An Open Catalog for Supernova Data

By J. Guillochon, J. Parrent, Luke Zoltan Kelley, Raffaella Margutti. 2016

357 citations recorded by the source corpus.

We present the Open Supernova Catalog, an online collection of observations and metadata for presently 36,000+ supernovae and related candidates. The catalog is freely available on the web (https://sne.space), with its main interface having been designed to be a user-friendly, rapidly searchable table accessible on desktop and mobile devices. In addition to the primary catalog table containing supernova metadata, an individual page is generated for each supernova, which displays its available metadata, light curves, and spectra spanning X-ray to radio frequencies. The data presented in the catalog is automatically rebuilt on a daily basis and is constructed by parsing several dozen sources, including the data presented in the supernova literature and from secondary sources such as other web-based catalogs. Individual supernova data is stored in the hierarchical, human- and machine-readable JSON format, with the entirety of each supernova’s data being contained within a single JSON file bearing its name. The setup we present here, which is based on open-source software maintained via git repositories hosted on github, enables anyone to download the entirety of the supernova data set to their home computer in minutes, and to make contributions of their own data back to the catalog via git. As the supernova data set continues to grow, especially in the upcoming era of all-sky synoptic telescopes, which will increase the total number of events by orders of magnitude, we hope that the catalog we have designed will be a valuable tool for the community to analyze both historical and contemporary supernovae.

Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/571f315b120ea1df1af316f00d79497fece26760

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In Astronomy and Astrophysics

1. B. Metzger
2. E. Berger
3. A. Riess
4. D. Kasen
5. Ryan Chornock
6. W. Fong
7. A. Filippenko
8. S. Jha

In Nuclear and High Energy Physics

1. E. Berger
2. B. Metzger
3. Ryan Chornock
4. D. Kasen
5. J. Guillochon
6. A. Filippenko
7. E. Ramirez-Ruiz
8. A. Riess

Citations in the corpus

• The Combined Ultraviolet, Optical, and Near-infrared Light Curves of the Kilonova Associated with the Binary Neutron Star Merger GW170817: Unified Data Set, Analytic Models, and Physical Implications (2017, methodology): “We model the combined data set using the light curve fitting package MOSFiT (Guillochon et al. 2017a; Nicholl et al. 2017; Villar et al. 2017), which uses an ensemble-based Markov Chain Monte Carlo method to produce posterior predictions for the model parameters.”
• A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km s−1 Mpc−1 Uncertainty from the Hubble Space Telescope and the SH0ES Team (2021, methodology): “We obtain spectra directly from the Open Supernova Catalog25 (OSC; Guillochon et al. 2017), which aggregates data from numerous sources (including notable low-redshift SN Ia spectroscopy releases; e.g., Silverman et al. 2012; Blondin et al. 2012; Folatelli et al. 2013; Stahl et al. 2020b).”
• Sub-Chandrasekhar-mass White Dwarf Detonations Revisited (2017, methodology): “Since this difference persists for higher WD masses, where Sim 3 Much of the data used in this work was obtained through https://sne.space (Guillochon et al. 2017).”
• PS16dtm: A Tidal Disruption Event in a Narrow-line Seyfert 1 Galaxy (2017, background): “This paper greatly benefited from the Open Supernova Catalog (Guillochon et al. 2017).”
• Weighing Black Holes Using Tidal Disruption Events (2018, methodology): “To compare and contrast between different TDEs, it is important to fit the events consistently, and to this end in this paper we introduce a theoretical model for fitting TDEs as part of MOSFiT, the Modular Open Source Fitter for Transients (Guillochon et al. 2017).”
• The Magnetar Model for Type I Superluminous Supernovae. I. Bayesian Analysis of the Full Multicolor Light-curve Sample with MOSFiT (2017, methodology): “Here we present the first fits to data, using MOSFiT to model the full published sample of SLSNe, including all available photometry to model the multicolor light-curve evolution (as opposed to only the bolometric properties as in most previous studies).”