Statistical techniques in cosmology

In these lectures I cover a number of topics in cosmological data analysis. I concentrate on general techniques which are common in cosmology, or techniques which have been developed in a cosmological context. In fact they have very general applicability, for problems in which the data are interpreted in the context of a theoretical model, and thus lend themselves to a Bayesian treatment. We consider the general problem of estimating parameters from data, and consider how one can use Fisher matrices to analyse survey designs before any data are taken, to see whether the survey will actually do what is required. We outline numerical methods for estimating parameters from data, including Monte Carlo Markov Chains and the Hamiltonian Monte Carlo method. We also look at Model Selection, which covers various scenarios such as whether an extra parameter is preferred by the data, or answering wider questions such as which theoretical framework is favoured, using General Relativity and braneworld gravity as an example. These notes are not a literature review, so there are relatively few references

Intrinsic Galaxy Alignments and Weak Gravitational Lensing

Gravitational lensing causes background galaxy images to become aligned, and the statistical characteristics of the image alignments can then be used to constrain the power spectrum of mass fluctuations. Analyses of gravitational lensing assume that intrinsic galaxy alignments are negligible, but if this assumption does not hold, then the interpretation of image alignments will be in error. As gravitational lensing experiments become more ambitious and seek very low-level alignments arising from lensing by large-scale structure, it becomes more important to estimate the level of intrinsic alignment in the galaxy population. In this article, I review the cluster of independent theoretical studies of this issue, as well as the current observational status. Theoretically, the calculation of intrinsic alignments is by no means straightforward, but some consensus has emerged from the existing works, despite each making very different assumptions. This consensus is that a) intrinsic alignments are a small but non-negligible (< 10%) contaminant of the lensing ellipticity correlation function, for samples with a median redshift z = 1; b) intrinsic alignments dominate the signal for low-redshift samples (z = 0.1), as expected in the SuperCOSMOS lensing survey and the Sloan Digital Sky SurveyComment: 8 pages. Invited talk at Yale Workshop on `The Shapes of Galaxies and their halos', May 200

Large-scale bias in the Universe: bispectrum method

Evidence that the Universe may be close to the critical density, required for its expansion eventually to be halted, comes principally from dynamical studies of large-scale structure. These studies either use the observed peculiar velocity field of galaxies directly, or indirectly by quantifying its anisotropic effect on galaxy clustering in redshift surveys. A potential difficulty with both such approaches is that the density parameter $\Omega_0$ is obtained only in the combination $\beta = \Omega_0^{0.6}/b$, if linear perturbation theory is used. The determination of the density parameter $\Omega_0$ is therefore compromised by the lack of a good measurement of the bias parameter $b$, which relates the clustering of sample galaxies to the clustering of mass. In this paper, we develop an idea of Fry (1994), using second-order perturbation theory to investigate how to measure the bias parameter on large scales. The use of higher-order statistics allows the degeneracy between $b$ and $\Omega_0$ to be lifted, and an unambiguous determination of $\Omega_0$ then becomes possible. We apply a likelihood approach to the bispectrum, the three-point function in Fourier space. This paper is the first step in turning the idea into a practical proposition for redshift surveys, and is principally concerned with noise properties of the bispectrum, which are non-trivial. The calculation of the required bispectrum covariances involves the six-point function, including many noise terms, for which we have developed a generating functional approach which will be of value in calculating high-order statistics in general.Comment: 12 pages, latex, 7 postscript figures included. Accepted by MNRAS. (Minor numerical typesetting errors corrected: results unchanged

The nonlinear redshift-space power spectrum of galaxies

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 $< 0.5$.Comment: 13 pages, 7 figures. Accepted by MNRA

3D Weak Gravitational Lensing of the CMB and Galaxies

In this paper we present a power spectrum formalism that combines the full three-dimensional information from the galaxy ellipticity field, with information from the cosmic microwave background (CMB). We include in this approach galaxy cosmic shear and galaxy intrinsic alignments, CMB deflection, CMB temperature and CMB polarisation data; including the inter-datum power spectra between all quantities. We apply this to forecasting cosmological parameter errors for CMB and imaging surveys for Euclid-like, Planck, ACTPoL, and CoRE-like experiments. We show that the additional covariance between the CMB and ellipticity measurements can improve dark energy equation of state measurements by 15%, and the combination of cosmic shear and the CMB, from Euclid-like and CoRE-like experiments, could in principle measure the sum of neutrino masses with an error of 0.003 eV.Comment: Accepted to MNRA

Measuring the cosmological constant with redshift surveys

It has been proposed that the cosmological constant $\Lambda$ might be measured from geometric effects on large-scale structure. A positive vacuum density leads to correlation-function contours which are squashed in the radial direction when calculated assuming a matter-dominated model. We show that this effect will be somewhat harder to detect than previous calculations have suggested: the squashing factor is likely to be $<1.3$, given realistic constraints on the matter contribution to $\Omega$. Moreover, the geometrical distortion risks being confused with the redshift-space distortions caused by the peculiar velocities associated with the growth of galaxy clustering. These depend on the density and bias parameters via the combination $\beta\equiv \Omega^{0.6}/b$, and we show that the main practical effect of a geometrical flattening factor $F$ is to simulate gravitational instability with $\beta_{\rm eff}\simeq 0.5(F-1)$. Nevertheless, with datasets of sufficient size it is possible to distinguish the two effects; we discuss in detail how this should be done. New-generation redshift surveys of galaxies and quasars are potentially capable of detecting a non-zero vacuum density, if it exists at a cosmologically interesting level.Comment: MNRAS in press. 12 pages LaTeX including Postscript figures. Uses mn.sty and epsf.st

Measuring dark energy properties with 3D cosmic shear

We present parameter estimation forecasts for present and future 3D cosmic shear surveys. We demonstrate that, in conjunction with results from cosmic microwave background (CMB) experiments, the properties of dark energy can be estimated with very high precision with large-scale, fully 3D weak lensing surveys. In particular, a 5-band, 10,000 square degree ground-based survey to a median redshift of zm=0.7 could achieve 1-$\sigma$ marginal statistical errors, in combination with the constraints expected from the CMB Planck Surveyor, of $\Delta$w0=0.108 and $\Delta$wa=0.099 where we parameterize w by w(a)=w0+wa(1-a) where a is the scale factor. Such a survey is achievable with a wide-field camera on a 4 metre class telescope. The error on the value of w at an intermediate pivot redshift of z=0.368 is constrained to $\Delta$w(z=0.368)=0.0175. We compare and combine the 3D weak lensing constraints with the cosmological and dark energy parameters measured from planned Baryon Acoustic Oscillation (BAO) and supernova Type Ia experiments, and find that 3D weak lensing significantly improves the marginalized errors. A combination of 3D weak lensing, CMB and BAO experiments could achieve $\Delta$w0=0.037 and $\Delta$wa=0.099. Fully 3D weak shear analysis avoids the loss of information inherent in tomographic binning, and we show that the sensitivity to systematic errors is much less. In conjunction with the fact that the physics of lensing is very soundly based, this analysis demonstrates that deep, wide-angle 3D weak lensing surveys are extremely promising for measuring dark energy properties.Comment: 18 pages, 16 figures. Accepted to MNRAS. Figures now in grayscale. Further discussions on non-Gaussianity and photometric redshift errors. Some references adde