Towards an Optimal Separation of Space and Length in Resolution
Jakob Nordstr\"om, Johan H{\aa}stad

TL;DR
This paper investigates the relationship between proof length and space in resolution proofs, providing new bounds and trade-offs that suggest these measures can be independent, with implications for SAT solver efficiency.
Contribution
It proves a tight polynomial lower bound on space for pebbling contradictions and enhances understanding of proof measure separations in resolution.
Findings
Established a Theta(sqrt(n)) space lower bound for pebbling contradictions.
Improved the separation between space and width from logarithmic to polynomial.
Presented new exponential trade-offs between proof length and space in resolution.
Abstract
Most state-of-the-art satisfiability algorithms today are variants of the DPLL procedure augmented with clause learning. The main bottleneck for such algorithms, other than the obvious one of time, is the amount of memory used. In the field of proof complexity, the resources of time and memory correspond to the length and space of resolution proofs. There has been a long line of research trying to understand these proof complexity measures, but while strong results have been proven on length our understanding of space is still quite poor. For instance, it remains open whether the fact that a formula is provable in short length implies that it is also provable in small space or whether on the contrary these measures are unrelated in the sense that short proofs can be arbitrarily complex with respect to space. In this paper, we present some evidence that the true answer should be that…
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Taxonomy
TopicsDigital Image Processing Techniques · Computational Geometry and Mesh Generation · Advanced Vision and Imaging
