Exponential Time Complexity of Weighted Counting of Independent Sets

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 2^{\Omega(n)} (i.e. there is a c>0 such that no algorithm can solve #3SAT in time 2^{cn}), counting the independent sets of size n/3 of an n-vertex graph needs time 2^{\Omega(n)} and weighted counting of independent sets needs time 2^{\Omega(n/log^3 n)} for all rational weights x\neq 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 Wahlen which enables interpolation by a family of reductions, each of which increases the instance size only polylogarithmically.Comment: Introduction revised, differences between versions of counting independent sets stated more precisely, minor improvements. 14 page

Measuring satisfaction in societies with opinion leaders and mediators

An opinion leader-follower model (OLF) is a two-action collective decision-making model for societies, in which three kinds of actors are considered:Preprin

Exponential Time Complexity of the Permanent and the Tutte Polynomial

We show conditional lower bounds for well-studied #P-hard problems: (a) The number of satisfying assignments of a 2-CNF formula with n variables cannot be counted in time exp(o(n)), and the same is true for computing the number of all independent sets in an n-vertex graph. (b) The permanent of an n x n matrix with entries 0 and 1 cannot be computed in time exp(o(n)). (c) The Tutte polynomial of an n-vertex multigraph cannot be computed in time exp(o(n)) at most evaluation points (x,y) in the case of multigraphs, and it cannot be computed in time exp(o(n/polylog n)) in the case of simple graphs. Our lower bounds are relative to (variants of) the Exponential Time Hypothesis (ETH), which says that the satisfiability of n-variable 3-CNF formulas cannot be decided in time exp(o(n)). We relax this hypothesis by introducing its counting version #ETH, namely that the satisfying assignments cannot be counted in time exp(o(n)). In order to use #ETH for our lower bounds, we transfer the sparsification lemma for d-CNF formulas to the counting setting

Lower bounds on dynamic programming for maximum weight independent set

Publisher Copyright: © 2021 Tuukka Korhonen.We prove lower bounds on pure dynamic programming algorithms for maximum weight independent set (MWIS). We model such algorithms as tropical circuits, i.e., circuits that compute with max and + operations. For a graph G, an MWIS-circuit of G is a tropical circuit whose inputs correspond to vertices of G and which computes the weight of a maximum weight independent set of G for any assignment of weights to the inputs. We show that if G has treewidth w and maximum degree d, then any MWIS-circuit of G has 2Ω(w/d) gates and that if G is planar, or more generally H-minor-free for any fixed graph H, then any MWIS-circuit of G has 2Ω(w) gates. An MWIS-formula is an MWIScircuit where each gate has fan-out at most one. We show that if G has treedepth t and maximum degree d, then any MWIS-formula of G has 2Ω(t/d) gates. It follows that treewidth characterizes optimal MWIS-circuits up to polynomials for all bounded degree graphs and H-minor-free graphs, and treedepth characterizes optimal MWIS-formulas up to polynomials for all bounded degree graphs.Peer reviewe

Measuring satisfaction and power in influence based decision systems

We introduce collective decision-making models associated with influence spread under the linear threshold model in social networks. We define the oblivious and the non-oblivious influence models. We also introduce the generalized opinion leader–follower model (gOLF) as an extension of the opinion leader–follower model (OLF) proposed by van den Brink et al. (2011). In our model we allow rules for the final decision different from the simple majority used in OLF. We show that gOLF models are non-oblivious influence models on a two-layered bipartite influence digraph. Together with OLF models, the satisfaction and the power measures were introduced and studied. We analyze the computational complexity of those measures for the decision models introduced in the paper. We show that the problem of computing the satisfaction or the power measure is #P-hard in all the introduced models even when the subjacent social network is a bipartite graph. Complementing this result, we provide two subfamilies of decision models in which both measures can be computed in polynomial time. We show that the collective decision functions are monotone and therefore they define an associated simple game. We relate the satisfaction and the power measures with the Rae index and the Banzhaf value of an associated simple game. This will allow the use of known approximation methods for computing the Banzhaf value, or the Rae index to their practical computation.Peer ReviewedPostprint (author's final draft

The simple, little and slow things count : on parameterized counting complexity

In this thesis, we study the parameterized complexity of counting problems, as introduced by Flum and Grohe. This area mainly involves questions of the following kind: On inputs x with a parameter k, can we solve a given counting problem in time f(k)*|x|^c for a function f that depends only on k? In the positive case, we call the problem fixed-parameter tractable (fpt). Otherwise, we try to prove its #W[1]-hardness, which is the parameterized analogue of #P-hardness. We introduce a general technique that bridges parameterized counting complexity and the so-called Holant framework. We then apply this technique to the problem of counting perfect matchings (or equivalently, the permanent) subject to structural parameters of the input graph G: On the algorithmic side, we introduce a new tractable structural parameter, namely, the minimal size of an excluded single-crossing minor of G. We complement this by showing that counting perfect matchings is #W[1]-hard when parameterized by the size of an arbitrary excluded minor. Then we turn our attention to counting general subgraphs H other than perfect matchings in a host graph G. Instead of imposing structural parameters on G, we parameterize by the size of H, giving rise to the problems #Sub(C) for fixed graph classes C: For inputs H and G with H in C, we wish to count H-copies in G. Here, C could be the class of matchings, cycles, paths, or any other recursively enumerable class. We give a full dichotomy for these problems: Either #Sub(C) has a polynomial-time algorithm or it is #W[1]-complete. Assuming that FPT and #W[1] do not coincide, we can thus precisely identify the graph classes C for which the subgraph counting problem #Sub(C) admits polynomial-time algorithms. Furthermore, we obtain an unexpected application of our extensions to the Holant framework: We show that, given two unweighted graphs, it is C=P-complete to decide whether they have the same number of perfect matchings. Finally, we prove conditional lower bounds for counting problems under the counting exponential-time hypothesis #ETH. This hypothesis, introduced by Dell et al., asserts that the satisfying assignments to n-variable formulas in 3-CNF cannot be counted in time 2^o(n). Building upon this, we introduce a general technique that allows to derive tight lower bounds for other counting problems, such as counting perfect matchings, the Tutte polynomial, and the matching polynomial.Die vorliegende Arbeit befasst sich mit der parametrisierten Komplexität von Zählproblemen, einem von Flum und Grohe gegründeten Gebiet, in welchem Fragen der folgenden Art betrachtet werden: Können gegebene Probleme auf Eingaben x mit Parameter k in Zeit f(k)*|x|^c gelöst werden, wobei f eine Funktion ist, die nur von k abhängt? Im positiven Falle bezeichnen wir das Problem als parametrisierbar (FPT). Andernfalls versuchen wir typischerweise, dessen #W[1]-Härte zu beweisen - diese lässt sich vereinfachend als ein parametrisiertes Äquivalent der #P-Härte auffassen. Wir führen zunächst eine allgemeine Technik ein, welche die parametrisierte Zählkomplexität mit dem sogenannten Holant-Rahmenwerk verbindet. Anschließend setzen wir diese zum Zählen perfekter Paarungen (oder äquivalent, zur Auswertung der Permanente) unter strukturellen Parametern des Eingabegraphens G ein: Wir zeigen, dass das Zählen perfekter Paarungen parametrisierbar ist durch die minimale Größe eines ausgeschlossenen Minors von G, der höchstens eine Kreuzung besitzt. Dieses algorithmische Resultat komplementieren wir durch die #W[1]-Härte des Zählens perfekter Paarungen, wenn die minimale Größe eines beliebigen ausgeschlossenen Minors als Parameter betrachtet wird. Anschließend widmen wir uns dem Zählen beliebiger Subgraphen H in Graphen G. Anstelle von strukturellen Parametern betrachten wir die Größe von H als Parameter und erhalten hierdurch die Probleme #Sub(C) für feste Graphklassen C: Auf Eingaben H und G mit H in C gilt es, die H-Kopien in G zu zählen. Hierbei kann C die Klasse der Paarungen, Zyklen, Pfade, oder eine beliebige andere Klasse von Graphen darstellen. Wir zeigen eine vollständige Dichotomie für diese Probleme: Das Problem #Sub(C) ist entweder in P oder #W[1]-hart. Unter der gängigen Annahme, dass FPT und #W[1] nicht zusammenfallen, erhalten wir somit eine vollständige Klassifikation der Polynomialzeit-lösbaren Probleme #Sub(C). Weiterhin erhalten wir eine unerwartete Anwendung unserer Erweiterungen des Holant-Rahmenwerks: Wir zeigen die C=P-Vollständigkeit der Frage, ob die Anzahlen perfekter Paarungen in zwei gegebenen ungewichteten Graphen übereinstimmen. Schlussendlich zeigen wir bedingte untere Schranken für Zählprobleme unter der Zählversion der Exponentialzeithypothese #ETH, eingeführt durch Dell et al. Diese postuliert, dass die erfüllenden Belegungen in 3-KNF-Formeln mit n Variablen nicht in Zeit 2^o(n) gezählt werden können. Darauf aufbauend führen wir eine allgemeine Technik ein, die es ermöglicht, scharfe untere Schranken für andere Zählprobleme zu erhalten: Dies umfasst das Zählen perfekter Paarungen, das Tutte-Polynom und das Paarungs-Polynom