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Constraints on cosmological parameters are often distilled from sky surveys by fitting templates to summary statistics of the data that are motivated by a fiducial cosmological model. However, recent work has shown how to estimate the distance scale using templates that are more generic: the basis functions used are not explicitly tied to any one cosmological model. We describe a Bayesian framework for (i) determining how many basis functions to use and (ii) comparing one basis set with another. Our formulation provides intuition into how (a) one's degree of belief in different basis sets, (b) the fact that the choice of priors depends on basis set, and (c) the data set itself, together determine the derived constraints. We illustrate our framework using measurements in simulated datasets before applying it to real data., 10 pages, 7 figures; v2: minor clarifications, fixed some typos, accepted in MNRAS

In general relativity (GR), the internal dynamics of a self-gravitating system under free-fall in an external gravitational field should not depend on the external field strength. Recent work has claimed a statistical detection of an `external field effect' (EFE) using galaxy rotation curve data. We show that large uncertainties in rotation curve analyses and inaccuracies in published simulation-based external field estimates compromise the significance of the claimed EFE detection. We further show analytically that a qualitatively similar statistical signal is, in fact, expected in a $\Lambda$-cold dark matter ($\Lambda$CDM) universe without any violation of the strong equivalence principle. Rather, such a signal arises simply because of the inherent correlations between galaxy clustering strength and intrinsic galaxy properties. We explicitly demonstrate the effect in a baryonified mock catalog of a $\Lambda$CDM universe. Although the detection of an EFE-like signal is not, by itself, evidence for physics beyond GR, our work shows that the $\textit{sign}$ of the EFE-like correlation between the external field strength and the shape of the radial acceleration relation can be used to probe new physics: e.g., in MOND, the predicted sign is opposite to that in our $\Lambda$CDM mocks., Comment: 11 pages, 6 figures; v2: minor changes and added discussion, accepted in MNRAS

We study the radial acceleration relation (RAR) between the total (atot) and baryonic (abary) centripetal acceleration profiles of central galaxies in the cold dark matter (CDM) paradigm. We analytically show that the RAR is intimately connected with the physics of the quasi-adiabatic relaxation of dark matter in the presence of baryons in deep potential wells. This cleanly demonstrates how the mean RAR and its scatter emerge in the low-acceleration regime ($10^{-12}{\rm \, m\, s}^{-2}\lesssim a_{\rm bary}\lesssim 10^{-10}{\rm \, m\, s}^{-2}$) from an interplay between baryonic feedback processes and the distribution of CDM in dark haloes. Our framework allows us to go further and study both higher and lower accelerations in detail, using analytical approximations and a realistic mock catalogue of ${\sim}342\, 000$ low-redshift central galaxies with Mr ≤ −19. We show that, while the RAR in the baryon-dominated high-acceleration regime ($a_{\rm bary}\gtrsim 10^{-10}{\rm \, m\, s}^{-2}$) is very sensitive to details of the relaxation physics, a simple ‘baryonification’ prescription matching the relaxation results of hydrodynamical CDM simulations is remarkably successful in reproducing the observed RAR without any tuning. And in the (currently unobserved) ultra-low-acceleration regime ($a_{\rm bary}\lesssim 10^{-12}{\rm \, m\, s}^{-2}$), the RAR is sensitive to the abundance of diffuse gas in the halo outskirts, with our default model predicting a distinctive break from a simple power-law-like relation for H i-deficient, diffuse gas-rich centrals. Our mocks also show that the RAR provides more robust, testable predictions of the ΛCDM paradigm at galactic scales, with implications for alternative gravity theories than the baryonic Tully–Fisher relation.

Large-scale sky surveys require companion large volume simulated mock catalogs. To ensure precision cosmology studies are unbiased, the correlations in these mocks between galaxy properties and their large-scale environments must be realistic. Since galaxies are embedded in dark matter halos, an important first step is to include such correlations -- sometimes called assembly bias -- for dark matter halos. However, galaxy properties correlate with smaller scale physics in halos which large simulations struggle to resolve. We describe an algorithm which addresses and largely mitigates this problem. Our algorithm exploits the fact that halo assembly bias is unchanged as long as correlations between halo property $c$ and the intermediate-scale tidal environment $\alpha$ are preserved. Therefore, knowledge of $\alpha$ is sufficient to assign small-scale, otherwise unresolved properties to a halo in a way which preserves its large-scale assembly bias accurately. We demonstrate this explicitly for halo internal properties like formation history (concentration $c_{\rm 200b}$), shape $c/a$, dynamics $c_{v}/a_{v}$, velocity anisotropy $\beta$ and angular momentum (spin $\lambda$). Our algorithm increases a simulation's reach in halo mass and number density by an order of magnitude, with improvements in the bias signal as large as 45% for 30-particle halos, thus significantly reducing the cost of mocks for future weak lensing and redshift space distortion studies., Comment: 13 pages, 10 figures, minor revisions, accepted in MNRAS

This is the third paper of a series where we study the stellar population gradients (SP; ages, metallicities, α-element abundance ratios, and stellar initial mass functions) of early-Type galaxies (ETGs) at $z$ ≤ 0.08 from the Mapping Nearby Galaxies at APO Data Release 15 (MaNGA-DR15) survey. In this work, we focus on the S0 population and quantify how the SP varies across the population as well as with galactocentric distance. We do this by measuring Lick indices and comparing them to SP synthesis models. This requires spectra with high signal-To-noise ratio which we achieve by stacking in bins of luminosity (Lr) and central velocity dispersion (σ0). We find that: (1) there is a bimodality in the S0 population: S0s more massive than $3\times 10^{10}\, \mathrm{M}_\odot$ show stronger velocity dispersion and age gradients (age and σr decrease outwards) but little or no metallicity gradient, while the less massive ones present relatively flat age and velocity dispersion profiles, but a significant metallicity gradient (i.e. [M/H] decreases outwards). Above $2\times 10^{11}\, \mathrm{M}_\odot$, the number of S0s drops sharply. These two mass scales are also where global scaling relations of ETGs change slope. (2) S0s have steeper velocity dispersion profiles than fast-rotating elliptical galaxies (E-FRs) of the same luminosity and velocity dispersion. The kinematic profiles and SP gradients of E-FRs are both more similar to those of slow-rotating ellipticals (E-SRs) than to S0s, suggesting that E-FRs are not simply S0s viewed face-on. (3) At fixed σ0, more luminous S0s and E-FRs are younger, more metal rich and less α-enhanced. Evidently for these galaxies, the usual statement that 'massive galaxies are older' is not true if σ0 is held fixed., his work was supported in part by NSF grant AST-1816330. HDS acknowledges support from Consejo Superior de Investigaciones Cientficas PIE2018-50E099. FN acknowledges support from the National Science Foundation Graduate Research Fellowship (NSF GRFP) under grant no. DGE-1845298. Funding for the Sloan Digital Sky Survey SDSS-IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org.

We estimate ages, metallicities, $\alpha$-element abundance ratios and stellar initial mass functions of elliptical (E) and S0 galaxies from the MaNGA-DR15 survey. We stack spectra and use a variety of single stellar population synthesis models to interpret the absorption line strengths in these spectra. We quantify how these properties vary across the population, as well as with galactocentric distance. This paper is the first of a series and is based on a sample of pure elliptical galaxies at z $\le$ 0.08. We show that the properties of the inner regions of Es with the largest luminosity (L$_r$) and central velocity dispersion ($\sigma_0$) are consistent with those associated with the commonly used Salpeter IMF, whereas a Kroupa-like IMF is a better description at $\sim$ 0.8R/Re (assuming [Ti/Fe] variations are limited). For these galaxies the stellar mass-to-light ratio decreases at most by a factor of 2 from the central regions to Re. In contrast, for lower L$_r$ and $\sigma_0$ galaxies, the IMF is shallower and M$_{*}$/L$_r$ in the central regions is similar to the outskirts. Although a factor of 2 is smaller than previous reports based on a handful of galaxies, it is still large enough to matter for dynamical mass estimates. Accounting self-consistently for these gradients when estimating both M$_{*}$ and M$_{dyn}$ brings the two into good agreement: gradients reduce M$_{dyn}$ by $\sim$ 0.2 dex while only slightly increasing the M$_{*}$ inferred using a Kroupa IMF. This is a different resolution of the M$_{*}$-M$_{dyn}$ discrepancy than has been followed in the recent literature where M$_{*}$ of massive galaxies is increased by adopting a Salpeter IMF while leaving Mdyn unchanged. A companion paper discusses how stellar population differences are even more pronounced if one separates slow from fast rotators.

The internal properties of dark matter haloes correlate with the large-scale halo clustering strength at fixed halo mass $-$ an effect known as assembly bias $-$ and are also strongly affected by the local, non-linear cosmic web. Characterising a halo's local web environment by its tidal anisotropy $\alpha$ at scales $\sim4$ x the halo radius, we demonstrate that these multi-scale correlations represent two distinct statistical links: one between the internal property and $\alpha$, and the other between $\alpha$ and large-scale ( $>30h^{-1}$Mpc) halo bias $b_1$. We focus on scalar internal properties of haloes related to formation time (concentration $c_{\rm vir}$), shape (mass ellipsoid asphericity $c/a$), velocity dispersion structure (velocity ellipsoid asphericity $c_v/a_v$ and velocity anisotropy $\beta$) and angular momentum (dimensionless spin $\lambda$) in the mass range $8\times10^{11}< M_{\rm vir}/(h^{-1}M_\odot), Comment: 21 pages, 14 figures; v2: Added discussion, results strengthened. Conclusions unchanged. Accepted by MNRAS

Velocity dispersion ($\sigma$) is a key driver for galaxy structure and evolution. We here present a comprehensive semi-empirical approach to compute $\sigma$ via detailed Jeans modelling assuming both a constant and scale-dependent mass-to-light ratio $M^*/L$. We compare with a large sample of local galaxies from MaNGA and find that both models can reproduce the Faber-Jackson (FJ) relation and the weak dependence of $\sigma$ on bulge-to-total ratio $B/T$ (for $B/T\gtrsim 0.25$). The dynamical-to-stellar mass ratio within $R\lesssim R_e$ can be fully accounted for by a gradient in $M^*/L$. We then build velocity dispersion evolutionary tracks $\sigma_{ap}[M^*,z]$ (within an aperture) along the main progenitor dark matter haloes assigning stellar masses, effective radii and Sersic indices via a variety of abundance matching and empirically motivated relations. We find: 1) clear evidence for downsizing in $\sigma_{ap}[M^*,z]$ along the progenitor tracks; 2) at fixed stellar mass $\sigma\propto(1+z)^{0.2-0.3}$ depending on the presence or not of a gradient in $M^*/L$. We extract $\sigma_{ap}[M^*,z]$ from the TNG50 hydrodynamic simulation and find very similar results to our models with constant $M^*/L$. The increasing dark matter fraction within $R_e$ tends to flatten the $\sigma_{ap}[M^*,z]$ along the progenitors at $z \gtrsim 1$ in constant $M^*/L$ models, while $\sigma_{ap}[M^*,z]$ have a steeper evolution in the presence of a stellar gradient. We then show that a combination of mergers and gas accretion are likely responsible for the constant or increasing $\sigma_{ap}[M^*,z]$ with time. Finally, our $\sigma_{ap}[M^*,z]$ are consistent with a nearly constant and steep $M_{bh}-\sigma$ relation at $z\lesssim 2$, with black hole masses derived from the $L_X-M^*$ relation., Comment: MNRAS accepted, 22 pages, 17 figures

Local samples of quiescent galaxies with dynamically measured black hole masses (Mbh) may suffer from an angular resolution-related selection effect, which could bias the observed scaling relations between Mbh and host galaxy properties away from the intrinsic relations. In particular, previous work has shown that the observed Mbh-Mstar (stellar mass) relation is more strongly biased than the Mbh-sigma (velocity dispersion) relation. Local samples of active galactic nuclei (AGN) do not suffer from this selection effect, as in these samples Mbh is estimated from megamasers and/or reverberation mapping-based techniques. With the exception of megamasers, Mbh-estimates in these AGN samples are proportional to a virial coefficient fvir. Direct modelling of the broad line region suggests that fvir~3.5. However, this results in a Mbh-Mstar relation for AGN which lies below and is steeper than the one observed for quiescent black hole samples. A similar though milder trend is seen for the Mbh-sigma relation. Matching the high-mass end of the Mbh-Mstar and Mbh-sigma relations observed in quiescent samples requires fvir~15 and fvir~7, respectively. On the other hand, fvir~3.5 yields Mbh-sigma and Mbh-Mstar relations for AGN which are remarkably consistent with the expected `intrinsic' correlations for quiescent samples (i.e., once account has been made of the angular resolution-related selection effect), providing additional evidence that the sample of local quiescent black holes is biased. We also show that, as is the case for quiescent black holes, the Mbh-Mstar scaling relation of AGN is driven by velocity dispersion, thus providing additional key constraints to black hole-galaxy co-evolution models., 15 pages, 5 Figures. MNRAS, accepted

Spatially resolved kinematics of nearby galaxies has shown that the ratio of dynamical- to stellar population-based estimates of the mass of a galaxy ($M_*^{\rm JAM}/M_*$) correlates with $\sigma_e$, if $M_*$ is estimated using the same IMF for all galaxies and the stellar M/L ratio within each galaxy is constant. This correlation may indicate that, in fact, the IMF is more dwarf-rich for galaxies with large $\sigma$. We use this correlation to estimate a dynamical or IMF-corrected stellar mass, $M_*^{\rm \alpha_{JAM}}$, from $M_{*}$ and $\sigma_e$ for a sample of $6 \times 10^5$ SDSS galaxies for which spatially resolved kinematics is not available. We also compute the `virial' mass estimate $k(n,R)\,R_e\,\sigma_R^2/G$, where $n$ is the Sersic index, in the SDSS and ATLAS$^{\rm 3D}$ samples. We show that an $n$-dependent correction must be applied to the $k(n,R)$ values provided by Prugniel & Simien (1997). Our analysis also shows that the shape of the velocity dispersion profile in the ATLAS$^{\rm 3D}$ sample varies weakly with $n$: $(\sigma_R/\sigma_e) = (R/R_e)^{-\gamma(n)}$. The resulting stellar mass functions, based on $M_*^{\rm \alpha_{JAM}}$ and the recalibrated virial mass, are in good agreement. If the $M_*^{\rm \alpha_{JAM}}/M_* - \sigma_e$ correlation is indeed due to the IMF, and stellar M/L gradients can be ignored, then our $\phi(M_*^{\rm \alpha_{JAM}})$ is an estimate of the stellar mass function in which $\sigma_e$-dependent variations in the IMF across the population have been accounted for. Using a Fundamental Plane based observational proxy for $\sigma_e$ produces comparable results. By demonstrating that cheaper proxies are sufficiently accurate, our analysis should enable a more reliable census of the mass in stars for large galaxy samples, at a fraction of the cost. Our results are provided in tabular form., Comment: 17 pages, 19 figures, 4 tables. Accepted for publication by MNRAS. Tables 1, C1 and C2 are provided as ancillary files

Recent work has confirmed that the masses of supermassive black holes, estimated from scaling relations with global properties such as the stellar masses of their host galaxies, may be biased high. Much of this may be caused by the requirement that the gravitational sphere of influence of the black hole must be resolved for the black-hole mass to be reliably estimated. We revisit this issue by using a comprehensive galaxy evolution semi-analytic model, which self-consistently evolves supermassive black holes from high-redshift seeds via gas accretion and mergers, and also includes AGN feedback. Once tuned to reproduce the (mean) correlation of black-hole mass with velocity dispersion, the model is unable to also account for the correlation with stellar mass. This behaviour is independent of the model's parameters, thus suggesting an internal inconsistency in the data. The predicted distributions, especially at the low-mass end, are also much broader than observed. However, if selection effects are included, the model's predictions tend to align with the observations. We also demonstrate that the correlations between the residuals of the local scaling relations are more effective than the scaling relations themselves at constraining AGN feedback models. In fact, we find that our semi-analytic model, while in apparent broad agreement with the scaling relations when accounting for selection biases, yields very weak correlations between their residuals at fixed stellar mass, in stark contrast with observations. This problem persists when changing the AGN feedback strength, and is also present in the $z\sim 0$ outputs of the hydrodynamic cosmological simulation Horizon-AGN, which includes state-of-the-art treatments of AGN feedback. This suggests that current AGN feedback models may be too weak or are simply not capturing the effect of the black hole on the stellar velocity dispersion., 11 pages, 7 figures. Minor changes to match version to be published in MNRAS

Cross-correlations between biased tracers and the dark matter field encode information about the physical variables which characterize these tracers. However, if the physical variables of interest are correlated with one another, then extracting this information is not as straightforward as one might naively have thought. We show how to exploit these correlations so as to estimate scale-independent bias factors of all orders in a model-independent way. We also show that failure to account for this will lead to incorrect conclusions about which variables matter and which do not. Morever, accounting for this allows one to use the scale dependence of bias to constrain the physics of halo formation; to date the argument has been phrased the other way around. We illustrate by showing that the scale dependence of linear and nonlinear bias, measured on nonlinear scales, can be used to provide consistent estimates of how the critical density for halo formation depends on halo mass. Our methods work even when the bias is nonlocal and stochastic, such as when, in addition to the spherically averaged density field and its derivatives, the quadrupolar shear field also matters for halo formation. In such models, the nonlocal bias factors are closely related to the more familiar local nonlinear bias factors, which are much easier to measure. Our analysis emphasizes the fact that biased tracers are biased because they do not sample fields (density, velocity, shear, etc.) at all positions in space in the same way that the dark matter does., Comment: 15 pages, 17 figures, submitted to MNRAS

The protohalo patches from which halos form are defined by a number of constraints imposed on the Lagrangian dark matter density field. Each of these constraints contributes to biasing the spatial distribution of the protohalos relative to the matter. We show how measurements of this spatial distribution -- linear combinations of protohalo bias factors -- can be used to make inferences about the physics of halo formation. Our analysis exploits the fact that halo bias factors satisfy consistency relations which encode this physics, and that these relations are the same even for sub-populations in which assembly bias has played a role. We illustrate our methods using a model in which three parameters matter: a density threshold, the local slope and the curvature of the smoothed density field. The latter two are nearly degenerate; our approach naturally allows one to build an accurate effective two-parameter model for which the consistency relations still apply. This, with an accurate description of the smoothing window, allows one to describe the protohalo-matter cross-correlation very well, both in Fourier and configuration space. We then use our determination of the large scale bias parameters together with the consistency relations, to estimate the enclosed density and mean slope on the Lagrangian radius scale of the protohalos. Direct measurements of these quantities, made on smaller scales than those on which the bias parameters are typically measured, are in good agreement., 17 pages, 19 figures, match the published version

We study the role of the local tidal environment in determining the assembly bias of dark matter haloes. Previous results suggest that the anisotropy of a halo's environment (i.e, whether it lies in a filament or in a more isotropic region) can play a significant role in determining the eventual mass and age of the halo. We statistically isolate this effect using correlations between the large-scale and small-scale environments of simulated haloes at $z=0$ with masses between $10^{11.6}\lesssim (m/h^{-1}M_{\odot})\lesssim10^{14.9}$. We probe the large-scale environment using a novel halo-by-halo estimator of linear bias. For the small-scale environment, we identify a variable $\alpha_R$ that captures the $\textit{tidal anisotropy}$ in a region of radius $R=4R_{\textrm{200b}}$ around the halo and correlates strongly with halo bias at fixed mass. Segregating haloes by $\alpha_R$ reveals two distinct populations. Haloes in highly isotropic local environments ($\alpha_R\lesssim0.2$) behave as expected from the simplest, spherically averaged analytical models of structure formation, showing a $\textit{negative}$ correlation between their concentration and large-scale bias at $\textit{all}$ masses. In contrast, haloes in anisotropic, filament-like environments ($\alpha_R\gtrsim0.5$) tend to show a $\textit{positive}$ correlation between bias and concentration at any mass. Our multi-scale analysis cleanly demonstrates how the overall assembly bias trend across halo mass emerges as an average over these different halo populations, and provides valuable insights towards building analytical models that correctly incorporate assembly bias. We also discuss potential implications for the nature and detectability of galaxy assembly bias., Comment: 19 pages, 15 figures; v2: revised in response to referee comments, added references and discussion, conclusions unchanged. Accepted in MNRAS

In hierarchical models, the time derivative of the halo mass function may be thought of as the difference of two terms - a creation term, which describes the increase in the number of haloes of mass m from mergers of less massive objects, and a destruction term, which describes the decrease in the number of m-haloes as these merge with other haloes, creating more massive haloes as a result. In models where haloes form from a spherical collapse, the distribution of halo creation times can be estimated from the same formalism which is used to estimate halo abundances: the constant-barrier excursion-set approach. In the excursion set approach, moving, rather than constant-barriers, are necessary for estimating halo abundances when the collapse is triaxial. We show how the corresponding estimates are modified by providing analytic estimates of the creation rate for a wide range of halo masses. We then show that these moving-barrier based predictions are in better agreement with measurements in numerical simulations than are the corresponding predictions of the spherical collapse model. These results should be useful for studies of merger-driven star-formation rates and AGN activity. We also present a similar study of creation of haloes conditioned on belonging to an object of a certain mass today, and reach similar conclusions - the moving barrier based estimates are in substantially better agreement with the simulations. This part of the study may be useful for understanding the tendency for the oldest stars to exist in the most massive objects., MNRAS accepted, 17 pages, 10 figures

The excursion set approach uses the statistics of the density field smoothed on a wide range of scales, to gain insight into a number of interesting processes in nonlinear structure formation, such as cluster assembly, merging and clustering. The approach treats the curve defined by the height of the overdensity fluctuation field when changing the smoothing scale as a random walk. The steps of the walks are often assumed to be uncorrelated, so that the walk heights are a Markov process, even though this assumption is known to be inaccurate for physically relevant filters. We develop a model in which the walk steps, rather than heights, are a Markov process, and correlations between steps arise because of nearest neighbour interactions. This model is a particular case of a general class, which we call Markov Velocity models. We show how these can approximate the walks generated by arbitrary power spectra and filters, and, unlike walks with Markov heights, provide a very good approximation to physically relevant models. We define a Markov Velocity Monte Carlo algorithm to generate walks whose first crossing distribution is very similar to that of TopHat-smoothed LCDM walks. Finally, we demonstrate that Markov Velocity walks generically exhibit a simple but realistic form of assembly bias, so we expect them to be useful in the construction of more realistic merger history trees., 14 pages, 7 figures. Matches MNRAS version

We describe a simple fully analytic model of the excursion set approach associated with two Gaussian random walks: the first walk represents the initial overdensity around a protohalo, and the second is a crude way of allowing for other factors which might influence halo formation. This model is richer than that based on a single walk, because it yields a distribution of heights at first crossing. We provide explicit expressions for the unconditional first crossing distribution which is usually used to model the halo mass function, the progenitor distributions, and the conditional distributions from which correlations with environment are usually estimated. These latter exhibit perhaps the simplest form of what is often called nonlocal bias, and which we prefer to call stochastic bias, since the new bias effects arise from `hidden-variables' other than density, but these may still be defined locally. We provide explicit expressions for these new bias factors. We also provide formulae for the distribution of heights at first crossing in the unconditional and conditional cases. In contrast to the first crossing distribution, these are exact, even for moving barriers, and for walks with correlated steps. The conditional distributions yield predictions for the distribution of halo concentrations at fixed mass and formation redshift. They also exhibit assembly bias like effects, even when the steps in the walks themselves are uncorrelated. Finally, we show how the predictions are modified if we add the requirement that halos form around peaks: these depend on whether the peaks constraint is applied to a combination of the overdensity and the other variable, or to the overdensity alone. Our results demonstrate the power of requiring models to reproduce not just halo counts but the distribution of overdensities at fixed protohalo mass as well., 9 pages, 5 figures, submitted to MNRAS

If one accounts for correlations between scales, then nonlocal, k-dependent halo bias is part and parcel of the excursion set approach, and hence of halo model predictions for galaxy bias. We present an analysis that distinguishes between a number of different effects, each one of which contributes to scale-dependent bias in real space. We show how to isolate these effects and remove the scale dependence, order by order, by cross-correlating the halo field with suitably transformed versions of the mass field. These transformations may be thought of as simple one-point, two-scale measurements that allow one to estimate quantities which are usually constrained using n-point statistics. As part of our analysis, we present a simple analytic approximation for the first crossing distribution of walks with correlated steps which are constrained to pass through a specified point, and demonstrate its accuracy. Although we concentrate on nonlinear, nonlocal bias with respect to a Gaussian random field, we show how to generalize our analysis to more general fields., 16 pages, 10 figures; v2 -- minor changes, typos fixed, references added, accepted in MNRAS

We describe a model of dark matter halo abundances and clustering which combines the two most widely used approaches to this problem: that based on peaks and the other based on excursion sets. Our approach can be thought of as addressing the cloud-in-cloud problem for peaks and/or modifying the excursion set approach so that it averages over a special subset, rather than all possible walks. In this respect, it seeks to account for correlations between steps in the walk as well as correlations between walks. We first show how the excursion set and peaks models can be written in the same formalism, and then use this correspondence to write our combined excursion set peaks model. We then give simple expressions for the mass function and bias, showing that even the linear halo bias factor is predicted to be k-dependent as a consequence of the nonlocality associated with the peak constraint. At large masses, our model has little or no need to rescale the variable delta_c from the value associated with spherical collapse, and suggests a simple explanation for why the linear halo bias factor appears to lie above that based on the peak-background split at high masses when such a rescaling is assumed. Although we have concentrated on peaks, our analysis is more generally applicable to other traditionally single-scale analyses of large-scale structure.

We show that the distribution of luminosities of Brightest Cluster Galaxies in an SDSS-based group catalog suggests that BCG luminosities are just the statistical extremes of the group galaxy luminosity function. This latter happens to be very well approximated by the all-galaxy luminosity function (restricted to Mr

The coefficients a and b of the Fundamental Plane relation R ~ Sigma^a I^b depend on whether one minimizes the scatter in the R direction or orthogonal to the Plane. We provide explicit expressions for a and b (and confidence limits) in terms of the covariances between logR, logSigma and logI. Our analysis is more generally applicable to any other correlations between three variables: e.g., the color-magnitude-Sigma relation, the L-Sigma-Mbh relation, or the relation between the X-ray luminosity, Sunyaev-Zeldovich decrement and optical richness of a cluster, so we provide IDL code which implements these ideas, and we show how our analysis generalizes further to correlations between more than three variables. We show how to account for correlated errors and selection effects, and quantify the difference between the direct, inverse and orthogonal fit coefficients. We show that the three vectors associated with the Fundamental Plane can all be written as simple combinations of a and b because the distribution of I is much broader than that of Sigma, and Sigma and I are only weakly correlated. Why this should be so for galaxies is a fundamental open question about the physics of early-type galaxy formation. If luminosity evolution is differential, and Rs and Sigmas do not evolve, then this is just an accident: Sigma and I must have been correlated in the past. On the other hand, if the (lack of) correlation is similar to that at the present time, then differential luminosity evolution must have been accompanied by structural evolution. A model in which the luminosities of low-L galaxies evolve more rapidly than do those of higher-L galaxies is able to produce the observed decrease in a (by a factor of 2 at z~1) while having b decrease by only about 20 percent. In such a model, the Mdyn/L ratio is a steeper function of Mdyn at higher z.

The Excursion Set approach has been used to make predictions for a number of interesting quantities in studies of nonlinear hierarchical clustering. These include the halo mass function, halo merger rates, halo formation times and masses, halo clustering, analogous quantities for voids, and the distribution of dark matter counts in randomly placed cells. The approach assumes that all these quantities can be mapped to problems involving the first crossing distribution of a suitably chosen barrier by random walks. Most analytic expressions for these distributions ignore the fact that, although different k-modes in the initial Gaussian field are uncorrelated, this is not true in real space: the values of the density field at a given spatial position, when smoothed on different real-space scales, are correlated in a nontrivial way. As a result, the problem is to estimate first crossing distribution by random walks having correlated rather than uncorrelated steps. In 1990, Peacock & Heavens presented a simple approximation for the first crossing distribution of a single barrier of constant height by walks with correlated steps. We show that their approximation can be thought of as a correction to the distribution associated with what we call smooth completely correlated walks. We then use this insight to extend their approach to treat moving barriers, as well as walks that are constrained to pass through a certain point before crossing the barrier. For the latter, we show that a simple rescaling, inspired by bivariate Gaussian statistics, of the unconditional first crossing distribution, accurately describes the conditional distribution, independently of the choice of analytical prescription for the former. In all cases, comparison with Monte-Carlo solutions of the problem shows reasonably good agreement. (Abridged)

In the Excursion Set approach, halo abundances and clustering are closely related. This relation is exploited in many modern methods which seek to constrain cosmological parameters on the basis of the observed spatial distribution of clusters. However, to obtain analytic expressions for these quantities, most Excursion Set based predictions ignore the fact that, although different k-modes in the initial Gaussian field are uncorrelated, this is not true in real space: the values of the density field at a given spatial position, when smoothed on different real-space scales, are correlated in a nontrivial way. We show that when the excursion set approach is extended to include such correlations, then one must be careful to account for the fact that the associated prediction for halo bias is explicitly a real-space quantity. Therefore, care must be taken when comparing the predictions of this approach with measurements in simulations, which are typically made in Fourier-space. We show how to correct for this effect, and demonstrate that ignorance of this effect in recent analyses of halo bias has led to incorrect conclusions and biased constraints.

We use extreme value statistics to assess the significance of two of the most dramatic structures in the local Universe: the Shapley supercluster and the Sloan Great Wall. If we assume that Shapley (volume ~ 1.2 x 10^5 (Mpc/h)^3) evolved from an overdense region in the initial Gaussian fluctuation field, with currently popular choices for the background cosmological model and the shape and amplitude sigma8 of the initial power spectrum, we estimate that the total mass of the system is within 20 percent of 1.8 x 10^16 Msun/h. Extreme value statistics show that the existence of this massive concentration is not unexpected if the initial fluctuation field was Gaussian, provided there are no other similar objects within a sphere of radius 200 Mpc/h centred on our Galaxy. However, a similar analysis of the Sloan Great Wall, a more distant (z ~ 0.08) and extended concentration of structures (volume ~ 7.2 x 10^5 (Mpc/h)^3) suggests that it is more unusual. We estimate its total mass to be within 20 percent of 1.2 x 10^17 Msun/h; even if it is the densest such object of its volume within z=0.2, its existence is difficult to reconcile with Gaussian initial conditions if sigma8 < 0.9. This tension can be alleviated if this structure is the densest within the Hubble volume. Finally, we show how extreme value statistics can be used to address the likelihood that an object like Shapley exists in the same volume which contains the Great Wall, finding, again, that Shapley is not particularly unusual. It is straightforward to incorporate other models of the initial fluctuation field into our formalism.

The color-magnitude relation of early-type galaxies differs slightly but significantly from a pure power-law, curving downwards at low and upwards at large luminosities (Mr>-20.5 and Mr 2x10^11 Msun). The upwards curvature at the massive end does not appear to be due to stellar population effects. In contrast, the color-sigma relation is well-described by a single power law. Since major dry mergers change neither the colors nor sigma, but they do change masses and sizes, the clear features observed in the scaling relations with M*, but not with sigma > 150 km/s, suggest that M* > 2x10^11 Msun is the scale above which major dry mergers dominate the assembly history. We discuss three models of the merger histories since z ~ 1 which are compatible with our measurements. In all three models, dry mergers are responsible for the flattening of the color-M* relation at M* > 3x10^10 Msun - wet mergers only matter at smaller masses. At M* > 2 x 10^11 Msun, the merger histories in one model are dominated by major rather than minor dry mergers, as suggested by the axis ratio and color gradient trends. In another, although both major and minor mergers occur at the high mass end, the minor mergers contribute primarily to the formation of the ICL, rather than to the mass growth of the central massive galaxy. A final model assumes that the reddest objects were assembled by a mix of major and minor dry mergers.

Using analytical models and cosmological N-body simulations, we study the free-free radio emission from ionized gas in clusters and groups of galaxies. The results obtained with the simulations are compared with analytical predictions based on the mass function and scaling relations. Earlier works based on analytical models have shown that the average free-free signal from small haloes (galaxies) during and after the reionization time could be detected with future experiments as a distortion of the CMB spectrum at low frequencies ($\nu 10^{13} h^{-1} M_{\odot}$ is less than 10% the signal from the more abundant and colder smaller mass haloes. However, the individual signal from the massive haloes could be detected with future experiments opening the door for a new window to study the intracluster medium.

Accurate knowledge of the non-linear dark-matter power spectrum is important for understanding the large-scale structure of the Universe, the statistics of dark-matter haloes and their evolution, and cosmological gravitational lensing. We analytically model the dark-matter power spectrum and its cross-power spectrum with dark-matter haloes. Our model extends the halo-model formalism, including realistic substructure population within individual dark-matter haloes and the scatter of the concentration parameter at fixed halo mass. We consider three prescriptions for the mass-concentration relation and two for the substructure distribution in dark-matter haloes. We show that this extension of the halo model mainly increases the predicted power on the small scales, and is crucial for proper modeling the cosmological weak-lensing signal due to low-mass haloes. Our extended formalism shows how the halo model approach can be improved in accuracy as one increases the number of ingredients that are calibrated from n-body simulations.

We use the ellipsoidal collapse approximation to investigate the nonlinear redshift space evolution of the density field with primordial non-Gaussianity of the local f_{nl}-type. We utilize the joint distribution of eigenvalues of the initial non-Gaussian shear field and evaluate the evolved redshift space probability distribution function (PDF). It is shown that, similar to the real space analysis, the underdense tail of the nonlinear redshift space PDF differs significantly from that for Gaussian initial conditions. We also derive the lowest order correction of the Kaiser's formulain the presence of a non-zero f_{nl}., Matched version accepted by MNRAS

The peak-background split argument is commonly used to relate the abundance of dark matter halos to their spatial clustering. Testing this argument requires an accurate determination of the halo mass function. We present a Maximum Likelihood method for fitting parametric functional forms to halo abundances which differs from previous work because it does not require binned counts. Our conclusions do not depend on whether we use our method or more conventional ones. In addition, halo abundances depend on how halos are defined. Our conclusions do not depend on the choice of link length associated with the friends-of-friends halo-finder, nor do they change if we identify halos using a spherical overdensity algorithm instead. The large scale halo bias measured from the matter-halo cross spectrum b_x and the halo autocorrelation function b_xi (on scales k~0.03h/Mpc and r ~50 Mpc/h) can differ by as much as 5% for halos that are significantly more massive than the characteristic mass M*. At these large masses, the peak background split estimate of the linear bias factor b1 is 3-5% smaller than b_xi, which is 5% smaller than b_x. We discuss the origin of these discrepancies: deterministic nonlinear local bias, with parameters determined by the peak-background split argument, is unable to account for the discrepancies we see. A simple linear but nonlocal bias model, motivated by peaks theory, may also be difficult to reconcile with our measurements. More work on such nonlocal bias models may be needed to understand the nature of halo bias at this level of precision.

We present measurements of the clustering of hot and cold patches in the microwave background sky as measured from the Wilkinson Microwave Anisotropy Probe 5-year data. These measurements are compared with theoretical predictions which assume that the cosmological signal obeys Gaussian statistics. We find significant differences from the simplest Gaussian-based prediction. However, the measurements are sensitive to the fact that the noise is spatially inhomogeneous (e.g. because different parts of the sky were observed for different lengths of time). We show how to account for this spatial inhomogeneity when making predictions. Differences from the Gaussian-based expectation remain even after this more careful accounting of the noise. In particular, we note that hot and cold pixels cluster differently within the same temperature thresholds at few-degree scales. While these findings may indicate primordial non-Gaussianity, we discuss other plausible explanations for these discrepancies. In addition, we find some deviations from Gaussianity at sub-degree scales, especially in the W band, whose origin may be associated with extragalactic dust emission.

We show how the excursion set moving barrier model for halo abundances may be generalized to the local non-Gaussian f_{nl} model. Our estimate assumes that the distribution of step sizes depends on f_{nl}, but that they are otherwise uncorrelated. Our analysis is consistent with previous results for the case of a constant barrier, and highlights some implicit assumptions. It also clarifies the basis of an approximate analytic solution to the moving barrier problem in the Gaussian case, and shows how it might be improved., 10 pages, 3 figures, match version accepted by MNRAS