From mixing time of Markov chains to Tracy-Widom law of inhomogeneous random matrices
报告人： 刘党政（中国科学技术大学）
时间：2025-10-27 14:00-16:30
地点：智华楼四元厅-225
Abstract:
Consider symmetric and Hermitian random matrices whose entries are independent random variables with an arbitrary variance pattern. Under a novel Short-to-Long Mixing condition, which is sharp in the sense that it precludes a corrected shift at the spectral edge, we establish GOE/GUE edge universality for such inhomogeneous random matrices that may be sparse or
far beyond the mean-field setting of classical random matrix theory. This condition effectively reduces the universality problem to verifying the mixing properties of Markov chains defined by the variance profile matrix. This talk is based on joint work with Guangyi Zou.
About the Speaker:
刘党政, 中国科学技术大学数学科学学院副教授，2010年北京大学数学科学学院博士毕业，研究兴趣随机矩阵理论与应用。
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