Abstract
We consider weighted counting of independent sets using a rational weight x: Given a graph with n vertices, count its independent sets such that each set of size k contributes x k. This is equivalent to computation of the partition function of the lattice gas with hard-core self-repulsion and hard-core pair interaction. We show the following conditional lower bounds: If counting the satisfying assignments of a 3-CNF formula in n variables (#3SAT) needs time 2Ω(n) (i.e. there is a c > 0 such that no algorithm can solve #3SAT in time 2cn), counting the independent sets of size n/3 of an n-vertex graph needs time 2Ω(n) and weighted counting of independent sets needs time \(2^{\Omega(n/\log^3 n)}\) for all rational weights x ≠ 0.
We have two technical ingredients: The first is a reduction from 3SAT to independent sets that preserves the number of solutions and increases the instance size only by a constant factor. Second, we devise a combination of vertex cloning and path addition. This graph transformation allows us to adapt a recent technique by Dell, Husfeldt, and Wahlén which enables interpolation by a family of reductions, each of which increases the instance size only polylogarithmically.
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Hoffmann, C. (2010). Exponential Time Complexity of Weighted Counting of Independent Sets. In: Raman, V., Saurabh, S. (eds) Parameterized and Exact Computation. IPEC 2010. Lecture Notes in Computer Science, vol 6478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17493-3_18
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DOI: https://doi.org/10.1007/978-3-642-17493-3_18
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