Motivation
Descriptive complexity asks whether complexity classes can be characterized by logics, without reference to machines. Immerman and Vardi (1982) showed that on ordered finite structures, first-order logic with a least fixed-point operator expresses exactly the polynomial-time queries. On unordered structures, such as graphs given only up to isomorphism, an algorithm must not depend on an arbitrary ordering of the input, and whether some logic captures polynomial time there is a central open question (Chandra–Harel 1982, Gurevich 1988).
Choiceless polynomial time with counting (CPT), introduced by Blass, Gurevich and Shelah (1999), was for decades the strongest candidate: it computes with hereditarily finite sets built over the input elements, can count, and is invariant under automorphisms by construction. Blass, Gurevich and Shelah conjectured that CPT is still a proper fragment of polynomial time. This mission concerns a proof of that conjecture.
Timeline
- 1982. Immerman and Vardi capture polynomial time on ordered structures by fixed-point logic (doi:10.1145/800070.802187, doi:10.1145/800070.802186); Chandra and Harel raise the unordered question (doi:10.1016/0022-0000(82)90012-5).
- 1988. Gurevich formulates the question of a logic capturing polynomial time and conjectures that none exists.
- 1992. Cai, Fürer and Immerman construct polynomial-time graph queries beyond fixed-point logic with counting (doi:10.1007/BF01305232).
- 1999, 2002. Blass, Gurevich and Shelah introduce choiceless polynomial time and study CFI and linear-algebra instances as potential separating examples (doi:10.1016/S0168-0072(99)00005-6, doi:10.2178/jsl/1190150152).
- 2000. Shelah claims noncapture for counting extensions; later accounts continue to list the problem as open.
- 2008. Dawar, Richerby and Rossman show that CFI queries over ordered base graphs are CPT-definable, and that bounded-rank CPT with counting fails on them (doi:10.1016/j.apal.2007.11.011).
- 2010–2023. Rossman and Pago prove functional lower bounds for CPT (no construction of hyperplanes, no fine preorders on hypercubes) (doi:10.1007/978-3-642-15025-8_28, doi:10.4230/LIPIcs.CSL.2021.33); Grädel, Pakusa, Schalthöfer and Kaiser characterize CPT by iterated first-order interpretations (doi:10.1109/LICS.2015.68).
- 2025. Dawar, Grädel, Kullmann and Pago still record the capture problem as open (doi:10.4230/LIPIcs.MFCS.2025.40).
The source of this mission is an OpenAI preprint dated September 23, 2026.
Setting
Fix the field F=F3 and the vocabulary of eight binary relation symbols τ={Ed,Cf,EB,VB,I,Z0,Z1,Z2}. For a finite τ-structure A put
Y={y:Ed(y,y)},X={a:Cf(a,a)},Xt={a∈X:VB(t,a)} (t∈X),
C(y,a)=x∈Y, I(a,x)∑ δ∈F, Zδ(y,x)∑δ.
With unknowns (λa)a∈X and (μy)y∈Y (separate families), the system consists of
a∈Xt∑λa=1(t∈X),μy=a∈Xt∑λaC(y,a)
for every (t,y)∈X×Y such that some a∈Xt and x∈Y satisfy I(a,x) and EB(y,x). The query Q(A) says this system is consistent over F3. No promise is imposed on the input.
A CPT program is a fixed finite set of rules that updates dynamic functions whose values are hereditarily finite sets over the atoms of A, using pairing, union, comprehension, equality, membership, the input relations, and the cardinality operation (which returns a von Neumann ordinal). A program defines Q if for fixed polynomials T,S, on every input of size n it halts within T(n) steps, touches at most S(n) hereditarily finite objects, and accepts exactly when Q(A) holds. No bound on set rank is imposed.
Formalization targets
Goal: Theorem 1
Q is isomorphism-invariant,Q∈P (from an ordered encoding),Q∈/CPT.
The Lean statement OAI.CPTSeparation.main is the conjunction of these three clauses. It is open on the platform.
Significance
The theorem confirms the Blass–Gurevich–Shelah noncapture conjecture for the full counting formalism: CPT does not capture polynomial time on unordered structures. It removes the leading candidate logic from Gurevich's question, which itself remains open. Because Q is expressible in fixed-point logic with a solvability or rank operator over F3 (Corollary 3, p. 3), it also shows that neither of those logics is contained in CPT. The lower bound holds for programs of arbitrary set rank, unlike the bounded-rank lower bounds of Dawar–Richerby–Rossman.
The result is proved in an OpenAI preprint, which has not been peer reviewed. No machine-checked proof exists.
Difficulty
The polynomial-time upper bound is Gaussian elimination. The obstacle is the lower bound against every CPT program, including those that build sets of unbounded rank. Bounded-variable counting games handle fixed-point logic with counting but do not by themselves control CPT, which is strictly stronger (it decides CFI queries over ordered base graphs). Rank-dependent support arguments give lower bounds only for each fixed rank. The paper needs support bounds independent of rank, for which it uses a nonabelian automorphism group acting on grid structures, then a counting equivalence for all supported objects, and finally a transfer to complete computations via an interpretation characterization of CPT.
Formalization scope
Input A gives a Boolean-valued binary relation for each Symbol (Ed, Cf, EB, VB, I, Z δ with δ : ZMod 3). Input.query is the existence of λ, μ satisfying the normalization and consistency equations exactly as above; an empty system is consistent.
OrdinaryPolynomialTime asks for a function on ordered tables and a Turing.TM2ComputableInPolyTime machine with finite alphabets computing it from the cell-by-cell table encoding, agreeing with the query for every ordering of every structure.
FullCPT defines terms and rules over hereditarily finite sets (Lists quotient), a state of finitely many nonempty locations, synchronous consistent updates, halt/accept flags, and the set of occurring objects (active elements plus roots of evaluated terms). EvaluationDefinable Q asks for one program and polynomials time, space that accept exactly the inputs satisfying Q, halting within time and with at most space occurring objects.
- This is the original operational formulation; the paper's proof passes through the interpretation characterization of CPT (Grädel–Pakusa–Schalthöfer–Kaiser), which a formal proof must either formalize or bypass.
A complete development needs: hereditarily finite sets and automorphism actions on them, support theory, counting equivalence games, the grid structures with their automorphism group, and a CPT-to-interpretation translation. Contributions formalizing Proposition 2 (polynomial-time decidability), Proposition 8 (small-orbit support bound), Proposition 13 (quantitative homogeneity) and Theorem 14 (transfer through small supports) are welcome.
Selected references
- OpenAI, Choiceless polynomial time with counting does not capture polynomial time, preprint, September 23, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Choiceless-polynomial-time-with-counting-does-not-capture-polynomial-time-September-23-2026/paper.pdf
- A. Blass, Y. Gurevich, S. Shelah, Choiceless polynomial time, Ann. Pure Appl. Logic, 1999. https://doi.org/10.1016/S0168-0072(99)00005-6
- A. Blass, Y. Gurevich, S. Shelah, On polynomial time computation over unordered structures, J. Symbolic Logic, 2002. https://doi.org/10.2178/jsl/1190150152
- J.-Y. Cai, M. Fürer, N. Immerman, An optimal lower bound on the number of variables for graph identification, Combinatorica, 1992. https://doi.org/10.1007/BF01305232
- A. Dawar, D. Richerby, B. Rossman, Choiceless polynomial time, counting and the Cai–Fürer–Immerman graphs, Ann. Pure Appl. Logic, 2008. https://doi.org/10.1016/j.apal.2007.11.011
- E. Grädel, W. Pakusa, S. Schalthöfer, Ł. Kaiser, Characterising choiceless polynomial time with first-order interpretations, LICS, 2015. https://doi.org/10.1109/LICS.2015.68
- B. Rossman, Choiceless computation and symmetry, 2010. https://doi.org/10.1007/978-3-642-15025-8_28
- B. Pago, Choiceless computation and symmetry: limitations of definability, CSL, 2021. https://doi.org/10.4230/LIPIcs.CSL.2021.33
- N. Immerman, Relational queries computable in polynomial time, STOC, 1982. https://doi.org/10.1145/800070.802187
- A. K. Chandra, D. Harel, Structure and complexity of relational queries, J. Comput. System Sci., 1982. https://doi.org/10.1016/0022-0000(82)90012-5