BPS Spectra, Barcodes and Walls

TL;DR

This paper applies persistent homology, a topological data analysis technique, to study the topological features of BPS spectra in supersymmetric theories, revealing insights into wall-crossing phenomena, string compactifications, and modularity.

Contribution

It introduces a novel application of persistent homology to analyze BPS spectra and their topological properties in various supersymmetric models and string theory contexts.

Findings

Topological features change across walls of marginal stability.

Distribution of BPS invariants exhibits distinct topological signatures.

Connections between persistent homology and modularity are explored.

Abstract

BPS spectra give important insights into the non-perturbative regimes of supersymmetric theories. Often from the study of BPS states one can infer properties of the geometrical or algebraic structures underlying such theories. In this paper we approach this problem from the perspective of persistent homology. Persistent homology is at the base of topological data analysis, which aims at extracting topological features out of a set of points. We use these techniques to investigate the topological properties which characterize the spectra of several supersymmetric models in field and string theory. We discuss how such features change upon crossing walls of marginal stability in a few examples. Then we look at the topological properties of the distributions of BPS invariants in string compactifications on compact threefolds, used to engineer black hole microstates. Finally we discuss the interplay between persistent homology and modularity by considering certain number theoretical functions used to count dyons in string compactifications and by studying equivariant elliptic genera in the context of the Mathieu moonshine.