The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

Abstract

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE’s magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (∼71%) SNe Ia, 339 (∼23%) SNe II, and 96 (∼6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.

First Impressions: Early-time Classification of Supernovae Using Host-galaxy Information and Shallow Learning

“…Simulations suggest that this survey at full operation will discover 2 SNe within 3 days of explosion per month, when they can be classified with ∼82% accuracy using our method. We aim to retrain our classifier using simulated YSE light curves and adapt the network using the light curves consolidated as part of the First Data Release for YSE (Aleo et al 2023). We predict that the increased wavelength coverage and higher cadence achieved by augmenting ZTF light curves with YSE observations will result in superior early classification results to the ones shown in this work.…”

Environmental Dependence of Type Ia Supernovae in Low-redshift Galaxy Clusters

“…Our cluster samples included 10 SNe with Pan-STARRS1 (Tonry et al 2012) photometric data from the Young Supernova Experiment (Jones et al 2021) first light-curve data release (Aleo et al 2023). We included these gri photometry in our analysis (but we did not include the z-band).…”

Flight of the Bumblebee: the Early Excess Flux of Type Ia Supernova 2023bee Revealed by TESS, Swift, and Young Supernova Experiment Observations

“…We also observed SN 2023bee in griz with DECam at the CTIO 4 m Blanco telescope (DePoy et al 2008;Flaugher et al 2015) and the PanSTARRS1 (PS1) telescope (Chambers et al 2016) as part of the Young Supernova Experiment (Jones et al 2021;Aleo et al 2023). Standard reductions for the DECam and PS1 images are performed by the NOIRLab community pipeline (Valdes et al 2014) and the PS1 image Image Processing Pipeline, respectively (Magnier et al 2020a(Magnier et al , 2020b(Magnier et al , 2020cWaters et al 2020).…”