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Astrophysics Source Code Library

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Searching for codes credited to 'Qu, Helen'

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[ascl:2503.037] SCONE: Supernova Classification with a Convolutional Neural Network

SCONE (Supernova Classification with a Convolutional Neural Network) classifies supernovae (SNe) by type using multi-band photometry data (lightcurves) using a convolutional neural networks. SCONE takes in supernova (SN) photometry data in the format output by SNANA simulations, separated into two types of files: metadata and observation data. Photometric data is pre-processed via 2D Gaussian process regression, which smooths over irregular sampling rates between filters and also allows SCONE to be independent of the filter set on which it was trained.