements based only on the Milky Way's satellite galaxies., 22 pages, 19 figures, 2 tables. Updated to published version. Survey website: http://sagasurvey.org/

We study the abundance of substructure in the matter density near galaxies using ALMA Science Verification observations of the strong lensing system SDP.81. We present a method to measure the abundance of subhalos around galaxies using interferometric observations of gravitational lenses. Using simulated ALMA observations, we explore the effects of various systematics, including antenna phase errors and source priors, and show how such errors may be measured or marginalized. We apply our formalism to ALMA observations of SDP.81. We find evidence for the presence of a $M=10^{8.96\pm 0.12} M_{\odot}$ subhalo near one of the images, with a significance of $6.9\sigma$ in a joint fit to data from bands 6 and 7; the effect of the subhalo is also detected in both bands individually. We also derive constraints on the abundance of dark matter subhalos down to $M\sim 2\times 10^7 M_{\odot}$, pushing down to the mass regime of the smallest detected satellites in the Local Group, where there are significant discrepancies between the observed population of luminous galaxies and predicted dark matter subhalos. We find hints of additional substructure, warranting further study using the full SDP.81 dataset (including, for example, the spectroscopic imaging of the lensed carbon monoxide emission). We compare the results of this search to the predictions of $\Lambda$CDM halos, and find that given current uncertainties in the host halo properties of SDP.81, our measurements of substructure are consistent with theoretical expectations. Observations of larger samples of gravitational lenses with ALMA should be able to improve the constraints on the abundance of galactic substructure., Comment: 18 pages, 13 figures, Comments are welcome