Large-deviation asymptotics of condition numbers of random matrices

Condition numbers of random matrices

Laws of Large Numbers for Random Linear

The computational solution of large scale linear programming problems contains various difficulties. One of the difficulties is to ensure numerical stability. There is another difficulty of a different nature, namely the original data, contains errors as well. In this paper, we show that the effect of the random errors in the original data has a diminishing tendency for the optimal value as the...

Condition Numbers of Gaussian Random Matrices

Abstract. Let Gm×n be an m × n real random matrix whose elements are independent and identically distributed standard normal random variables, and let κ2(Gm×n) be the 2-norm condition number of Gm×n. We prove that, for any m ≥ 2, n ≥ 2, and x ≥ |n − m| + 1, κ2(Gm×n) satisfies 1 √ 2π (c/x)|n−m|+1 < P ( κ2(Gm×n) n/(|n−m|+1) > x) < 1 √ 2π (C/x)|n−m|+1, where 0.245 ≤ c ≤ 2.000 and 5.013 ≤ C ≤ 6.414...

Condition Numbers of Random Triangular Matrices

Let L n be a lower triangular matrix of dimension n each of whose nonzero entries is an independent N(0; 1) variable, i.e., a random normal variable of mean 0 and variance 1. It is shown that n , the 2-norm condition number of L n , satisses n p n ! 2 almost surely as n ! 1. This exponential growth of n with n is in striking contrast to the linear growth of the condition numbers of random dense...

Asymptotics of the Eulerian Numbers Revisited: a Large Deviation Analysis

Using the Saddle point method and multiseries expansions, we obtain from the generating function of the Eulerian numbers An,k and Cauchy’s integral formula, asymptotic results in non-central region. In the region k = n −nα, 1 >α> 1/2, we analyze the dependence of An,k on α. This paper fits within the framework of Analytic Combinatorics.