We show that counting Euler tours in undirected bounded tree-width graphs is tractable even in parallel -by proving a #SAC 1 ⊆ NC 2 ⊆ P upper bound. This is in stark contrast to #P-completeness of the same problem in general graphs. Our main technical contribution is to show how (an instance of) dynamic programming on bounded clique-width graphs can be performed efficiently in parallel. Thus we show that the sequential result of Espelage, Gurski and Wanke [16] for efficiently computing Hamiltonian paths in bounded clique-width graphs can be adapted in the parallel setting to count the number of Hamiltonian paths which in turn is a tool for counting the number of Euler tours in bounded tree-width graphs. Our technique also yields parallel algorithms for counting longest paths and bipartite perfect matchings in bounded-clique width graphs. While establishing that counting Euler tours in bounded tree-width graphs can be computed by non-uniform monotone arithmetic circuits of polynomial degree (which characterize #SAC 1 ) is relatively easy, establishing a uniform #SAC 1 bound needs a careful use of polynomial interpolation.
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Counting Euler Tours in Undirected Bounded Treewidth Graphs
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