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We prove that the propositional translations of the Kneser-Lov\'asz theorem have polynomial size extended Frege proofs and quasi-polynomial size Frege proofs. We present a new counting-based combinatorial proof of the Kneser-Lov\'asz…

We investigate the proof complexity of a class of propositional formulas expressing a combinatorial principle known as the Kneser-Lov\'{a}sz Theorem. This is a family of propositional tautologies, indexed by an nonnegative integer parameter…

Computational Complexity · Computer Science 2018-05-16 Gabriel Istrate , Adrian Crăciun

Does every Boolean tautology have a short propositional-calculus proof? Here, a propositional calculus (i.e. Frege) proof is a proof starting from a set of axioms and deriving new Boolean formulas using a set of fixed sound derivation…

Computational Complexity · Computer Science 2015-09-14 Fu Li , Iddo Tzameret , Zhengyu Wang

We analyse how the standard reductions between constraint satisfaction problems affect their proof complexity. We show that, for the most studied propositional, algebraic, and semi-algebraic proof systems, the classical constructions of…

Computational Complexity · Computer Science 2018-09-26 Albert Atserias , Joanna Ochremiak

We prove superpolynomial length lower bounds for the semantic tree-like Frege refutation system with bounded line size. Concretely, for any function $n^{2-\varepsilon} \leq s(n) \leq 2^{n^{1-\varepsilon}}$ we exhibit an explicit family…

Computational Complexity · Computer Science 2026-05-01 Susanna F. de Rezende , David Engström , Yassine Ghannane , Kilian Risse

Kernelization---a mathematical key concept for provably effective polynomial-time preprocessing of NP-hard problems---plays a central role in parameterized complexity and has triggered an extensive line of research. This is in part due to a…

Computational Complexity · Computer Science 2017-08-28 Henning Fernau , Till Fluschnik , Danny Hermelin , Andreas Krebs , Hendrik Molter , Rolf Niedermeier

A kernelization for a parameterized decision problem $\mathcal{Q}$ is a polynomial-time preprocessing algorithm that reduces any parameterized instance $(x,k)$ into an instance $(x',k')$ whose size is bounded by a function of $k$ alone and…

Data Structures and Algorithms · Computer Science 2023-10-09 Bart M. P. Jansen , Bart van der Steenhoven

In this paper, we investigate the proof complexity of a wide range of substructural systems. For any proof system $\mathbf{P}$ at least as strong as Full Lambek calculus, $\mathbf{FL}$, and polynomially simulated by the extended Frege…

Logic · Mathematics 2020-08-21 Raheleh Jalali

A kernelization algorithm for a computational problem is a procedure which compresses an instance into an equivalent instance whose size is bounded with respect to a complexity parameter. For the Boolean satisfiability problem (SAT), and…

Computational Complexity · Computer Science 2017-06-20 Victor Lagerkvist , Magnus Wahlström

A major open problem in proof complexity is to demonstrate that random 3-CNFs with a linear number of clauses require super-polynomial size refutations in bounded-depth Frege systems. We take the first step towards addressing this question…

Computational Complexity · Computer Science 2024-09-04 Svyatoslav Gryaznov , Navid Talebanfard

Proving proof-size lower bounds for $\mathbf{LK}$, the sequent calculus for classical propositional logic, remains a major open problem in proof complexity. We shed new light on this challenge by isolating the power of structural rules,…

Logic in Computer Science · Computer Science 2026-02-02 Amirhossein Akbar Tabatabai , Raheleh Jalali

We consider the proof complexity of the minimal complete fragment, KS, of standard deep inference systems for propositional logic. To examine the size of proofs we employ atomic flows, diagrams that trace structural changes through a proof…

Logic in Computer Science · Computer Science 2019-03-14 Anupam Das

The technique of kernelization consists in extracting, from an instance of a problem, an essentially equivalent instance whose size is bounded in a parameter k. Besides being the basis for efficient param-eterized algorithms, this method…

Artificial Intelligence · Computer Science 2017-02-09 Clément Carbonnel , Emmanuel Hébrard

Dealing with NP-hard problems, kernelization is a fundamental notion for polynomial-time data reduction with performance guarantees: in polynomial time, a problem instance is reduced to an equivalent instance with size upper-bounded by a…

Data Structures and Algorithms · Computer Science 2022-12-26 Matthias Bentert , René van Bevern , Till Fluschnik , André Nichterlein , Rolf Niedermeier

The propositional planning problem is a notoriously difficult computational problem. Downey et al. (1999) initiated the parameterized analysis of planning (with plan length as the parameter) and B\"ackstr\"om et al. (2012) picked up this…

Data Structures and Algorithms · Computer Science 2013-07-16 Christer Bäckström , Peter Jonsson , Sebastian Ordyniak , Stefan Szeider

In a parameterized problem, every instance I comes with a positive integer k. The problem is said to admit a polynomial kernel if, in polynomial time, one can reduce the size of the instance I to a polynomial in k, while preserving the…

Discrete Mathematics · Computer Science 2013-09-26 Hans L. Bodlaender , Fedor V. Fomin , Daniel Lokshtanov , Eelko Penninkx , Saket Saurabh , Dimitrios M. Thilikos

We introduce a new framework for the analysis of preprocessing routines for parameterized counting problems. Existing frameworks that encapsulate parameterized counting problems permit the usage of exponential (rather than polynomial) time…

Data Structures and Algorithms · Computer Science 2023-08-07 Daniel Lokshtanov , Pranabendu Misra , Saket Saurabh , Meirav Zehavi

We study initial cuts of models of weak two-sorted Bounded Arithmetics with respect to the strength of their theories and show that these theories are stronger than the original one. More explicitly we will see that polylogarithmic cuts of…

Logic in Computer Science · Computer Science 2015-07-01 Sebastian Müller

Kernelization is a general theoretical framework for preprocessing instances of NP-hard problems into (generally smaller) instances with bounded size, via the repeated application of data reduction rules. For the fundamental Max Cut…

Data Structures and Algorithms · Computer Science 2019-05-28 Damir Ferizovic , Demian Hespe , Sebastian Lamm , Matthias Mnich , Christian Schulz , Darren Strash

In this paper we propose a new framework for analyzing the performance of preprocessing algorithms. Our framework builds on the notion of kernelization from parameterized complexity. However, as opposed to the original notion of…

Data Structures and Algorithms · Computer Science 2016-11-07 Daniel Lokshtanov , Fahad Panolan , M. S. Ramanujan , Saket Saurabh
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