In the first part of this thesis we consider large random matrices with arbitrary expectation and a general slowly decaying correlation among its entries. We prove universality of the local eigenvalue statistics and optimal local laws for the resolvent in the bulk and edge regime. The main novel tool is a systematic diagrammatic control of a multivariate cumulant expansion. In the second part we consider Wigner-type matrices and show that at any cusp singularity of the limiting eigenvalue distribution the local eigenvalue statistics are universal and form a Pearcey process. Since the density of states typically exhibits only square root or cubic root cusp singularities, our work complements previous results on the bulk and edge universal...
We consider real symmetric or complex hermitian random matrices with correlated entries. We prove lo...
We consider N × N Hermitian Wigner random matrices H where the probability density for each matrix e...
We consider the local eigenvalue distribution of large self-adjoint N×N random matrices H=H∗ with ce...
In the first part of this thesis we consider large random matrices with arbitrary expectation and a ...
In the first part of this thesis we consider large random matrices with arbitrary expectation and a ...
In the first part of the thesis we consider Hermitian random matrices. Firstly, we consider sample c...
For complex Wigner-type matrices, i.e. Hermitian random matrices with independent, not necessarily i...
For complex Wigner-type matrices, i.e. Hermitian random matrices with independent, not necessarily i...
The eigenvalue density of many large random matrices is well approximated by a deterministic measure...
We consider large random matrices with a general slowly decaying correlation among its entries. We p...
We consider large random matrices with a general slowly decaying correlation among its entries. We p...
The eigenvalue density of many large random matrices is well approximated by a deterministic measure...
We consider large random matrices with a general slowly decaying correlation among its entries. We p...
The eigenvalue density of many large random matrices is well approximated by a deterministic measure...
We consider real symmetric or complex hermitian random matrices with correlated entries. We prove lo...
We consider real symmetric or complex hermitian random matrices with correlated entries. We prove lo...
We consider N × N Hermitian Wigner random matrices H where the probability density for each matrix e...
We consider the local eigenvalue distribution of large self-adjoint N×N random matrices H=H∗ with ce...
In the first part of this thesis we consider large random matrices with arbitrary expectation and a ...
In the first part of this thesis we consider large random matrices with arbitrary expectation and a ...
In the first part of the thesis we consider Hermitian random matrices. Firstly, we consider sample c...
For complex Wigner-type matrices, i.e. Hermitian random matrices with independent, not necessarily i...
For complex Wigner-type matrices, i.e. Hermitian random matrices with independent, not necessarily i...
The eigenvalue density of many large random matrices is well approximated by a deterministic measure...
We consider large random matrices with a general slowly decaying correlation among its entries. We p...
We consider large random matrices with a general slowly decaying correlation among its entries. We p...
The eigenvalue density of many large random matrices is well approximated by a deterministic measure...
We consider large random matrices with a general slowly decaying correlation among its entries. We p...
The eigenvalue density of many large random matrices is well approximated by a deterministic measure...
We consider real symmetric or complex hermitian random matrices with correlated entries. We prove lo...
We consider real symmetric or complex hermitian random matrices with correlated entries. We prove lo...
We consider N × N Hermitian Wigner random matrices H where the probability density for each matrix e...
We consider the local eigenvalue distribution of large self-adjoint N×N random matrices H=H∗ with ce...