Wavelets and WMAP non-Gaussianity

We study the statistical properties of the 1st year WMAP data on different scales using the spherical mexican hat wavelet transform. Consistent with the results of Vielva et al. (2003) we find a deviation from Gaussianity in the form of kurtosis of wavelet coefficients on $3-4^\circ$ scales in the southern Galactic hemisphere. This paper extends the work of Vielva et al. as follows. We find that the non-Gaussian signal shows up more strongly in the form of a larger than expected number of cold pixels and also in the form of scale-scale correlations amongst wavelet coefficients. We establish the robustness of the non-Gaussian signal under more wide-ranging assumptions regarding the Galactic mask applied to the data and the noise statistics. This signal is unlikely to be due to the usual quadratic term parametrized by the non-linearity parameter $f_{NL}$. We use the skewness of the spherical mexican hat wavelet coefficients to constrain $f_{NL}$ with the 1st year WMAP data. Our results constrain $f_{NL}$ to be $50\pm 80$ at 68% confidence, and less than 280 at 99% confidence.Comment: 22 pages, 10 figures, ApJ accepte

General CMB bispectrum analysis using wavelets and separable modes

In this paper we combine partial-wave (`modal') methods with a wavelet analysis of the CMB bispectrum. Our implementation exploits the advantages of both approaches to produce robust, reliable and efficient estimators which can constrain the amplitude of arbitrary primordial bispectra. This will be particularly important for upcoming surveys such as \emph{Planck}. A key advantage is the computational efficiency of calculating the inverse covariance matrix in wavelet space, producing an error bar which is close to optimal. We verify the efficacy and robustness of the method by applying it to WMAP7 data, finding \fnllocal=38.4 \pm 23.6 and \fnlequil=-119.2 \pm 123.6

On what scale should inflationary observables be constrained?

We examine the choice of scale at which constraints on inflationary observables are presented. We describe an implementation of the hierarchy of inflationary consistency equations which ensures that they remain enforced on different scales, and then seek to optimize the scale for presentation of constraints on marginalized inflationary parameters from WMAP3 data. For models with spectral index running, we find a strong variation of the constraints through the range of observational scales available, and optimize by finding the scale which decorrelates constraints on the spectral index n_S and the running. This scale is k=0.017 Mpc^{-1}, and gives a reduction by a factor of more than four in the allowed parameter area in the n_S-r plane (r being the tensor-to-scalar ratio) relative to k=0.002 Mpc^{-1}. These optimized constraints are similar to those obtained in the no-running case. We also extend the analysis to a larger compilation of data, finding essentially the same conclusions.Comment: 7 pages RevTeX4 with 9 figures included. v2: References added, new section added analyzing additional datasets alongside WMAP3. v3: Minor corrections to match version accepted by PR

Observational Bounds on Modified Gravity Models

Modified gravity provides a possible explanation for the currently observed cosmic accelaration. In this paper, we study general classes of modified gravity models. The Einstein-Hilbert action is modified by using general functions of the Ricci and the Gauss-Bonnet scalars, both in the metric and in the Palatini formalisms. We do not use an explicit form for the functions, but a general form with a valid Taylor expansion up to second order about redshift zero in the Riemann-scalars. The coefficients of this expansion are then reconstructed via the cosmic expansion history measured using current cosmological observations. These are the quantities of interest for theoretical considerations relating to ghosts and instabilities. We find that current data provide interesting constraints on the coefficients. The next-generation dark energy surveys should shrink the allowed parameter space for modifed gravity models quite dramatically.Comment: 23 pages, 5 figures, uses RevTe

A Comparative Study of Dark Energy Constraints from Current Observational Data

We examine how dark energy constraints from current observational data depend on the analysis methods used: the analysis of Type Ia supernovae (SNe Ia), and that of galaxy clustering data. We generalize the flux-averaging analysis method of SNe Ia to allow correlated errors of SNe Ia, in order to reduce the systematic bias due to weak lensing of SNe Ia. We find that flux-averaging leads to larger errors on dark energy and cosmological parameters if only SN Ia data are used. When SN Ia data (the latest compilation by the SNLS team) are combined with WMAP 7 year results (in terms of our Gaussian fits to the probability distributions of the CMB shift parameters), the latest Hubble constant (H_0) measurement using the Hubble Space Telescope (HST), and gamma ray burst (GRB) data, flux-averaging of SNe Ia increases the concordance with other data, and leads to significantly tighter constraints on the dark energy density at z=1, and the cosmic curvature \Omega_k. The galaxy clustering measurements of H(z=0.35)r_s(z_d) and r_s(z_d)/D_A(z=0.35) (where H(z) is the Hubble parameter, D_A(z) is the angular diameter distance, and r_s(z_d) is the sound horizon at the drag epoch) by Chuang & Wang (2011) are consistent with SN Ia data, given the same pirors (CMB+H_0+GRB), and lead to significantly improved dark energy constraints when combined. Current data are fully consistent with a cosmological constant and a flat universe.Comment: 11 pages, 9 figures. Slightly revised version, to appear in PRD. Supernova flux-averaging code available at http://www.nhn.ou.edu/~wang/SNcode

Comment on `Tainted evidence: cosmological model selection versus fitting', by Eric V. Linder and Ramon Miquel (astro-ph/0702542v2)

In astro-ph/0702542v2, Linder and Miquel seek to criticize the use of Bayesian model selection for data analysis and for survey forecasting and design. Their discussion is based on three serious misunderstandings of the conceptual underpinnings and application of model-level Bayesian inference, which invalidate all their main conclusions. Their paper includes numerous further inaccuracies, including an erroneous calculation of the Bayesian Information Criterion. Here we seek to set the record straight.Comment: 6 pages RevTeX

Planck priors for dark energy surveys

Although cosmic microwave background (CMB) anisotropy data alone cannot constrain simultaneously the spatial curvature and the equation of state of dark energy, CMB data provide a valuable addition to other experimental results. However computing a full CMB power spectrum with a Boltzmann code is quite slow; for instance if we want to work with many dark energy and/or modified gravity models, or would like to optimize experiments where many different configurations need to be tested, it is possible to adopt a quicker and more efficient approach. In this paper we consider the compression of the projected Planck CMB data into four parameters, R (scaled distance to last scattering surface), l_a (angular scale of sound horizon at last scattering), Omega_b h^2 (baryon density fraction) and n_s (powerlaw index of primordial matter power spectrum), all of which can be computed quickly. We show that, although this compression loses information compared to the full likelihood, such information loss becomes negligible when more data is added. We also demonstrate that the method can be used for scalar field dark energy independently of the parametrisation of the equation of state, and discuss how this method should be used for other kinds of dark energy models.Comment: 8 pages, 3 figures, 4 table