Log-Concave Polynomials I: Entropy and a Deterministic Approximation Algorithm for Counting Bases of Matroids

TL;DR

This paper introduces a deterministic polynomial-time approximation algorithm for counting matroid bases, leveraging log-concave polynomials and entropy-based convex optimization, marking a significant advance in combinatorial counting methods.

Contribution

It establishes the first nontrivial deterministic approximation algorithm for counting bases of arbitrary matroids using log-concavity and entropy techniques.

Findings

Provides a $2^{O(r)}$-approximation algorithm for matroid bases

Shows the multivariate generating polynomial of matroid bases is log-concave

Develops a convex optimization framework for approximate counting

Abstract

We give a deterministic polynomial time $2^{O(r)}$-approximation algorithm for the number of bases of a given matroid of rank $r$ and the number of common bases of any two matroids of rank $r$. To the best of our knowledge, this is the first nontrivial deterministic approximation algorithm that works for arbitrary matroids. Based on a lower bound of Azar, Broder, and Frieze [ABF94] this is almost the best possible result assuming oracle access to independent sets of the matroid. There are two main ingredients in our result: For the first, we build upon recent results of Adiprasito, Huh, and Katz [AHK15] and Huh and Wang [HW17] on combinatorial hodge theory to derive a connection between matroids and log-concave polynomials. We expect that several new applications in approximation algorithms will be derived from this connection in future. Formally, we prove that the multivariate generating polynomial of the bases of any matroid is log-concave as a function over the positive orthant. For the second ingredient, we develop a general framework for approximate counting in discrete problems, based on convex optimization. The connection goes through subadditivity of the entropy. For matroids, we prove that an approximate superadditivity of the entropy holds by relying on the log-concavity of the corresponding polynomials.