Galaxy Bias and Halo-Occupation Numbers from Large-Scale Clustering

We show that current surveys have at least as much signal to noise in higher-order statistics as in the power spectrum at weakly nonlinear scales. We discuss how one can use this information to determine the mean of the galaxy halo occupation distribution (HOD) using only large-scale information, through galaxy bias parameters determined from the galaxy bispectrum and trispectrum. After introducing an averaged, reasonably fast to evaluate, trispectrum estimator, we show that the expected errors on linear and quadratic bias parameters can be reduced by at least 20-40%. Also, the inclusion of the trispectrum information, which is sensitive to "three-dimensionality" of structures, helps significantly in constraining the mass dependence of the HOD mean. Our approach depends only on adequate modeling of the abundance and large-scale clustering of halos and thus is independent of details of how galaxies are distributed within halos. This provides a consistency check on the traditional approach of using two-point statistics down to small scales, which necessarily makes more assumptions. We present a detailed forecast of how well our approach can be carried out in the case of the SDSS.Comment: 16 pages, 9 figure

On the streaming motions of haloes and galaxies

A simple model of how objects of different masses stream towards each other as they cluster gravitationally is described. The model shows how the mean streaming velocity of dark matter particles is related to the motions of the parent dark matter haloes. It also provides a reasonably accurate description of how the pairwise velocity dispersion of dark matter particles differs from that of the parent haloes. The analysis is then extended to describe the streaming motions of galaxies. This shows explicitly that the streaming motions measured in a given galaxy sample depend on how the sample was selected, and shows how to account for this dependence on sample selection. In addition,we show that the pairwise dispersion should also depend on sample type. Our model predicts that, on small scales, redshift space distortions should affect red galaxies more strongly than blue.Comment: 10 pages, submitted to MNRA

Large-scale Bias and Efficient Generation of Initial Conditions for Non-Local Primordial Non-Gaussianity

We study the scale-dependence of halo bias in generic (non-local) primordial non-Gaussian (PNG) initial conditions of the type motivated by inflation, parametrized by an arbitrary quadratic kernel. We first show how to generate non-local PNG initial conditions with minimal overhead compared to local PNG models for a general class of primordial bispectra that can be written as linear combinations of separable templates. We run cosmological simulations for the local, and non-local equilateral and orthogonal models and present results on the scale-dependence of halo bias. We also derive a general formula for the Fourier-space bias using the peak-background split (PBS) in the context of the excursion set approach to halos and discuss the difference and similarities with the known corresponding result from local bias models. Our PBS bias formula generalizes previous results in the literature to include non-Markovian effects and non-universality of the mass function and are in better agreement with measurements in numerical simulations than previous results for a variety of halo masses, redshifts and halo definitions. We also derive for the first time quadratic bias results for arbitrary non-local PNG, and show that non-linear bias loops give small corrections at large-scales. The resulting well-behaved perturbation theory paves the way to constrain non-local PNG from measurements of the power spectrum and bispectrum in galaxy redshift surveys.Comment: 43 pages, 10 figures. v2: references added. 2LPT parallel code for generating non-local PNG initial conditions available at http://cosmo.nyu.edu/roman/2LP

Gravity and Large-Scale Non-local Bias

The relationship between galaxy and matter overdensities, bias, is most often assumed to be local. This is however unstable under time evolution, we provide proofs under several sets of assumptions. In the simplest model galaxies are created locally and linearly biased at a single time, and subsequently move with the matter (no velocity bias) conserving their comoving number density (no merging). We show that, after this formation time, the bias becomes unavoidably non-local and non-linear at large scales. We identify the non-local gravitationally induced fields in which the galaxy overdensity can be expanded, showing that they can be constructed out of the invariants of the deformation tensor (Galileons). In addition, we show that this result persists if we include an arbitrary evolution of the comoving number density of tracers. We then include velocity bias, and show that new contributions appear, a dipole field being the signature at second order. We test these predictions by studying the dependence of halo overdensities in cells of fixed matter density: measurements in simulations show that departures from the mean bias relation are strongly correlated with the non-local gravitationally induced fields identified by our formalism. The effects on non-local bias seen in the simulations are most important for the most biased halos, as expected from our predictions. The non-locality seen in the simulations is not fully captured by assuming local bias in Lagrangian space. Accounting for these effects when modeling galaxy bias is essential for correctly describing the dependence on triangle shape of the galaxy bispectrum, and hence constraining cosmological parameters and primordial non-Gaussianity. We show that using our formalism we remove an important systematic in the determination of bias parameters from the galaxy bispectrum, particularly for luminous galaxies. (abridged)Comment: 26 pages, 9 figures. v2: improved appendix

Halo Sampling, Local Bias and Loop Corrections

We develop a new test of local bias, by constructing a locally biased halo density field from sampling the dark matter-halo distribution. Our test differs from conventional tests in that it preserves the full scatter in the bias relation and it does not rely on perturbation theory. We put forward that bias parameters obtained using a smoothing scale R can only be applied to computing the halo power spectrum at scales k ~ 1/R. Our calculations can automatically include the running of bias parameters and give vanishingly small loop corrections at low-k. Our proposal results in much better agreement of the sampling and perturbation theory results with simulations. In particular, unlike the standard interpretation of local bias in the literature, our treatment of local bias does not generate a constant power in the low-k limit. We search for extra noise in the Poisson corrected halo power spectrum at wavenumbers below its turn-over and find no evidence of significant positive noise (as predicted by the standard interpretation) while we find evidence of negative noise coming from halo exclusion for very massive halos. Using perturbation theory and our non-perturbative sampling technique we also demonstrate that nonlocal bias effects discovered recently in simulations impact the power spectrum only at the few percent level in the weakly nonlinear regime.Comment: 25 pages, 14 figures; V2: significant revision including more details about halo exclusion and low-k noise. Conclusions unchange

PTHalos: A fast method for generating mock galaxy distributions

Current models of galaxy formation applied to understanding the large-scale structure of the universe have two parts. The first is an accurate solution of the equations of motion for the dark matter due to gravitational clustering. The second consists of making physically reasonable approximations to the behavior of baryons inside dark matter halos. The first uses large, computationally intensive, $n$-body simulations. We argue that because the second step is, at least at present, uncertain, it is possible to obtain similar galaxy distributions without solving the first step exactly. We describe an algorithm which is several orders of magnitude faster than n-body simulations, but which is, nevertheless, rather accurate. The algorithm combines perturbation theory with virialized halo models of the nonlinear density and velocity fields. For two- and three-point statistics the resulting fields are exact on large scales, and rather accurate well into the nonlinear regime, particularly for two-point statistics in real and redshift space. We then show how to use this algorithm to generate mock galaxy distributions from halo occupation numbers. As a first application, we show that it provides a good description of the clustering of galaxies in the PSCz survey. We also discuss applications to the estimation of non-Gaussian contributions to error bars and covariance matrix of the power spectrum, in real and redshift space, for galaxies and dark matter. The results for the latter show good agreement with simulations, supporting the use of our method to constrain cosmological parameters from upcoming galaxy surveys.Comment: 13 pages, 10 figures. (references added

Remote sensing of night lights: a review and an outlook for the future

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordRemote sensing of night light emissions in the visible band offers a unique opportunity to directly observe human activity from space. This has allowed a host of applications including mapping urban areas, estimating population and GDP, monitoring disasters and conflicts. More recently, remotely sensed night lights data have found use in understanding the environmental impacts of light emissions (light pollution), including their impacts on human health. In this review, we outline the historical development of night-time optical sensors up to the current state of the art sensors, highlight various applications of night light data, discuss the special challenges associated with remote sensing of night lights with a focus on the limitations of current sensors, and provide an outlook for the future of remote sensing of night lights. While the paper mainly focuses on space borne remote sensing, ground based sensing of night-time brightness for studies on astronomical and ecological light pollution, as well as for calibration and validation of space borne data, are also discussed. Although the development of night light sensors lags behind day-time sensors, we demonstrate that the field is in a stage of rapid development. The worldwide transition to LED lights poses a particular challenge for remote sensing of night lights, and strongly highlights the need for a new generation of space borne night lights instruments. This work shows that future sensors are needed to monitor temporal changes during the night (for example from a geostationary platform or constellation of satellites), and to better understand the angular patterns of light emission (roughly analogous to the BRDF in daylight sensing). Perhaps most importantly, we make the case that higher spatial resolution and multispectral sensors covering the range from blue to NIR are needed to more effectively identify lighting technologies, map urban functions, and monitor energy use.European Union Horizon 2020Helmholtz AssociationNatural Environment Research Council (NERC)Chinese Academy of ScienceLeibniz AssociationIGB Leibniz Institut