Manuscript Topics

Random Matrix Theory (RMT) has evolved into a fundamental area of modern mathematics with deep connections to probability theory, mathematical physics, statistics, number theory, data science, and quantitative finance. Originally developed to model complex quantum systems, RMT now provides powerful tools for understanding large-dimensional phenomena across a wide range of disciplines.  
This special issue aims to bring together recent theoretical advances and novel applications of Random Matrix Theory, highlighting both rigorous mathematical developments and interdisciplinary contributions. The objective is to provide a comprehensive snapshot of current research trends and emerging directions within RMT.  
Submissions may address, but are not limited to, the following topics:

• Spectral theory of random matrices
• Universality principles and limit laws
• Wigner, Wishart, and sample covariance matrices
• Non-Hermitian random matrices
• Free probability and its connections to RMT
• Random matrix models in number theory
• Large deviations and concentration inequalities
• RMT in high-dimensional statistics and machine learning
• Applications in physics (quantum chaos, disordered systems)
• Applications in finance and econometrics
• Numerical methods and simulations for random matrices
• Emerging applications of RMT in data science and network theory

The special issue welcomes:

• Original research articles presenting new theoretical results
• Applied and interdisciplinary studies grounded in RMT
• Survey or review papers synthesizing recent developments
• Methodological papers with strong mathematical foundations

Instructions for authors
https://www.aimspress.com/math/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/