| Autor: |
Möller, A., Ruhlmann-Kleider, V., Leloup, C., Neveu, J., Palanque-Delabrouille, N., Rich, J., Carlberg, R., Lidman, C., Pritchet, C. |
| Rok vydání: |
2016 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| DOI: |
10.1088/1475-7516/2016/12/008 |
| Popis: |
In the era of large astronomical surveys, photometric classification of supernovae (SNe) has become an important research field due to limited spectroscopic resources for candidate follow-up and classification. In this work, we present a method to photometrically classify type Ia supernovae based on machine learning with redshifts that are derived from the SN light-curves. This method is implemented on real data from the SNLS deferred pipeline, a purely photometric pipeline that identifies SNe Ia at high-redshifts ($0.2Comment: v2: accepted to JCAP. v1: 27 pages, submitted to JCAP |
| Databáze: |
arXiv |
| Externí odkaz: |
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