Related papers: Towards the Future of Supernova Cosmology
Type Ia Supernovae are in many aspects still enigmatic objects. Recent years have witnessed a bonanza of supernova observations. The increased samples from dedicated searches have allowed the statistical investigation of Type Ia Supernovae…
We present a comprehensive statistical analysis of the properties of Type Ia SN light curves in the near infrared using recent data from PAIRITEL and the literature. We construct a hierarchical Bayesian framework, incorporating several…
How to analyse Terabytes of photometric data, and extract knowledge on variable stars? How to detect variable phenomena? How to combine different photometric bands? Which algorithm to search for periods? How to characterize and classify the…
We introduce a statistical measure of the effective model complexity, called the Bayesian complexity. We demonstrate that the Bayesian complexity can be used to assess how many effective parameters a set of data can support and that it is a…
As commonly understood, the noise spectroscopy problem---characterizing the statistical properties of a noise process affecting a quantum system by measuring its response---is ill-posed. Ad-hoc solutions assume implicit structure which is…
The increased availability of observation data from engineering systems in operation poses the question of how to incorporate this data into finite element models. To this end, we propose a novel statistical construction of the finite…
We present the cosmological analysis of 752 photometrically-classified Type Ia Supernovae (SNe Ia) obtained from the full Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey, supplemented with host-galaxy spectroscopy from the…
In the era of large-scale photometric surveys, scalable and robust methods for classifying supernova (SN) populations are increasingly necessary. Often, spectroscopy is essential in addition to photometry to reliably classify SNe; however,…
We perform a Bayesian model selection analysis for different classes of phenomenological coupled scenarios of dark matter and dark energy with linear and non-linear interacting terms. We use a combination of some of the latest cosmological…
Cosmologists are facing the problem of the analysis of a huge quantity of data when observing the sky. The methods used in cosmology are, for the most of them, relying on astrophysical models, and thus, for the classification, they usually…
Bayesian Inference is a powerful approach to data analysis that is based almost entirely on probability theory. In this approach, probabilities model {\it uncertainty} rather than randomness or variability. This thesis is composed of a…
In this paper we give a pedagogical review of the recent observational results in cosmology from the study of type Ia supernovae and anisotropies in the cosmic microwave background. By providing consistent constrainst on the cosmological…
In this work, we present EDRIS (French for Distance Estimator for Incomplete Supernova Surveys), a cosmological inference framework tailored to reconstruct unbiased cosmological distances from type Ia supernovae light-curve parameters. This…
Bayesian approach, as a useful tool for quantifying uncertainties, has been widely used for solving inverse problems of partial differential equations (PDEs). One of the key difficulties for employing Bayesian approach for the issue is how…
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods…
For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of their free parameters. In this study, we review and compare…
A two-component fluid representing dark energy is studied. One of the components has a polytropic form, while the other has a barotropic form. Exact solutions are obtained and the cosmological parameters are constrained using supernova type…
The experimental problem of converting a measured binomial quantity, the fraction of events in a sample that pass a cut, into a physical binomial quantity, the fraction of events originating from a signal source, is described as a system of…
Strong gravitational lenses are unique cosmological probes. These produce multiple images of a single source. Whether a single galaxy, a group or a cluster, extracting cosmologically relevant information requires an accurate modeling of the…
In order to investigate non-uniformity in the luminosity evolution of Type Ia supernovae, we fit the lightcurves with a multi-parameter empirical model. The model provides a quantitative method of analyzing the lightcurves of Type I…