Lecture Notes in Computer Science, 2010, Volume 6198/2010, 426-437, DOI: 10.1007/978-3-642-14165-2_37

Exponential Time Complexity of the Permanent and the Tutte Polynomial
(Extended Abstract)

Holger Dell, Thore Husfeldt and Martin Wahlén

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Abstract

The Exponential Time Hypothesis (ETH) says that deciding the satisfiability of n-variable 3-CNF formulas requires time exp(W(n))\exp(\Omega(n)). We relax this hypothesis by introducing its counting version #ETH, namely that every algorithm that counts the satisfying assignments requires time exp(W(n))\exp(\Omega(n)). We transfer the sparsification lemma for d-CNF formulas to the counting setting, which makes #ETH robust.
Under this hypothesis, we show lower bounds for well-studied #P-hard problems: Computing the permanent of an n×n matrix with m nonzero entries requires time exp(W(m))\exp(\Omega(m)). Restricted to 01-matrices, the bound is exp(W(m/logm))\exp(\Omega(m/\log m)). Computing the Tutte polynomial of a multigraph with n vertices and m edges requires time exp(W(n))\exp(\Omega(n)) at points (x,y) with (x − 1)(y − 1) ≠ 1 and y ∉ {0,±1}. At points (x,0) with x \not Î {0,±1}x \not \in \{0,\pm 1\} it requires time exp(W(n))\exp(\Omega(n)), and if x = − 2, − 3,..., it requires time exp(W(m))\exp(\Omega(m)). For simple graphs, the bound is exp(W(m/log3 m))\exp(\Omega(m/\log^3 m)).

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