Abstract:
In this non-specialist review I look at how weak lensing can provide information on the dark sector of the Universe. The review concentrates on what can be learned about Dark Matter, Dark Energy and Dark Gravity, and why. On Dark Matter, results on the confrontation of theoretical profiles with observation are reviewed, and measurements of neutrino masses discussed. On Dark Energy, the interest is whether this could be Einstein's cosmological constant, and prospects for high-precision studies of the equation of state are considered. On Dark Gravity, we consider the exciting prospects for future weak lensing surveys to distinguish General Relativity from extra-dimensional or other gravity theories.

Abstract:
I propose an analysis method, based on spin-spherical harmonics and spherical Bessel functions, for large-scale weak lensing surveys which have source distance information through photometric redshifts. I show that the distance information can significantly reduce statistical errors on cosmological parameters; in particular, 3D lensing analysis offers excellent prospects for constraining the equation of state of the vacuum energy which dominates the energy density of the Universe. I show that the ratio of pressure to energy density could be determined to an accuracy of $\sim 1%$ or better. Having distance information also offers significant advantages in the control of systematic effects such as the intrinsic alignment of galaxies. The case for obtaining photometric redshifts is therefore compelling. A signal-to-noise eigenmode analysis of the modes shows that the modes with highest signal-to-noise correspond quite closely to ignoring the redshift information, but there is significant extra information from a few radial modes. These modes are generally long-wavelength, suggesting that useful information can be gleaned even if the photometric redshifts are relatively inaccurate.

Abstract:
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.

Abstract:
In these lectures I give an overview of gravitational lensing, concentrating on theoretical aspects, including derivations of some of the important results. Topics covered include the determination of surface mass densities of intervening lenses, as well as the statistical analysis of distortions of galaxy images by general inhomogeneities (cosmic shear), both in 2D projection on the sky, and in 3D where source distance information is available. 3D mass reconstruction and the shear ratio test are also considered, and the sensitivity of observables to Dark Energy is used to show how its equation of state may be determined using weak lensing. Finally, the article considers the prospect of testing Einstein's General Relativity with weak lensing, exploiting the differences in growth rates of perturbations in different models.} \abstract{In these lectures I give an overview of gravitational lensing, concentrating on theoretical aspects, including derivations of some of the important results. Topics covered include the determination of surface mass densities of intervening lenses, as well as the statistical analysis of distortions of galaxy images by general inhomogeneities (cosmic shear), both in 2D projection on the sky, and in 3D where source distance information is available. 3D mass reconstruction and the shear ratio test are also considered, and the sensitivity of observables to Dark Energy is used to show how its equation of state may be determined using weak lensing. Finally, the article considers the prospect of testing Einstein's General Relativity with weak lensing, exploiting the differences in growth rates of perturbations in different models.

Abstract:
We address the dual challenge of estimating deviations from Gaussianity arising in models of the Early Universe, whilst retaining information necessary to assess whether a detection of non-Gaussianity is primordial. We do this by constructing a new statistic, the bispectrum-related power spectrum, which is constructed from a map of the Cosmic Microwave Background. The estimator is optimised for primordial non-Gaussianity detection, but can also be useful in distinguishing primordial non-Gaussianity from secondary non-Gaussianity, such as may arise from unsubtracted point sources, or residuals from component separation. Extending earlier studies we present unbiased non-Gaussianity estimators optimised for partial sky coverage and inhomogeneous noise associated with realistic scan strategies, but which retain the ability to assess foreground contamination.

Abstract:
Intrinsic alignments of galaxies can mimic to an extent the effects of shear caused by weak gravitational lensing. Previous studies have shown that for shallow surveys with median redshifts z_m = 0.1, the intrinsic alignment dominates the lensing signal. For deep surveys with z_m = 1, intrinsic alignments are believed to be a significant contaminant of the lensing signal, preventing high-precision measurements of the matter power spectrum. In this paper we show how distance information, either spectroscopic or photometric redshifts, can be used to down-weight nearby pairs in an optimised way, to reduce the errors in the shear signal arising from intrinsic alignments. Provided a conservatively large intrinsic alignment is assumed, the optimised weights will essentially remove all traces of contamination. For the Sloan spectroscopic galaxy sample, residual shot noise continues to render it unsuitable for weak lensing studies. However, a dramatic improvement for the slightly deeper Sloan photometric survey is found, whereby the intrinsic contribution, at angular scales greater than 1 arcminute, is reduced from about 80 times the lensing signal to a 10% effect. For deeper surveys such as the COMBO-17 survey with z_m = 0.6, the optimisation reduces the error from a largely systematic 220% error at small angular scales to a much smaller and largely statistical error of only 17% of the expected lensing signal. We therefore propose that future weak lensing surveys be accompanied by the acquisition of photometric redshifts, in order to remove fully the unknown intrinsic alignment errors from weak lensing detections.

Abstract:
The statistical properties of a map of the primary fluctuations in the cosmic microwave background (CMB) may be specified to high accuracy by a few thousand power spectra measurements, provided the fluctuations are gaussian, yet the number of parameters relevant for the CMB is probably no more than about 10-20. There is consequently a large degree of redundancy in the power spectrum data. In this paper, we show that the MOPED data compression technique can reduce the CMB power spectrum measurements to about 10-20 numbers (one for each parameter), from which the cosmological parameters can be estimated virtually as accurately as from the complete power spectrum. This offers opportunities for very fast parameter estimation from real and simulated CMB skies, with accurate likelihood calculations at Planck resolution being speeded up by a factor of around five hundred million.

Abstract:
We compute precise predictions for the two-point correlation function of local maxima (or minima) in the temperature of the microwave background, under the assumption that it is a random gaussian field. For a given power spectrum and peak threshold there are no adjustable parameters, and since this analysis does not make the small-angle approximation of Heavens & Sheth (1999), it is essentially complete. We find oscillatory features which are absent in the temperature autocorrelation function, and we also find that the small-angle approximation to the peak-peak correlation function is accurate to better than 0.01 on all scales. These high-precision predictions can form the basis of a sensitive test of the gaussian hypothesis with upcoming all-sky microwave background experiments MAP and Planck, affording a thorough test of the inflationary theory of the early Universe. To illustrate the effectiveness of the technique, we apply it to simulated maps of the microwave sky arising from the cosmic string model of structure formation, and compare with the bispectrum as a non-gaussian discriminant. We also show how peak statistics can be a valuable tool in assessing and statistically removing contamination of the map by foreground point sources.

Abstract:
We investigate to what extent future microwave background experiments might be able to detect a suppression of fluctuation power on large scales in flat and open universe models. Such suppression would arise if fluctuations are generated by causal processes, and a measurement of a small suppression scale would be problematic for inflation models, but consistent with many defect models. More speculatively, a measurement of a suppression scale of the order of the present Hubble radius could provide independent evidence for a fine-tuned inflation model leading to a low-density universe. We find that, depending on the primordial power spectrum, a suppression scale modestly larger than the visible Horizon can be detected, but that the detectability drops very rapidly with increasing scale. For models with two periods of inflation, there is essentially no possibility of detecting a causal suppression scale.

Abstract:
In the standard model for structure formation, bound objects originate from the gravitational collapse of small perturbations arising from quantum fluctuations with random phases. In other scenarios, based on defects, structures are seeded by localized energy density. In principle, it is possible to differentiate between these models on the basis of their statistical properties; only in the former case is the initial density field an almost-perfect random gaussian field. In this paper, we investigate the use of the trispectrum of the galaxy density field, which is the connected four-point function in Fourier space, as a discriminant between gaussian and non-gaussian models. It has the advantage of having only weak non-linear growth. We define a related statistic $\tau$ which, as a test of the gaussian hypothesis, is independent of cosmology, the power spectrum and biasing, in real space, and which is, in principle, a measure of the departure from gaussian statistics. For galaxy redshift surveys, the statistic depends on cosmology and bias only through the potentially observable parameter $\beta$. We compute the expected errors on the estimate of $\tau$, and demonstrate with numerical simulations that it can be a useful discriminant of models, with the important proviso that any bias is linear on large scales. Whether it is the most effective method is uncertain and depends on the nature of the departure from gaussianity.