Persistent Homology and String Vacua

Understand

We use methods from topological data analysis to study the topological features of certain distributions of string vacua.

• Topological data analysis is a multi-scale approach used to analyze the topological features of a dataset by identifying which homological characteristics persist over a long range of scales.
• We apply these techniques in several contexts.
• We analyze N=2 vacua by focusing on certain distributions of Calabi-Yau varieties and Landau-Ginzburg models.