Towards structures in the flux landscape at large number of moduli

TL;DR

This paper explores the structure of the string flux landscape with many moduli, showing that certain analytic features emerge at large moduli numbers and are influenced by sampling bias, using the ADK model.

Contribution

It demonstrates the feasibility of sampling at large moduli in the ADK landscape and identifies analytic structures that are insensitive to UV parameter distributions.

Findings

Structures emerge only at large number of moduli

Analytic structures are insensitive to UV parameter distribution

Sampling bias influences observed structures

Abstract

Sampling string flux vacua enables us to study structures in the string landscape. Here we demonstrate that sampling at large number of moduli is possible for the simplified landscape model of ADK. Using dimensional reduction, we identify analytic structures in these samples. In this example, we find that these structures are rather insensitive to the underlying distribution of UV parameters but they emerge only at large number of moduli and they can be attributed to sampling bias.