The 2dF Galaxy Redshift Survey: the nature of the relative bias between galaxies of different spectral type (original) (raw)
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The Astrophysical Journal, 1999
We analyze di †erent volume-limited samples extracted from the Southern-Sky Redshift Survey (SSRS2), using counts-in-cells to compute the count probability distribution function (CPDF). From the CPDF we derive volume-averaged correlation functions to fourth order and the normalized skewness and kurtosis and We Ðnd that the data satisÐes the hierarchical relations in the S 3 \ m 6 3 /m 6 2 2 S 4 \ m 6 4 /m 6 2 3. range
The nature of the relative bias between galaxies of different spectral type in 2dFGRS
Monthly Notices of The Royal Astronomical Society - MON NOTIC ROY ASTRON SOC, 2004
We present an analysis of the relative bias between early- and late-type galaxies in the Two-degree Field Galaxy Redshift Survey (2dFGRS) - as defined by the η parameter of Madgwick et al., which quantifies the spectral type of galaxies in the survey. We calculate counts in cells for flux-limited samples of early- and late-type galaxies, using approximately cubical cells with sides ranging from 7 to 42 h-1 Mpc. We measure the variance of the counts in cells using the method of Efstathiou et al., which we find requires a correction for a finite volume effect equivalent to the integral constraint bias of the autocorrelation function. Using a maximum-likelihood technique we fit lognormal models to the one-point density distribution, and develop methods of dealing with biases in the recovered variances resulting from this technique. We then examine the joint density distribution function, f(δE, δL), and directly fit deterministic bias models to the joint counts in cells. We measure a linear relative bias of ~1.3, which does not vary significantly with l. A deterministic linear bias model is, however, a poor approximation to the data, especially on small scales (l<= 28h-1 Mpc) where deterministic linear bias is excluded at high significance. A power-law bias model with index b1~ 0.75 is a significantly better fit to the data on all scales, although linear bias becomes consistent with the data for l>~ 40h-1 Mpc.
The 2dF Galaxy Redshift Survey: stochastic relative biasing between galaxy populations
Monthly Notices of The Royal Astronomical Society, 2004
It is well known that the clustering of galaxies depends on galaxy type.Such relative bias complicates the inference of cosmological parameters from galaxy redshift surveys, and is a challenge to theories of galaxy formation and evolution. In this paper we perform a joint counts-in-cells analysis on galaxies in the 2dF Galaxy Redshift Survey, classified by both colour and spectral type, eta, as early or late type galaxies. We fit three different models of relative bias to the joint probability distribution of the cell counts, assuming Poisson sampling of the galaxy density field. We investigate the nonlinearity and stochasticity of the relative bias, with cubical cells of side 10Mpc \leq L \leq 45Mpc (h=0.7). Exact linear bias is ruled out with high significance on all scales. Power law bias gives a better fit, but likelihood ratios prefer a bivariate lognormal distribution, with a non-zero `stochasticity' - i.e. scatter that may result from physical effects on galaxy formation other than those from the local density field. Using this model, we measure a correlation coefficient in log-density space (r_LN) of 0.958 for cells of length L=10Mpc, increasing to 0.970 by L=45Mpc. This corresponds to a stochasticity sigma_b/bhat of 0.44\pm0.02 and 0.27\pm0.05 respectively. For smaller cells, the Poisson sampled lognormal distribution presents an increasingly poor fit to the data, especially with regard to the fraction of completely empty cells. We compare these trends with the predictions of semianalytic galaxy formation models: these match the data well in terms of overall level of stochasticity, variation with scale, and fraction of empty cells.
The non-linear redshift-space power spectrum of galaxies
Monthly Notices of the Royal Astronomical Society, 1998
We study the power spectrum of galaxies in redshift space, with third order perturbation theory to include corrections that are absent in linear theory. We assume a local bias for the galaxies: i.e. the galaxy density is sampled from some local function of the underlying mass distribution. We find that the effect of the nonlinear bias in real space is to introduce two new features: first, there is a contribution to the power which is constant with wavenumber, whose nature we reveal as essentially a shot-noise term. In principle this contribution can mask the primordial power spectrum, and could limit the accuracy with which the latter might be measured on very large scales. Secondly, the effect of second-and third-order bias is to modify the effective bias (defined as the square root of the ratio of galaxy power spectrum to matter power spectrum). The effective bias is almost scale-independent over a wide range of scales. These general conclusions also hold in redshift space. In addition, we have investigated the distortion of the power spectrum by peculiar velocities, which may be used to constrain the density of the Universe. We look at the quadrupole-to-monopole ratio, and find that higher-order terms can mimic linear theory bias, but the bias implied is neither the linear bias, nor the effective bias referred to above. We test the theory with biased N-body simulations, and find excellent agreement in both real and redshift space, providing the local biasing is applied on a scale whose fractional r.m.s. density fluctuations are < 0.5.
Journal of Cosmology and Astroparticle Physics, 2008
We explore and compare the performances of two nonlinear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM cosmologies. The first model is the well known Q model, first applied in the analysis of 2dFGRS data. The second, the P model, is inspired by the halo model, in which nonlinear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while both models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalisation, a technique sometimes used in the marginalisation of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended nonlinear correction model also because of its physical transparency.
Empirical Validation of the Ising Galaxy Bias Model
2019
Repp and Szapudi (2019) present a physically-motivated galaxy bias model which remains physical in low-density regions and which also provides a better fit to simulation data than do typical survey-analysis bias models. Given plausible simplifying assumptions, the physics of this model (surprisingly) proves to be analogous to the Ising model of statistical mechanics. In the present work we present a method of testing this Ising bias model against empirical galaxy survey data. Using this method, we compare our model (as well as three reference models -- linear, quadratic, and logarithmic) to SDSS, 6dFGS, and COSMOS2015 results, finding that for spectroscopic redshift surveys, the Ising bias model provides a superior fit compared to the reference models. Photometric redshifts, on the other hand, introduce enough error into the radial coordinate that none of the models yields a good fit. A physically meaningful galaxy bias model is necessary for optimal extraction of cosmological infor...
Constraints on a scale-dependent bias from galaxy clustering
ABSTRACT We forecast the future constraints on scale-dependent parametrizations of galaxy bias and their impact on the estimate of cosmological parameters from the power spectrum of galaxies measured in a spectroscopic redshift survey. For the latter we assume a wide survey at relatively large redshifts, similar to the planned Euclid survey, as baseline for future experiments. To assess the impact of the bias we perform a Fisher matrix analysis and we adopt two different parametrizations of scale-dependent bias. The fiducial models for galaxy bias are calibrated using a mock catalogs of H$\alpha$ emitting galaxies mimicking the expected properties of the objects that will be targeted by the Euclid survey. In our analysis we have obtained two main results. First of all, allowing for a scale-dependent bias does not significantly increase the errors on the other cosmological parameters apart from the rms amplitude of density fluctuations, sigma8\sigma_{8}sigma8, and the growth index gamma\gammagamma, whose uncertainties increase by a factor up to two, depending on the bias model adopted. Second, we find that the accuracy in the linear bias parameter b0b_{0}b0 can be estimated to within 1-2\% at various redshifts regardless of the fiducial model. The non-linear bias parameters have significantly large errors that depend on the model adopted. Despite of this, in the more realistic scenarios departures from the simple linear bias prescription can be detected with a sim2,sigma\sim2\,\sigmasim2,sigma significance at each redshift explored.
Cosmos: Stochastic Bias from Measurements of Weak Lensing and Galaxy Clustering
The Astrophysical Journal, 2012
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 ). 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 M ⊙ and 10 10 < M * < 10 11 h −2 M ⊙ ). At scales R > 2 h −1 Mpc, our measurements support a model of bias increasing with redshift. The 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 M ⊙ ) = 11.7 +0.6 −1.3 and log(M 200 /h −1 M ⊙ ) = 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 ± 1.5h −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. mate of stochasticity and non-linearity. In the zCOS-MOS redshift survey found non-linearity to contribute less than ∼ 0.2% to the bias relation for luminosity-selected galaxies (M B < −20 − z). Therefore in the following, we will assume that the correlation coefficient r mostly quantifies bias stochasticity. With respect to the bias parameter b, found the bias relation to be scale-independent between scales R = 8 h −1 Mpc and R = 10 h −1 Mpc, and redshift-dependent between redshifts z = 0.4 and z = 1.
Galaxy formation and large-scale bias
Monthly Notices of the Royal Astronomical Society, 1997
We outline a simple approach to understanding the physical origin of bias in the distribution of galaxies relative to that of dark matter. The rst step is to specify how collapsed, virialized halos of dark matter trace the overall matter distribution.
The Stromlo-APM Redshift Survey. III. Redshift Space Distortions, Omega, and Bias
The Astrophysical Journal, 1996
Galaxy redshift surveys provide a distorted picture of the universe due to the non-Hubble component of galaxy motions. By measuring such distortions in the linear regime one can constrain the quantity β = Ω 0.6 /b where Ω is the cosmological density parameter and b is the (linear) bias factor for optically-selected galaxies. In this paper we apply two techniques for estimating β from the Stromlo-APM redshift survey-(1) measuring the anisotropy of the redshift space correlation function in spherical harmonics and (2) comparing the amplitude of the direction-averaged redshift space correlation function to the real space correlation function. We test the validity of these techniques, particularly whether the assumption of linear theory is justified, using two sets of large N-body simulations. We find that the first technique is affected by non-linearities on scales up to ∼ 30h −1 Mpc. The second technique is less sensitive to non-linear effects and so is more useful for existing redshift surveys. The Stromlo-APM survey data favours a low value for β, with β ∼ < 0.6. A bias parameter b ≈ 2 is thus required if Ω ≡ 1. However, higher-order correlations measured from the APM galaxy survey (Gaztañaga and Frieman 1994) indicate a low value for the bias parameter b ≈ 1, requiring that Ω ∼ < 0.5. We also measure the relative bias for samples of galaxies of various luminosity and morphological type and find that low-luminosity galaxies are roughly three times less biased than L * galaxies. For the galaxy population as a whole, we measure a real space variance of galaxy counts in 8h −1 Mpc spheres of (σ 2 8) g = 0.89 ± 0.05.