A Generic Convolution Algorithm for Join Operations on Tree Decompositions

Publication date

2021-06-28

Authors

van Rooij, JohanORCID 0000-0001-9149-4162ISNI 0000000395860005

Editors

Santhanam, Rahul
Musatov, Daniil

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

The fast subset convolution algorithm by Björklund et al. (STOC 2007) has made quite an impact on parameterised complexity. Amongst the many applications are dynamic programming algorithms on tree decompositions, where the computations in so-called join nodes are a recurring example of where convolution-like operations are used. As such, several generalisations of the original fast subset convolution algorithm have been proposed, all based on concepts that strongly relate to either Möbius transforms or to Fourier transforms. We present a new convolution generalisation that uses both Möbius transforms and Fourier transforms on the same transformation domain. This results in new faster algorithms on tree decompositions for a broad class of vertex subset problems known as the [ σ, ρ] -domination problems. We solve them in O(st+2tn2(tlog (s) + log (n) ) ) arithmetic operations, where t is the treewidth, s is the (fixed) number of states required to represent partial solutions of the specific problem, and n is the number of vertices in the graph. This improves the previous best bound of O(st+2(st) 2(s-2)n3) arithmetic operations (van Rooij, Bodlaender, Rossmanith, ESA 2009). Specifically, this removes the dependence of the degree of the polynomial on s.

Keywords

Taverne, Theoretical Computer Science, General Computer Science

Citation

van Rooij, J 2021, A Generic Convolution Algorithm for Join Operations on Tree Decompositions. in R Santhanam & D Musatov (eds), CSR 2021: Computer Science – Theory and Applications. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12730 LNCS, Springer, pp. 435-459. https://doi.org/10.1007/978-3-030-79416-3_27