| Issue |
EPJ Web Conf.
Volume 319, 2025
RICAP-24, 9th Roma International Conference on Astroparticle Physics
|
|
|---|---|---|
| Article Number | 13002 | |
| Number of page(s) | 2 | |
| Section | Poster | |
| DOI | https://doi.org/10.1051/epjconf/202531913002 | |
| Published online | 06 March 2025 | |
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
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