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

The Legacy Survey of Space and Time (LSST) will revolutionize Time Domain Astronomy by detecting millions of transients. In particular, it is expected to increment the number of type Ia supernovae (SNIa) of a factor of 100 compared to…

We examine the light curve parameters of 97 nearby Type Ia supernovae in the ultraviolet and optical using observations from the Swift Ultra-Violet/Optical Telescope. Our light curve models used a linear combinations of templates, which…

We compare models of supernova (SN) neutrino emission with the Kamiokande II data on SN 1987A using the Bayesian approach. These models are taken from simulations and are representative of current 1D SN models. We find that models with a…

We compare models for Type Ia supernova (SN Ia) light curves and spectra with an extensive set of observations. The models come from a recent survey of 44 two-dimensional delayed-detonation models computed by Kasen, Roepke & Woosley (2009),…

We present Sequential Neural Likelihood (SNL), a new method for Bayesian inference in simulator models, where the likelihood is intractable but simulating data from the model is possible. SNL trains an autoregressive flow on simulated data…

State-space models (SSMs) are powerful probabilistic tools for modeling time-varying systems with latent dynamics. Inference in SSMs involves the estimation of latent states and parameters. In this work, we focus on parameter inference,…

(Abridged) Precision cosmology with Type Ia supernovae (SNe Ia) makes use of the fact that SN Ia luminosities depend on their light-curve shapes and colours. Using Supernova Legacy Survey (SNLS) and other data, we show that there is an…

We have performed Monte Carlo simulations of type Ia supernova (SN Ia) surveys to quantify their efficiency in discovering peculiar overluminous and underluminous SNe Ia. We determined how the type of survey (magnitude-limited,…

We present a cosmological analysis of the Lick Observatory Supernova Search (LOSS) Type Ia supernova (SN Ia) photometry sample introduced by Ganeshalingam et al. (2010). These SNe provide an effective anchor point to estimate cosmological…

We present a new solution to the problem of classifying Type Ia supernovae from their light curves alone given a spectroscopically confirmed but biased training set, circumventing the need to obtain an observationally expensive unbiased…

In analogy to compressed sensing, which allows sample-efficient signal reconstruction given prior knowledge of its sparsity in frequency domain, we propose to utilize policy simplicity (Occam's Razor) as a prior to enable sample-efficient…

Type Ia supernovae (SNe Ia) constitute an historical probe to derive cosmological parameters through the fit of the Hubble-Lema\^itre diagram, i.e. SN Ia distance modulus versus their redshift. In the era of precision cosmology, realistic…

To reduce systematic uncertainties in Type Ia supernova (SN Ia) cosmology, the host galaxy dust law shape parameter, $R_V$, must be accurately constrained. We thus develop a computationally-inexpensive pipeline, Bird-Snack, to rapidly infer…

Type Ia supernovae (SNe Ia) have been essential for probing the nature of dark energy; however, most SN analyses rely on the same low-redshift sample, which may lead to shared systematics. In a companion paper (arXiv:2508.10878), we…

The task of parametric model selection is cast in terms of a statistical mechanics on the space of probability distributions. Using the techniques of low-temperature expansions, we arrive at a systematic series for the Bayesian posterior…

We use Monte Carlo simulations of the Calan/Tololo photographic supernova survey to show that a simple model of the survey's selection effects accounts for the observed distributions of recession velocity, apparent magnitude, angular…

The use of Type Ia Supernovae (SNe Ia) as cosmological tools has motivated significant effort to: understand what drives the intrinsic scatter of SN Ia distance modulus residuals after standardization, characterize the distribution of SN Ia…

Using current observations forecast type Ia supernovae (SNe Ia) Joint Lightcurve Analysis (JLA) and baryon acoustic oscillations (BAO), in this paper we investigate six bidimensional dark energy parameterisations in order to explore which…

We compare two Type Ia supernova (SN Ia) samples that are drawn from a spectroscopically confirmed SN Ia sample: a host-selected sample in which SNe Ia are restricted to those that have a spectroscopic redshift from the host; and a broader,…

We investigate the evidence/flexibility (i.e., "Occam") paradigm and demonstrate the theoretical and empirical consistency of Bayesian evidence for the task of determining an appropriate generative model for network data. This model…