{"paper":{"title":"The first Hubble diagram and cosmological constraints using superluminous supernova","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.HE"],"primary_cat":"astro-ph.CO","authors_text":"A. A. Plazas Malag\\'on, A. Carnero Rosell, A. G. Kim, A. K. Romer, A. M\\\"oller, A. Roodman, A. R. Walker, B. E. Tucker (for the DES Collaboration), B. Flaugher, B. P. Thomas, C. B. D'Andrea, C. Frohmaier, C. Inserra, C. Lidman, C. P. Guti\\'errez, C. R. Angus, D. A. Finley, D. Brooks, D. Brout, D. Carollo, D. Gruen, D. J. James, D. L. Burke, D. L. Hollowood, D. L. Tucker, D. Scolnic, D. Thomas, D. W. Gerdes, E. Bertin, E. Gaztanaga, E. Krause, E. Macaulay, E. Sanchez, E. Suchyta, E. Swann, F. J. Castander, F. Menanteau, F. Sobreira, G. F. Lewis, G. Gutierrez, G. Tarle, H. T. Diehl, I. Sevilla-Noarbe, J. Annis, J. Asorey, J. Calcino, J. Carretero, J. Frieman, J. Garcia-Bellido, J. Gschwend, J. K. Hoormann, J. L. Marshall, K. Glazebrook, K. Honscheid, K. Kuehn, L. Galbany, M. A. G. Maia, M. Carrasco Kind, M. E. C. Swanson, M. Lima, M. Pursiainen, M. Sako, M. Schubnell, M. Smith, M. Soares-Santos, M. Sullivan, M. Vicenzi, N. Kuropatkin, P. Fosalba, P. J. Brown, P. Martini, P. Wiseman, R. A. Gruendl, R. Cawthon, R. C. Nichol, R. Kessler, R. Miquel, R. Sharp, S. Avila, S. Desai, S. R. Hinton, S. Serrano, T. F. Eifler, T. Giannantonio, T. M. C. Abbott, T. M. Davis, T. S. Li, V. Scarpine, V. Vikram, Y.-C. Pan, Y. Zhang","submitted_at":"2020-04-25T19:39:47Z","abstract_excerpt":"We present the first Hubble diagram of superluminous supernovae (SLSNe) out to a redshift of two, together with constraints on the matter density, $\\Omega_{\\rm M}$, and the dark energy equation-of-state parameter, $w(\\equiv p/\\rho)$. We build a sample of 20 cosmologically useful SLSNe~I based on light curve and spectroscopy quality cuts. We confirm the robustness of the peak decline SLSN~I standardization relation with a larger dataset and improved fitting techniques than previous works. We then solve the SLSN model based on the above standardisation via minimisation of the $\\chi^2$ computed f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.12218","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2004.12218/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}