Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

Type: Article

Publication Date: 2021-02-22

Citations: 27

DOI: https://doi.org/10.1093/mnras/stab526

Abstract

Beyond-$\Lambda$CDM physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analyzed assuming $\Lambda$CDM. We present an application of internal consistency tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of $\Lambda$CDM. We find that the DES Y1 data have an acceptable goodness of fit to $\Lambda$CDM, with a probability of finding a worse fit by random chance of ${p = 0.046}$. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5%) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the $p$-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.

Locations

  • Monthly Notices of the Royal Astronomical Society - View - PDF
  • UCL Discovery (University College London) - View - PDF
  • arXiv (Cornell University) - View - PDF
  • Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad) - View - PDF
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) - View - PDF
  • Duo Research Archive (University of Oslo) - View - PDF
  • ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) - View - PDF
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) - View - PDF
  • HAL (Le Centre pour la Communication Scientifique Directe) - View - PDF
  • ANU Open Research (Australian National University) - View - PDF
  • DataCite API - View

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