1. The Dark Energy Survey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set
- Author
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DES Collaboration: T. M. C. Abbott, M. Acevedo, M. Aguena, A. Alarcon, S. Allam, O. Alves, A. Amon, F. Andrade-Oliveira, J. Annis, P. Armstrong, J. Asorey, S. Avila, D. Bacon, B. A. Bassett, K. Bechtol, P. H. Bernardinelli, G. M. Bernstein, E. Bertin, J. Blazek, S. Bocquet, D. Brooks, D. Brout, E. Buckley-Geer, D. L. Burke, H. Camacho, R. Camilleri, A. Campos, A. Carnero Rosell, D. Carollo, A. Carr, J. Carretero, F. J. Castander, R. Cawthon, C. Chang, R. Chen, A. Choi, C. Conselice, M. Costanzi, L. N. da Costa, M. Crocce, T. M. Davis, D. L. DePoy, S. Desai, H. T. Diehl, M. Dixon, S. Dodelson, P. Doel, C. Doux, A. Drlica-Wagner, J. Elvin-Poole, S. Everett, I. Ferrero, A. Ferté, B. Flaugher, R. J. Foley, P. Fosalba, D. Friedel, J. Frieman, C. Frohmaier, L. Galbany, J. García-Bellido, M. Gatti, E. Gaztanaga, G. Giannini, K. Glazebrook, O. Graur, D. Gruen, R. A. Gruendl, G. Gutierrez, W. G. Hartley, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. Huterer, B. Jain, D. J. James, N. Jeffrey, E. Kasai, L. Kelsey, S. Kent, R. Kessler, A. G. Kim, R. P. Kirshner, E. Kovacs, K. Kuehn, O. Lahav, J. Lee, S. Lee, G. F. Lewis, T. S. Li, C. Lidman, H. Lin, U. Malik, J. L. Marshall, P. Martini, J. Mena-Fernández, F. Menanteau, R. Miquel, J. J. Mohr, J. Mould, J. Muir, A. Möller, E. Neilsen, R. C. Nichol, P. Nugent, R. L. C. Ogando, A. Palmese, Y.-C. Pan, M. Paterno, W. J. Percival, M. E. S. Pereira, A. Pieres, A. A. Plazas Malagón, B. Popovic, A. Porredon, J. Prat, H. Qu, M. Raveri, M. Rodríguez-Monroy, A. K. Romer, A. Roodman, B. Rose, M. Sako, E. Sanchez, D. Sanchez Cid, M. Schubnell, D. Scolnic, I. Sevilla-Noarbe, P. Shah, J. Allyn. Smith, M. Smith, M. Soares-Santos, E. Suchyta, M. Sullivan, N. Suntzeff, M. E. C. Swanson, B. O. Sánchez, G. Tarle, G. Taylor, D. Thomas, C. To, M. Toy, M. A. Troxel, B. E. Tucker, D. L. Tucker, S. A. Uddin, M. Vincenzi, A. R. Walker, N. Weaverdyck, R. H. Wechsler, J. Weller, W. Wester, P. Wiseman, M. Yamamoto, F. Yuan, B. Zhang, and Y. Zhang
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Cosmology ,Type Ia supernovae ,Dark energy ,Dark matter ,Astrophysics ,QB460-466 - Abstract
We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω _M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q _0 < 0 in ΛCDM) with over 5 σ confidence. We find $({{\rm{\Omega }}}_{{\rm{M}}},w)=({0.264}_{-0.096}^{+0.074},-{0.80}_{-0.16}^{+0.14})$ in flat w CDM. For flat w _0 w _a CDM, we find $({{\rm{\Omega }}}_{{\rm{M}}},{w}_{0},{w}_{a})=({0.495}_{-0.043}^{+0.033},-{0.36}_{-0.30}^{+0.36},-{8.8}_{-4.5}^{+3.7})$ , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω _M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.
- Published
- 2024
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