论文标题
年轻的超新星实验数据版本1（YSE DR1）：1975年超新星的光曲线和光度分类
The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae
论文作者
论文摘要
We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multi-color Pan-STARRS1 (PS1) griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host-galaxy associations, redshifts, spectroscopic/photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries以及从年轻和快速升高的超新星（SNE）到持续一年多的瞬变的观察结果，红移分布达到Z〜0.5。我们介绍了YSE的幅度和体积受限调查的相对SN速率，这些速率与未确定性调查的估计不确定性中先前发表的值一致。我们将YSE和ZTF数据组合在一起，并创建多调查SN模拟来训练parsnip和Superraenn光度分类算法；在验证472个光谱分类的YSE YSE DR1 SNE上的欧洲防风草分类器时，我们在三个SN类（SNE IA，II，IB/IC）中达到了82％的精度，并且在两个SN类（SNE IA，Core-Colle-Collapse SNE）的精度上达到了90％的精度。我们的分类器在SNE IA上的表现特别出色，具有较高（> 90％）的个人完整性和纯度，这将有助于为宇宙学构建锚定光度SNE IA样本。然后，我们使用我们的光度分类器来表征1483 SNE的光度样本，标记1048（〜71％）SNE IA，339（〜23％）SNE II和96（〜6％）SNE IB/IC。 YSE DR1为建立发现，异常检测和分类算法，进行宇宙学分析，了解红色和稀有瞬态的性质，探索潮汐破坏事件和核变异性以及为即将到来的Vera C. Rubin C. Rubin C. Rubin Perservatory对空间和时间的调查做准备。
We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multi-color Pan-STARRS1 (PS1) griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host-galaxy associations, redshifts, spectroscopic/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 multi-survey 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.
