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A formalism for study of spectral correlations in non-Gaussian, unitary invariant ensembles of large random matrices with strong level confinement is reviewed. It is based on the Shohat method in the theory of orthogonal polynomials. The…

Statistical Mechanics · Physics 2016-08-31 E. Kanzieper , V. Freilikher

We consider two non-Gaussian ensembles of large Hermitian random matrices with strong level confinement and show that near the soft edge of the spectrum both scaled density of states and eigenvalue correlations follow so-called Airy laws…

chao-dyn · Physics 2009-10-30 E. Kanzieper , V. Freilikher

Using the diagrammatic method, we derive a set of self-consistent equations that describe eigenvalue distributions of large correlated asymmetric random matrices. The matrix elements can have different variances and be correlated with each…

Disordered Systems and Neural Networks · Physics 2016-12-21 Alexander Kuczala , Tatyana O. Sharpee

Orthogonal - unitary and symplectic - unitary crossover ensembles of random matrices are relevant in many contexts, especially in the study of time reversal symmetry breaking in quantum chaotic systems. Using skew-orthogonal polynomials we…

Mathematical Physics · Physics 2011-05-30 Santosh Kumar , Akhilesh Pandey

We show that eigenvalue correlations in unitary-invariant ensembles of large random matrices adhere to novel universal laws that only depend on a multicriticality of the bulk density of states near the soft edge of the spectrum. Our…

chao-dyn · Physics 2009-10-30 E. Kanzieper , V. Freilikher

We consider large random matrices with a general slowly decaying correlation among its entries. We prove universality of the local eigenvalue statistics and optimal local laws for the resolvent away from the spectral edges, generalizing the…

Probability · Mathematics 2020-06-01 László Erdős , Torben Krüger , Dominik Schröder

We prove the universality for the eigenvalue gap statistics in the bulk of the spectrum for band matrices, in the regime where the band width is comparable with the dimension of the matrix, $W\sim N$. All previous results concerning…

Probability · Mathematics 2016-04-18 Paul Bourgade , Laszlo Erdos , Horng-Tzer Yau , Jun Yin

We study the universal properties of distributions of eigenvalues of random matrices in the large $N$ limit. The distributions fall in universality classes characterized entirely by the support of the spectral density.

Condensed Matter · Physics 2009-10-28 J. Ambjorn , G. Akemann

Quantum chaotic systems with one-dimensional spectra follow spectral correlations of orthogonal (OE), unitary (UE), or symplectic ensembles (SE) of random matrices depending on their invariance under time reversal and rotation. In this…

Quantum Physics · Physics 2024-01-09 Jisha C , Ravi Prakash

Random matrix theory allows one to deduce the eigenvalue spectrum of a large matrix given only statistical information about its elements. Such results provide insight into what factors contribute to the stability of complex dynamical…

Disordered Systems and Neural Networks · Physics 2025-01-30 Joseph W. Baron , Thomas Jun Jewell , Christopher Ryder , Tobias Galla

Non-Hermitian random matrices with statistical spectral characteristics beyond the standard Ginibre ensembles have recently emerged in the description of dissipative quantum many-body systems as well as in non-ergodic wave transport in…

Mathematical Physics · Physics 2025-11-27 Gernot Akemann , Yan V. Fyodorov , Dmitry V. Savin

We consider non-gaussian ensembles of random normal matrices with the constraint that the ensembles are invariant under unitary transformations. We show that the level density of eigenvalues exhibits disk to ring transition in the complex…

Mathematical Physics · Physics 2015-07-07 Ravi Prakash , Akhilesh Pandey

We consider the Gaussian ensembles of random matrices and describe the normal modes of the eigenvalue spectrum, i.e., the correlated fluctuations of eigenvalues about their most probable values. The associated normal mode spectrum is…

Nuclear Theory · Physics 2009-10-31 A. Andersen , A. D. Jackson , H. J. Pedersen

Quantifying the eigenvalue spectra of large random matrices allows one to understand the factors that contribute to the stability of dynamical systems with many interacting components. This work explores the effect that the interaction…

Disordered Systems and Neural Networks · Physics 2022-12-08 Joseph W. Baron

Strongly non-Gaussian ensembles of large random matrices possessing unitary symmetry and logarithmic level repulsion are studied both in presence and absence of hard edge in their energy spectra. Employing a theory of polynomials orthogonal…

Condensed Matter · Physics 2009-10-28 V. Freilikher , E. Kanzieper , I. Yurkevich

We show that correlation matrices with particular average and variance of the correlation coefficients have a notably restricted spectral structure. Applying geometric methods, we derive lower bounds for the largest eigenvalue and the…

Mathematical Physics · Physics 2021-08-25 Yuriy Stepanov , Hendrik Herrmann , Thomas Guhr

Statistical properties of non--symmetric real random matrices of size $M$, obtained as truncations of random orthogonal $N\times N$ matrices are investigated. We derive an exact formula for the density of eigenvalues which consists of two…

Statistical Mechanics · Physics 2010-10-21 Boris A. Khoruzhenko , Hans-Juergen Sommers , Karol Zyczkowski

We consider the uniform random $d$-regular graph on $N$ vertices, with $d \in [N^\alpha, N^{2/3-\alpha}]$ for arbitrary $\alpha > 0$. We prove that in the bulk of the spectrum the local eigenvalue correlation functions and the distribution…

Probability · Mathematics 2019-08-21 Roland Bauerschmidt , Jiaoyang Huang , Antti Knowles , Horng-Tzer Yau

We analyze statistical properties of the complex system with conditions which manifests through specific constraints on the column/row sum of the matrix elements. The presence of additional constraints besides symmetry leads to new…

Statistical Mechanics · Physics 2015-10-28 Pragya Shukla , Suchetana Sadhukhan

The remarkable universality of the eigenvalue correlation functions is perhaps one of the most salient findings in random matrix theory. Particularly for short-range separations of the eigenvalues, the correlation functions have been shown…

Disordered Systems and Neural Networks · Physics 2025-08-28 Joseph W. Baron
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