Combination of cluster number counts and two-point correlations: Validation on mock Dark Energy Survey

Chun Hao To, Elisabeth Krause, Eduardo Rozo, Hao Yi Wu, Daniel Gruen, Joseph Derose, Eli Rykoff, Risa H. Wechsler, Matthew Becker, Matteo Costanzi, Tim Eifler, Maria Elidaiana Da Silva Pereira, Nickolas Kokron

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy-cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.

Original languageEnglish (US)
Pages (from-to)4093-4111
Number of pages19
JournalMonthly Notices of the Royal Astronomical Society
Issue number3
StatePublished - Apr 1 2021


  • cosmological parameters
  • cosmology: theory
  • large-scale structure of Universe

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science


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