arXiv subjects

Andreas A. Berlind

Publications and source records attributed to Andreas A. Berlind.

At least 19 recordsLinked to original sources

arXiv2023

Why do semi-analytic models predict higher scatter in the stellar mass-halo mass relation than cosmological hydrodynamic simulations?

Semi-analytic models (SAMs) systematically predict higher stellar-mass scatter at a given halo mass than hydrodynamical simulations and most empirical models. Our goal is to investigate the physical origin of this scatter by exploring modifications to the physics in the SAM Dark Sage. We design two black hole formation models that approximate results from the IllustrisTNG 300-1 hydrodynamical simulation. In the first model, we assign a fixed black hole mass of $10^{6}\, \mathrm{M}_{\odot}$ to every halo that reaches $10^{10.5}\, \mathrm{M}_{\odot}$. In the second model, we disregard any black hole growth as implemented in the standard Dark Sage model. Instead, we force all black hole masses to follow the median black hole mass-halo mass relation in IllustrisTNG 300-1 with a fixed scatter. We find that each model on its own does not significantly reduce the scatter in stellar mass. To do this, we replace the native Dark Sage AGN feedback model with a simple model where we turn off cooling for galaxies with black hole masses above $10^{8}\, \mathrm{M}_{\odot}$. With this additional modification, the SMBH seeding and fixed conditional distribution models find a significant reduction in the scatter in stellar mass at halo masses between $10^{11-14}\, \mathrm{M}_{\odot}$. These results suggest that AGN feedback in SAMs acts in a qualitatively different way than feedback implemented in cosmological simulations. Either or both may require substantial modification to match the empirically inferred scatter in the Stellar Mass Halo Mass Relation (SMHMR).

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arXiv2023

Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension

This paper represents an effort to provide robust constraints on the galaxy-halo connection and simultaneously test the Planck LCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this "decorated" HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high luminosity galaxies may be due to a problem with our assumed cosmological model.

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arXiv2021

The impact of baryonic physics on the abundance, clustering, and concentration of halos

We examine the impact of baryonic physics on the halo distribution in hydrodynamic simulations (Illustris, IllustrisTNG, and EAGLE), particularly with regards to how it differs from that in dark matter only (DMO) simulations. We find that, in general, DMO simulations produce halo mass functions (HMF) that are shifted to higher halo masses than their hydrodynamic counterparts, due to the lack of baryonic physics. However, the exact nature of this mass shift is a complex function of mass, halo definition, redshift, and larger-scale environment, and it also depends on the specifics of the baryonic physics implemented in the simulation. We present fitting formulae for the corrections one would need to apply to each DMO halo catalogue in order to reproduce the HMF found in its hydrodynamic counterpart. We provide these formulae for all three simulations, for five different halo definitions at redshifts 0, 1, and 2. Additionally, we explore the dependence on environment of this HMF discrepancy, and find that, in most cases, halos in low density environments are slightly more impacted by baryonic physics than halos in high density environments. We thus also provide environment-dependent mass correction formulae that can reproduce the conditional, as well as global, HMF. We show that our mass corrections also repair the large-scale clustering of halos, though the environment-dependent corrections are required to achieve an accuracy better than 2%. Finally, we examine the impact of baryonic physics on the halo mass - concentration relation, and find that its slope in hydrodynamic simulations is consistent with that in DMO simulations. Ultimately, we recommend that any future work relying on DMO halo catalogues incorporate our mass corrections to test the robustness of their results to baryonic effects.

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arXiv2021

Toward Accurate Modeling of Galaxy Clustering on Small Scales: Constraining the Galaxy-Halo Connection with Optimal Statistics

Applying halo models to analyze the small-scale clustering of galaxies is a proven method for characterizing the connection between galaxies and their host halos. Such works are often plagued by systematic errors or are limited to clustering statistics which can be predicted analytically. In this work, we employ a numerical mock-based modeling procedure to examine the clustering of SDSS DR7 galaxies. We apply a standard halo occupation distribution (HOD) model to dark-matter-only simulations with a LCDM cosmology. To constrain the theoretical models, we utilize a combination of galaxy number density and selected scales of the projected correlation function, redshift-space correlation function, group multiplicity function, average group velocity dispersion, mark correlation function, and counts-in-cells statistics. We design an algorithm to choose an optimal combination of measurements that yields tight and accurate constraints on our model parameters. Compared to previous work using fewer clustering statistics, we find significant improvement in the constraints on all parameters of our halo model for two different luminosity-threshold galaxy samples. Most interestingly, we obtain unprecedented high-precision constraints on the scatter in the relationship between galaxy luminosity and halo mass. However, our best-fit model results in significant tension (>4 sigma) for both samples, indicating the need to add second-order features to the standard HOD model. To guarantee the robustness of these results, we perform an extensive analysis of the systematic and statistical errors in our modeling procedure, including a first-of-its-kind study of the sensitivity of our constraints to changes in the halo mass function due to baryonic physics.

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arXiv2020

Void Galaxies Follow a Distinct Evolutionary Path in the Environmental COntext Catalog

We measure the environmental dependence, where environment is defined by the distance to the third nearest neighbor, of multiple galaxy properties inside the Environmental COntext (ECO) catalog. We focus primarily on void galaxies, which we define as the $10 \%$ of galaxies having the lowest local density. We compare the properties of void and non-void galaxies: baryonic mass, color, fractional stellar mass growth rate (FSMGR), morphology, and gas-to-stellar-mass ratio (estimated from a combination of HI data and photometric gas fractions calibrated with the RESOLVE survey). Our void galaxies typically have lower baryonic masses than galaxies in denser environments, and they display the properties expected of a lower mass population: they have more late-types, are bluer, have higher FSMGR, and are more gas rich. We control for baryonic mass and investigate the extent to which void galaxies are different at fixed mass. Void galaxies are bluer, more gas-rich, and more star forming at fixed mass than non-void galaxies, which is a possible signature of galaxy assembly bias. Furthermore, we show that these trends persist even at fixed mass and morphology, and we find that voids host a distinct population of early-types that are bluer and more star-forming than the typical red and quenched early-types. In addition to these empirical observational results, we also present theoretical results from mock catalogs with built-in galaxy assembly bias. We show that a simple matching of galaxy properties to (sub)halo properties, such as mass and age, can recover the observed environmental trends in ECO galaxies.

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arXiv2020

Machine Learning the Fates of Dark Matter Subhalos: A Fuzzy Crystal Ball

The evolution of a dark matter halo in a dark matter only simulation is governed purely byNewtonian gravity, making a clean testbed to determine what halo properties drive its fate.Using machine learning, we predict the survival, mass loss, final position, and merging time of subhalos within a cosmological N-body simulation, focusing on what instantaneous initial features of the halo, interaction, and environment matter most. Survival is well predicted, with our model achieving 96.5% accuracy using only 3 model inputs from the initial interaction.However, the mass loss, final location, and merging times are much more stochastic processes, with significant margins of error between the true and predicted quantities for much of our sample. The redshift, impact angle, relative velocity, and the masses of the host and subhalo are the only relevant initial inputs for determining subhalo evolution. In general, subhalos that enter their hosts at a mid-range of redshifts (typically z = 0.67-0.43) are the most challenging to make predictions for, across all of our final outcomes. Subhalo orbits that come in more perpendicular to the host are also easier to predict, except for in the case of predicting disruption, where the opposite appears to be true. We conclude that the detailed evolution of individual subhalos within N-body simulations is quite difficult to predict, pointing to a stochasticity in the merging process. We discuss implications for both simulations and observations

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arXiv2019

Testing the Accuracy of Halo Occupation Distribution Modelling using Hydrodynamic Simulations

Halo models provide a simple and computationally inexpensive way to investigate the connection between galaxies and their dark matter haloes. However, these models rely on the assumption that the role of baryons can be easily parametrized in the modelling procedure. We aim to examine the ability of halo occupation distribution (HOD) modelling to reproduce the galaxy clustering found in two different hydrodynamic simulations, Illustris and EAGLE. For each simulation, we measure several galaxy clustering statistics on two different luminosity threshold samples. We then apply a simple five parameter HOD, which was fit to each simulation separately, to the corresponding dark matter only simulations, and measure the same clustering statistics. We find that the halo mass function is shifted to lower masses in the hydrodynamic simulations, resulting in a galaxy number density that is too high when an HOD is applied to the dark matter only simulation. However, the exact way in which baryons alter the mass function is remarkably different in the two simulations. After applying a correction to the halo mass function in each simulation, the HOD is able to accurately reproduce all clustering statistics for the high luminosity sample of galaxies. For the low luminosity sample, we find evidence that in addition to correcting the halo mass function, including spatial, velocity, and assembly bias parameters in the HOD is necessary to accurately reproduce clustering statistics.

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arXiv2019

Angular momentum and morphological sequence of massive galaxies through Dark Sage

We study the present-day connection between galaxy morphology and angular momentum using the {\sc Dark Sage} semi-analytic model of galaxy formation. For galaxies between $ 10^{11}-10^{12} \mathrm{M}_{\odot}$ in stellar mass, the model successfully predicts the observed trend whereby galaxies with more prominent disks exhibit higher {\em stellar} disk specific angular momentum ($j_{\rm stellar, disk}$) at fixed stellar mass. However, when we include the gas in the disk, bulge-dominated galaxies have the highest {\em total} disk specific angular momentum ($j_{\rm total, disk}$). We attribute this to a large contribution from an extended disk of cold gas in typical bulge-dominated galaxies. We find the relationship between $j_{\rm dark matter}$ and morphology to be quite complex. Surprisingly, in this stellar mass range, not only do bulge-dominated galaxies tend to live in halos with higher $j_{\rm dark matter}$ than disk-dominated galaxies, but intermediate galaxies (those with roughly equal fractions of bulge and disk mass) have the lowest $j_{\rm dark matter}$ of all. Yet, when controlling for halo mass, rather than stellar mass, the relationship between $j_{\rm dark matter}$ and morphology vanishes. Based on these results, halo mass rather than angular momentum is the main driver of the predicted morphology sequence at high masses. In fact, in our stellar mass range, disk-dominated galaxies live in dark matter halos that are roughly 1/10th the mass of their bulge-dominated counterparts.

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arXiv2019

Prediction of galaxy halo masses in SDSS DR7 via a machine learning approach

We present a machine learning (ML) approach for the prediction of galaxies' dark matter halo masses that achieves an improved performance over conventional methods. We train three ML algorithms (\texttt{XGBoost}, Random Forests, and neural network) to predict halo masses using a set of synthetic galaxy catalogues that are built by populating dark matter haloes in N-body simulations with galaxies, and that match both the clustering and the joint-distributions of properties of galaxies in the Sloan Digital Sky Survey (SDSS). We explore the correlation of different galaxy- and group-related properties with halo mass, and extract the set of nine features that contribute the most to the prediction of halo mass. We find that mass predictions from the ML algorithms are more accurate than those from halo abundance matching (\texttt{HAM}) or dynamical mass (\texttt{DYN}) estimates. Since the danger of this approach is that our training data might not accurately represent the real Universe, we explore the effect of testing the model on synthetic catalogues built with different assumptions than the ones used in the training phase. We test a variety of models with different ways of populating dark matter haloes, such as adding velocity bias for satellite galaxies. We determine that, though training and testing on different data can lead to systematic errors in predicted masses, the ML approach still yields substantially better masses than either \texttt{HAM}or \texttt{DYN}. Finally, we apply the trained model to a galaxy and group catalogue from the SDSS DR7 and present the resulting halo masses.

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arXiv2018

The Secondary Spin Bias of Dark Matter Haloes

We investigate the role of angular momentum in the clustering of dark matter haloes. We make use of data from two high-resolution N-body simulations spanning over four orders of magnitude in halo mass, from $10^{9.8}$ to $10^{14}\ h^{-1}\ \text{M}_\odot$. We explore the hypothesis that mass accretion in filamentary environments alters the angular momentum of a halo, thereby driving a correlation between the spin parameter $λ$ and the strength of clustering. However, we do not find evidence that the distribution of matter on large scales is related to the spin of haloes. We find that a halo's spin is correlated with its age, concentration, sphericity, and mass accretion rate. Removing these correlations strongly affects the strength of secondary spin bias at low halo masses. We also find that high spin haloes are slightly more likely to be found near another halo of comparable mass. These haloes that are found near a comparable mass neighbour - a \textit{twin} - are strongly spatially biased. We demonstrate that this \textit{twin bias}, along with the relationship between spin and mass accretion rates, statistically accounts for halo spin secondary bias.

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arXiv2018

The Ultraviolet Detection of Diffuse Gas in Galaxy Groups

A small survey of the UV-absorbing gas in 12 low-$z$ galaxy groups has been conducted using the Cosmic Origins Spectrograph (COS) on-board the Hubble Space Telescope (HST). Targets were selected from a large, homogeneously-selected sample of groups found in the Sloan Digital Sky Survey (SDSS). A critical selection criterion excluded sight lines that pass close ($<1.5$ virial radii) to a group galaxy, to ensure absorber association with the group as a whole. Deeper galaxy redshift observations are used both to search for closer galaxies and also to characterize these $10^{13.5}$ to $10^{14.5} M_{\odot}$ groups, the most massive of which are highly-virialized with numerous early-type galaxies (ETGs). This sample also includes two spiral-rich groups, not yet fully-virialized. At group-centric impact parameters of 0.3-2 Mpc, these $\mathrm{S/N}=15$-30 spectra detected HI absorption in 7 of 12 groups; high (OVI) and low (SiIII) ion metal lines are present in 2/3 of the absorption components. None of the three most highly-virialized, ETG-dominated groups are detected in absorption. Covering fractions $\gtrsim50$% are seen at all impact parameters probed, but do not require large filling factors despite an enormous extent. Unlike halo clouds in individual galaxies, group absorbers have radial velocities which are too low to escape the group potential well without doubt. This suggests that these groups are "closed boxes" for galactic evolution in the current epoch. Evidence is presented that the cool and warm group absorbers are not a pervasive intra-group medium (IGrM), requiring a hotter ($T\sim10^6$ to $10^7$ K) IGrM to be present to close the baryon accounting.

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arXiv2018

Small- and Large-Scale Galactic Conformity in SDSS DR7

Galactic conformity is the phenomenon whereby galaxy properties exhibit excess correlations across distance than that expected if these properties only depended on halo mass. We perform a comprehensive study of conformity at low redshift using a galaxy group catalogue from the SDSS DR7 spectroscopic sample. We study correlations both between central galaxies and their satellites (1-halo), and between central galaxies in separate haloes (2-halo). We use the quenched fractions and the marked correlation function (MCF), to probe for conformity in three galaxy properties, $(g-r)$ colour, specific star formation rate (sSFR), and morphology. We assess the statistical significance of conformity signals with a suite of mock galaxy catalogues that have no built-in conformity, but contain the same group-finding and mass assignment errors as the real data. In the case of 1-halo conformity, quenched fractions show strong signals at all group masses. However, these signals are equally strong in mock catalogues, indicating that the conformity signal is spurious and likely entirely caused by group-finding systematics, calling into question previous claims of 1-halo conformity detection. The MCF reveals a significant detection of radial segregation within massive groups, but no evidence of conformity. In the case of 2-halo conformity, quenched fractions show no significant evidence of conformity in colour or sSFR once compared with mock catalogues, but a clear signal using morphology. In contrast, the MCF reveals a small, yet highly significant signal for all three properties in low mass groups and scales of $0.8-4\ h^{-1}\textrm{Mpc}$, possibly representing the first robust detection of 2-halo conformity.

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arXiv2018

Towards Accurate Modelling of Galaxy Clustering on Small Scales: Testing the Standard $Λ\mathrm{CDM}$ + Halo Model

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard $Λ\mathrm{CDM}$ + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3$σ$ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

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arXiv2018

Spatial Clustering of Dark Matter Halos: Secondary Bias, Neighbor Bias, and the Influence of Massive Neighbors on Halo Properties

We explore the phenomenon commonly known as halo assembly bias, whereby dark matter halos of the same mass are found to be more or less clustered when a second halo property is considered, for halos in the mass range $3.7 \times 10^{11} \; h^{-1} \mathrm{M_{\odot}} - 5.0 \times 10^{13} \; h^{-1} \mathrm{M_{\odot}}$. Using the Large Suite of Dark Matter Simulations (LasDamas) we consider nine commonly used halo properties and find that a clustering bias exists if halos are binned by mass or by any other halo property. This secondary bias implies that no single halo property encompasses all the spatial clustering information of the halo population. The mean values of some halo properties depend on their halo's distance to a more massive neighbor. Halo samples selected by having high values of one of these properties therefore inherit a neighbor bias such that they are much more likely to be close to a much more massive neighbor. This neighbor bias largely accounts for the secondary bias seen in halos binned by mass and split by concentration or age. However, halos binned by other mass-like properties still show a secondary bias even when the neighbor bias is removed. The secondary bias of halos selected by their spin behaves differently than that for other halo properties, suggesting that the origin of the spin bias is different than of other secondary biases.

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arXiv2017

The Baryonic Collapse Efficiency of Galaxy Groups in the RESOLVE and ECO Surveys

We examine the z = 0 group-integrated stellar and cold baryonic (stars + cold atomic gas) mass functions (group SMF and CBMF) and the baryonic collapse efficiency (group cold baryonic to dark matter halo mass ratio) using the RESOLVE and ECO survey galaxy group catalogs and a galform semi-analytic model (SAM) mock catalog. The group SMF and CBMF fall off more steeply at high masses and rise with a shallower low-mass slope than the theoretical halo mass function (HMF). The transition occurs at group-integrated cold baryonic mass M_coldbary ~ 10^11 Msun. The SAM, however, has significantly fewer groups at the transition mass ~ 10^11 Msun and a steeper low-mass slope than the data, suggesting that feedback is too weak in low-mass halos and conversely too strong near the transition mass. Using literature prescriptions to include hot halo gas and potential unobservable galaxy gas produces a group BMF with slope similar to the HMF even below the transition mass. Its normalization is lower by a factor of ~2, in agreement with estimates of warm-hot gas making up the remaining difference. We compute baryonic collapse efficiency with the halo mass calculated two ways, via halo abundance matching (HAM) and via dynamics (extended all the way to three-galaxy groups using stacking). Using HAM, we find that baryonic collapse efficiencies reach a flat maximum for groups across the halo mass range of M_halo ~ 10^11.4-12 Msun, which we label "nascent groups." Using dynamics, however, we find greater scatter in baryonic collapse efficiencies, likely indicating variation in group hot-to-cold baryon ratios. Similarly, we see higher scatter in baryonic collapse efficiencies in the SAM when using its true groups and their group halo masses as opposed to friends-of-friends groups and HAM masses.

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arXiv2017

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratio in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially-resolved spectroscopy for thousands of nearby galaxies (median redshift of z = 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between redshifts z = 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGN and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5-meter Sloan Foundation Telescope at Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5-meter du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in July 2016.

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arXiv2016

The lensing and temperature imprints of voids on the Cosmic Microwave Background

We have searched for the signature of cosmic voids in the CMB, in both the Planck temperature and lensing-convergence maps; voids should give decrements in both. We use zobov voids from the DR12 SDSS CMASS galaxy sample. We base our analysis on N-body simulations, to avoid a posteriori bias. For the first time, we detect the signature of voids in CMB lensing: the significance is $3.2σ$, close to $Λ$CDM in both amplitude and projected density-profile shape. A temperature dip is also seen, at modest significance ($2.3σ$), with amplitude about 6 times the prediction. This temperature signal is induced mostly by voids with radius between 100 and 150 Mpc/h, while the lensing signal is mostly contributed by smaller voids -- as expected; lensing relates directly to density, while ISW depends on gravitational potential. The void abundance in observations and simulations agree, as well. We also repeated the analysis excluding lower-significance voids: no lensing signal is detected, with an upper limit of about twice the $Λ$CDM prediction. But the mean temperature decrement now becomes non-zero at the $3.7σ$ level (similar to that found by Granett et al.), with amplitude about 20 times the prediction. However, the observed dependence of temperature on void size is in poor agreement with simulations, whereas the lensing results are consistent with $Λ$CDM theory. Thus, the overall tension between theory and observations does not favour non-standard theories of gravity, despite the hints of an enhanced amplitude for the ISW effect from voids.

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arXiv2016

The RESOLVE Survey Atomic Gas Census and Environmental Influences on Galaxy Gas Reservoirs

We present the HI mass inventory for the RESOLVE survey, a volume-limited, multi-wavelength census of >1500 z=0 galaxies spanning diverse environments and complete in baryonic mass down to dwarfs of 10^9 Msun. This first 21cm data release provides robust detections or strong upper limits (1.4M_HI < 5 to 10% of stellar mass M_stars) for 94% of RESOLVE. We examine global atomic gas-to-stellar mass ratios (G/S) in relation to galaxy environment using several metrics: group dark matter halo mass M_h , central/satellite designation, relative mass density of the cosmic web, and distance to nearest massive group. We find that at fixed M_stars, satellites have decreasing G/S with increasing M_h starting clearly at M_h = 10^12 Msun, suggesting the presence of starvation and/or stripping mechanisms associated with halo gas heating in intermediate-mass groups. The analogous relationship for centrals is uncertain because halo abundance matching builds in relationships between central G/S, stellar mass, and halo mass, which depend on the integrated group property used as a proxy for halo mass (stellar or baryonic mass). On larger scales G/S trends are less sensitive to the abundance matching method. At fixed M_h < 10^12 Msun, the fraction of gas-poor centrals increases with large-scale structure density. In overdense regions, we identify a rare population of gas-poor centrals in low-mass (M_h < 10^11.4 Msun) halos primarily located within 1.5 times the virial radius of more massive (M_h > 10^12 Msun) halos, suggesting that gas stripping and/or starvation may be induced by interactions with larger halos or the surrounding cosmic web. We find that the detailed relationship between G/S and environment varies when we examine different subvolumes of RESOLVE independently, which we suggest may be a signature of assembly bias.

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