On the Satisfaction Probabilities of $k$-CNF Formulas
Till Tantau

TL;DR
This paper characterizes the computational complexity of determining whether the satisfaction probability of a $k$-CNF formula exceeds a threshold, revealing a trichotomy into AC$^0$, NL-complete, or NP-complete cases.
Contribution
It provides a complete classification of the complexity for $k$SAT-Pr$_{>p}$, introducing a new order-theoretic insight and kernelization techniques.
Findings
The problem $k$SAT-Pr$_{>p}$ is in AC$^0$, NL-complete, or NP-complete depending on parameters.
Every set of $k$CNF formulas contains a maximum satisfaction probability formula.
Kernelization and backdoor set characterizations are established for certain cases.
Abstract
The satisfaction probability Pr[] := Pr of a propositional formula is the likelihood that a random assignment makes the formula true. We study the complexity of the problem SAT-Pr = { is a CNF formula | Pr[] > p} for fixed and . While 3SAT-Pr = 3SAT is NP-complete and SAT-Pr is PP-complete, Akmal and Williams recently showed that 3SAT-Pr lies in P and 4SAT-Pr is NP-complete; but the methods used to prove these striking results stay silent about, say, 4SAT-Pr, leaving the computational complexity of SAT-Pr open for most and . In the present paper we give a complete characterization in the form of a trichotomy: SAT-Pr lies in AC, is NL-complete, or is NP-complete. The proof of the trichotomy hinges on a new…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
