56 research outputs found
A simple polynomial time algorithm to approximate the permanent within a simply exponential factor
We present a simple randomized polynomial time algorithm to approximate the
mixed discriminant of positive semidefinite matrices within a
factor . Consequently, the algorithm allows us to approximate in
randomized polynomial time the permanent of a given non-negative
matrix within a factor . When applied to approximating the permanent,
the algorithm turns out to be a simple modification of the well-known
Godsil-Gutman estimator
Enumerating contingency tables via random permanents
Given m positive integers R=(r_i), n positive integers C=(c_j) such that sum
r_i = sum c_j =N, and mn non-negative weights W=(w_{ij}), we consider the total
weight T=T(R, C; W) of non-negative integer matrices (contingency tables)
D=(d_{ij}) with the row sums r_i, column sums c_j, and the weight of D equal to
prod w_{ij}^{d_{ij}}. We present a randomized algorithm of a polynomial in N
complexity which computes a number T'=T'(R,C; W) such that T' < T < alpha(R, C)
T' where alpha(R,C) = min{prod r_i! r_i^{-r_i}, prod c_j! c_j^{-c_j}} N^N/N!.
In many cases, ln T' provides an asymptotically accurate estimate of ln T. The
idea of the algorithm is to express T as the expectation of the permanent of an
N x N random matrix with exponentially distributed entries and approximate the
expectation by the integral T' of an efficiently computable log-concave
function on R^{mn}. Applications to counting integer flows in graphs are also
discussed.Comment: 19 pages, bounds are sharpened, references are adde
A permanent formula for the Jones polynomial
The permanent of a square matrix is defined in a way similar to the
determinant, but without using signs. The exact computation of the permanent is
hard, but there are Monte-Carlo algorithms that can estimate general
permanents. Given a planar diagram of a link L with crossings, we define a
7n by 7n matrix whose permanent equals to the Jones polynomial of L. This
result accompanied with recent work of Freedman, Kitaev, Larson and Wang
provides a Monte-Carlo algorithm to any decision problem belonging to the class
BQP, i.e. such that it can be computed with bounded error in polynomial time
using quantum resources.Comment: To appear in Advances in Applied Mathematic
Computing the permanent of (some) complex matrices
We present a deterministic algorithm, which, for any given 0< epsilon < 1 and
an nxn real or complex matrix A=(a_{ij}) such that | a_{ij}-1| < 0.19 for all
i, j computes the permanent of A within relative error epsilon in n^{O(ln n -ln
epsilon)} time. The method can be extended to computing hafnians and
multidimensional permanents.Comment: 12 pages, results extended to hafnians and multidimensional
permanents, minor improvement
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