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 [7] this is almost the best possible 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 [1] and Huh and Wang [23] on combinatorial hodge theory to derive a connection between matroids and logconcave 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 logconcave 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.
In REF , a subset of the authors gave a deterministic e r approximation to the number of bases using the fact that д µ (M) is log-concave over R n ⩾0 .
Log-Concave Polynomials, Entropy, and a Deterministic Approximation Algorithm for Counting Bases of Matroids
2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS)
2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS)
Mathematics Computer Science