EiffL/btsbot

---
description: 'This is the production version of the BTSbot training set, limited to

public (programid=1) ZTF alerts.

Original codebase: https://github.com/nabeelre/BTSbot

' homepage: https://zenodo.org/records/10839691 version: 1.0.0 citation: "% % ACKNOWLEDGEMENTS\n% % Based on the Acknowledgements in Rehemtulla et
\ al. (2024). We suggest including a variant of the following in your acknowledgements:\n
% A great number of people have contributed to BTS and BTS scanning over the years.
\ We thank the following people who have saved 10 or more sources to internal BTS
\ catalogs on Fritz as of October 2023: Ivan Altunin, Raphael Baer-Way, Pallas A.
\ Beddow, Ofek Bengiat, Joshua S. Bloom, Ola Bochenek, Emma Born, Kate Bostow, Victoria
\ Mei Brendel, Rachel Bruch, Vidhi Chander, Matthew Chu, Elma Chuang, Aishwarya
\ Dahiwale, Asia deGraw, Dmitry Duev, Kingsley Ehrich, Eli Gendreau-Distler, Nachiket
\ Girish, Xander Hall, KRyan Hinds, Ido Irani, Cooper Jacobus, Connor Jennings,
\ Joel Johansson, Snehaa Ganesh Kumar, Michael May, William Meynardie, Shaunak Modak,
\ Kishore Patra, Neil Pichay, Sophia Risin, Yashvi Sharma, Gabrielle Stewart, Nora
\ Linn Strotjohann, James Sunseri, Edgar Vidal, Jacob Wise, Abel Yagubyan, Yoomee
\ Zeng, and Erez A. Zimmerman.\n% \n% We also thank Jakob Nordin for discussions
\ relating to AMPEL.\n% \n% The material contained in this document is based upon
\ work supported by a National Aeronautics and Space Administration (NASA) grant
\ or cooperative agreement. Any opinions, findings, conclusions, or recommendations
\ expressed in this material are those of the author and do not necessarily reflect
\ the views of NASA. This work was supported through a NASA grant awarded to the
\ Illinois/NASA Space Grant Consortium. This research was supported in part through
\ the computational resources and staff contributions provided for the Quest high
\ performance computing facility at Northwestern University which is jointly supported
\ by the Office of the Provost, the Office for Research, and Northwestern University
\ Information Technology.\n% \n% Based on observations obtained with the Samuel
\ Oschin Telescope 48-inch and the 60-inch Telescope at the Palomar Observatory
\ as part of the Zwicky Transient Facility project. ZTF is supported by the National
\ Science Foundation under Grants No. AST-1440341 and AST-2034437 and a collaboration
\ including current partners Caltech, IPAC, the Oskar Klein Center at Stockholm
\ University, the University of Maryland, University of California, Berkeley , the
\ University of Wisconsin at Milwaukee, University of Warwick, Ruhr University,
\ Cornell University, Northwestern University and Drexel University. Operations
\ are conducted by COO, IPAC, and UW.\n% \n% CITATION\n@misc{rehemtulla2024zwicky,\n
\ title={The Zwicky Transient Facility Bright Transient Survey. III. $\texttt{BTSbot}$:
\ Automated Identification and Follow-up of Bright Transients with Deep Learning},
\ \n author={Nabeel Rehemtulla and Adam A. Miller and Theophile Jegou Du Laz
\ and Michael W. Coughlin and Christoffer Fremling and Daniel A. Perley and Yu-Jing
\ Qin and Jesper Sollerman and Ashish A. Mahabal and Russ R. Laher and Reed Riddle
\ and Ben Rusholme and Shrinivas R. Kulkarni},\n year={2024},\n eprint={2401.15167},\n
\ archivePrefix={arXiv},\n primaryClass={astro-ph.IM}\n}\n\n@ARTICLE{Rehemtulla2024BTWBot,\n
\ author = {{Rehemtulla}, Nabeel and {Miller}, Adam A. and {Jegou Du Laz},
\ Theophile and {Coughlin}, Michael W. and {Fremling}, Christoffer and {Perley},
\ Daniel A. and {Qin}, Yu-Jing and {Sollerman}, Jesper and {Mahabal}, Ashish A.
\ and {Laher}, Russ R. and {Riddle}, Reed and {Rusholme}, Ben and {Kulkarni}, Shrinivas
\ R.},\n title = "{The Zwicky Transient Facility Bright Transient Survey.
\ III. BTSbot: Automated Identification and Follow-up of Bright Transients with
\ Deep Learning}",\n journal = {\apj},\n keywords = {Time domain astronomy,
\ Sky surveys, Supernovae, Convolutional neural networks, 2109, 1464, 1668, 1938,
\ Astrophysics - Instrumentation and Methods for Astrophysics},\n year =
\ 2024,\n month = sep,\n volume = {972},\n number = {1},\n
\ eid = {7},\n pages = {7},\n doi = {10.3847/1538-4357/ad5666},\n
archivePrefix = {arXiv},\n eprint = {2401.15167},\n primaryClass = {astro-ph.IM},\n
\ adsurl = {https://ui.adsabs.harvard.edu/abs/2024ApJ...972....7R},\n
\ adsnote = {Provided by the SAO/NASA Astrophysics Data System}\n}\n" ---

# Btsbot Dataset

CC BY 4.0

This is the production version of the BTSbot training set, limited to public (programid=1) ZTF alerts.

Original codebase: https://github.com/nabeelre/BTSbot

% % ACKNOWLEDGEMENTS

% % Based on the Acknowledgements in Rehemtulla et al. (2024). We suggest including a variant of the following in your acknowledgements: % A great number of people have contributed to BTS and BTS scanning over the years. We thank the following people who have saved 10 or more sources to internal BTS catalogs on Fritz as of October 2023: Ivan Altunin, Raphael Baer-Way, Pallas A. Beddow, Ofek Bengiat, Joshua S. Bloom, Ola Bochenek, Emma Born, Kate Bostow, Victoria Mei Brendel, Rachel Bruch, Vidhi Chander, Matthew Chu, Elma Chuang, Aishwarya Dahiwale, Asia deGraw, Dmitry Duev, Kingsley Ehrich, Eli Gendreau-Distler, Nachiket Girish, Xander Hall, KRyan Hinds, Ido Irani, Cooper Jacobus, Connor Jennings, Joel Johansson, Snehaa Ganesh Kumar, Michael May, William Meynardie, Shaunak Modak, Kishore Patra, Neil Pichay, Sophia Risin, Yashvi Sharma, Gabrielle Stewart, Nora Linn Strotjohann, James Sunseri, Edgar Vidal, Jacob Wise, Abel Yagubyan, Yoomee Zeng, and Erez A. Zimmerman. % % We also thank Jakob Nordin for discussions relating to AMPEL. % % The material contained in this document is based upon work supported by a National Aeronautics and Space Administration (NASA) grant or cooperative agreement. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author and do not necessarily reflect the views of NASA. This work was supported through a NASA grant awarded to the Illinois/NASA Space Grant Consortium. This research was supported in part through the computational resources and staff contributions provided for the Quest high performance computing facility at Northwestern University which is jointly supported by the Office of the Provost, the Office for Research, and Northwestern University Information Technology. % % Based on observations obtained with the Samuel Oschin Telescope 48-inch and the 60-inch Telescope at the Palomar Observatory as part of the Zwicky Transient Facility project. ZTF is supported by the National Science Foundation under Grants No. AST-1440341 and AST-2034437 and a collaboration including current partners Caltech, IPAC, the Oskar Klein Center at Stockholm University, the University of Maryland, University of California, Berkeley , the University of Wisconsin at Milwaukee, University of Warwick, Ruhr University, Cornell University, Northwestern University and Drexel University. Operations are conducted by COO, IPAC, and UW. % % CITATION @misc{rehemtulla2024zwicky, title={The Zwicky Transient Facility Bright Transient Survey. III. $\texttt{BTSbot}$: Automated Identification and Follow-up of Bright Transients with Deep Learning}, author={Nabeel Rehemtulla and Adam A. Miller and Theophile Jegou Du Laz and Michael W. Coughlin and Christoffer Fremling and Daniel A. Perley and Yu-Jing Qin and Jesper Sollerman and Ashish A. Mahabal and Russ R. Laher and Reed Riddle and Ben Rusholme and Shrinivas R. Kulkarni}, year={2024}, eprint={2401.15167}, archivePrefix={arXiv}, primaryClass={astro-ph.IM} }

@ARTICLE{Rehemtulla2024BTWBot, author = {{Rehemtulla}, Nabeel and {Miller}, Adam A. and {Jegou Du Laz}, Theophile and {Coughlin}, Michael W. and {Fremling}, Christoffer and {Perley}, Daniel A. and {Qin}, Yu-Jing and {Sollerman}, Jesper and {Mahabal}, Ashish A. and {Laher}, Russ R. and {Riddle}, Reed and {Rusholme}, Ben and {Kulkarni}, Shrinivas R.}, title = "{The Zwicky Transient Facility Bright Transient Survey. III. BTSbot: Automated Identification and Follow-up of Bright Transients with Deep Learning}", journal = {\apj}, keywords = {Time domain astronomy, Sky surveys, Supernovae, Convolutional neural networks, 2109, 1464, 1668, 1938, Astrophysics - Instrumentation and Methods for Astrophysics}, year = 2024, month = sep, volume = {972}, number = {1}, eid = {7}, pages = {7}, doi = {10.3847/1538-4357/ad5666}, archivePrefix = {arXiv}, eprint = {2401.15167}, primaryClass = {astro-ph.IM}, adsurl = {https://ui.adsabs.harvard.edu/abs/2024ApJ...972....7R}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }