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Questions tagged [random-matrices]

Statistics of spectral properties of matrix-valued random variables.

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A naive question about non-Hermitian random matrix

The resolvent of a matrix $\mathbf{A}$ is defined as \begin{equation} \mathbf{G}_{\mathbf{A}}(z) = \left(\mathbf{A} - z \mathbf{1}_n\right)^{-1}, \quad z \in \mathbb{C} \setminus \sigma(\mathbf{A}), \...
stopro's user avatar
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3 votes
0 answers
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Maximizing a Gaussian quadratic form

Let $u$ denote a fixed unit vector in $\mathbb{R}^n$ and $g$ a standard Gaussian vector (in $\mathbb{R}^n$). Consider the map $$ f_n(X) = \mathbb{E} \langle (X^{-1} + gg^T)^{-1} u, u\rangle, $$ ...
Drew Brady's user avatar
2 votes
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100 views

Stiefel C-manifold: volume and uniform distribution

I'm trying to define the uniform distribution on the Stiefel $C$-manifold (Downs 1972), given by $\mathcal{V}_{p,n}(C) = \{ X \in \mathbb{R}^{n \times p} : X' X = C \}$ for $n \geq p$ and $C > 0$. ...
seneca's user avatar
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4 votes
1 answer
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Distinct eigenvalues of random matrix over finite field

Let $A$ be a uniformly random matrix in $\mathrm{M}_n(\mathbf{F}_p)$. It is well known that, as $p$ is fixed and $n$ tends to infinity, $A$ has repeated eigenvalues (over the algebraic closure $\...
darko's user avatar
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Asymptotic unitary invariance of rank-one spiked Gaussian matrix

I'm working on some Random Matrix Theory related stuff for my thesis, and i've come across the following problem: Consider a (normalized) spiked Wigner matrix $\mathbf{A}$ $$ \mathbf{A} = \frac{\beta}{...
Kawa's user avatar
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Asymptotically small submatrices of random matrices

Consider an ensemble of $N \times N$ random Hermitian matrices distributed according to some unitarily invariant measure $$P(M) \mathrm{d}M = \frac{1}{Z_{N}} e^{-\mathrm{tr}[ Q(M)]}\mathrm{d}M,$$ for ...
anon1802's user avatar
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3 votes
1 answer
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Error bound for MonteCarlo estimate of elements in Gram-Matrix

Suppose I have a $n\times n$-symmetric positive-definite matrix $A$ with elements: \begin{align} [A]_{ij}=\int_{\Omega}f_i(x)f_j(x) \, dx, \quad i,j=1,\ldots,n \end{align} where $\Omega\subset \mathbb{...
Jjj's user avatar
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1 vote
1 answer
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Parameters of Wishart distribution and generalized inverse

I recently came across the Wishart Distribution and a few things are unclear to me. The Wikipedia page for the Wishart Distribution says that if $G=[g_1 \vert \; g_2\vert \; \ldots \vert g_n]$ is a $...
randomize's user avatar
0 votes
2 answers
135 views

Expectation of supremum of sub gaussians

I am trying to prove Lemma 2.3 of ON THE SPECTRAL NORM OF GAUSSIAN RANDOM MATRICES, which states that Let $X_1,\cdots,X_n$ be not necessarily independent random variables with $\mathbb{P}[X_i > x] ...
Sudipta Roy's user avatar
7 votes
1 answer
274 views

Smallest eigenvalue of a random matrix

Let $A \in \mathbb R^{n\times n}$ be a positive semi-definite matrix, and let $b \in \mathbb R^n$. For a random vector $x \sim \mathcal N(0, I_{n\times n})$, consider the random matrices $$ B_1 = A + ...
Rastapopoulos's user avatar
2 votes
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68 views

Nonlinear random matrix equations

Let $C$ be a matrix; $v$ be a column vector; $P$, $\Delta$ are random matrices; $x$ is a random column vector. $$Cvv^T - \mathbb{E}[P^Tx]v^T - \mathbb{E}[P^Tx v^T \Delta] + O(\Delta^2)= 0$$ $$C^TCv - ...
Paul Deerock's user avatar
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Analytic / algebraic characterization of the limiting value of the unique nonnegative root of a polynomial

I'm interested in the following problem which arises from some "random matrix theory" calculations. Let $\phi,s_1,s_2, p > 0$ with $p \in [0,1]$, and set $p_1=p$, $p_2=1-p$, and $q_k := ...
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Why has the random Koopman matrix $ G_{xx}^{(-)} G_{yx} $ only eigenvalues on the complex unit circle?

Let U be a $\Bbb{R}^{(n+1)(n+1)} $ matrix with entries drawn from a independent normal distribution, e.g. $$ U_{i j} \sim N(0,1) \quad \quad i,j=1,...n+1$$ Let $ G=U U^* $ be a Gram matrix where $ U^* ...
user3072048's user avatar
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Variance and expected value of power of normal matrix elements

Here is the next problem: we have $n\times n$ random matrix $\hat{A}$, each element of this matrix is independent real random variable with normal distribution ($\mu=0, \sigma^2=1/n$). Matrix is no-...
StrangerK's user avatar
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0 answers
27 views

Expectation of the Inverse of Sum of Weighted Identity Wishart Matrices

As noted in the title, suppose $A=\sum_{i=1}^{n}\lambda_ig_ig_i^T$ where $g_i\sim N(0,I_d)$ and $d < n$. Essentially, $A$ is the weighted sum of $W_d(I_d,n)$. Ultimately, I want to calculate the ...
Jake Freeman's user avatar
1 vote
0 answers
80 views

Moments from characteristic function for matrices

When $x$ is a random variable with the smooth characteristic function $\phi_x(t) = \mathbb{E}e^{itx}$, we can easily compute the moments as $\mathbb{E}[x^k] = i^{-n}\phi_x^{(n)}(0)$. There is no magic ...
user3826143's user avatar
3 votes
0 answers
98 views

Bounding the norm of a sum of fourth-order Gaussian vectors

Let $a_1, \cdots, a_n\in\mathbb{R}^k$ be independent random vectors sampled from $N(0,\Sigma)$, where $\Sigma = \operatorname{diag}(\lambda_1, \cdots, \lambda_k)$ and $\lambda_1 \ge \cdots \ge \...
Nicole's user avatar
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6 votes
0 answers
203 views

Spectrum of $\prod_i^d \left(I-x_ix_i^T\right)$ for isotropic $x_i$

Suppose $x_i\in \mathbb{R}^d$ are IID isotropic random vectors with $\|x_i\|=1$ and matrix $A_d$ is defined as follows: $$A_d=\prod_i^d \left(I-x_ix_i^T\right)$$ Is anything known about the spectrum ...
Yaroslav Bulatov's user avatar
1 vote
0 answers
43 views

Moments on the Stiefel manifold

Let $S_{n, k} = \{V \in \mathbb{R}^{n \times k} : V^T V = I_k\}$ denote the Stiefel manifold, $1 \leq k \leq n$. Let $P \in \mathbb{R}^{n \times n}$ denote a symmetric real, positive definite matrix, ...
Drew Brady's user avatar
3 votes
0 answers
131 views

Matrix-Gaussian distributions

The point of this question is to ask for references on matrix-variate Gaussian distributions. But I will explain what I mean by a matrix-variate Gaussian with an example (the notion I have in mind is ...
user3826143's user avatar
2 votes
1 answer
111 views

"High complexity" of eigenbasis of Wigner matrices?

Let $W$ be an $N \times N$ complex Wigner matrix, i.e. i.i.d. entries restricted to Hermitian matrices. Let $W=UDU^{\ast}$, i.e. $U$ encodes the eigenbasis of $W$. Are there any statements known about ...
Marcin Kotowski's user avatar
2 votes
0 answers
29 views

Spectral bound for sample covariance matrix without assuming $X = \Sigma^{\frac{1}{2}} Z$

Let $X$ be a random $(p \times n)$-matrix with iid centered columns and suppose the entries of $X$ all have light tails (in a strong enough sense, for example sub-Gaussian). Are there any results ...
Ben Deitmar's user avatar
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29 views

What is known about the distribution of eigenvectors for random positive semidefinite matrices?

Let $\{x_i\}_{i=1}^n \subset \mathbb{R}^d$ be iid random vectors drawn from probability measure $P$. Define the random $d \times d$ real positive semidefinite matrix, $$ S_n = \frac{1}{n} \sum_{i=1}^n ...
Drew Brady's user avatar
1 vote
1 answer
274 views

Does free multiplicative convolution become free additive convolution under logarithm?

Let $X$ and $Y$ be two $n\times n$ random matrices that have zero measure over degenerate matrices. For a positive definite matrix with eigen-decomposition $A = U \Lambda U^\top$, let $\log(A) = U \...
kvphxga's user avatar
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Bound p-th order moments for a random Wishart matrix to show the sub-exponential property

Let $a\in\mathbb{R}^k$ be a random vector sampled from $N(0,\Sigma)$. Let $X = aa^T - \Sigma$. Then we have $\mathbb{E} X = 0$. Can we find a constant $C\in\mathbb{R}$ and another fixed matrix $A\in\...
Nicole's user avatar
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1 vote
1 answer
111 views

Matrix concentration inequality for unbounded (sub-exponential) matrices

Let $a_1, \cdots, a_n\in\mathbb{R}^k$ be independent random vectors sampled from $N(0,\Sigma)$. We aim to establish a high probability bound on the eigenvalues $\lambda_{\min}(\sum_{i=1}^n a_ia_i^T)$ ...
Nicole's user avatar
  • 97
8 votes
1 answer
428 views

Wishart matrices: are eigenvalues and eigenvectors independent?

Let $W = X^TX$ denote a standard Wishart matrix, i.e., where $X$ is a Gaussian random matrix with iid standard Normal entries. In this case we can write $W = U D U^T$, where $U$ is orthogonal and $D$ ...
Drew Brady's user avatar
1 vote
1 answer
84 views

Limiting value of Stieltjes transform of sum of independent Wishart matrices

Let $n_1$, $n_2$, and $d$ positive integers tending to infinity such that $d/n_k \to \phi_k \in (0,\infty)$ and $n_1/(n_1+n_2) \to p \in (0,1)$. Let $X_k$ be an $n_k \times d$ random matrix with iid ...
dohmatob's user avatar
  • 6,853
2 votes
2 answers
192 views

Behavior of a Wishart quadratic form

Let $X \in \mathbb{R}^{n \times d}$ be a random matrix with iid standard Gaussian entries. Let $e_1$ denote the first canonical basis vector in $\mathbb{R}^d$. Define $$ P_d(\lambda) = (1-\lambda) e_1 ...
Drew Brady's user avatar
3 votes
1 answer
145 views

Orthogonal projection $X X^+$ from random Gaussian matrix $X$

Given a standard Gaussian matrix $X\in\mathbb{R}^{n\times d}$, $d<n$, with entries sampled i.i.d. from $\mathcal{N}(0,1)$, is the corresponding orthogonal projection $X X^+ = X (X^\top X)^{-1} X^\...
João F. Doriguello's user avatar
2 votes
1 answer
246 views

Inequality with Hermite polynomials

Consider the (physicist's) Hermite polynomials $H_n(x)$ which are divided by $$\sqrt{\sqrt{\pi} 2^n n!}$$ for the purpose of normalization. These are orthogonal with respect to the weight function $e^{...
T. Amdeberhan's user avatar
0 votes
1 answer
159 views

Dot product of a randomly orientated vector and a fixed vector

Let us consider a random variable $Z$ with a probability density function $f$ with respect to the Haar measure on $\mathrm{SO}(3)$. Next, we consider two fixed normal vectors $u,v$ in $\mathbb{R}^3$. ...
user avatar
0 votes
1 answer
108 views

RMT for modified Wishard matrix $Y'Y$ (where $i$th row of $Y$ is zero if $|x_i^\top u| \le \theta$; else it equals $x_i$)

Let $n$ and $d$ be positive integers tending to infinity such that $d/n \to \phi \in (0,\infty)$. Let $X$ be an $n \times d$ random matrix with iid rows $x_1,\ldots,x_n$ from $N(0, \Sigma)$, where $\...
dohmatob's user avatar
  • 6,853
-1 votes
1 answer
163 views

Is it true that if a random vector has independent coordinates each bounded by $1$ then $P[ \|X\| \leq \epsilon\sqrt{n}] \leq (C\epsilon)^{n}$?

I'm studying Vershynin's well-written book on "High Dimensional Probability" and the third chapter on concentration of random vectors. Exercise 3.1.7 from the book is the following. Let $X =...
user135520's user avatar
2 votes
0 answers
116 views

Random matrix with power law decay in eigenvalues

What positive semi-definite random matrices have (roughly) $n^{-\alpha}$ for $n^{th}$ singular value? The power law decay need not be exact. I want to find random matrix ensembles that naturally ...
CWC's user avatar
  • 433
6 votes
1 answer
252 views

Poisson kernel for the orthogonal groups

For the complex ball $|z|^2\le 1$ in $\mathbb{C}^n$, there is a Poisson kernel proportional to $|x-z|^{-2n}$. This is generalized to the unitary group $U(N)$ so that in the complex matrix ball $Z^\...
thedude's user avatar
  • 1,549
0 votes
0 answers
56 views

Random pseudo-inverse matrix problem

Given a matrix $M \in \mathbb{R}^{n \times N_d}$, $N_d \gg n$ and $\mathrm{rank}(M) = n$, the entries of $M$ are denoted as $M_{[ij]}, i = 1,...,n, j = 1,..., N_d$ and $M_{[ij]} \in [-\textbf{m}, \...
Michael Miller's user avatar
1 vote
1 answer
110 views

Bounded density for determinant of GOE

Let $M$ a random GOE matrix, i.e. $M=(M_{i,j})$ is a symmetric matrix and the $M_{i,j},i\leq j$ are independent centred Gaussien entries with variance 1, except on the diagonal where the variance is $...
kaleidoscop's user avatar
  • 1,352
1 vote
1 answer
99 views

Maximum column norm of random $A^{-1}B$

Suppose that $A$ is an $n$ by $n$ Gaussian matrix (each component i.i.d. normal distributed with mean 0 and variance 1). Let $b$ be a $n$-Gaussian vector. Then it could be easily proven that the ...
ZZZZZZ's user avatar
  • 33
1 vote
0 answers
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Multilinear non-commutative Khintchine inequality

Let $g_1,\ldots,g_k$ be independent standard Gaussians and for each index $(i_1,\ldots,i_k)\in [n]^k$ let $A_{i_1,\ldots,i_k}$ be a $d\times d$ symmetric matrix. Question: Is there a known bound for ...
user293794's user avatar
8 votes
2 answers
752 views

Computing Haar measure of matrices sampled from SO(n)

I am looking to sample uniform matrices from SO(n). I know that uniform matrices can be sampled from O(n) by taking the QR decomposition of Gaussian random square matrices and adjusting the sign of ...
magnesium's user avatar
  • 181
1 vote
2 answers
66 views

Distribution of the constraint matrix conditioned on the solution of the linear system

Suppose that A is a random matrix in $R^{n\times n}$, with each component independently and identically distributed (iid) according to $\mathcal{N}(0,1)$. Additionally, b is a random vector in $R^n$, ...
ZZZZZZ's user avatar
  • 33
0 votes
0 answers
35 views

Question about the spectrum of a deformed GOE matrix

Consider a fixed real value $\sigma>0$. Let $A,Z$ be two independent $n\times n$ GOE matrices, and define $B=A+\sigma Z$. I am interested in finding a bound (possibly dependent on $n$) for the ...
EJAV's user avatar
  • 1
0 votes
1 answer
68 views

Convergence of edge eigenvalues for Gaussian matrices

I am reading this lecture note. I have a difficulty in understanding the third section in chapter 6. Particularly, in Theorem 4.1, they claimed that Let $X$ be a Gaussian Wigner matrix satisfying ...
Pipnap's user avatar
  • 129
2 votes
1 answer
124 views

Functional calculation for Hermitian matrices

First, let me recall some useful definitions We recall that if $A=U \Lambda U^*$ is a Hermitian matrix with $U U^*=U^* U=I$ and $\Lambda=\operatorname{diag}\left(\lambda_1\right)$ and $f: \mathbb{R} \...
Pipnap's user avatar
  • 129
0 votes
0 answers
92 views

Convergence in probability of quadratic form with positive mean

Let $\boldsymbol{X}_n\in\mathbb{R}^n$ be a sequence of Gaussian random vectors with independent entries, such that $X_{n,i}\sim \mathcal{N}(\mu_i,\sigma^2)$ (that is, all entries of the $n$th vector ...
Student88's user avatar
  • 503
0 votes
0 answers
42 views

Limiting value of trace of resolvent matrix involving two independent Wishart random matrices

Let $n_1$, $n_2$, and $d$ be positive integers tending to infinity such that $$ d/n_k \to \phi_k \in (0,\infty). $$ Let $X_1 \in \mathbb R^{n_1 \times d}$ and $X_2^{n_2 \times d}$ be independent ...
dohmatob's user avatar
  • 6,853
0 votes
0 answers
48 views

Computation of Brown measure of the shift operator on $\ell^2(\mathbb N)$?

This looks an extremely simple question - I am just trying to give an example of Brown measure, https://en.wikipedia.org/wiki/Brown_measure, so I try to compute it for the left/right-shift operator on ...
Ma Joad's user avatar
  • 1,755
2 votes
1 answer
128 views

Eigenvalue analysis of $X^T (XX^T + \mathrm{Id})^{-1} X$ for $X$ iid random matrix

Consider the following quantity $$X^T (XX^T + \mathrm{Id})^{-1} X,$$ where $X \in \mathbb{R}^{m\times n}$ is a iid random matrix with 0 mean and finite variance. The empiric covariance matrix ${X^T X}$...
Goulifet's user avatar
  • 2,306
0 votes
0 answers
77 views

Maximizing the trace of the resolvent of a Wishart matrix over positive unit trace matrices?

Let $G$ be a standard $d \times d$ Wishart random matrix and consider the problem of maximizing the function $$ f(M) = \mathbb{E}\Big[\mathrm{tr}((G + M^{-1})^{-1})\Big], $$ over the class of real ...
Drew Brady's user avatar

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