Algebraic Diagonals and Walks: Algorithms, Bounds, Complexity

TL;DR

This paper develops algorithms for computing algebraic diagonals of bivariate rational functions and applies these methods to efficiently enumerate lattice walks, improving computational complexity for these combinatorial problems.

Contribution

It introduces a new algorithm to compute minimal annihilating polynomials for diagonals of rational functions with bounds on size and complexity, and applies this to lattice walk enumeration.

Findings

Algorithm computes annihilating polynomials in quasi-linear time.

Bounds on polynomial size are established and shown to be tight.

New method for enumerating lattice walks with quasi-linear complexity.

Abstract

The diagonal of a multivariate power series F is the univariate power series Diag(F) generated by the diagonal terms of F. Diagonals form an important class of power series; they occur frequently in number theory, theoretical physics and enumerative combinatorics. We study algorithmic questions related to diagonals in the case where F is the Taylor expansion of a bivariate rational function. It is classical that in this case Diag(F) is an algebraic function. We propose an algorithm that computes an annihilating polynomial for Diag(F). We give a precise bound on the size of this polynomial and show that generically, this polynomial is the minimal polynomial and that its size reaches the bound. The algorithm runs in time quasi-linear in this bound, which grows exponentially with the degree of the input rational function. We then address the related problem of enumerating directed lattice walks. The insight given by our study leads to a new method for expanding the generating power series of bridges, excursions and meanders. We show that their first N terms can be computed in quasi-linear complexity in N, without first computing a very large polynomial equation.