The dark energy survey 5-yr photometrically identified type Ia supernovae

Möller, A.; Smith, M.; Sako, M.; Sullivan, M.; Vincenzi, M.; Wiseman, P.; Armstrong, P.; Asorey, J.; Brout, D.; Carollo, D.; Davis, T. M.; Frohmaier, C.; Galbany, L.; Glazebrook, K.; Kelsey, L.; Kessler, R.; Lewis, G. F.; Lidman, C.; Malik, U.; Nichol, R. C.; Scolnic, D.; Tucker, B. E.; Abbott, T. M. C.; Aguena, M.; Allam, S.; Annis, J.; Bertin, E.; Bocquet, S.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Castander, F. J.; Conselice, C.; Costanzi, M.; Crocce, M.; da Costa, L. N.; De Vicente, J.; Desai, S.; Diehl, H. T.; Doel, P.; Everett, S.; Ferrero, I.; Finley, D. A.; Flaugher, B.; Friedel, D.; Frieman, J.; García-Bellido, J.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Herner, K.; Hinton, S. R.; Hollowood, D. L.; Honscheid, K.; James, D. J.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; March, M.; Marshall, J. L.; Menanteau, F.; Miquel, R.; Morgan, R.; Palmese, A.; Paz-Chinchón, F.; Pieres, A.; Plazas Malagón, A. A.; Romer, A. K.; Roodman, A.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Serrano, S.; Sevilla-Noarbe, I.; Suchyta, E.; Tarle, G.; Thomas, D.; To, C.; Varga, T. N.

doi:10.1093/mnras/stac1691

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

The dark energy survey 5-yr photometrically identified type Ia supernovae

MPS-Authors

/persons/resource/persons221802

Varga, T. N.
Optical and Interpretative Astronomy, MPI for Extraterrestrial Physics, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Möller, A., Smith, M., Sako, M., Sullivan, M., Vincenzi, M., Wiseman, P., et al. (2022). The dark energy survey 5-yr photometrically identified type Ia supernovae. Monthly Notices of the Royal Astronomical Society, 514(4), 5159-5177. doi:10.1093/mnras/stac1691.

Cite as: https://hdl.handle.net/21.11116/0000-000C-2BA7-8

Abstract

As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multiband light curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNovatrained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1863 SNe Ia from which we select 1484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Survey of Space and Time.