Marco Tarzia, Sorbonne University, France

Sparse Random Matrices: Cavity Approach and Anderson Localization



1. Brief overview to sparse random matrices

2. The resolvent and its properties

The statistics of the resolvent and its connections to eigenfunctions, spectral statistics, unitary dynamics, etc.

3. Self-consistent cavity approach

4. Anderson localization

Understanding Anderson localization and its impact on transport, eigenfunctions, and spectral statistics.

5. Anderson localization on the Bethe lattice

Critical properties

A few numerical methods to solve the cavity equations

Relationship with directed polymers in random media

Other Applications

Lévy matrices, Erdos-Renyi graphs, links with Many-Body Localization, etc.