Related papers: A Bayesian Approach to Classifying Supernovae With…

The ratio of Bayesian evidences is a popular tool in cosmology to compare different models. There are however several issues with this method: Bayes' ratio depends on the prior even in the limit of non-informative priors, and Jeffrey's…

Bayesian nonparametric models offer a flexible and powerful framework for statistical model selection, enabling the adaptation of model complexity to the intricacies of diverse datasets. This survey intends to delve into the significance of…

Advancements in optical quantum technologies have been enabled by the generation, manipulation, and characterization of light, with identification based on its photon statistics. However, characterizing light and its sources through single…

We apply Bayesian methods to study the sensitivity to neutrino masses of a Galactic supernova neutrino signal. Our procedure makes use of the full statistics of events and is remarkably independent of astrophysical assumptions. Present…

Despite decades of dedicated efforts there are still basic questions to answer with regard to Supernova progenitor systems and explosion mechanisms. In particular, in the last years a number of exceptionally bright objects and extremely…

The Zwicky Transient Facility (ZTF) was expected to detect more than one strong gravitationally-lensed supernova (glSN) per year, but only one event was identified in the first four years of the survey. This work investigates selection…

The large sky localization regions offered by the gravitational-wave interferometers require efficient follow-up of the many counterpart candidates identified by the wide field-of-view telescopes. Given the restricted telescope time, the…

The use of advanced statistical analysis tools is crucial in order to improve cosmological parameter estimates via removal of systematic errors and identification of previously unaccounted for cosmological signals. Here we demonstrate the…

We present a new empirical method for fitting multicolor light curves of Type Ia supernovae. Our method combines elements from two widely used techniques in the literature: the delta_m15 template fitting method and the Multicolor…

The present study is the first of a series of three papers where we characterise the type II supernovae (SNe~II) from the Carnegie Supernova Project-I to understand their diversity in terms of progenitor and explosion properties. In this…

In this talk, I argue that the method of analysing the m-z data of Type Ia Supernovae (SNe Ia) by assuming exotic energy densities with strange equations of state is misleading and the reasonable remaining option is to make a…

Type Ia supernovae are key tools for measuring distances on a cosmic scale. They are generally thought to be the thermonuclear explosion of an accreting white dwarf in a close binary system. The nature of the mass donor is still uncertain.…

We develop a new framework for use in exploring Type Ia Supernova (SN Ia) spectra. Combining Principal Component Analysis (PCA) and Partial Least Square analysis (PLS) we are able to establish correlations between the Principal Components…

Since type Ia Supernovae (SNe) explode in galaxies, they can, in principle, be used as the same tracer of the large-scale structure as their hosts to measure baryon acoustic oscillations (BAOs). To realize this, one must obtain a dense…

Nanopore sensors detect the substructure of individual molecules from modulations in an ion current as molecules pass through them. In this work, we present the classification of features in the substructure as a case study to illustrate…

A method is developed for fitting theoretically predicted astronomical spectra to an observed spectrum. Using a hierarchical Bayesian principle, the method takes both systematic and statistical measurement errors into account, which has not…

Central to model selection is a trade-off between performing a good fit and low model complexity: A model of higher complexity should only be favoured over a simpler model if it provides significantly better fits. In Bayesian terms, this…

Due to their great flexibility, nonparametric Bayes methods have proven to be a valuable tool for discovering complicated patterns in data. The term "nonparametric Bayes" suggests that these methods inherit model-free operating…

We present a sample of 485 photometrically identified Type Ia supernova candidates mined from the first three years of data of the CFHT SuperNova Legacy Survey (SNLS). The images were submitted to a deferred processing independent of the…

Continuous-variable (CV) photonic states are of increasing interest in quantum information science, bolstered by features such as deterministic resource state generation and error correction via bosonic codes. Data-efficient…