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arxiv: 2406.05048 · v2 · pith:5KSXQUTSnew · submitted 2024-06-07 · 🌌 astro-ph.CO

The Dark Energy Survey Supernova Program: Investigating Beyond-ΛCDM

R. Camilleri , T. M. Davis , M. Vincenzi , P. Shah , J. Frieman , R. Kessler , P. Armstrong , D. Brout
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A. Carr R. Chen L. Galbany K. Glazebrook S. R. Hinton J. Lee C. Lidman A. M\"oller B. Popovic H. Qu M. Sako D. Scolnic M. Smith M. Sullivan B. O. S\'anchez G. Taylor M. Toy P. Wiseman T. M. C. Abbott M. Aguena S. Allam O. Alves J. Annis S. Avila D. Bacon E. Bertin S. Bocquet D. Brooks D. L. Burke A. Carnero Rosell J. Carretero F. J. Castander L. N. da Costa M. E. S. Pereira S. Desai H. T. Diehl P. Doel C. Doux S. Everett I. Ferrero B. Flaugher P. Fosalba J. Garc\'ia-Bellido M. Gatti E. Gaztanaga G. Giannini D. Gruen D. L. Hollowood K. Honscheid D. J. James K. Kuehn O. Lahav S. Lee J. L. Marshall J. Mena-Fern\'andez R. Miquel J. Muir J. Myles R. L. C. Ogando A. Pieres A. A. Plazas Malag\'on A. Porredon M. Rodriguez-Monroy E. Sanchez D. Sanchez Cid M. Schubnell I. Sevilla-Noarbe E. Suchyta M. E. C. Swanson G. Tarle A. R. Walker N. Weaverdyck (DES Collaboration)
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keywords cosmologicalmodelsbiasnon-standardsupernovaapproximateassumptionsdark
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We report constraints on a variety of non-standard cosmological models using the full 5-year photometrically-classified type Ia supernova sample from the Dark Energy Survey (DES-SN5YR). Both Akaike Information Criterion (AIC) and Suspiciousness calculations find no strong evidence for or against any of the non-standard models we explore. When combined with external probes, the AIC and Suspiciousness agree that 11 of the 15 models are moderately preferred over Flat-$\Lambda$CDM suggesting additional flexibility in our cosmological models may be required beyond the cosmological constant. We also provide a detailed discussion of all cosmological assumptions that appear in the DES supernova cosmology analyses, evaluate their impact, and provide guidance on using the DES Hubble diagram to test non-standard models. An approximate cosmological model, used to perform bias corrections to the data holds the biggest potential for harbouring cosmological assumptions. We show that even if the approximate cosmological model is constructed with a matter density shifted by $\Delta\Omega_m\sim0.2$ from the true matter density of a simulated data set the bias that arises is sub-dominant to statistical uncertainties. Nevertheless, we present and validate a methodology to reduce this bias.

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