Maximum eigenvalue of symmetric random matrices with dependent heavy tailed entries

Arijit Chakrabarty; Rajat Subhra Hazra; Parthanil Roy

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arXiv · 1309.1407

Maximum eigenvalue of symmetric random matrices with dependent heavy tailed entries

Arijit Chakrabarty·Rajat Subhra Hazra·Parthanil Roy

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Abstract

This paper deals with symmetric random matrices whose upper diagonal entries are obtained from a linear random field with heavy tailed noise. It is shown that the maximum eigenvalue and the spectral radius of such a random matrix with dependent entries converge to the Frechét distribution after appropriate scaling. This extends a seminal result of Soshnikov(2004) when the tail index is strictly less than one.

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BibTeX RIS

Arijit Chakrabarty, Rajat Subhra Hazra, Parthanil Roy. 2014-06-11. Maximum eigenvalue of symmetric random matrices with dependent heavy tailed entries. https://arxiv.org/abs/1309.1407

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