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Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory.
10
votes
Convex combination iid Bernoulli random variables
One can get a bound which is within a constant of the optimal bound using the following
Paley-Zygmund type inequality Let $X$ be a real random variable with mean zero and finite fourth moment, th …
15
votes
Accepted
When does a pointwise CLT hold?
Bounded density will suffice, I think. Basically what one needs is for the Fourier transforms (aka characteristic functions) of the $X_1 + \ldots + X_n / \sqrt{n}$ to converge pointwise to the Fourie …
5
votes
Accepted
Convex combination iid Bernoulli random variables
To complement my other answer, I will show
Proposition 1 Let $\xi_k$ be a finite number of iid Bernoulli random variables of expectation $p > 1/2$, and let $a_k > 0$ be real numbers. Then ${\bf …
5
votes
Accepted
Prove an inequality related to moments
As observed in a (now deleted) previous comment, the exponent of $\|\alpha\|_2$ should be $2k$ instead of $2$ for homogeneity reasons.
If the $\varepsilon_i$ are symmetric, then this can be proven by …
11
votes
Accepted
Distribution of the spectrum of large non-negative matrices
This is a non-centered iid random matrix whose entries have mean one and variance one (and decay exponentially at infinity), and as such, is subject to the circular law with one outlier. Thus, there …
6
votes
Accepted
'Focusing' the mass of the Probability Density Function for a Random Walk
Hmm, you're asking for concentration for heat kernels. Over long periods of time, these kernels are dominated by the low-energy eigenfunctions, so basically one needs to construct domains which have …
6
votes
Accepted
Distribution of 1-norm for Gaussian Unitary Ensemble
Let's normalise the variance of the entries to be $1$. Then GUE asymptotically obeys the semicircular law, i.e., the eigenvalues (which equal the singular values, as GUE is Hermitian), after dividing …
21
votes
Can random variables that almost surely solve equations be repaired to surely solve these eq...
After chasing down references relating to the paper of Shelah mentioned by Will Brian, I now have a satisfactory answer to the question. It all hinges on whether there is a splitting of the quotient …
28
votes
Accepted
Is there a noncommutative Gaussian?
The theory of classical independence and classical convolution can be generalised to noncommutative settings in several ways. The most famous one is that of free independence and free convolution (int …
9
votes
Accepted
Joint distribution of minor of Wigner Hermitian matrices
There is certainly no asymptotic independence between $\det M_{11}, \det M_{22}$. From the base times height formula for parallelepipeds we see that
\begin{align*} \frac{|\det M_{12}|}{|\det M_{22}|} …
6
votes
Why do Littlewood-Paley projections behave like iid random variables
If one replaces the real line with the Walsh ring $F_2[t](\frac{1}{t})$ (or equivalently, replaces the Fourier transform by the Fourier-Walsh transform), then Littlewood-Paley projections become preci …
43
votes
Accepted
Anti-concentration bound for permanents of Gaussian matrices?
I did a preliminary feasibility analysis of our methods and it appears possible that one may be able to tighten our $n^\epsilon$ loss to something more like $\exp( \sqrt{n} )$ in the Gaussian case, bu …
38
votes
If $X$ and $Y$ independent and identically distributed, then $E(|X-Y|)\leq E(|X+Y|)$. Are ot...
Shorn of probabilistic language, this inequality follows from the assertion that $|x+y|-|x-y|$ is a positive semi-definite kernel, and is therefore the sum (or integral) of squares. Your Fourier-anal …
3
votes
Accepted
Tail bounds on eigenvalue gaps for GUE
This is studied in
Gérard Ben Arous and Paul Bourgade, Extreme gaps between eigenvalues of random matrices, Ann. Probab. 41 (2013), no. 4, 2648--2681.
(Ah, so that's how the "insert citation" butto …
16
votes
Accepted
Some models for random graphs that I am curious about
The Lovasz-Szegedy theory of graphons is likely to be relevant. Every measurable symmetric function $p: [0,1] \times [0,1] \to [0,1]$ (otherwise known as a graphon) determines a random graph model, i …