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The general correlation function for the eigenvalues of $p$ complex hermitian matrices coupled in a chain is given as a single determinant. For this we use a slight generalization of a theorem of Dyson.

Condensed Matter · Physics 2009-10-30 B. Eynard , M. L. Mehta

Let $A$ be an $n\times n$ random matrix with independent, identically distributed mean 0, variance 1 subgaussian entries. We prove that $$ \mathbb{P}(A\text{ has distinct singular values})\geq 1-e^{-cn} $$ for some $c>0$, confirming a…

Probability · Mathematics 2025-03-04 Yi Han

We show the density of eigenvalues for three classes of random matrix ensembles is determinantal. First we derive the density of eigenvalues of product of $k$ independent $n\times n$ matrices with i.i.d. complex Gaussian entries with a few…

Probability · Mathematics 2016-05-05 Kartick Adhikari , Nanda Kishore Reddy , Tulasi Ram Reddy , Koushik Saha

We calculate the autocorrelation functions (or shifted moments) of the characteristic polynomials of matrices drawn uniformly with respect to Haar measure from the groups U(N), O(2N) and USp(2N). In each case the result can be expressed in…

Mathematical Physics · Physics 2016-09-07 J. B. Conrey , D. W. Farmer , J. P. Keating , M. O. Rubinstein , N. C. Snaith

We introduce and study a 2-parameter family of unitarily invariant probability measures on the space of infinite Hermitian matrices. We show that the decomposition of a measure from this family on ergodic components is described by a…

Mathematical Physics · Physics 2009-10-31 Alexei Borodin , Grigori Olshanski

We derive the connected correlation functions for eigenvalues of large Hermitian random matrices with independently distributed elements using both a diagrammatic and a renormalization group (RG) inspired approach. With the diagrammatic…

Condensed Matter · Physics 2009-10-28 J. D'Anna , A. Zee

The circular and Jacobi ensembles of random matrices have their eigenvalue support on the unit circle of the complex plane and the interval $(0,1)$ of the real line respectively. The averaged value of the modulus of the corresponding…

Mathematical Physics · Physics 2015-06-16 P. J. Forrester , J. P. Keating

We consider the problem of detecting the dimensionality of entanglement with the use of correlations between measurements in randomized directions. First, exploiting the recently derived covariance matrix criterion for the entanglement…

Quantum Physics · Physics 2023-07-20 Shuheng Liu , Qiongyi He , Marcus Huber , Otfried Gühne , Giuseppe Vitagliano

Pickrell has fully characterized the unitarily invariant probability measures on infinite Hermitian matrices, and an alternative proof of this classification has been found by Olshanski and Vershik. Borodin and Olshanski deduced from this…

Probability · Mathematics 2020-04-27 Joseph Najnudel

We develop an algorithm for sampling from the unitary invariant random matrix ensembles. The algorithm is based on the representation of their eigenvalues as a determinantal point process whose kernel is given in terms of orthogonal…

Mathematical Physics · Physics 2014-04-02 Sheehan Olver , Raj Rao Nadakuditi , Thomas Trogdon

We establish a general framework to explore parametric statistics of individual energy levels in unitary random matrix ensembles. For a generic confinement potential $W(H)$, we (i) find the joint distribution functions of the eigenvalues of…

Condensed Matter · Physics 2009-11-10 I. E. Smolyarenko , B. D. Simons

We propose new measures of shared information, unique information and synergistic information that can be used to decompose the multi-information of a pair of random variables $(Y,Z)$ with a third random variable $X$. Our measures are…

Information Theory · Computer Science 2014-06-18 Nils Bertschinger , Johannes Rauh , Eckehard Olbrich , Jürgen Jost , Nihat Ay

This thesis reviews recent progress on products of random matrices from the perspective of exactly solved Gaussian random matrix models. We derive exact formulae for the correlation functions for the eigen- and singular values at arbitrary…

Mathematical Physics · Physics 2015-10-22 J. R. Ipsen

The zeros of the random Laurent series $1/\mu - \sum_{j=1}^\infty c_j/z^j$, where each $c_j$ is an independent standard complex Gaussian, is known to correspond to the scaled eigenvalues of a particular additive rank 1 perturbation of a…

Mathematical Physics · Physics 2018-07-19 Peter J. Forrester , Jesper R. Ipsen

Number theorists have studied extensively the connections between the distribution of zeros of the Riemann $\zeta$-function, and of some generalizations, with the statistics of the eigenvalues of large random matrices. It is interesting to…

Mathematical Physics · Physics 2009-10-31 E. Brezin , S. Hikami

We consider the product of n complex non-Hermitian, independent random matrices, each of size NxN with independent identically distributed Gaussian entries (Ginibre matrices). The joint probability distribution of the complex eigenvalues of…

Mathematical Physics · Physics 2015-06-11 G. Akemann , Z. Burda

We consider the correlation functions of eigenvalues of a unidimensional chain of large random hermitian matrices. An asymptotic expression of the orthogonal polynomials allows to find new results for the correlations of eigenvalues of…

Mesoscale and Nanoscale Physics · Physics 2008-11-26 Bertrand Eynard

We obtain general, exact formulas for the overlaps between the eigenvectors of large correlated random matrices, with additive or multiplicative noise. These results have potential applications in many different contexts, from quantum…

Statistical Mechanics · Physics 2018-12-05 Joël Bun , Jean-Philippe Bouchaud , Marc Potters

We discuss the product of independent induced quaternion ($\beta=4$) Ginibre matrices, and the eigenvalue correlations of this product matrix. The joint probability density function for the eigenvalues of the product matrix is shown to be…

Mathematical Physics · Physics 2015-06-12 J. R. Ipsen

In this work, the possibility of clustering correlated random variables was examined, both because of their mutual similarity and because of their similarity to the principal components. The k-means algorithm and spectral algorithms were…

Machine Learning · Computer Science 2019-09-10 Zenon Gniazdowski , Dawid Kaliszewski