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Related papers: Local Marchenko-Pastur Law for Random Bipartite Gr…

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We prove a local law in the bulk of the spectrum for random Gram matrices $XX^*$, a generalization of sample covariance matrices, where $X$ is a large matrix with independent, centered entries with arbitrary variances. The limiting…

Probability · Mathematics 2017-03-13 Johannes Alt , László Erdős , Torben Krüger

In this paper we study the local law for eigenvalues of large random regular bipartite graphs with degree growing arbitrarily fast. We prove that the empirical spectral distribution of the adjacency matrix converges to a scaled down copy of…

Combinatorics · Mathematics 2013-10-18 Linh V. Tran

Let $X_N$ be a $N\times N$ matrix whose entries are i.i.d. complex random variables with mean zero and variance $\frac{1}{N}$. We study the asymptotic spectral distribution of the eigenvalues of the covariance matrix $X_N^*X_N$ for…

Mathematical Physics · Physics 2015-06-05 Claudio Cacciapuoti , Anna Maltsev , Benjamin Schlein

We prove that the empirical spectral distribution of a (d_L, d_R)-biregular, bipartite random graph, under certain conditions, converges to a symmetrization of the Mar\v{c}enko-Pastur distribution of random matrix theory. This convergence…

Probability · Mathematics 2016-01-22 Ioana Dumitriu , Tobias Johnson

Consider an $N$ by $N$ matrix $X$ of complex entries with iid real and imaginary parts. We show that the local density of eigenvalues of $X^*X$ converges to the Marchenko-Pastur law on the optimal scale with probability $1$. We also obtain…

Probability · Mathematics 2022-06-07 Anastasis Kafetzopoulos , Anna Maltsev

We extend the proof of the local semicircle law for generalized Wigner matrices given in [4] to the case when the matrix of variances has an eigenvalue $ -1 $. In particular, this result provides a short proof of the optimal local…

Probability · Mathematics 2013-11-11 Oskari Ajanki , Laszlo Erdos , Torben Krüger

We study the limiting spectral distribution of large-dimensional sample covariance matrices associated with symmetric random tensors formed by $\binom{n}{d}$ different products of $d$ variables chosen from $n$ independent standardized…

Probability · Mathematics 2021-11-09 Pavel Yaskov

This paper is the second chapter of three of the author's undergraduate thesis. In this paper, we consider the random matrix ensemble given by $(d_b, d_w)$-regular graphs on $M$ black vertices and $N$ white vertices, where $d_b \in…

Probability · Mathematics 2018-01-18 Kevin Yang

We consider random $d$-regular graphs on $N$ vertices, with degree $d$ at least $(\log N)^4$. We prove that the Green's function of the adjacency matrix and the Stieltjes transform of its empirical spectral measure are well approximated by…

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

We review the application of the notion of local convergence on locally finite randomly rooted graphs, known as Benjamini-Schramm convergence, to the calculation of the global eigenvalue density of random matrices from the beta-Gaussian and…

Probability · Mathematics 2018-05-29 Sergio Andraus

We study the adjacency matrices of random $d$-regular graphs with large but fixed degree $d$. In the bulk of the spectrum $[-2\sqrt{d-1}+\varepsilon, 2\sqrt{d-1}-\varepsilon]$ down to the optimal spectral scale, we prove that the Green's…

Probability · Mathematics 2020-04-28 Roland Bauerschmidt , Jiaoyang Huang , Horng-Tzer Yau

We introduce the $N\times N$ random matrices $$ X_{j,k}=\exp\left(2\pi i \sum_{q=1}^d\ \omega_{j,q} k^q\right) \quad \text{with } \{\omega_{j,q}\}_{\substack{1\leq j\leq N\\ 1\leq q\leq d}} \text{ i.i.d. random variables}, $$ and $d$ a…

Probability · Mathematics 2020-05-11 Arka Adhikari , Marius Lemm

This paper studies the asymptotic spectral properties of the sample covariance matrix for high dimensional compositional data, including the limiting spectral distribution, the limit of extreme eigenvalues, and the central limit theorem for…

Statistics Theory · Mathematics 2023-12-25 Qianqian Jiang , Jiaxin Qiu , Zeng Li

We obtain the limiting spectral distribution for large sample covariance matrices associated with random vectors having graph-dependent entries under the assumption that the interdependence among the entries grows with the sample size n.…

Probability · Mathematics 2021-05-21 Pavel Yaskov

Several well-known results from the random matrix theory, such as Wigner's law and the Marchenko--Pastur law, can be interpreted (and proved) in terms of non-backtracking walks on a certain graph. Orthogonal polynomials with respect to the…

Mathematical Physics · Physics 2009-11-13 Sasha Sodin

We consider sample covariance matrices of the form $X^*X$, where $X$ is an $M \times N$ matrix with independent random entries. We prove the isotropic local Marchenko-Pastur law, i.e. we prove that the resolvent $(X^* X - z)^{-1}$ converges…

Probability · Mathematics 2015-07-17 Alex Bloemendal , Laszlo Erdos , Antti Knowles , Horng-Tzer Yau , Jun Yin

This paper is concerned with extensions of the classical Mar\v{c}enko-Pastur law to time series. Specifically, $p$-dimensional linear processes are considered which are built from innovation vectors with independent, identically distributed…

Statistics Theory · Mathematics 2015-04-03 Haoyang Liu , Alexander Aue , Debashis Paul

Consider a random regular graph of fixed degree $d$ with $n$ vertices. We study spectral properties of the adjacency matrix and of random Schr\"odinger operators on such a graph as $n$ tends to infinity. We prove that the integrated density…

Mathematical Physics · Physics 2014-05-09 Leander Geisinger

We consider spectral properties of sparse sample covariance matrices, which includes biadjacency matrices of the bipartite Erd\H{o}s-R\'enyi graph model. We prove a local law for the eigenvalue density up to the upper spectral edge. Under a…

Probability · Mathematics 2018-08-06 Jong Yun Hwang , Ji Oon Lee , Kevin Schnelli

We consider the singular vectors of any $m \times n$ submatrix of a rectangular $M \times N$ Gaussian matrix and study their asymptotic overlaps with those of the full matrix, in the macroscopic regime where $N \,/\, M\,$, $m \,/\, M$ as…

Probability · Mathematics 2025-01-16 Elie Attal , Romain Allez
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