https://doi.org/10.1051/epjconf/202531913002
Core collaApse Supernovae parameTers estimatOR a novel software for data analysis
1 INAF, Osservatorio Astronomico di Roma, Via di Frascati 33, I-00078 Monteporzio Catone, Italy
2 Università Tor Vergata, Dipartimento di Fisica, Via della Ricerca Scientifica 1, I-00133 Rome, Italy
3 Dipartimento di Fisica “Ettore Pancini”, Università di Napoli Federico II, Via Cinthia 9, 80126 Naples, Italy
4 INAF - Osservatorio Astronomico di Capodimonte, Via Moiariello 16, I-80131 Naples, Italy
5 Universitá La Sapienza, Dipartimento di Fisica, Piazzale Aldo Moro 2, I-00185 Rome, Italy
6 INFN, Sezione di Roma, 00133 Rome, Italy
* e-mail: andreasimongini@inaf.it
Published online: 6 March 2025
In this poster we presented the novel open-access software for core collapse supernovae optical analysis: CASTOR. This software enables the reconstruction of synthetic light curves and spectra via a machine learning technique that allows to retrieve the complete parameter map of a supernova having as only input the multi-band photometry data. This approach is particularly significant in view of the Large Synoptic Survey Telescope (LSST), which will create a deficiency in spectroscopic data necessary to confirm the nature and fully characterize each event.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
