Published June 24, 2024 | Version v2
Dataset Open

Data for "Superphot+: Realtime Fitting and Classification of Supernova Light Curves"

  • 1. ROR icon Center for Astrophysics Harvard & Smithsonian
  • 2. ROR icon The NSF AI Institute for Artificial Intelligence and Fundamental Interactions
  • 3. ROR icon Space Telescope Science Institute
  • 4. Steward Observatory, University of Arizona
  • 5. DiRAC Institute and the Department of Astronomy, University of Washington
  • 6. McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University

Description

This is the dataset and static code base associated with the paper: "Superphot+: Real-Time Fitting and Classification of Supernova Light Curves". The contents are as follows:

  • superphot-plus-v0.0.7.tar: Superphot+ code base downloaded at time of paper submission. Static copy of the Github repo: https://github.com/VTDA-Group/superphot-plus -- This version corresponds to commit: 956b5d555f58800c01a74b3977e0a3b5476ea9cd and tag v0.0.8.
  • dataset_spec_pruned.csv: Spectroscopic dataset pruned according to Table 1 of the paper.
  • dataset_phot_final.csv: Photometric dataset (without spectroscopic labels) pruned according to Section 2 of the paper. Label and probability columns are values from the ALeRCE-SN classifier.
  • model_0.pt: One of the 10 (redshift-independent) LightGBM models trained for 5-way SN classification.
  • model_0.yaml: Configuration file associated with model_0.pt.
  • model_z_0.pt: Same as model_0.pt, but trained using redshift information.
  • model_z_0.yaml: Configuration file associated with model_z_0.pt.
  • early_phase_classifier_0.pt: Same as model_0.pt, but trained only using early-phase light curve features. Tailored for realtime classification.
  • early_phase_classifier_0.yaml: Configuration file for early_phase_classifier_0.pt.
  • probs_concat.csv: Spectroscopic set's classification results without using redshift information.
  • probs_z_concat.csv: Spectroscopic set's classification results using redshift information.
  • probs_photometric_v2.mrt: Superphot+'s probabilities for the photometric set without using redshift information. Updated to correct for missing IAU names.

Files

dataset_phot_final.csv

Files (147.9 MB)

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Additional details

Related works

Is described by
Preprint: arXiv:2403.07975 (arXiv)

Software

Repository URL
https://github.com/VTDA-Group/superphot-plus
Programming language
Python
Development Status
Active