Space characterizations of complexity measures and size-space trade-offs in propositional proof systems

We identify two new big clusters of proof complexity measures equivalent up to polynomial and log n factors. The first cluster contains, among others, the logarithm of tree-like resolution size, regularized (that is, multiplied by the logarithm of proof length) clause and monomial space, and clause space, both ordinary and regularized, in regular and tree-like resolution. As a consequence, separating clause or monomial space from the (logarithm of) tree-like resolution size is the same as showing a strong trade-off between clause or monomial space and proof length, and is the same as showing a super-critical trade-off between clause space and depth. The second cluster contains width, Σ2 space (a generalization of clause space to depth 2 Frege systems), both ordinary and regularized, as well as the logarithm of tree-like size in the system R(log). As an application of some of these simulations, we improve a known size-space trade-off for polynomial calculus with resolution. In terms of lower bounds, we show a quadratic lower bound on tree-like resolution size for formulas refutable in clause space 4. We introduce on our way yet another proof complexity measure intermediate between depth and the logarithm of tree-like size that might be of independent interest.

[1]  Alexander A. Razborov,et al.  A New Kind of Tradeoffs in Propositional Proof Complexity , 2016, J. ACM.

[2]  Robert E. Tarjan,et al.  Asymptotically tight bounds on time-space trade-offs in a pebble game , 1982, JACM.

[3]  Eli Ben-Sasson,et al.  Short proofs are narrow—resolution made simple , 2001, JACM.

[4]  Robert E. Tarjan,et al.  Space bounds for a game on graphs , 1976, STOC '76.

[5]  Eli Ben-Sasson,et al.  Size space tradeoffs for resolution , 2002, STOC '02.

[6]  Massimo Lauria,et al.  A note about k-DNF resolution , 2018, Inf. Process. Lett..

[7]  Eli Ben-Sasson,et al.  Understanding Space in Proof Complexity: Separations and Trade-offs via Substitutions , 2011, ICS.

[8]  Jacobo Torán,et al.  A combinatorial characterization of treelike resolution space , 2003, Inf. Process. Lett..

[9]  Michael Alekhnovich,et al.  Space complexity in propositional calculus , 2000, STOC '00.

[10]  Eli Ben-Sasson,et al.  Short Proofs May Be Spacious: An Optimal Separation of Space and Length in Resolution , 2008, 2008 49th Annual IEEE Symposium on Foundations of Computer Science.

[11]  Avi Wigderson,et al.  Superconcentrators, generalizers and generalized connectors with limited depth , 1983, STOC.

[12]  Albert Atserias,et al.  A combinatorial characterization of resolution width , 2003, 18th IEEE Annual Conference on Computational Complexity, 2003. Proceedings..

[13]  Neil Thapen,et al.  Resolution and Pebbling Games , 2005, SAT.

[14]  Maria Luisa Bonet,et al.  Optimality of size-width tradeoffs for resolution , 2001, computational complexity.

[15]  Johan Håstad,et al.  Towards an optimal separation of space and length in resolution , 2008, Theory Comput..

[16]  Jacobo Torán,et al.  Space Bounds for Resolution , 1999, STACS.

[17]  Jochen Messner,et al.  On Minimal Unsatisfiability and Time-Space Trade-offs for k-DNF Resolution , 2009, ICALP.

[18]  Alasdair Urquhart The Depth of Resolution Proofs , 2011, Stud Logica.

[19]  Stephen A. Cook,et al.  The Relative Efficiency of Propositional Proof Systems , 1979, Journal of Symbolic Logic.

[20]  Jakob Nordström,et al.  On the virtue of succinct proofs: amplifying communication complexity hardness to time-space trade-offs in proof complexity , 2012, STOC '12.

[21]  Bruno Loff,et al.  Lifting Theorems for Equality , 2018, Electron. Colloquium Comput. Complex..

[22]  Alexander A. Razborov On Space and Depth in Resolution , 2017, computational complexity.

[23]  Eli Ben-Sasson,et al.  Near Optimal Separation Of Tree-Like And General Resolution , 2004, Comb..

[24]  Stephen A. Cook,et al.  Storage requirements for deterministic / polynomial time recognizable languages , 1974, STOC '74.

[25]  Yuval Filmus,et al.  From Small Space to Small Width in Resolution , 2014, ACM Trans. Comput. Log..

[26]  Russell Impagliazzo,et al.  A lower bound for DLL algorithms for k-SAT (preliminary version) , 2000, SODA '00.

[27]  Ilario Bonacina,et al.  Total Space in Resolution Is at Least Width Squared , 2016, ICALP.

[28]  J. Kraj On the Weak Pigeonhole Principle , 2001 .

[29]  Jakob Nordstr PEBBLE GAMES, PROOF COMPLEXITY, AND TIME-SPACE TRADE-OFFS ∗ , 2013 .

[30]  Jakob Nordström,et al.  Pebble Games, Proof Complexity, and Time-Space Trade-offs , 2013, Log. Methods Comput. Sci..

[31]  Jan Kra,et al.  Lower Bounds to the Size of Constant-depth Propositional Proofs , 1994 .

[32]  Chris Beck,et al.  Some trade-off results for polynomial calculus: extended abstract , 2013, STOC '13.

[33]  Leszek Aleksander Kolodziejczyk,et al.  Polynomial Calculus Space and Resolution Width , 2019, 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS).

[34]  Russell Impagliazzo,et al.  Using the Groebner basis algorithm to find proofs of unsatisfiability , 1996, STOC '96.

[35]  Toniann Pitassi,et al.  Communication lower bounds via critical block sensitivity , 2013, STOC.