Related papers: Fast cosmological parameter estimation using neura…
Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and…
Optimal power spectrum estimation on the largest angular scales of the cosmic microwave background relies on the Quadratic Maximum Likelihood (QML) estimator. Existing public implementations, however, each address only a subset of the…
The accelerating expansion of the universe is the most surprising cosmological discovery in many decades. In this short review, we briefly summarize theories for the origin of cosmic acceleration and the observational methods being used to…
In this work we present the results of the study of the cosmic microwave background TT power spectrum through auto-encoders in which the latent variables are the cosmological parameters. This method was trained and calibrated using a…
Observations of large scale structure (LSS) and the Cosmic Microwave Background (CMB) each place separate constraints on the values of cosmological parameters. We calculate a joint likelihood based on various CMB experiments and the IRAS…
We report an investigation of cosmological parameters based on the measurements of anisotropy in the cosmic microwave background radiation (CMB) made by ACBAR. We use the ACBAR data in concert with other recent CMB measurements to derive…
Recently, BICEP2 collaboration has released their results on the measurements of the CMB polarizations. In the framework of the $\Lambda$CDM with a power law form of the scalar primordial power spectrum, this new measurement on the B-mode…
We describe our methodology for comparing the WMAP measurements of the cosmic microwave background (CMB) and other complementary data sets to theoretical models. The unprecedented quality of the WMAP data, and the tight constraints on…
Over the last decade, measurements of the CMB anisotropy has spearheaded the remarkable transition of cosmology into a precision science. However, addressing the systematic effects in the increasingly sensitive, high resolution, `full' sky…
We use an iterative generalized least squares map-making algorithm, in conjunction with Monte Carlo techniques, to obtain estimates of the angular power spectrum from cosmic microwave background (CMB) maps. This is achieved by…
We examine the use of a novel variant of Physics-Informed Neural Networks to predict cosmological parameters from recent supernovae and baryon acoustic oscillations (BAO) datasets. Our machine learning framework generates uncertainty…
We compare and combine likelihood functions of the cosmological parameters Omega_m, h and sigma_8, from peculiar velocities, CMB and type Ia supernovae. These three data sets directly probe the mass in the Universe, without the need to…
The lensing effect of the cosmic microwave background (CMB) is a powerful tool for our study of the distribution of matter in the universe. Currently, the quadratic estimator (EQ) method, which is widely used to reconstruct lensing…
The WMAP 7-year temperature maps have been re-analized to extract a CMB map and CMB power spectrum with reduced contamination by astrophysical foregrounds and noise. The method used is based on linear combinations of WMAP data and…
The peculiar motion of an observer with respect to the CMB rest frame induces an apparent deflection of the observed CMB photons, {\it i.e.} aberration, and a shift in their frequency, {\it i.e.} Doppler effect. Both effects distort the…
Bayesian statistics and Markov Chain Monte Carlo (MCMC) algorithms have found their place in the field of Cosmology. They have become important mathematical and numerical tools, especially in parameter estimation and model comparison. In…
We present a novel Bayesian inference tool that uses a neural network to parameterise efficient Markov Chain Monte-Carlo (MCMC) proposals. The target distribution is first transformed into a diagonal, unit variance Gaussian by a series of…
We use two subsets of 2000 and 1000 Quijote simulations to build two power spectrum emulators, allowing for fast computations of the non-linear matter power spectrum. The first emulator is built in terms of seven cosmological parameters:…
The Cosmic Microwave Background Radiation (CMBR) holds information about almost all the fundamental cosmological parameters, and by performing a likelihood analysis of high precision CMBR fluctuation data, these parameters can be inferred.…
Cosmological constraints are usually derived under the assumption of a $6$ parameters $\Lambda$-CDM theoretical framework or simple one-parameter extensions. In this paper we present, for the first time, cosmological constraints in a…