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It is well known that the joint probability density of the eigenvalues of Gaussian ensembles of random matrices may be interpreted as a Coulomb gas. We review these classical results for hermitian and complex random matrices, with special…

Statistical Mechanics · Physics 2007-05-23 P. Leboeuf

We compute the average characteristic polynomial of the hermitised product of $M$ real or complex Wigner matrices of size $N\times N$ and the average of the characteristic polynomial of a product of $M$ such Wigner matrices times the…

Probability · Mathematics 2021-05-27 Gernot Akemann , Friedrich Götze , Thorsten Neuschel

We consider the problem of improving kernel approximation via randomized feature maps. These maps arise as Monte Carlo approximation to integral representations of kernel functions and scale up kernel methods for larger datasets. Based on…

Machine Learning · Computer Science 2018-10-31 Marina Munkhoeva , Yermek Kapushev , Evgeny Burnaev , Ivan Oseledets

The kernel polynomial method allows to sample overall spectral properties of a quantum system, while sparse diagonalization provides accurate information about a few important states. We present a method combining these two approaches…

We compute symplectic cohomology for Milnor fibres of certain compound Du Val singularities that admit small resolution by using homological mirror symmetry. Our computations suggest a new conjecture that the existence of a small resolution…

Symplectic Geometry · Mathematics 2022-06-09 Jonathan David Evans , Yanki Lekili

We calculate smoothed correlators for a large random matrix model with a potential containing products of two traces $\tr W_1(M) \cdot \tr W_2(M)$ in addition to a single trace $\tr V(M)$. Connected correlation function of density…

Disordered Systems and Neural Networks · Physics 2009-10-30 Satoshi Iso , Andrew Kavalov

In these lecture notes we present some connections between random matrices, the asymmetric exclusion process, random tilings. These three apparently unrelated objects have (sometimes) a similar mathematical structure, an interlacing…

Mathematical Physics · Physics 2013-07-03 Patrik L. Ferrari

We consider a class of rotationally invariant unitary random matrix ensembles where the eigenvalue density falls off as an inverse power law. Under a new scaling appropriate for such power law densities (different from the scaling required…

Statistical Mechanics · Physics 2009-11-13 K. A. Muttalib , Mourad E. H. Ismail

We study the behavior of eigenvalues of matrix P_N + Q_N where P_N and Q_N are two N -by-N random orthogonal projections. We relate the joint eigenvalue distribution of this matrix to the Jacobi matrix ensemble and establish the universal…

Probability · Mathematics 2012-10-25 Vladislav Kargin

In this manuscript we consider the problem of jointly estimating multiple graphical models in high dimensions. We assume that the data are collected from n subjects, each of which consists of T possibly dependent observations. The graphical…

Machine Learning · Statistics 2014-10-09 Huitong Qiu , Fang Han , Han Liu , Brian Caffo

Approximation of non-linear kernels using random feature maps has become a powerful technique for scaling kernel methods to large datasets. We propose $\textit{Tensor Sketch}$, an efficient random feature map for approximating polynomial…

Data Structures and Algorithms · Computer Science 2025-05-20 Ninh Pham , Rasmus Pagh

We compute exact asymptotic of the statistical density of random matrices belonging to invariant random matrices ensemble (RMT) orthogonal, unitary and symplectic ensembles, where all its eigenvalues lie within the interval $[\sigma,…

Probability · Mathematics 2015-09-23 Mohamed Bouali

The product of M complex random Gaussian matrices of size N has recently been studied by Akemann, Kieburg and Wei. They showed that, for fixed M and N, the joint probability distribution for the squared singular values of the product matrix…

Mathematical Physics · Physics 2015-06-15 Lun Zhang

We show that elliptic curves with complex multiplication (CM) naturally emerge in the spectral geometry of Hermitian one-matrix models in the two-cut phase. Focusing on a symmetric quartic potential, we derive the corresponding genus-one…

High Energy Physics - Theory · Physics 2025-09-23 Ali Nassar

We study the spectrum of inner-product kernel matrices, i.e., $n \times n$ matrices with entries $h (\langle \textbf{x}_i ,\textbf{x}_j \rangle/d)$ where the $( \textbf{x}_i)_{i \leq n}$ are i.i.d.~random covariates in $\mathbb{R}^d$. In…

Statistics Theory · Mathematics 2022-04-25 Theodor Misiakiewicz

Using a character expansion method, we calculate exactly the eigenvalue density of random matrices of the form M^\dagger M where M is a complex matrix drawn from a normalized distribution P(M) ~ exp(-\Tr(A M B M^\dagger) with A and B…

Mathematical Physics · Physics 2009-11-10 Steven H. Simon , Aris L. Moustakas

The theory of zonal polynomials is used to compute the average of a Schur polynomial of argument $AX$, where $A$ is a fixed matrix and $X$ is from the real Ginibre ensemble. This generalizes a recent result of Sommers and Khorozhenko [J.…

Mathematical Physics · Physics 2015-06-16 Peter J. Forrester , Eric M. Rains

A kernel method is proposed to estimate the condensed density of the generalized eigenvalues of pencils of Hankel matrices whose elements have a joint noncentral Gaussian distribution with nonidentical covariance. These pencils arise when…

Statistics Theory · Mathematics 2015-10-02 Piero Barone

We calculate a general spectral correlation function of products and ratios of characteristic polynomials for a $N\times N$ random matrix taken from the chiral Gaussian Unitary Ensemble (chGUE). Our derivation is based upon finding an…

High Energy Physics - Theory · Physics 2009-11-07 Yan V Fyodorov , Eugene Strahov

Compound matrices play an important role in many fields of mathematics and have recently found new applications in systems and control theory. However, the explicit formulas for these compounds are non-trivial and not always easy to use.…

Classical Analysis and ODEs · Mathematics 2024-01-05 Ron Ofir , Michael Margaliot