The discovery and classification of 16 supernovae at high redshifts in ELAIS-S1 - the Stockholm VIMOS Supernova Survey II
J. Melinder, T. Dahlen, L. Mencia Trinchant, G. \"Ostlin, S. Mattila,, J. Sollerman, C. Fransson, M. Hayes, S. Nasoudi-Shoar

TL;DR
This paper reports the discovery and classification of 16 high-redshift supernovae from the Stockholm VIMOS Supernova Survey, demonstrating methods for detection, photometry, and type estimation, with implications for cosmology and star formation studies.
Contribution
The study introduces a comprehensive approach combining difference imaging, Bayesian classification, and simulations to detect and classify supernovae at high redshift.
Findings
Detected 16 supernovae with a mean redshift of 0.58
Achieved a low misclassification error rate of about 5%
Identified a potential pair instability supernova candidate
Abstract
Supernova surveys can be used to study a variety of subjects such as: (i) cosmology through type Ia supernovae (SNe), (ii) star-formation rates through core-collapse SNe, and (iii) supernova properties and their connection to host galaxy characteristics. The Stockholm VIMOS Supernova Survey (SVISS) is a multi-band imaging survey aiming to detect supernovae at redshift ~0.5 and derive thermonuclear and core-collapse supernova rates at high redshift. In this paper we present the supernovae discovered in the survey along with light curves and a photometric classification into thermonuclear and core-collapse types. To detect the supernovae in the VLT/VIMOS multi-epoch images, we used difference imaging and a combination of automatic and manual source detection to minimise the number of spurious detections. Photometry for the found variable sources was obtained and careful simulations were…
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Taxonomy
TopicsGamma-ray bursts and supernovae · Astrophysics and Cosmic Phenomena · Galaxies: Formation, Evolution, Phenomena
