Random walks in a convex body and an improved volume algorithm

László Lovász, Miklós Simonovits

Random Structures and Algorithms · 1993 · 425 citations · 27 references

Concepts

TL;DR

The authors present randomized algorithms that approximate the volume of a convex body and sample uniformly from it with fixed relative error. They analyze mixing rates of Markov chains and random walks on convex bodies, extending Sinclair–Jerrum results to arbitrary chains and studying walks with unit‑ball steps. The algorithms achieve O(n⁶ log⁴n) bounds for centrally symmetric bodies and O(n⁵ log⁴n) for centrally symmetric polytopes, and the study yields additional useful tools. © 1993 John Wiley & Sons, Inc.

Abstract

Abstract We give a randomized algorithm using O ( n 7 log 2 n ) separation calls to approximate the volume of a convex body with a fixed relative error. The bound is O ( n 6 log 4 n ) for centrally symmpetric bodies and for polytopes with a polynomial number of facets, and O ( n 5 log 4 n ) for centrally symmetric polytopes with a polynomial number of facets. We also give an O ( n 6 log n ) algorithm to sample a point from the uniform distribution over a convex body. Several tools are developed that may be interesting on their own. We extend results of Sinclair–Jerrum [43] and the authors [34] on the mixing rate of Markov chains from finite to arbitrary Markov chains. We also analyze the mixing rate of various random walks on convex bodies, in particular the random walk with steps from the uniform distribution over a unit ball. © 1993 John Wiley & Sons, Inc.

References

27