DeepZipper. II. Searching for lensed supernovae in Dark Energy Survey Data with deep learning

R. Morgan, B. Nord*, K. Bechtol, A. Möller, W. G. Hartley, S. Birrer, S. J. González, M. Martinez, R. A. Gruendl, E. J. Buckley-Geer, A. J. Shajib, A. Carnero Rosell, C. Lidman, T. Collett, T. M. C. Abbott, M. Aguena, F. Andrade-Oliveira, J. Annis, D. Bacon, S. BocquetD. Brooks, D. L. Burke, M. Carrasco Kind, J. Carretero, F. J. Castander, C. Conselice, L. N. da Costa, M. Costanzi, J. De Vicente, S. Desai, P. Doel, S. Everett, I. Ferrero, B. Flaugher, D. Friedel, J. Frieman, J. García-Bellido, E. Gaztanaga, D. Gruen, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, K. Kuehn, N. Kuropatkin, O. Lahav, M. Lima, F. Menanteau, R. Miquel, A. Palmese, F. Paz-Chinchón, M. E. S. Pereira, A. Pieres, A. A. Plazas Malagón, J. Prat, M. Rodriguez-Monroy, A. K. Romer, A. Roodman, E. Sanchez, V. Scarpine, I. Sevilla-Noarbe, M. Smith, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, T. N. Varga

*Corresponding author for this work

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Abstract

Gravitationally lensed supernovae (LSNe) are important probes of cosmic expansion, but they remain rare and difficult to find. Current cosmic surveys likely contain 5-10 LSNe in total while next-generation experiments are expected to contain several hundred to a few thousand of these systems. We search for these systems in observed Dark Energy Survey (DES) five year SN fields—10 3 sq. deg. regions of sky imaged in the griz bands approximately every six nights over five years. To perform the search, we utilize the DeepZipper approach: a multi-branch deep learning architecture trained on image-level simulations of LSNe that simultaneously learns spatial and temporal relationships from time series of images. We find that our method obtains an LSN recall of 61.13% and a false-positive rate of 0.02% on the DES SN field data. DeepZipper selected 2245 candidates from a magnitude-limited (m i < 22.5) catalog of 3,459,186 systems. We employ human visual inspection to review systems selected by the network and find three candidate LSNe in the DES SN fields.

Original languageEnglish
Article number19
Pages (from-to)1-14
Number of pages14
JournalAstrophysical Journal
Volume943
Issue number1
DOIs
Publication statusPublished - 20 Jan 2023

Bibliographical note

Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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