Showing papers by "Van Vu published in 2007"

On the singularity probability of random Bernoulli matrices

Abstract: Let $n$ be a large integer and $M_n$ be a random $n$ by $n$ matrix whose entries are i.i.d. Bernoulli random variables (each entry is $\pm 1$ with probability 1/2). We show that the probability that $M_n$ is singular is at most $(3/4 +o(1))^n$, improving an earlier estimate of Kahn, Komlos and Szemeredi, as well as earlier work by the authors. The key new ingredient is the applications of Freiman type inverse theorems and other tools from additive combinatorics.

Spectral norm of random matrices

Abstract: In this paper, we present a new upper bound for the spectral norm of symmetric random matrices with independent (but not necessarily identical) entries. Our results improve an earlier result of Furedi and Komlos.

Local resilience of graphs

Abstract: In this paper, we initiate a systematic study of graph resilience. The (local) resilience of a graph G with respect to a property P measures how much one has to change G (locally) in order to destroy P. Estimating the resilience leads to many new and challenging problems. Here we focus on random and pseudo-random graphs and prove several sharp results.

The condition number of a randomly perturbed matrix

Abstract: Let M be an arbitrary n by n matrix. We study the conditionnumber a random perturbation M+Nn of M, where Nn is arandom matrix. It is shown that, under very general conditions on M and Mn, the condition number of M+Nn is polynomial in nwith very high probability. The main novelty here is that we allow Nn to have discrete distribution.

The condition number of a randomly perturbed matrix

Abstract: Let $M$ be an arbitrary $n$ by $n$ matrix. We study the condition number a random perturbation $M+N_n$ of $M$, where $N_n$ is a random matrix. It is shown that, under very general conditions on $M$ and $M_n$, the condition number of $M+N_n$ is polynomial in $n$ with very high probability. The main novelty here is that we allow $N_n$ to have discrete distribution.

Random Matrices: The circular Law

Abstract: Let $\a$ be a complex random variable with mean zero and bounded variance $\sigma^{2}$. Let $N_{n}$ be a random matrix of order $n$ with entries being i.i.d. copies of $\a$. Let $\lambda_{1}, ..., \lambda_{n}$ be the eigenvalues of $\frac{1}{\sigma \sqrt n}N_{n}$. Define the empirical spectral distribution $\mu_{n}$ of $N_{n}$ by the formula $$ \mu_n(s,t) := \frac{1}{n} # \{k \leq n| \Re(\lambda_k) \leq s; \Im(\lambda_k) \leq t \}.$$ The Circular law conjecture asserts that $\mu_{n}$ converges to the uniform distribution $\mu_\infty$ over the unit disk as $n$ tends to infinity. We prove this conjecture under the slightly stronger assumption that the $(2+\eta)þ$-moment of $\a$ is bounded, for any $\eta >0$. Our method builds and improves upon earlier work of Girko, Bai, Gotze-Tikhomirov, and Pan-Zhou, and also applies for sparse random matrices. The new key ingredient in the paper is a general result about the least singular value of random matrices, which was obtained using tools and ideas from additive combinatorics.

On the Rank of Random Sparse Matrices

Abstract: We investigate the rank of random (symmetric) sparse matrices. Our main finding is that with high probability, any dependency that occurs in such a matrix is formed by a set of few rows that contains an overwhelming number of zeros. This allows us to obtain an exact estimate for the co-rank.

Mapping Incidences

Abstract: We show that any finite set S in a characteristic zero integral domain can be mapped to the finite field of order p, for infinitely many primes p, preserving all algebraic incidences in S. This can be seen as a generalization of the well-known Freiman isomorphism lemma, and we give several combinatorial applications (such as sum-product estimates).

Random inscribing polytopes

Abstract: For convex bodies K with C^2 boundary in R^d, we explore random polytopes with vertices chosen along the boundary of K. In particular, we determine asymptotic properties of the volume of these random polytopes. We provide results concerning the variance and higher moments of this functional, as well as an analogous central limit theorem.

Sum-product estimates via directed expanders

Abstract: Let $\F_q$ be a finite field of order $q$ and $P$ be a polynomial in $\F_q[x_1, x_2]$. For a set $A \subset \F_q$, define $P(A):=\{P(x_1, x_2) | x_i \in A \}$. Using certain constructions of expanders, we characterize all polynomials $P$ for which the following holds \vskip2mm \centerline{\it If $|A+A|$ is small, then $|P(A)|$ is large.} \vskip2mm The case $P=x_1x_2$ corresponds to the well-known sum-product problem.