Related papers: Single-epoch supernova classification with deep co…

Type Ia Supernovae (SNe Ia) spectra are compared regarding the coefficient of the largest wavelet scale in their decomposition. Two distinct subgroups were identified and their occurrence is discussed in light of use of SNe Ia as…

In this work, we propose the use of Kernel Principal Component Analysis (KPCA) combined with k = 1 nearest neighbour algorithm (1NN) as a framework for supernovae (SNe) photometric classification. The classification is entirely based on…

Type Ia supernovae (SNe Ia) play a crucial role as standardizable candles in measurements of the Hubble constant and dark energy. Increasing evidence points towards multiple possible explosion channels as the origin of normal SNe Ia, with…

We present optical light curves, redshifts, and classifications for 365 spectroscopically confirmed Type Ia supernovae (SNe Ia) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. We detail improvements to the PS1 SN photometry,…

Spectroscopic and photometric evidence indicates that Type Ia supernovae (SNe Ia) are the thermonuclear explosions of accreting white dwarfs. However, the progenitor binary systems and hydrodynamical models for SNe Ia are still…

Type Ia Supernovae (SNe Ia) are powerful standardizable candles for constraining cosmological models and provided the first evidence of the accelerated expansion of the universe. Their precision derives from empirical correlations, now…

In the epoch of precise and accurate cosmology, cross-confirmation using a variety of cosmographic methods is paramount to circumvent systematic uncertainties. Owing to progenitor histories and explosion physics differing from those of Type…

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…

We present the snapshot distance method (SDM), a modern incarnation of a proposed technique for estimating the distance to a Type Ia supernova (SN Ia) from minimal observations. Our method, which has become possible owing to recent work in…

We describe a procedure for accurately determining luminosity distances to Type Ia supernovae (SNe Ia) without knowledge of redshift. This procedure, which may be used as an extension of any of the various distance determination methods…

Type Ia supernovae (SNe Ia) are among the most precise cosmological distance indicators used to study the expansion history of the Universe. The vast increase of SN Ia data due to large-scale astrophysical surveys has led to the discovery…

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…

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…

The $Euclid$ mission will provide first-of-its-kind coverage in the near-infrared over deep (three fields, $\sim$10-20 square degrees each) and wide ($\sim$10000 square degrees) fields. While the survey is not designed to discover…

Strongly lensed type Ia supernovae (SNe Ia) provide a unique cosmological probe to address the Hubble tension problem in cosmology. In addition to the sensitivity of the time delays to the value of the Hubble constant, the transient and…

Type Ia supernovae (SNe Ia) are essential tools for addressing key cosmic questions, including the Hubble tension and the nature of dark energy. Modern surveys are predominantly photometry-based, making the construction of a clean…

We present {\tt deepSIP} (deep learning of Supernova Ia Parameters), a software package for measuring the phase and -- for the first time using deep learning -- the light-curve shape of a Type Ia supernova (SN~Ia) from an optical spectrum.…

A quantitative data-driven comparison among supernovae (SNe) based on their spectral time series combined with multi-band photometry is presented. We use an unsupervised Random Forest algorithm as a metric on a set of 82 well-documented SNe…

We present a semi-supervised method for photometric supernova typing. Our approach is to first use the nonlinear dimension reduction technique diffusion map to detect structure in a database of supernova light curves and subsequently employ…

Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses…