Maximum Likelihood Random Galaxy Catalogues and Luminosity Function Estimation

TL;DR

This paper introduces a maximum likelihood algorithm for creating unclustered galaxy catalogues that accurately incorporate galaxy evolution and large-scale structure effects, improving clustering analyses.

Contribution

The paper presents a novel ML-based method for generating random galaxy catalogues that jointly estimate luminosity functions and overdensities, surpassing traditional approaches.

Findings

The new ML method accurately estimates luminosity functions considering evolution.

Generated catalogues better reflect the true galaxy distribution and properties.

The approach generalizes the 1/Vmax method by incorporating density corrections.

Abstract

We present a new algorithm to generate a random (unclustered) version of an magnitude limited observational galaxy redshift catalogue. It takes into account both galaxy evolution and the perturbing effects of large scale structure. The key to the algorithm is a maximum likelihood (ML) method for jointly estimating both the luminosity function (LF) and the overdensity as a function of redshift. The random catalogue algorithm then works by cloning each galaxy in the original catalogue, with the number of clones determined by the ML solution. Each of these cloned galaxies is then assigned a random redshift uniformly distributed over the accessible survey volume, taking account of the survey magnitude limit(s) and, optionally, both luminosity and number density evolution. The resulting random catalogues, which can be employed in traditional estimates of galaxy clustering, make fuller use of the information available in the original catalogue and hence are superior to simply fitting a functional form to the observed redshift distribution. They are particularly well suited to studies of the dependence of galaxy clustering on galaxy properties as each galaxy in the random catalogue has the same list of attributes as measured for the galaxies in the genuine catalogue. The derivation of the joint overdensity and LF estimator reveals the limit in which the ML estimate reduces to the standard 1/Vmax LF estimate, namely when one makes the prior assumption that the are no fluctuations in the radial overdensity. The new ML estimator can be viewed as a generalization of the 1/Vmax estimate in which Vmax is replaced by a density corrected Vdc,max.