Related papers: A systematic reclassification of type IIn supernov…

Early-phase Type Ia supernovae (SNe Ia), especially those with luminosity enhancement within the first few days of explosions ("early-excess SNe Ia"), play an irreplaceable role in addressing the long-standing progenitor and explosion issue…

The ever-growing sample of observed supernovae enhances our capacity for comprehensive supernova population studies, providing a richer dataset for understanding the diverse characteristics of Type Ia supernovae and possibly that of their…

Attempts to reveal the spectroscopic diversity of Type Ia supernovae (SNe Ia) have led to subclassification schemes such as the Branch system, which classifies SNe Ia into four categories: core normal (CN), broad line (BL), cool (CL), and…

While many studies have shown a correlation between properties of the light curves of Type Ia SN (SNe Ia) and properties of their host galaxies, it remains unclear what is driving these correlations. We introduce a new direct method to…

With the upcoming Vera C.~Rubin Observatory Legacy Survey of Space and Time (LSST), it is expected that only $\sim 0.1\%$ of all transients will be classified spectroscopically. To conduct studies of rare transients, such as Type I…

All Type IIn supernovae (SNe IIn) show narrow hydrogen emission lines in their spectra. Apart from this common feature, they demonstrate very broad diversity in brightness, duration, and morphology of their light curves, which indicates…

We investigate the identification of hydrogen-poor superluminous supernovae (SLSNe I) using a photometric analysis, without including an arbitrary magnitude threshold. We assemble a homogeneous sample of previously classified SLSNe I from…

We present the spectroscopy from 5254 galaxies that hosted supernovae (SNe) or other transient events in the Sloan Digital Sky Survey II (SDSS-II). Obtained during SDSS-I, SDSS-II, and the Baryon Oscillation Spectroscopic Survey (BOSS),…

Hydrogen-poor superluminous supernovae (SLSNe) are among the most energetic explosions in the universe, reaching luminosities up to 100 times greater than those of normal supernovae. Detailed spectral analysis hold the potential to reveal…

We constructed 70 SuperNova IDentification (SNID; Blondin & Tonry 2007) supernova (SN) templates using 640 spectra of stripped-envelope core-collapse SNe (SESNe) published by Modjaz et al. (2014). Fifty-six SN templates which are…

We present ultraviolet/optical/near-infrared observations and modeling of Type II supernovae (SNe II) whose early-time ($\delta t < 2$ days) spectra show transient, narrow emission lines from shock ionization of confined ($r < 10^{15}$ cm)…

We present the second and final release of optical spectroscopy of Type Ia Supernovae (SNe Ia) obtained during the first and second phases of the Carnegie Supernova Project (CSP-I and CSP-II). The newly released data consist of 148 spectra…

We present the largest and most homogeneous collection of near-infrared (NIR) spectra of Type Ia supernovae (SNe Ia): 339 spectra of 98 individual SNe obtained as part of the Carnegie Supernova Project-II. These spectra, obtained with the…

Type Ibn supernovae (SNe) are characterized by narrow helium (He I) lines from photons produced by the unshocked circumstellar material (CSM). About 80 SNe Ibn have been discovered to date, and only a handful have extensive observational…

We describe a research program to improve the understanding of Type Ia Supernovae (SNe Ia) by modeling and observing near infrared (NIR) spectra of these events. The NIR between 0.9 microns and 2.5 microns is optimal for examining certain…

We report near infrared (NIR) spectroscopic observations of twelve ``Branch-normal'' Type Ia supernovae (SNe Ia) which cover the wavelength region from 0.8-2.5 microns. Our sample more than doubles the number of SNe Ia with published NIR…

This paper presents spectroscopy of supernovae discovered in the first season of the Sloan Digital Sky Survey-II Supernova Survey. This program searches for and measures multi-band light curves of supernovae in the redshift range z = 0.05 -…

We present a simple and well defined prescription to compare absorption lines in supernova (SN) spectra with lists of transitions drawn from the National Institute of Standards and Technology (NIST) database. The method is designed to be…

In the upcoming decade large astronomical surveys will discover millions of transients raising unprecedented data challenges in the process. Only the use of the machine learning algorithms can process such large data volumes. Most of the…

We present a novel method of classifying Type Ia supernovae using convolutional neural networks, a neural network framework typically used for image recognition. Our model is trained on photometric information only, eliminating the need for…