A Sublinear Treewidth Exponent for Binary Constraint Satisfaction
Version 1 / Nov 02, 2026 / CC BY 4.0
Abstract
We give a deterministic algorithm for binary constraint satisfaction whose exponent
in the input size is sublinear in treewidth on a class of graphs with unbounded treewidth. There
are a class G of graphs of bounded maximum degree, a constant c, and a function f such that
one algorithm correctly decides every binary CSP instance and, on instances I with primal graph
G ∈ G, runs in time
f(G) · ||I||^(c · tw(G) / sqrt(log tw(G)))
.
This contradicts the literal formulation of Conjecture 1.4 of Marx (2010). The algorithm follows
from a domain-uniform counting bound: for every fixed maximum degree ∆, complete-table in-
stances with k variables and domain size D ≥ 2 can be counted in time LO∆ (1)DO∆ (k/√log k) for
sufficiently large k. The constants are independent of D and of the constraint relations. We obtain
this bound from the tensor-network recursion of Claude (Anthropic), and use attributed graph
foundations from OpenAI to construct the required expander family. Support pruning connects
the counting routine to sparse tuple-list inputs without expanding the original domain. The algo-
rithm, its native finite-alphabet machine implementation, and the conjecture counterexample are
formalized in Lean 4.
Provenance statement
References
- Claude (Anthropic), A time algorithm for -SAT , preprint, October 2026, version 1, October 27, 2026. https://hexagonmath.org/2610.00577v1.hexagon
- Eugene C. Freuder, Complexity of k-tree structured constraint satisfaction problems , Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI), 1990, pp. 4--9. Proceedings paper (https://www.aiinternational.org/Papers/AAAI/1990/AAAI90-001.pdf).link
- Russell Impagliazzo and Ramamohan Paturi, On the complexity of -SAT , Journal of Computer and System Sciences 62 (2001), no. 2, 367--375. doi:10.1006/jcss.2000.1727 (https://doi.org/10.1006/jcss.2000.1727).DOI
- Iyad Kanj and Stefan Szeider, On the subexponential time complexity of CSP , Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013, pp. 459--465. Proceedings paper (https://cdn.aaai.org/ojs/8609/8609-13-12137-1-2-20201228.pdf).link
- Dániel Marx, Can you beat treewidth? , Theory of Computing 6 (2010), 85--112. doi:10.4086/toc.2010.v006a005 (https://doi.org/10.4086/toc.2010.v006a005).DOI
- OpenAI, The Exponential Time Hypothesis is false , preprint and accompanying Lean development, October 25, 2026. OpenAI Math Release preprint (https://github.com/openai/math/tree/main/preprints/The-Exponential-Time-Hypothesis-is-False-October-25-2026).link
- OpenAI, Native exact-counting and satisfiability verification , Lean 4 formalization accompanying the ETH refutation, revision 7ef5c0c , 2026. SqrtLogSpace/Final.lean (https://github.com/openai/math/blob/7ef5c0cc5ca4b0e072b7a050fca09ab24bc6fa3a/lean/OAI/Algorithms/SubexponentialSAT/SqrtLogSpace/Final.lean).link
- Anthropic, Formalization accompanying ``A time algorithm for -SAT'' , Lean 4 source repository, revision 16a5ce4 , 2026. Pinned source repository (https://github.com/anthropics/formal-math/tree/16a5ce41304fcdaea4e0be7c132e1c361dc26da5/eth).link
- OpenAI, Spectral expander and weighted-tree proof foundations , OpenAI mathematics repository, revision 7ef5c0c , 2026. Pinned source repository (https://github.com/openai/math/tree/7ef5c0cc5ca4b0e072b7a050fca09ab24bc6fa3a). The companion GraphPortManifest.json records the exact source blocks and their adaptations.link
Version history
- v1 · 16 pagesSubmitted by Troy Tri NguyenInitial depositCurrentNov 01, 2026