Related papers: ESC Supernova spectroscopy of non-ESC targets

The program package SME (Spectroscopy Made Easy), designed to perform an analysis of stellar spectra using spectral fitting techniques, was updated due to adding new functions (isotopic and hyperfine splittins) in VALD and including grids…

Along the life of the IUE project, a large archive with spectral data has been generated, requiring automated classification methods to be analyzed in an objective form. Previous automated classification methods used with IUE spectra were…

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…

Anomaly detection aims to distinguish observations that are rare and different from the majority. While most existing algorithms assume that instances are i.i.d., in many practical scenarios, links describing instance-to-instance…

We present spectroscopy from the first three seasons of the Dark Energy Survey Supernova Program (DES-SN). We describe the supernova spectroscopic program in full: strategy, observations, data reduction, and classification. We have…

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…

The letter presents 25 discovered supernova candidates from SDSS-DR7 with our dedicated method, called Sample Decrease, and 10 of them were confirmed by other research groups, and listed in this letter. Another 15 are first discovered…

In the current era of time-domain astronomy, it is increasingly important to have rigorous, data driven models for classifying transients, including supernovae. We present the first application of Principal Component Analysis to the spectra…

Innovation in the ground and space-based instruments has taken us into a new age of spectroscopy, in which a large amount of stellar content is becoming available. So, automatic classification of stellar spectra became subjective in recent…

We present a result of X-ray supernovae (SNe) survey using the Swift satellite public archive. An automatic searching program was designed to search X-ray SNe among all of the Swift archival observations between November 2004 and February…

While the spectroscopic classification scheme for Stripped envelope supernovae (SESNe) is clear, and we know that they originate from massive stars that lost some or all their envelopes of Hydrogen and Helium, the photometric evolution of…

In this Letter we present evidence for a spectral sequence among Type Ia supernovae (SNe Ia). The sequence is based on the systematic variation of several features seen in the near-maximum light spectrum. This sequence is analogous to the…

We analyse photometric data of nine supernovae (SNe) in filters V, R and I obtained during observational campaigns at the OAUNI site in 2016, 2017 and 2023. The calibrated magnitudes of the observed SNe were compared with their respective…

In the era of large-scale photometric surveys, scalable and robust methods for classifying supernova (SN) populations are increasingly necessary. Often, spectroscopy is essential in addition to photometry to reliably classify SNe; however,…

Using the largest spectroscopic dataset of stripped-envelope core-collapse supernovae (stripped SNe), we present a systematic investigation of spectral properties of Type IIb SNe (SNe IIb), Type Ib SNe (SNe Ib), and Type Ic SNe (SNe Ic).…

Over the past years type Ia supernovae (SNe Ia) have become a major tool to determine the expansion history of the Universe, and considerable attention has been given to, both, observations and models of these events. However, until now,…

Context. The SDSS-II Supernova Survey, conducted between 2005 and 2007, was designed to detect a large number of Type Ia supernovae (SNe Ia) around z~0.2, the redshift "gap" between low-z and high-z SN searches. The survey has provided…

High resolution galaxy spectra contain much information about galactic physics, but the high dimensionality of these spectra makes it difficult to fully utilize the information they contain. We apply variational autoencoders (VAEs), a…

Using the ESO-Sculptor galaxy redshift survey data (ESS), we have extensively tested the Principal Components Analysis (PCA) method to perform the spectral classification of galaxies with $z \la$ 0.5. This method allows us to classify all…

We study supernova (SN) classification using the machine learning method of the Recurrent Neural Network (RNN) in the Chinese Space Station Survey Telescope Ultra-Deep Field (CSST-UDF) photometric survey, and explore the improvement of the…