Abstract:
We study whether the bias factors of galaxies can be unbiasedly recovered from their power spectra and bispectra. We use a set of numerical N-body simulations and construct large mock galaxy catalogs based upon the semi-analytical model of Croton et al. (2006). We measure the reduced bispectra for galaxies of different luminosity, and determine the linear and first nonlinear bias factors from their bispectra. We find that on large scales down to that of the wavenumber k=0.1h/Mpc, the bias factors b1 and b2 are nearly constant, and b1 obtained with the bispectrum method agrees very well with the expected value. The nonlinear bias factor b2 is negative, except for the most luminous galaxies with M<-23 which have a positive b2. The behavior of b2 of galaxies is consistent with the b2 mass dependence of their host halos. We show that it is essential to have an accurate estimation of the dark matter bispectrum in order to have an unbiased measurement of b1 and b2. We also test the analytical approach of incorporating halo occupation distribution to model the galaxy power spectrum and bispectrum. The halo model predictions do not fit the simulation results well on the precision requirement of current cosmological studies.

Abstract:
In the theory of structure formation, galaxies are biased tracers of the underlying matter density field. The statistical relation between galaxy and matter density field is commonly referred as galaxy bias. In this paper, we test the linear bias model with weak-lensing and galaxy clustering measurements in the 2 square degrees COSMOS field (Scoville et al. 2007). We estimate the bias of galaxies between redshifts z=0.2 and z=1, and over correlation scales between R=0.2 h^-1 Mpc and R=15 h^-1 Mpc. We focus on three galaxy samples, selected in flux (simultaneous cuts I_814W < 26.5 and K_s < 24), and in stellar-mass (10^9 < M_* < 10^10 h^-2 Msun and 10^10 < M^*< 10^11 h^-2 Msun). At scales R > 2 h^-1 Mpc, our measurements support a model of bias increasing with redshift. The Tinker et al. (2010) fitting function provides a good fit to the data. We find the best fit mass of the galaxy halos to be log(M_200 h^-1 Msun) = 11.7^+0.6_-1.3 and log(M_200 h^-1 Msun) = 12.4^+0.2_-2.9 respectively for the low and high stellar-mass samples. In the halo model framework, bias is scale-dependent with a change of slope at the transition scale between the one and the two halo terms. We detect a scale-dependence of bias with a turn-down at scale R=2.3\pm1.5 h^-1 Mpc, in agreement with previous galaxy clustering studies. We find no significant amount of stochasticity, suggesting that a linear bias model is sufficient to describe our data. We use N-body simulations to quantify both the amount of cosmic variance and systematic errors in the measurement.

Abstract:
Via the magnification bias, gravitational lensing by large-scale structures causes angular cross-correlations between distant quasars and foreground galaxies on angular scales of arc minutes and above. We investigate the three-point cross-correlation between quasars and galaxy pairs measurable via the second moment of the galaxy counts around quasars and show that it reaches the level of a few per cent on angular scales near one arc minute. Combining two- and three-point correlations, a skewness parameter can be defined which is shown to be virtually independent on the shape and normalisation of the dark-matter power spectrum. If the galaxy bias is linear and deterministic, the skewness depends on the cosmic matter density parameter Omega_0 only; otherwise, it can be used to probe the linearity and stochasticity of the bias. We finally estimate the signal-to-noise ratio of a skewness determination and find that around twenty thousand distant quasars e.g. from the Sloan Digital Sky Survey should suffice for a direct measurement of Omega_0.

Abstract:
We present a simple and accurate method to constrain galaxy bias based on the distribution of counts in cells. The most unique feature of our technique is that it is applicable to non-linear scales, where both dark matter statistics and the nature of galaxy bias are fairly complex. First, we estimate the underlying continuous distribution function from precise counts-in-cells measurements assuming local Poisson sampling. Then a robust, non-parametric inversion of the bias function is recovered from the comparison of the cumulative distributions in simulated dark matter and galaxy catalogs. Obtaining continuous statistics from the discrete counts is the most delicate novel part of our recipe. It corresponds to a deconvolution of a (Poisson) kernel. For this we present two alternatives: a model independent algorithm based on Richardson-Lucy iteration, and a solution using a parametric skewed lognormal model. We find that the latter is an excellent approximation for the dark matter distribution, but the model independent iterative procedure is more suitable for galaxies. Tests based on high resolution dark matter simulations and corresponding mock galaxy catalogs show that we can reconstruct the non-linear bias function down to highly non-linear scales with high precision in the range of $-1 \le \delta \le 5$. As far as the stochasticity of the bias, we have found a remarkably simple and accurate formula based on Poisson noise, which provides an excellent approximation for the scatter around the mean non-linear bias function. In addition we have found that redshift distortions have a negligible effect on our bias reconstruction, therefore our recipe can be safely applied to redshift surveys.

Abstract:
We have used a combination of high resolution cosmological N-body simulations and semi-analytic modelling of galaxy formation to investigate the processes that determine the spatial distribution of galaxies in cold dark matter (CDM) models. The galaxy distribution depends sensitively on the efficiency with which galaxies form in halos of different mass. In small mass halos, galaxy formation is inhibited by the reheating of cooled gas by feedback processes, whereas in large mass halos, it is inhibited by the long cooling time of the gas. As a result, the mass-to-light ratio of halos has a deep minimum at the halo mass associated with L* galaxies. This leads to a scale dependent bias in the distribution of galaxies relative to the distribution of mass. On large scales, the bias in the galaxy distribution is related in a simple way to the bias in the distribution of massive halos. On small scales, the correlation function is determined by the interplay between various effects including the spatial exclusion of dark matter halos, the distribution function of the number of galaxies occupying a single dark matter halo and, to a lesser extent, dynamical friction. Remarkably, these processes conspire to produce a correlation function in a flat, Omega_0=0.3, CDM model that is close to a power-law over nearly four orders of magnitude in amplitude. This model agrees well with the correlation function of galaxies measured in the APM survey. On small scales, the model galaxies are less strongly clustered than the dark matter whereas on large scales, they trace the occupied halos. Our clustering predictions are robust to changes in the parameters of the galaxy formation model, provided only those models that match the bright end of the galaxy luminosity function are considered. (abridged)

Abstract:
We investigate the effects on cosmological clustering statistics of empirical biasing, where the galaxy distribution is a local transformation of the present-day Eulerian density field. The effects of the suppression of galaxy numbers in voids, and their enhancement in regions of high density, are considered, independently and in combination. We compare results from numerical simulations with the predictions of simple analytic models. We find that the bias is generally scale-dependent, so that the shape of the galaxy power spectrum differs from that of the underlying mass distribution. The degree of bias is always a monotonic function of scale, tending to an asymptotic value on scales where the density fluctuations are linear. The scale dependence is often rather weak, with many reasonable prescriptions giving a bias which is nearly independent of scale. We have investigated whether such an Eulerian bias can reconcile a range of theoretical power spectra with the twin requirements of fitting the galaxy power spectrum and reproducing the observed mass-to-light ratios in clusters. It is not possible to satisfy these constraints for any member of the family of CDM-like power spectra in an Einstein - de Sitter universe when normalised to match COBE on large scales and galaxy cluster abundances on intermediate scales. We discuss what modifications of the mass power spectrum might produce agreement with the observational data.

Abstract:
The weak gravitational lensing distortion of distant galaxy images (defined as sources) probes the projected large-scale matter distribution in the Universe. To improve quality in the 3D mass mapping using 3D-lensing, we combine the lensing information with the spatial clustering of a population of galaxies that trace the matter density with a known galaxy bias (defined as tracers). For our minimum variance estimator, merely all the second-order bias of the tracers has to be known, which can in principle be self-consistently constrained in the data by lensing techniques. This synergy introduces a new noise component because of the stochasticity in the matter-tracer density relation. We give a description of the stochasticity noise in the Gaussian regime, and we investigate the estimator characteristics analytically. We apply the estimator to a mock survey based on the Millennium Simulation. The estimator linearly mixes the individual lensing mass and tracer number density maps into a combined smoothed mass map. The weighting in the mix depends on the S/N of the individual maps and the correlation, $r$, between the matter and galaxy density. The weight of the tracers can be reduced by hand. For moderate mixing, the S/N in the mass map improves by a factor $\sim2-3$ for $r\gtrsim0.4$; the systematic offset between a true and apparent mass peak distance ($z$-shift bias) in a lensing-only map is eliminated, even for weak correlations of $r\sim0.4$. If the second-order bias of tracer galaxies can be determined, the synergy technique potentially provides an option to improve redshift accuracy and completeness of the lensing 3D mass map. However,the estimator's performance on sub-degree, non-Gaussian scales depends on all details in the galaxy bias mechanism and, hence, its accuracy on the choice of the tracer population.[abridged]

Abstract:
This paper examines several methods of tracing galaxies in N-body simulations and their effects on the derived galaxy statistics, especially measurements of velocity bias. Using two simulations with identical initial conditions, one following dark matter only and the other following dark matter and baryons, both collisionless and collisional methods of tracing galaxies are compared to one another and against a set of idealized criteria. None of the collisionless methods proves satisfactory, including an elaborate scheme developed here to circumvent previously known problems. The main problem is that galactic overdensities are both secularly and impulsively disrupted while orbiting in cluster potentials. With dissipation, the baryonic tracers have much higher density contrasts and much smaller cross sections, allowing them to remain distinct within the cluster potential. The question remains whether the incomplete physical model introduces systematic biases. Statistical measures determined from simulations can vary significantly based solely on the galaxy tracing method utilized. The two point correlation function differs most on sub-cluster scales with generally good agreement on larger scales. Pairwise velocity dispersions show less uniformity on all scales addressed here. All tracing methods show a velocity bias to varying degrees, but the predictions are not firm: either the tracing method is not robust or the statistical significance has not been demonstrated. Though theoretical arguments suggest that a mild velocity bias should exist, simulation results are not yet conclusive.

Abstract:
Examining the nature of the relative clustering of different galaxy types can help tell us how galaxies formed. To measure this relative clustering, I perform a joint counts-in-cells analysis of galaxies of different spectral types in the Las Campanas Redshift Survey (LCRS). I develop a maximum-likelihood technique to fit for the relationship between the density fields of early- and late-type galaxies. This technique can directly measure nonlinearity and stochasticity in the biasing relation. At high significance, a small amount of stochasticity is measured, corresponding to a correlation coefficient of about 0.87 on scales corresponding to 15 Mpc/h spheres. A large proportion of this signal appears to derive from errors in the selection function, and a more realistic estimate finds a correlation coefficient of about 0.95. These selection function errors probably account for the large stochasticity measured by Tegmark & Bromley (1999), and may have affected measurements of very large-scale structure in the LCRS. Analysis of the data and of mock catalogs shows that the peculiar geometry, variable flux limits, and central surface-brightness selection effects of the LCRS do not seem to cause the effect.

Abstract:
The spatial distribution of galaxies we observed is subject to the given condition that we, human beings are sitting right in a galaxy -- the Milky Way. Thus the ergodicity assumption is questionable in interpretation of the observed galaxy distribution. The resultant difference between observed statistics (volume average) and the true cosmic value (ensemble average) is termed as the ergodicity bias. We perform explicit numerical investigation of the effect for a set of galaxy survey depths and near-end distance cuts. It is found that the ergodicity bias in observed two- and three-point correlation functions in most cases is insignificant for modern analysis of samples from galaxy surveys and thus close a loophole in precision cosmology. However, it may become non-negligible in certain circumstances, such as those applications involving three-point correlation function at large scales of local galaxy samples. Thus one is reminded to take extra care in galaxy sample construction and interpretation of the statistics of the sample, especially when the characteristic redshift is low.