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We derive the mean eigenvalue density for symmetric Gaussian random N x N matrices in the limit of large N, with a constraint implying that the row sum of matrix elements should vanish. The result is shown to be equivalent to a result found…

Disordered Systems and Neural Networks · Physics 2009-11-10 J. Staering , B. Mehlig , Yan V. Fyodorov , J. M. Luck

This paper investigates limiting properties of eigenvalues of multivariate sample spatial-sign covariance matrices when both the number of variables and the sample size grow to infinity. The underlying p-variate populations are general…

Statistics Theory · Mathematics 2021-01-25 Weiming Li , Qinwen Wang , Jianfeng Yao , Wang Zhou

This paper uses an incremental matrix expansion approach to derive asymptotic eigenvalue distributions (a.e.d.'s) of sums and products of large random matrices. We show that the result can be derived directly as a consequence of two common…

Information Theory · Computer Science 2007-07-13 Matthew J. M. Peacock , Iain B. Collings , Michael L. Honig

Spectral properties of Toeplitz operators and their finite truncations have long been central in operator theory. In the finite dimensional, non-normal setting, the spectrum is notoriously unstable under perturbations. Random perturbations…

Probability · Mathematics 2025-09-17 Anirban Basak

Hybrid Euler-Hadamard products have previously been studied for the Riemann zeta function on its critical line and for Dirichlet L-functions in the context of the calculation of moments and connections with Random Matrix Theory. According…

Number Theory · Mathematics 2012-11-06 H. M. Bui , J. P. Keating

The paper establishes error orders for integral limit approximations to the traces of products of Toeplitz matrices generated by integrable real symmetric functions defined on the unit circle. These approximations and the corresponding…

Probability · Mathematics 2014-05-15 M. S. Ginovyan , A. A. Sahakyan

Spatial-sign covariance matrix (SSCM) is an important substitute of sample covariance matrix (SCM) in robust statistics. This paper investigates the SSCM on its asymptotic spectral behaviors under high-dimensional elliptical populations,…

Statistics Theory · Mathematics 2017-05-19 Weiming Li , Wang Zhou

Spectral statistics of hermitian random Toeplitz matrices with independent identically distributed elements is investigated numerically. It is found that the eigenvalue statistics of complex Toeplitz matrices is surprisingly well…

Quantum Physics · Physics 2020-10-14 Eugene Bogomolny

By using the independence structure of points following a determinantal point process, we study the radii of the spherical ensemble, the truncation of the circular unitary ensemble and the product ensemble with parameter n and k. The…

Probability · Mathematics 2014-11-10 Tiefeng Jiang , Yongcheng Qi

Spectral properties of Hermitian Toeplitz, Hankel, and Toeplitz-plus-Hankel random matrices with independent identically distributed entries are investigated. Combining numerical and analytic arguments it is demonstrated that spectral…

Mathematical Physics · Physics 2021-04-28 Eugene Bogomolny , Olivier Giraud

The statistical behaviour of a product of independent, identically distributed random matrices in $\text{SL}(2,{\mathbb R})$ is encoded in the generalised Lyapunov exponent $\Lambda$; this is a function whose value at the complex number $2…

Mathematical Physics · Physics 2019-11-04 Alain Comtet , Christophe Texier , Yves Tourigny

For a large class of symmetric random matrices with correlated entries, selected from stationary random fields of centered and square integrable variables, we show that the limiting distribution of eigenvalue counting measure always exists…

Probability · Mathematics 2016-03-08 Costel Peligrad , Magda Peligrad

Consider the product of $m$ independent $n\times n$ random matrices from the spherical ensemble for $m\ge 1$. The empirical distribution based on the $n$ eigenvalues of the product is called the empirical spectral distribution. Two recent…

Statistics Theory · Mathematics 2017-04-06 Shuhua Chang , Yongcheng Qi

By calculating all terms of the high-density expansion of the euclidean random matrix theory (up to second-order in the inverse density) for the vibrational spectrum of a topologically disordered system we show that the low-frequency…

Disordered Systems and Neural Networks · Physics 2015-05-18 Carl Ganter , Walter Schirmacher

I study the product of independent identically distributed $D\times D$ random probability matrices. Some exact asymptotic results are obtained. I find that both the left and the right products approach exponentially to a probability…

Condensed Matter · Physics 2007-05-23 X. R. Wang

We show that singular numbers (also known as invariant factors or Smith normal forms) of products and corners of random matrices over $\mathbb{Q}_p$ are governed by the Hall-Littlewood polynomials, in a structurally identical manner to the…

Probability · Mathematics 2021-10-22 Roger Van Peski

We consider the eigenvalues of a fixed, non-normal matrix subject to a small additive perturbation. In particular, we consider the case when the fixed matrix is a banded Toeplitz matrix, where the bandwidth is allowed to grow slowly with…

Probability · Mathematics 2022-08-29 Sean O'Rourke , Philip Matchett Wood

We develop a new toolbox for the analysis of the global behavior of stochastic discrete particle systems. We introduce and study the notion of the Schur generating function of a random discrete configuration. Our main result provides a…

Probability · Mathematics 2021-01-01 Alexey Bufetov , Vadim Gorin

Under the high-dimensional setting that data dimension and sample size tend to infinity proportionally, we derive the central limit theorem (CLT) for linear spectral statistics (LSS) of large-dimensional sample covariance matrix. Different…

Statistics Theory · Mathematics 2021-06-21 Liu Zhijun , Bai Zhidong , Hu Jiang , Song Haiyan

Suppose $X_p$ is a real $p \times n$ matrix with independent entries and consider the (unscaled) sample covariance matrix $S_p=X_pX_p^T$. The Marchenko-Pastur law was discovered as the limit of the bulk distribution of the sample covariance…

Probability · Mathematics 2022-01-04 Arup Bose , Priyanka Sen
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