Andrew P. Hearin

SHAM beyond clustering: new tests of galaxy–halo abundance matching with galaxy groups

We construct mock catalogs of galaxy groups using subhalo abundance matching (SHAM) and undertake several new tests of the SHAM prescription for the galaxy-dark matter connection. All SHAM models we studied exhibit significant tension with galaxy groups observed in the Sloan Digital Sky Survey (SDSS). The SHAM prediction for the field galaxy luminosity function is systematically too dim, and the group galaxy luminosity function systematically too bright, regardless of the details of the SHAM prescription. SHAM models connecting r-band luminosity, Mr, to V acc max , the maximum circular velocity of a subhalo at the time of accretion onto the host, faithfully reproduce the abundance of galaxy groups as a function of richness, g(N). However, SHAM models connecting Mr with V peak max , the peak value of Vmax over the entire merger history of the halo, over-predict the abundance of galaxy groups. Our results suggest that SHAM models for the galaxy-dark matter connection may be unable to simultaneously reproduce the observed group multiplicity function and two-point projected galaxy clustering. Nevertheless, we also report a new success of the abundance matching prescription: an accurate prediction for �(m12), the abundance of galaxy groups as a function of magnitude gap m12, defined as the difference between the r-band absolute magnitude of the two brightest group members. We demonstrate that it may be possible to use joint measurements of g(N) and �(m12) to provide tight constraints on the details of the SHAM implementation. Additionally, we show that the hypothesis that the luminosity gap is constructed via random draws from a universal luminosity function provides a poor description of the data, contradicting recent claims in the literature. Finally, we test a common assumption of the Conditional Luminosity Function formalism, that the satel

Introducing decorated HODs: modelling assembly bias in the galaxy–halo connection

The connection between galaxies and dark matter halos is often inferred from data using probabilistic models, such as the Halo Occupation Distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD program. We introduce decorated HODs, a new, exible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the inuence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of two on r 200 kpc scales and 15% in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r . 1 Mpc. We performed our calculations with Halotools, an open-source, community-driven python package for studying the galaxy-halo connection (http://halotools.readthedocs.org). We conclude by describing the use of decorated HODs to treat assembly bias in otherwise conventional likelihood analyses.

Accounting for Baryons in Cosmological Constraints from Cosmic Shear

One of the most pernicious theoretical systematics facing upcoming gravitational lensing surveys is the uncertainty introduced by the effects of baryons on the power spectrum of the convergence field. One method that has been proposed to account for these effects is to allow several additional parameters (that characterize dark matter halos) to vary and to fit lensing data to these halo parameters concurrently with the standard set of cosmological parameters. We test this method. In particular, we use this technique to model convergence power spectrum predictions from a set of cosmological simulations. We estimate biases in dark energy equation-of-state parameters that would be incurred if one were to fit the spectra predicted by the simulations either with no model for baryons or with the proposed method. We show that neglecting baryonic effect leads to biases in dark energy parameters that are several times the statistical errors for a survey like the Dark Energy Survey. The proposed method to correct for baryonic effects renders the residual biases in dark energy equation-of-state parameters smaller than the statistical errors. These results suggest that this mitigation method may be applied to analyze convergence spectra from a survey like the Dark Energy Survey. For significantly larger surveys, such as will be carried out by the Large Synoptic Survey Telescope, the biases introduced by baryonic effects are much more significant. We show that this mitigation technique significantly reduces the biases for such larger surveys, but that a more effective mitigation strategy will need to be developed in order ensure that the residual biases in these surveys fall below the statistical errors.

A General Study of the Influence of Catastrophic Photometric Redshift Errors on Cosmology with Cosmic Shear Tomography

A goal of forthcoming imaging surveys is to use weak gravitational lensing shear measurements to constrain dark energy. A challenge to this program is that redshifts to the lensed, source galaxies must be determined using photometric, rather than spectroscopic, information. We quantify the importance of uncalibrated photometric redshift outliers to the dark energy goals of forthcoming imaging surveys in a manner that does not assume any particular photometric redshift technique or template. In so doing, we provide an approximate blueprint for computing the influence of specific outlier populations on dark energy constraints. We find that outlier populations whose photo-z distributions are tightly localized about a significantly biased redshift must be controlled to a per-galaxy rate of (1-3) × 10–3 to insure that systematic errors on dark energy parameters are rendered negligible. In the complementary limit, a subset of imaged galaxies with uncalibrated photometric redshifts distributed over a broad range must be limited to fewer than a per-galaxy error rate of F cat (2-4) × 10–4. Additionally, we explore the relative importance of calibrating the photo-zs of a core set of relatively well-understood galaxies as compared to the need to identify potential catastrophic photo-z outliers. We discuss the degradation of the statistical constraints on dark energy parameters induced by excising source galaxies at high- and low-photometric redshifts, concluding that removing galaxies with photometric redshifts z ph 2.4 and z ph 0.3 may mitigate damaging catastrophic redshift outliers at a relatively small (20%) cost in statistical error. In an Appendix, we show that forecasts for the degradation in dark energy parameter constraints due to uncertain photometric redshifts depend sensitively on the treatment of the nonlinear matter power spectrum. In particular, previous work using Peacock & Dodds may have overestimated the photo-z calibration requirements of future surveys.

Assessing colour-dependent occupation statistics inferred from galaxy group catalogues

We investigate the ability of current implementations of galaxy group finders to recover colour-dependent halo occupation statistics. To test the fidelity of group catalogue inferred statistics, we run three different group finders used in the literature over a mock that includes galaxy colours in a realistic manner. Overall, the resulting mock group catalogues are remarkably similar, and most colour-dependent statistics are recovered with reasonable accuracy. However, it is also clear that certain systematic errors arise as a consequence of correlated errors in group membership determination, central/satellite designation, and halo mass assignment. We introduce a new statistic, the halo transition probability (HTP), which captures the combined impact of all these errors. As a rule of thumb, errors tend to equalize the properties of distinct galaxy populations (i.e. red versus blue galaxies or centrals versus satellites), and to result in inferred occupation statistics that are more accurate for red galaxies than for blue galaxies. A statistic that is particularly poorly recovered from the group catalogues is the red fraction of central galaxies as a function of halo mass. Group finders do a good job in recovering galactic conformity, but also have a tendency to introduce weak conformity when none is present. We conclude that proper inference of colour-dependent statistics from group catalogues is best achieved using forward modelling (i.e. running group finders over mock data) or by implementing a correction scheme based on the HTP, as long as the latter is not too strongly model dependent.

Coming of Age in the Dark Sector: How Dark Matter Haloes grow their Gravitational Potential Wells

We present a detailed study of how dark matter haloes assemble their mass and grow their (central) potential well. We characterize these via their mass accretion histories (MAHs) and potential well growth histories (PWGHs), which we extract from the Bolshoi simulation and from semi-analytical merger trees supplemented with a method to compute the maximum circular velocity, Vmax, of progenitor haloes. The results of both methods are in excellent agreement, both in terms of the average and the scatter. We show that the MAH and PWGH are tightly correlated, and that growth of the central potential precedes the assembly of mass; the maximum circular velocity is already half the present day value by the time the halo has accreted only 2 percent of its final mass. Finally, we demonstrate that MAHs have a universal form, which we use to develop a new and improved universal model that can be used to compute the

General requirements on matter power spectrum predictions for cosmology with weak lensing tomography

Forthcoming projects such as DES, LSST, WFIRST, and Euclid aim to measure weak lensing shear correlations with unprecedented precision, constraining the dark energy equation of state at the percent level. Reliance on photometrically-determined redshifts constitutes a major source of uncertainty for these surveys. Additionally, interpreting the weak lensing signal requires a detailed understanding of the nonlinear physics of gravitational collapse. We present a new analysis of the stringent calibration requirements for weak lensing analyses of future imaging surveys that addresses both photo-z uncertainty and errors in the calibration of the matter power spectrum. We find that when photo-z uncertainty is taken into account the requirements on the level of precision in the prediction for the matter power spectrum are more stringent than previously thought. Including degree-scale galaxy clustering statistics in a joint analysis with weak lensing not only strengthens the surveys constraining power by ~ 20%, but can also have a profound impact on the calibration demands, decreasing the degradation in dark energy constraints with matter power spectrum uncertainty by a factor of 2-5. Similarly, using galaxy clustering information significantly relaxes the demands on photo-z calibration. We compare these calibration requirements to the contemporary state-of-the-art in photometric redshift estimation and predictions of the power spectrum and suggest strategies to utilize forthcoming data optimally.

Mind the gap: tightening the mass–richness relation with magnitude gaps

We investigate the potential to improve optical tracers of cluster mass by exploiting measurements of the magnitude gap, m12, defined as the difference between the r-band absolute magnitude of the two brightest cluster members. We find that in a mock sample of galaxy groups and clusters constructed from the Bolshoi simulation, the scatter about the mass-richness relation decreases by 15-20% when magnitude gap information is included. A similar trend is evident in a volume-limited, spectroscopic sample of galaxy groups observed in the Sloan Digital Sky Survey (SDSS). We find that SDSS groups with small magnitude gaps are richer than large-gap groups at fixed values of the one-dimensional velocity dispersion among group members sigma_v, which we use as a mass proxy. We demonstrate explicitly that m12 contains information about cluster mass that supplements the information provided by group richness and the luminosity of the brightest cluster galaxy, L_bcg. In so doing, we show that the luminosities of the members of a group with richness N are inconsistent with the distribution of luminosities that results from N random draws from the global galaxy luminosity function. As the cosmological constraining power of galaxy clusters is limited by the precision in cluster mass determination, our findings suggest a new way to improve the cosmological constraints derived from galaxy clusters.

The Scale-Dependence of Halo Assembly Bias

The two-point clustering of dark matter halos is influenced by halo properties besides mass, a phenomenon referred to as halo assembly bias. Using the depth of the gravitational potential well, Vmax; as our secondary halo property, in this paper we present the first study of the scale-dependence assembly bias. In the large-scale linear regime, r & 10Mpc=h; our findings are in keeping with previous results. In particular, at the low-mass end (Mvir < Mcoll 10 12:5 M =h), halos with high-Vmax show stronger large-scale clustering relative to halos with low-Vmax of the same mass; this trend weakens and reverses for Mvir & Mcoll: In the nonlinear regime, assembly bias in low-mass halos exhibits a pronounced scale-dependent “bump” at 500kpc=h 5Mpc=h; a new result. This feature weakens and eventually vanishes for halos of higher mass. We show that this scale-dependent signature can primarily be attributed to a special subpopulation of ejected halos, defined as present-day host halos that were previously members of a higher-mass halo at some point in their past history. A corollary of our results is that galaxy clustering on scales of r 1 2Mpc=h can be impacted by up to 15% by the choice of the halo property used in the halo model, even for stellar mass-limited samples.

The influence of galaxy formation physics on weak lensing tests of general relativity

Forthcoming projects such as the Dark Energy Survey, Joint Dark Energy Mission, and the Large Synoptic Survey Telescope, aim to measure weak lensing shear correlations with unprecedented accuracy. Weak lensing observables are sensitive to both the distance-redshift relation and the growth of structure in the Universe. If the cause of accelerated cosmic expansion is dark energy within general relativity, both cosmic distances and structure growth are governed by the properties of dark energy. Consequently, one may use lensing to check for this consistency and test general relativity. After reviewing the phenomenology of such tests, we address a major challenge to such a program. The evolution of the baryonic component of the Universe is highly uncertain and can influence lensing observables, manifesting as modified structure growth for a fixed cosmic distance scale. Using two proposed methods, we show that one could be led to reject the null hypothesis of general relativity when it is the true theory if this uncertainty in baryonic processes is neglected. Recent simulations suggest that we can correct for baryonic effects using a parameterized model in which the halo mass-concentration relation is modified. The correction suffices to render biases small compared to statistical uncertainties. We study the ability of future weak lensing surveys to constrain the internal structures of halos and test the null hypothesis of general relativity simultaneously. Compared to alternative methods which null information from small-scales to mitigate sensitivity to baryonic physics, this internal calibration program should provide limits on deviations from general relativity that are several times more constraining. Specifically, we find that limits on general relativity in the case of internal calibration are degraded by only ~ 30% or less compared to the case of perfect knowledge of nonlinear structure.