The cosmic web through the lens of graph entropy

TL;DR

This paper introduces graph entropy as a new scalar measure to quantify the cosmic web's connectivity, distinguishing between different cosmic structures and influenced by survey parameters, applicable to both simulations and observations.

Contribution

It proposes a novel application of graph entropy to cosmology, providing a simple, computable statistic to analyze the cosmic web's structure and its dependence on survey conditions.

Findings

Graph entropy ranges between 1.5 and 3.2 bits.

Entropy distinguishes between clustered and random points.

Number density significantly affects entropy values.

Abstract

We explore the information theory entropy of a graph as a scalar to quantify the cosmic web. We find entropy values in the range between 1.5 and 3.2 bits. We argue that this entropy can be used as a discrete analogue of scalars used to quantify the connectivity in continuous density fields. After showing that the entropy clearly distinguishes between clustered and random points, we use simulations to gauge the influence of survey geometry, cosmic variance, redshift space distortions, redshift evolution, cosmological parameters and spatial number density. Cosmic variance shows the least important influence while changes from the survey geometry, redshift space distortions, cosmological parameters and redshift evolution produce larger changes on the order of $10^{-2}$ bits. The largest influence on the graph entropy comes from changes in the number density of clustered points. As the number density decreases, and the cosmic web is less pronounced, the entropy can diminish up to 0.2 bits. The graph entropy is simple to compute and can be applied both to simulations and observational data from large galaxy redshift surveys; it is a new statistic that can be used in a complementary way to other kinds of topological or clustering measurements.