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

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