Published January 2, 2025 | Version v1
Dataset Open

Representation learning for time-domain high-energy astrophysics: Transient candidates catalog of X-ray flares and dips

Creators

  • 1. ROR icon Stanford University
  • 2. ROR icon Center for Astrophysics Harvard & Smithsonian
  • 3. INAF
  • 4. ROR icon University of Chinese Academy of Sciences

Description

Description

The transient candidates catalog of X-ray flares and dips compiled in 'Representation learning for time-domain high-energy astrophysics: Discovery of extragalactic Fast X-ray Transient XRT 200515' by Dillmann et al. (2024): https://doi.org/10.1093/mnras/stae2808

Citation

Please make sure to cite the paper https://doi.org/10.1093/mnras/stae2808 if you make use of this material.

Files

CATALOG_PAPER_SUBMISSION_MNRAS_FINAL.csv

Files (62.3 MB)

Name Size Download all
md5:a8e06ee9379a8b46a8da779153f7a63c
2.5 MB Preview Download
md5:5726d06cc3f1b4a00ac8ea4bb3a2c77a
2.0 MB Preview Download
md5:e1ae5b49e9a1147b6a691576eca25127
57.8 MB Preview Download

Additional details

Related works

Is supplement to
Journal article: 10.1093/mnras/stae2808 (DOI)
Preprint: arXiv:2412.01150 (arXiv)

Dates

Accepted
2024-12

Software

Repository URL
https://github.com/StevenDillmann/ml-xraytransients-mnras
Programming language
Python
Development Status
Active