Precise Estimation of Cosmological Parameters Using a More Accurate Likelihood Function

TL;DR

This paper introduces a copula-based likelihood function for weak lensing data, improving the accuracy of cosmological parameter estimation by reducing systematic biases present in traditional Gaussian likelihood methods.

Contribution

The paper develops a Gaussian copula likelihood function for weak lensing convergence spectra, demonstrating its superiority over Gaussian likelihood in reducing systematic errors.

Findings

Gaussian copula likelihood reduces systematic bias in parameter estimation.

Traditional Gaussian likelihood introduces significant errors in dark energy parameter w.

Copula likelihood provides more accurate confidence regions for cosmological parameters.

Abstract

The estimation of cosmological parameters from a given data set requires a construction of a likelihood function which, in general, has a complicated functional form. We adopt a Gaussian copula and constructed a copula likelihood function for the convergence power spectrum from a weak lensing survey. We show that the parameter estimation based on the Gaussian likelihood erroneously introduces a systematic shift in the confidence region, in particular for a parameter of the dark energy equation of state w. Thus, the copula likelihood should be used in future cosmological observations.