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Stochastics and Statistics Seminar

Computing partition functions by interpolation

March 3, 2017 @ 11:00 am - 12:00 pm

Alexander Barvinok (University of Michigan)


Abstract: Partition functions are just multivariate polynomials with great many monomials enumerating combinatorial structures of a particular type and their efficient computation (approximation) are of interest for combinatorics, statistics, physics and computational complexity. I’ll present a general principle: the partition function can be efficiently approximated in a domain if it has no complex zeros in a slightly larger domain, and illustrate it on the examples of the permanent of a matrix, the independence polynomial of a graph and, time permitting, the graph homomorphism partition function.

Biography: Alexander Barvinok is a Professor of Mathematics at the University of Michigan, Ann Arbor. He is interested in computational complexity and algorithms in algebra, geometry and combinatorics.

MIT Statistics + Data Science Center
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307