Related papers: Optimal constraint on g_NL from CMB
We consider the problem of estimating the parameter $\fnl$ in the standard local model of primordial CMB non-Gaussianity. We determine the properties of maximum likelihood (ML) estimates and show that the problem is not the typical ML…
We apply a new method to measure primordial non-Gaussianity, using the cross-correlation between galaxy surveys and the CMB lensing signal to measure galaxy bias on very large scales, where local-type primordial non-Gaussianity predicts a…
We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the Lambda-cdm best-fit solution with respect to previously-released results, and the construction of…
A new method to constrain the local non-linear coupling parameter fNL based on a fast wavelet decomposition is presented. Using a multiresolution wavelet adapted to the HEALPix pixelization, we have developed a method that is 10^2 times…
In this work we present constraints on different shapes of primordial non-Gaussianity using the Wilkinson Microwave Anisotropy Probe (WMAP) 7-year data and the spherical Mexican hat wavelet fnl estimator including the linear term…
We develop a method to constrain the level of non-Gaussianity of density perturbations when the 3-point function is of the "equilateral" type. Departures from Gaussianity of this form are produced by single field models such as ghost or DBI…
We systematically analyze the primordial non-Gaussianity estimator used by the Wilkinson Microwave Anisotropy Probe (WMAP) science team with the basic ideas of estimation theory in order to see if the limited Cosmic Microwave Background…
One of the most powerful cosmological datasets when it comes to constraining neutrino masses is represented by galaxy power spectrum measurements, $P_{gg}(k)$. The constraining power of $P_{gg}(k)$ is however severely limited by…
We perform a Fisher matrix calculation of the predicted uncertainties on estimates of the cosmic string tension Gmu from upcoming observational data (namely, cosmic microwave background power spectra from the Planck satellite and an…
Structural matrix-variate observations routinely arise in diverse fields such as multi-layer network analysis and brain image clustering. While data of this type have been extensively investigated with fruitful outcomes being delivered, the…
We discuss the problems of applying Maximum Likelihood methods to the CMB and how one can make it both efficient and optimal. The solution is a generalised eigenvalue problem that allows virtually no loss of information about the parameter…
The cosmic microwave background (CMB) temperature bispectrum is currently the most precise tool for constraining primordial non-Gaussianity (NG). The Planck temperature data tightly constrain the amplitude of local-type NG: $f_{\rm NL}^{\rm…
Cosmological parameter estimation is traditionally performed in the Bayesian context. By adopting an "agnostic" statistical point of view, we show the interest of confronting the Bayesian results to a frequentist approach based on…
We present a multi-level solver for drawing constrained Gaussian realizations or finding the maximum likelihood estimate of the CMB sky, given noisy sky maps with partial sky coverage. The method converges substantially faster than existing…
Focusing on the well motivated aperture mass statistics $\Map$, we study the possibility of constraining cosmological parameters using future space based SNAP class weak lensing missions. Using completely analytical results we construct the…
We present cosmological parameter constraints as estimated using the Bayesian BeyondPlanck (BP) analysis framework. This method supports seamless end-to-end error propagation from raw time-ordered data to final cosmological parameters. As a…
When constraining the primordial non-Gaussianity parameter f_NL with cosmic microwave background anisotropy maps, the bias resulting from the covariance between primordial non-Gaussianity and secondary non-Gaussianities to the estimator of…
We use quadratic maximum-likelihood (QML) estimators to constrain models with Gaussian but statistically anisotropic Cosmic Microwave Background (CMB) fluctuations, using CMB maps with realistic sky-coverage and instrumental noise. This…
We reconstruct the Cosmic Microwave Background (CMB) lensing potential on the latest Planck CMB PR4 (NPIPE) maps, which include slightly more data than the 2018 PR3 release, and implement quadratic estimators using more optimal filtering.…
We determine the best-fit values and confidence limits for dynamical dark energy parameters together with other cosmological parameters on the basis of different datasets which include WMAP9 or Planck-2013 results on CMB anisotropy, BAO…