Skip to main content

All Questions

Filter by
Sorted by
Tagged with
42 votes
3 answers
5k views

The probability for a symmetric matrix to be positive definite

Let me give a reasonable model for the question in the title. In ${\rm Sym}_n({\mathbb R})$, the positive definite matrices form a convex cone $S_n^+$. The probability I have in mind is the ratio $p_n=...
Denis Serre's user avatar
  • 52.3k
7 votes
1 answer
880 views

Bound for largest eigenvalue of symmetric matrices of uniform random variables over $[0,1]$ and fixed $1$s along diagonal and scattered $1$s

Given a $n\times n$ symmetric random matrix whose diagonal elements are all fixed as $1$. In addition, there are $k$ $1$s will be randomly scattered in upper triangular (of course, the corresponding ...
Tony's user avatar
  • 272
25 votes
1 answer
4k views

What kind of random matrices have rapidly decaying singular values?

I've been told that in machine learning it's common to compute the singular value decomposition of matrices in order to throw out all information in the matrix except that corresponding to, say, the $...
Qiaochu Yuan's user avatar
6 votes
1 answer
274 views

Spectrum asymptotics for a product of $k$ random matrices?

How does the spectrum of a product of $k$ random matrices behave around 0? In particular, I'm wondering if the CDF of squared singular values behaves as $x^{\frac{1}{k+1}}$ around 0. The result for $k=...
Yaroslav Bulatov's user avatar
4 votes
1 answer
626 views

How to get the lower bound of the following $\tau$?

Let $A=\{a_{ij}\}_{1\le i,j\le n}$ be an $n$ by $n$ normalized Gaussian random matrix with $E[a_{ij}]=0$ and $E[a_{ij}^2]=1/n$. Ordering its eigenvalues by $\lambda_1\le \lambda_2\le \cdots \lambda_n$ ...
Hermi's user avatar
  • 288
45 votes
1 answer
6k views

Anti-concentration bound for permanents of Gaussian matrices?

In a recent paper with Alex Arkhipov on "The Computational Complexity of Linear Optics," we needed to assume a reasonable-sounding probabilistic conjecture: namely, that the permanent of a matrix of i....
Scott Aaronson's user avatar
40 votes
1 answer
5k views

When should we expect Tracy-Widom?

The Tracy-Widom law describes, among other things, the fluctuations of maximal eigenvalues of many random large matrix models. Because of its universal character, it obtained his position on the ...
Adrien Hardy's user avatar
  • 2,135
17 votes
1 answer
9k views

Intuitive understanding of the Stieltjes transform

I have been using random matrix theory in signal processing and have some trouble understanding what the Stieltjes transform does. The gist of my work is that I have an $N\times N$ true covariance ...
user avatar
16 votes
5 answers
2k views

Expected value of determinant of simple infinite random matrix

Suppose we have a matrix $A \in \mathbb{R}^{n\times n}$ where $$A_{ij} = \begin{cases} 1 & \text{with probability} \quad p\\ 0 &\text{with probability} \quad1-p\end{cases}$$ I would like to ...
Hipstpaka's user avatar
  • 355
4 votes
2 answers
1k views

Expectation of the trace of inverse of a Gaussian random matrix

Given a $N×M$ random complex gaussian matrix $X$ and $N×K$ random complex gaussian matrix $Y$ I'm interested in approximating the expectation expressed as: \begin{align} E[trace({(aX{X^H} + I)^{ - ...
hichem hb's user avatar
  • 377
4 votes
1 answer
485 views

Expected norms of Wishart matrices

Suppose $x_i \stackrel{\text{i.i.d}}{\sim} \mathcal{N}(\mu,\Sigma)$. What can we say about dependence on $b$ of Frobenius/spectral norm quantities below? $$f(b)=\left\|\frac{1}{b}\sum_{i=1}^b x_i x_i^...
Yaroslav Bulatov's user avatar
3 votes
1 answer
3k views

Singular value decomposition of random rectangular matrices

Let $A$ be a $m\times n$ real matrix, whose entries are independent, identically distributed random variables, following standard normal distributions (mean zero and unit variance). What is the ...
valle's user avatar
  • 884
18 votes
1 answer
1k views

How fast can extreme eigenvalues of the average of random matrices converge to their expectation?

Suppose that $X_1,X_2,\ldots,X_m$ are independent $d\times d$ random matrices and let $\overline{X} := \frac{1}{m}\sum_{i=1}^m X_i$. One of the questions studied under the theory of random matrices is ...
sbahmani's user avatar
  • 181
15 votes
2 answers
3k views

What do we actually know about logarithmic energy ?

In potential theory, the $\textit{logarithmic energy}$ of a Radon measure $\mu$ acting on $\mathbb{C}$ is defined by $$I(\mu)=\iint\log\frac{1}{|x-y|}\mu(dx)\mu(dy).$$ Of course it is not well ...
Adrien Hardy's user avatar
  • 2,135
11 votes
1 answer
636 views

A simple proof for a theorem of Szekeres and Turán

Szekeres and Turán found in 1937 a formula for the sum of the squares and the sum of the fourth powers of determinants of all $n$ by $n$ matrices with $\pm 1$ entries. (The sum of squares case follows ...
Gil Kalai's user avatar
  • 24.7k
10 votes
2 answers
1k views

Probability of random (0,1) Toeplitz matrix being invertible

A Toeplitz matrix or diagonal-constant matrix is a matrix in which each descending diagonal from left to right is constant. What is the probability that a random $n \times n$ binary Toeplitz ...
user avatar
10 votes
1 answer
441 views

Probability that a random distance function is metric

Take a random $n \times n$ nonnegative symmetric matrix $D$ with zero diagonal. What is the probability that it is an abstract distance matrix, i.e. satisfies $D_{xy}+D_{yz} \geq D_{xz}$ for all index ...
Felix Goldberg's user avatar
9 votes
1 answer
652 views

Scaling in Mehta's integral

The following expression is known as Mehta's integral and deeply connected to random matrix theory: $$\frac{1}{(2\pi)^{n/2}}\int_{-\infty}^{\infty} \cdots \int_{-\infty}^{\infty} \prod_{i=1}^n e^{-...
Pritam Bemis's user avatar
9 votes
2 answers
4k views

Eigenvalue densities of sample covariance matrices when the population covariance matrix is a perturbed identity matrix

TLDR: I'm looking for a random matrix theory reference for the eigenvalue densities of sample covariance matrices (both dimensions approaching infinity at the same rate) when the true (population) ...
user avatar
8 votes
0 answers
232 views

Decay of orthogonal contributions in a random set of vectors

Suppose we sample $k$ vectors $v$ from normal distribution centered at zero and diagonal covariance with diagonal entries $1,\frac{1}{2},\ldots,\frac{1}{d}$ and normalize $v$: $$\frac{v_1}{\|v_1\|},\...
Yaroslav Bulatov's user avatar
7 votes
4 answers
476 views

What does $\mathbb E_V \max_{x \in V,\,\|x\|=1} x^T Ax$ evaluate to when $V$ is random $k$-dim suspace of $\mathbb R^n$ and $A$ is fixed psd matrix?

Let $G_{k,n}$ be the grassmannian of $k$-dimensional vector spaces of $\mathbb R^n$. By the Courant–Fisher characterization, the $k$th largest eigenvalue of an $n \times n$ psd matrix $A$ is given by $...
dohmatob's user avatar
  • 6,853
7 votes
1 answer
857 views

Trace of inverse of random positive-definite matrix in high dimension?

Consider a random matrix $A \in \mathbb{R}^{n\times n}$ with i.i.d. entries, with symmetric law and finite variance. I am curious about the behavior of $$\mathrm{Tr}( (A^T A + \lambda \mathrm{Id})^{-1}...
Goulifet's user avatar
  • 2,306
6 votes
0 answers
1k views

Relationship between R-transform and free convolution of random matrices?

I've been using the R-transform to calculate the free convolution of the eigenvalue spectra of two random matrices and I am trying to understand how it works, and in particular how it relates to ...
Jiahao Chen's user avatar
  • 1,890
6 votes
0 answers
295 views

Dimension-free sample complexity for estimating Gaussian covariance

(also asked on math.se, with no answers) Suppose I have $m$ samples drawn from a Gaussian in $\mathbb{R}^n$, and need sample covariance $\Sigma_m$ to be $\epsilon$-close to true covariance $\Sigma$: $$...
Yaroslav Bulatov's user avatar
6 votes
1 answer
837 views

Average minimum number of random k-sparse vectors in GF(2) to span the whole space?

What is the average minimum required number of independent $k$-sparse (having at most $k$ non-zero elements) random vectors belonging to $\mathbb{F}_2^n$ to span the whole space of $\mathbb{F}_2^n$? ...
mhsnk's user avatar
  • 307
5 votes
0 answers
235 views

Riemann theta function inequality for a class of large random matrices

The following is essentially the same question as in this previous post, but since I have completely re-formulated it (hopefully for the better ;-), I decided to post a new question instead of an edit....
Dierk Bormann's user avatar
4 votes
0 answers
970 views

Expected operator norm of inverse Wishart matrix

Let $ W\sim W_p(n,I)$ be a white $p\times p$ Wishart matrix, and assume $n>p+1$, which ensures that $W$ is invertible almost surely. Let $\|W^{-1}\|_{\text{op}}$ be the operator norm (maximum ...
mlopes's user avatar
  • 41
4 votes
1 answer
637 views

Characterizations of the GOE/GUE family of distributions

This question is somewhat related to this one. Loosely speaking, when should I expect a GOE/GUE distribution? The angle of my approach to this is not through statements such as "there is a natural ...
Alex R.'s user avatar
  • 4,952
4 votes
1 answer
225 views

Is the inequality of the random matrices correct?

I am not familiar with random matrices but I need to confirm the correctness of the inequality below. Let $\xi_i\in\{\pm 1\}$ be independent random signs, and let $A_1,\ldots, A_n$ be $m\times m$ ...
Nate's user avatar
  • 131
3 votes
1 answer
206 views

Asymptotic results for smallest gap of Gaussian random matrix

For a symmetric Gaussian random matrix $G=\{G\}_{1\le i,j \le n}$ with iid $E[G_{ij}]=0$ and $E[G_{ij}^2]=1/n$ (it is normalized), ordering its eigenvalues $\lambda_1\le \lambda_2\le\cdots \lambda_n$. ...
Hermi's user avatar
  • 288
3 votes
1 answer
184 views

Why is number of single cell clusters always greatest in a random matrix?

Consider a large $N\times N$ square lattice, where each cell has a probability $p$ of being "occupied" (let's call denote them as "black") and a probability $1-p$ of being empty (let's denote them as "...
user avatar
3 votes
0 answers
202 views

Difficult Gaussian-sum inequality for large random Bernoulli-Toeplitz matrices

I have come across the following problem in an attempt to prove an entropy bound for large random Bernoulli-Toeplitz matrices (Conjecture 1 on p. 16 of this preprint by Clifford et al. 2015), which is ...
Dierk Bormann's user avatar
2 votes
0 answers
173 views

Why do larger random matrices maximize their number of clusters with lower densities?

Consider a matrix whose elements are independently assigned a value $1$ with probability $p$ and a value $0$ with probability $1-p$. Define a cluster of cells as a maximal connected component in the ...
alphauser's user avatar
2 votes
3 answers
999 views

Sum of Square of the Eigenvalues of Wishart Matrix

Let $A\in\mathbb{R}^{m\times d}$ matrix with iid standard normal entries, and $m\geqslant d$, and define $S=A^T A$. I want to have a tight upper bound for $\sum_{k=1}^d \lambda_k^2$, where $\...
hookah's user avatar
  • 1,096
2 votes
1 answer
591 views

Resolvent (Green's function) of this random matrix

I have a matrix $A$ as follows: $$ A=\begin{pmatrix} 0 & \boldsymbol{W} \\ \boldsymbol{W}^{\dagger} & \boldsymbol{H} \end{pmatrix} $$ where $H$ and $W$ are a random Hermitian $N\times N$ ...
Guoqing's user avatar
  • 375
2 votes
1 answer
834 views

Jacobian of changing of variables to singular value decomposition

It is well known that changing variables from a symmetric matrix to its eigenvalue decomposition involves a Jacobian which is just the Vandermonde determinant of the eigenvalues. Now suppose I have a ...
valle's user avatar
  • 884
2 votes
1 answer
796 views

Can we get that $ P(N^{2/3}(\lambda_N-\lambda_{N-1})\le c)\ge 1-\epsilon$?

Following this question: Can we apply the continuous mapping theorem for the limiting joint distribution of the Tracy-Widom law?. We know that $$ \lim_{N\to\infty}P(N^{2/3}(\lambda_N-2)\le s_1,\dotsc,...
Hermi's user avatar
  • 288
2 votes
1 answer
378 views

Distribution of the Gram matrix

Let $\mathbf{X}$ be an $m\times k$ random matrix ($m>k$) of rank $k$, having the density function $f_\mathbf{X}(X)$. What is the distribution of $\mathbf{Y}=\mathbf{XX}^T$? Basically my question is ...
Peter's user avatar
  • 141
2 votes
1 answer
936 views

Upper-bound for spectral norm of the covariance matrix of a certain Gaussian vector with correlated entries

Let $n$ and $m$ be large positive integers. Let $x=(x_1,\ldots,x_n)$ be a vector of independent random variables from $N(0,1)$. It is clear that the covariance matrix of $x$ is $I_n$, the identity ...
dohmatob's user avatar
  • 6,853
2 votes
1 answer
212 views

Prove / disprove: If $1 \le n < N$ and $A$ is an $N \times n$ matrix with iid from $\mathcal N(0,1)$, then $s_\min(A) \ge c\sqrt{N}$ w.p $1-2e^{-N}$

Let $1 \le n < N$ be integers and $A$ be a random $N\times n$ matrix with iid entries from $\mathcal N(0,1)$. This paper (Rudelson and Vershynin) claims in the paragraph just before formula (3.4) ...
dohmatob's user avatar
  • 6,853
2 votes
1 answer
90 views

Generalization: (The "number" of) smaller sized clusters in large random binary matrices follow a descending order. Why?

This is a sequel to the question: Why is number of single cell clusters always greatest in a random matrix? In their answer, @Aaron Meyerowitz came up with a nice strategy to prove why the number of ...
user avatar
2 votes
1 answer
213 views

For fixed $\lambda \ge 0$, Integrate the function $f_\lambda(x):=x/(x + \lambda)^2$ w.r.t. Marchenko-Pastur density

In trying to solve another the problem posed in the question https://www.mathoverflow.net/q/385777/78539, I'm led to consider the following problem. Let $\mu_\gamma$ be the Marchenko-Pastur ...
dohmatob's user avatar
  • 6,853
2 votes
1 answer
905 views

Diagonalizability of Gaussian random matrices

Let $X$ be an $n\times n$ matrix whose elements are i.i.d. sampled from a normal distribution of zero mean and unit variance. Is $X$ diagonalizable over $\mathbb{C}$ with probability 1? Is there a ...
user50394's user avatar
  • 123
2 votes
1 answer
132 views

Independent decomposition of coordinate distribution

Let $\mathbf{x}$ be a random Gaussian vector in $\mathbb{R}^n$, i.e. $\mathbf{x}\sim\mathcal{N}(\mathbf{0},\mathbf{I}_n)$. Then for any fixed unit vector $\mathbf{u}$, one has $\mathbf{u}\mathbf{u}^\...
Wuchen's user avatar
  • 515
2 votes
1 answer
299 views

Can this particular random matrix model be converted/related to any existing graph theory model?

Context: This a sequel to the question: Is the Erdős–Rényi giant component result applicable here? Consider a matrix whose elements are independently assigned a value $1$ with probability $p$ ...
user avatar
1 vote
1 answer
84 views

Asymptotic property of the left singular vectors of i.i.d. data matrix

Let $\mathbf{X}$ be $(n \times p)$-dimensional data matrix ($n > p$) whose rows $\mathbf{x}_i$ are i.i.d. with some finite moments: $$ \mathbf{X}^\top = [\mathbf{x}_1, \ldots \mathbf{x}_n]^\top. ...
Seung Hyeon Yu's user avatar
1 vote
1 answer
415 views

Approximate the singular values of a certain random dot-product kernel matrix (in the sense of El Karoui, Cheng-Singer, etc.)

Let $g:\mathbb R \to \mathbb R $ be a continuous function which is "sufficiently smooth" (e.g $\mathcal C^3$) around $0$, and "sufficiently integrable" (e.g integrable w.r.t $N(0,...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
83 views

Tracy Widom type results for asymptotic distribution of the $k$-th largest eigenvalue of the sample covariance when $n, p \to \infty$?

Earlier I asked a question: Distribution of the $k$-th largest eigenvalue of in the sample covariance matrix?, but I forgot to mention that I'd like results for asymtotic regime. So, I'm posting here ...
Learning math's user avatar
0 votes
0 answers
115 views

Distribution of the $k$-th largest eigenvalue of in the sample covariance matrix?

Let us assume we've a rectangular data matrix $X=[x_1 \dots x_n] \in \mathbb{R}^{p \times n}$, where the $x_i \in \mathbb{R}^{p \times 1}$ are iid column vectors. I'm not assuming here that the ...
Learning math's user avatar
0 votes
1 answer
203 views

LDP for Marchenko Pastur with k/n tending to 0

I am interested in the determinant of $W = X * X'$, where $X \in \mathbb{R}^{k \times n}$ is a matrix with each row drawn IID from some sub-Gaussian distribution on $\mathbb{R}^{n}$. (I am aware of ...
DJA's user avatar
  • 435