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20182022
most citedExistence of the free energy for heavy-tailed spin glasses

1 citations · 1 across the 1 of their papers we have counts for

collaborators

6 papers

math.PR20221 cited

Existence of the free energy for heavy-tailed spin glasses

Aukosh Jagannath, Patrick Lopatto

We study the free energy of a mean-field spin glass whose coupling distribution has power law tails. Under the assumption that the couplings have infinite variance and finite mean,…

math.PR2020

Eigenvector Statistics of Lévy Matrices

Amol Aggarwal, Patrick Lopatto, Jake Marcinek

We analyze statistics for eigenvector entries of heavy-tailed random symmetric matrices (also called Lévy matrices) whose associated eigenvalues are sufficiently small. We show tha…

math.PR2019

Universality of the least singular value for the sum of random matrices

Ziliang Che, Patrick Lopatto

We consider the least singular value of , where are independent Haar-distributed unitary matrices and are deterministic diagonal matrices. Un…

math.PR2019

Tail bounds for gaps between eigenvalues of sparse random matrices

Patrick Lopatto, Kyle Luh

We prove the first eigenvalue repulsion bound for sparse random matrices. As a consequence, we show that these matrices have simple spectrum, improving the range of sparsity and er…

math.PR2018

Comparison theorem for some extremal eigenvalue statistics

Benjamin Landon, Patrick Lopatto, Jake Marcinek

We introduce a method for the comparison of some extremal eigenvalue statistics of random matrices. For example, it allows one to compare the maximal eigenvalue gap in the bulk of…

math.PR2018

GOE Statistics for Levy Matrices

Amol Aggarwal, Patrick Lopatto, Horng-Tzer Yau

In this paper we establish eigenvector delocalization and bulk universality for Lévy matrices, which are real, symmetric, random matrices whose upper tria…