Random Matrix Theory and Networks

Virtual Workshop
7 - 18 June 2021

Random matrix theory was initiated about 80 years ago as a new mathematical tool to study many-body systems, such as, heavy nuclei or atoms. Standard models of random matrix theory rely on independent and identically distributed matrix entries. Recent years, new random matrix models have been developed that incorporate features of real-world systems, such as, network architecture, modularity, and recurrent motifs. These network models appear in the study of complex systems, such as, financial markets, signalling networks, neural networks, or ecosystems. Potential topics of the workshop are the analysis of systemic risk in financial markets, the stability of ecosystems, or applications of random matrix theory in statistical inference, to name a few. The aim of the workshop is to bring together researchers working on random matrix theory and complex systems.

• Applications of random matrices and network theory in ecology, neural networks or economics 
• Statistical inference and spectral algorithms
• Dynamics of complex systems
• Mathematical aspects of spectral graph theory