Recent CMB Data Research Articles

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0. [Abridged]

CONSISTENCY TEST OF DARK ENERGY MODELS

Recently we proposed a new approach to test dark energy models based on the observational data. In that work we focused particularly on quintessence models for demonstration and invoked a widely used parametrization of the dark energy equation of state. In this paper we take the more recent SN Ia , CMB and BAO data, invoke the same parametrization, and apply this method of consistency test to five dark energy models, including the ΛCDM model, the generalized Chaplygin gas, and three quintessence models: exponential, power-law and inverse-exponential potentials. We find that the exponential potential of quintessence is ruled out at the 95.4% confidence level, while the other four models are consistent with data. This consistency test can be efficiently performed since for all models it requires the constraint of only a single parameter space that by choice can be easily accessed.

Primordial “fNL” non-Gaussianity and perturbations beyond the present horizon

We show a primordial nonlinear (``${f}_{\mathrm{NL}}$'') term may produce unphysically large CMB anisotropy for a red-tilted primordial power spectrum ($n<1$) because of coupling to primordial fluctuation on the largest scale. We consider a primordial power spectrum models of a running spectral index, and a transition at very low wave numbers. We find that only negative running spectral index models are allowed, provided that there is no transition at a low wave numbers (i.e. $k\ensuremath{\ll}1$). For models of a constant spectral index, we find $\mathrm{log}({k}_{c}/{k}_{0})\ensuremath{\gtrsim}\ensuremath{-}184$, at $1\ensuremath{\sigma}$ level, on the transition scale of sharp cutoff models, using recent CMB and SDSS data.

Age constraints on the cosmic equation of state

Dark energy is the invisible fuel that seems to drive the current acceleration of the Universe. Its presence, which is inferred from an impressive convergence of high-quality observational results along with some sucessful theoretical predictions, is also supported by the current estimates of the age of the Universe from dating of local and high-z objects. In this work we study observational constraints on the dark energy equation of state (w) from lookback time measurements of high- galaxies, as recently published by the Gemini Deep Deep Survey (GDDS). To build up our lookback time sample from these observations we use 8 high- galaxies in the redshift interval 1.3 ≤z ≤2.2 and assume the total expanding age of the Universe to be t obs 0 = 13.6 +0.4 -0.3 Gyr, as obtained from current cosmic microwave background data. We show that these age measurements are compatible with values of w close to -1, although there is still space for quintessence (w > -1) and phantom (w < -1) behaviors. To break possible degeneracies in the Ωm - w plane, we also discuss the bounds on this parametric space when GDDS lookback time measurements are combined with the most recent SNe la, CMB, and LSS data.

Bayesian evidence as a tool for comparing datasets

We introduce a conservative test for quantifying the consistency of two or more datasets. The test is based on the Bayesian answer to the question, ''How much more probable is it that all my data were generated from the same model system than if each dataset were generated from an independent set of model parameters''. The behavior of the resulting odds ratio is demonstrated with a two-dimensional toy example. We make explicit the connection between evidence ratios and the differences in peak-chisquared values, the later of which is more widely used and more cheaply calculated. Calculating evidence ratios for three cosmological datasets (recent CMB data (WMAP, ACBAR, CBI, VSA), SDSS and the most recent SNe Type 1A data) we find that concordance is favored and the tightening of constraints on cosmological parameters is indeed justified.

CMB power spectrum from noncommutative spacetime

Very recent CMB data of WMAP offers an opportunity to test inflation models, in particular, the running of spectral index is quite new and can be used to rule out some models. We show that an noncommutative spacetime inflation model gives a good explanation of these new results. In fitting the data, we also obtain a relationship between the noncommutative parameter (string scale) and the ending time of inflation.

Constraining evolution of quintessence with CMB and SNIa data

The equation of state of the hypothetical dark energy component, which constitutes about two thirds of the critical density of the universe, may be very different from that of a cosmological constant. Employing a phenomenological model, we investigate semi-analytically the constraints imposed on the scalar quintessence by supernovae observations, and by the acoustic scale extracted from recent CMB data. We show that a universe with a quintessence-dominated phase in the dark age is consistent with the current observational constraints.

The supercluster-void network V.

We analyze the distribution of Abell clusters of galaxies to study the regularity of the supercluster-void network. We apply a new method, the regularity periodogram, that is sensitive to the geometry of the location of clusters, and measure the regularity of the network. We find that the supercluster-void network resembles a cubic lattice over the entire volume considered (out to the distance of 350 h-1 Mpc). The distribution of clusters in rich superclusters is not isotropic: it is periodic along a cubic lattice approximately aligned with the supergalactic coordinates . This large-scale inhomogeneity does not contradict recent CMB data, but its theoretical explanation remains a challenge.

Current Cosmological Constraints from a 10 Parameter Cosmic Microwave Background Analysis

We compute the constraints on a standard 10 parameter cold dark matter (CDM) model from the most recent CMB data and other observations, exploring 30 million discrete models and two continuous parameters. Our parameters are the densities of CDM, baryons, neutrinos, vacuum energy and curvature, the reionization optical depth, and the normalization and tilt for both scalar and tensor fluctuations. Our strongest constraints are on spatial curvature, -0.24 < Ωk < 0.38, and CDM density, h2Ωcdm < 0.3, both at 95%. Including Type Ia supernova constraints gives a positive cosmological constant at high significance. We explore the robustness of our results to various assumptions. We find that three different data subsets give qualitatively consistent constraints. Some of the technical issues that have the largest impact are the inclusion of calibration errors, closed models, gravity waves, reionization, nucleosynthesis constraints, and ten-dimensional likelihood interpolation.