Combinatorial Insight of Riemann Boundary Value Problem in Lattice Walk Problems
Ruijie Xu

TL;DR
This paper reveals a combinatorial connection between the Riemann boundary value problem approach and the kernel method in enumerating quarter-plane lattice walks, unifying different analytical techniques.
Contribution
It introduces a combinatorial perspective that links the RBVP approach with the kernel method and Tutte's invariants in lattice walk enumeration.
Findings
The index in RBVP corresponds to the kernel method's canonical factorization.
The conformal gluing function acts as a mapping facilitating positive term extraction.
Establishes a unifying framework connecting multiple analytical methods in lattice walk enumeration.
Abstract
The enumeration of quarter-plane lattice walks with small steps is a classical problem in combinatorics. An effective approach is the kernel method, where the solution is derived by positive term extraction. Alternatively, one may reduce the lattice walk problem to a Carleman-type Riemann boundary value problem (RBVP) and solve it via analytic method. In the RBVP framework, two parameters govern the solution: the index the conformal gluing function . In this paper, we propose a combinatorial insight into the RBVP approach. We show that the index corresponds to the canonical factorization in the kernel method. The conformal gluing function can be viewed as a mapping that enables the application of positive term extraction. The combinatorial insight of RBVP establishes a unifying link between the kernel method, the RBVP approach and the Tutte's invariants method.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Combinatorial Mathematics · Advanced Mathematical Theories and Applications · semigroups and automata theory
