Related papers: SimSIMS: Simulation-based Supernova Ia Model Selec…

We have analyzed multi-band light curves of 328 intermediate redshift (0.05 <= z < 0.24) type Ia supernovae (SNe Ia) observed by the Sloan Digital Sky Survey-II Supernova Survey (SDSS-II SN Survey). The multi-band light curves were…

Comparison of appropriate models to describe observational data is a fundamental task of science. The Bayesian model evidence, or marginal likelihood, is a computationally challenging, yet crucial, quantity to estimate to perform Bayesian…

There is growing evidence for the dependence of Type Ia supernova (SN Ia) luminosities on their environments. While the impact of this trend on estimating cosmological parameters is widely acknowledged, the origin of this correlation is…

The peculiar motions of galaxies are powerful cosmological probes that trace the growth of structures and the distribution of matter in the universe, providing a means to investigate the nature of dark energy and test gravity on…

Dust extinction and reddening greatly contribute to type Ia supernovae (SNe Ia) observed color and magnitude variations. The models used to describe the extinction probability density function (PDF) are often simplistic, which can…

Shifting the focus of Type Ia supernova (SN Ia) cosmology to the near-infrared (NIR) is a promising way to significantly reduce the systematic errors, as the strategy minimizes our reliance on the empirical width-luminosity relation and…

In the course of the Sloan Digital Sky Survey (SDSS-I), a large fraction of the surveyed area was observed more than once due to field tiling overlap, usually at different epochs. We utilize some of these data to perform a supernova (SN)…

We present bolometric light curves constructed from multi-wavelength photometry of Type Ia supernovae (SNe Ia) from the Carnegie Supernova Project and the CfA Supernova Group, using near-infrared observations to provide robust constraints…

We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R $\sim100$) data. The goal of SNIascore is fully automated classification of SNe Ia with…

Type Ia supernovae (SNe Ia) are considered standardizable candles and are therefore important probes of the universe's expansion history and cosmic distances. In comparison to the optical and IR photometric observations, NIR light curves of…

Type Ia Supernova(SN Ia) are a powerful, albeit not completely understood, tool for cosmology. Gaps in our understanding of their progenitors and detailed physics can lead to systematic errors in the cosmological distances they measure. We…

Bayesian model reduction provides an efficient approach for comparing the performance of all nested sub-models of a model, without re-evaluating any of these sub-models. Until now, Bayesian model reduction has been applied mainly in the…

We apply the hierarchical probabilistic SED model BayeSN to analyse a sample of 475 SNe Ia (0.015 < z < 0.4) from Foundation, DES3YR and PS1MD to investigate the properties of dust in their host galaxies. We jointly infer the dust law $R_V$…

Stochastic Ising machines, sIMs, are highly promising accelerators for optimization and sampling of computational problems that can be formulated as an Ising model. Here we investigate the computational advantage of sIM for simulations of…

Using data from the Sloan Digital Sky Supernova Survey-II, we measure the rate of Type Ia Supernovae (SNe Ia) as a function of galaxy properties at intermediate redshift. A sample of 342 SNe Ia with 0.05<z<0.25 is constructed. Using…

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…

We present an analysis of the host galaxy dependencies of Type Ia Supernovae (SNe Ia) from the full three year sample of the SDSS-II Supernova Survey. We rediscover, to high significance, the strong correlation between host galaxy typeand…

High-dimensional variable selection, with many more covariates than observations, is widely documented in standard regression models, but there are still few tools to address it in non-linear mixed-effects models where data are collected…

Precision cosmology with Type Ia supernovae (SNe Ia) requires robust quality control of large, heterogeneous datasets. Current data processing often relies on manual, subjective rejection of photometric data, a practice that is not scalable…

We use type-Ia supernovae (SNe Ia) discovered by the SDSS-II SN Survey to search for dependencies between SN Ia properties and the projected distance to the host galaxy center, using the distance as a proxy for local galaxy properties…