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How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

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✓ 1 result · all verified · 0 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 1 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

The Polynomial Hierarchy and Relativization

1 · Prerequisites

2 · Summary

Polynomially bounded quantifiers give a hierarchy of decision classes. The proofs connect those quantifiers to adaptive oracle computations, establish conditional collapse results, and construct two opposite oracle worlds. High and low sets and promise reductions use explicitly separate conventions.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Polynomial hierarchy levels

Definition

All languages are subsets of {0,1}∗. Put Σ0p=Π0p=P as in The class P. For a fixed integer k≥1, L∈Σkp means that a deterministic polynomial-time predicate R and polynomially bounded, polynomial-time computable lengths p1,…,pk satisfy x∈L  ⟺  ∃y1∈{0,1}p1(∣x∣) ∀y2∈{0,1}p2(∣x∣)⋯Qkyk∈{0,1}pk(∣x∣) R(x,y1,…,yk). Here Qj is existential for odd j and universal for even j. Starting universally defines Πkp. Write PH=⋃k≥0Σkp. The level and all polynomials are fixed for a language, not part of the input. Length zero allows the single empty string. Variable-length witnesses can be encoded with a length field and padding; every padded string decodes to a bounded-length string, so universal blocks introduce no invalid-witness exception.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Relativized complexity class

Definition

Fix a total language A⊆{0,1}∗. An oracle machine writes a query word and receives its membership bit in A in one answer step. Query writing counts toward time and the query tape toward space. A polynomial time clock bounds every branch for every oracle. PA and NPA are deterministic and nondeterministic polynomial-time oracle classes, respectively; the latter equivalently uses a polynomial-length witness and a deterministic polynomial-time A-oracle verifier. Use the conventions of The class P and The class NP via polynomial-time verifiers.

For Σkp,A and Πkp,A, replace the deterministic predicate in Polynomial hierarchy levels by a PA predicate; level zero is PA. Define PSPACEA by deterministic polynomial space under the charged-query convention. For a language class D, PD=⋃B∈DPB and NPD=⋃B∈DNPB. Finally Δk+1p=PΣkp. With a fixed base oracle, a machine may query both A and a language B; encode this by the tagged union A⊕B={0x:x∈A}∪{1x:x∈B}.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Ph quantifier block closure

Statement

For each fixed k≥0, both Σkp and Πkp are closed under polynomial-time many-one preimages and polynomially many uniformly indexed conjunctions and disjunctions. Precisely, if the language of pairs (x,i) lies in the class and 0≤i<q(∣x∣) for a polynomial-time computable polynomial bound q, then both “every such i” and “some such i” define languages in that class. Complements interchange Σkp and Πkp, and each is contained in both classes at level k+1. These assertions also hold with one fixed base oracle.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

The levels are defined by a fixed number of alternating polynomial-length string blocks over a uniform polynomial-time predicate. (Polynomial hierarchy levels).

Proof

1.1F1

The bounded-block definition supplies one uniform predicate for (x,i), not a separately chosen machine for each index. A polynomial-time preimage first computes its image; witness lengths can be padded to a polynomial bound in ∣x∣. At level zero all these operations are deterministic polynomial-time loops.

2.1step 1.1algebra

For positive k, conjunctions use a tuple of independent variables at each quantifier block and the conjunction of the matrix tests. The identities (Qa U(a))∧(Qb V(b))  ⟺  Q(a,b)(U(a)∧V(b)) hold for either quantifier over nonempty domains. One verifies the universal identity by fixing an arbitrary value of the other variable, and the existential identity by combining witnesses. Repeated application proves both directions of the tuple construction. A tuple contains only polynomially many polynomial-length strings.

3.1step 2.1algebra

Disjunction follows by complementing a conjunction of complements; this simultaneously proves closure for both starting polarities. Negating a quantified predicate flips every quantifier and negates its deterministic matrix. A zero-term conjunction is true and a zero-term disjunction is false, both deterministic. Length-zero blocks still have one value.

4.1F1step 3.1∎

Append an unused last block for containment in the next level of the same polarity; prepend an unused opposite block for the other polarity. Both preserve truth because binary-string domains are nonempty. The proof copies calls to a fixed base oracle verbatim, so all constructions relativize.

PropositionStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Np and conp are the first levels

Statement

Σ1p=NP and Π1p=coNP.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

First-level existential and universal polynomial-time predicates define the first hierarchy levels. (Polynomial hierarchy levels).

[F2]

NP consists of languages admitting polynomial-time verifiers with polynomially bounded certificates. (The class NP via polynomial-time verifiers).

[F3]

coNP consists of complements of NP languages in the same binary-string universe. (The class coNP).

Proof

1.1F1F2

A first-level existential predicate is a polynomial-time verifier with a polynomial-length certificate, so it defines an NP language. Conversely, encode a bounded-length verifier certificate by a length field and padding; a total decoding onto all allowed certificates preserves existence and gives the first-level predicate. This includes length zero and the empty input.

2.1F3step 1.1∎

Negating that existential formula yields a universal formula for the complement. Conversely negating a universal formula yields an NP verifier. By the definition of coNP these are exactly the languages of Π1p.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Ph circuit matrix final block encoding

Statement

For a fixed polynomial-time Boolean predicate R(x,y), and a polynomial bound on ∣y∣ in ∣x∣, one can construct in time polynomial in ∣x∣ formulas F∃(x;y,z) in 3CNF and F∀(x;y,z) in 3DNF such that, for every allowed y, R(x,y)  ⟺  ∃z F∃(x;y,z)  ⟺  ∀z F∀(x;y,z). Here clauses or terms have at most three literals. Both formula length and ∣z∣ are polynomially bounded.

When the allowed strings have varying lengths at most a fixed bound p(∣x∣), the formula's y-block is a fixed-width encoding: a ⌈log⁡2(p(∣x∣)+1)⌉-bit length field followed by p(∣x∣) payload bits. A length field outside {0,…,p(∣x∣)} decodes to the empty string, and otherwise the decoder returns the indicated initial payload segment. Thus every fixed-width string decodes to an allowed y, every allowed y has an encoding, and R(x,y) in the display means R applied to that decoded string. For a prescribed exact length, use the identity encoding.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

For every fixed deterministic Turing machine M that halts in polynomial time, there is a polynomial-size logspace-uniform Boolean circuit family (Cn) such that Cn(x)=1 exactly when M accepts x∈{0,1}n. (Polynomial-time computations have logspace-uniform circuit families).

[F2]

A Boolean circuit on n inputs is a finite directed acyclic graph with inputs x1,…,xn, constants 0 and 1, and NOT, AND, and OR gates; AND and OR have fan-in two, while NOT has fan-in one. One node is designated as the output. The circuit's value is the value at that node after evaluating the graph in topological order. Its size is its number of non-input gates, and its depth is the largest number of non-input gates on a directed path ending at the output (a path may begin at an input or a constant). If two fixed finite bounded-arity bases can simulate every gate (and every constant) of one another by fixed finite circuits, then changing between them costs only constant factors in size and depth. In particular this holds for any two such functionally complete bases with simulable constants. No such claim is made for an arbitrary finite basis that may fail to express one of the Boolean operations. (Boolean circuits: basis, fan-in, size, and depth).

Proof

1.1F1F2

Compile the fixed machine that first applies the stated total decoder and then evaluates R at the exact encoded-pair length determined by ∣x∣ and the fixed bound; then fix the bits of x. The decoder is polynomial-time and never changes R by silently padding its argument. A halting logspace uniformity procedure on polynomial-length gate indices has polynomially many configurations and hence runs in polynomial time; enumerating the polynomially many gates therefore takes polynomial time. Use the NOT, binary AND/OR and constant basis.

2.1step 1.1algebra

Introduce a variable for every gate output. For z=a∧b, use (¬z∨a)∧(¬z∨b)∧(z∨¬a∨¬b); for z=a∨b, use (z∨¬a)∧(z∨¬b)∧(¬z∨a∨b); for z=¬a, use (z∨a)∧(¬z∨¬a). Constants use unit clauses. If necessary add an output gate copying the designated input via two negations. Let C be the conjunction. Each assignment to the inputs extends uniquely to one assignment satisfying C, by gate order.

3.1step 2.1algebra∎

With output variable o, set F∃=C∧o and F∀=¬(C∧¬o). If R is true, the unique consistent extension witnesses the first formula and every extension satisfies the second. If R is false, no extension satisfies the first and the consistent extension falsifies the second. Negating the 3CNF C∧¬o gives a 3DNF of the same linear size. Constant predicates and zero input bits obey the same construction.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Bounded alternation qbf is level complete

Statement

For every fixed k≥1, truth of prenex Boolean formulas with k alternating blocks beginning existentially is Σkp-complete under polynomial-time many-one reductions. The universally starting version is Πkp-complete. The matrix is a general Boolean formula, empty blocks are allowed, and malformed encodings are rejected.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

All languages are subsets of {0,1}∗. Put Σ0p=Π0p=P as in the stated convention. For a fixed integer k≥1, L∈Σkp means that a deterministic polynomial-time predicate R and polynomially bounded, polynomial-time computable lengths p1,…,pk satisfy x∈L  ⟺  ∃y1∈{0,1}p1(∣x∣) ∀y2∈{0,1}p2(∣x∣)⋯Qkyk∈{0,1}pk(∣x∣) R(x,y1,…,yk). Here Qj is existential for odd j and universal for even j. Starting universally defines Πkp. Write PH=⋃k≥0Σkp. The level and all polynomials are fixed for a language, not part of the input. Length zero allows the single empty string. Variable-length witnesses can be encoded with a length field and padding; every padded string decodes to a bounded-length string, so universal blocks introduce no invalid-witness exception. (Polynomial hierarchy levels).

[F2]

For a fixed polynomial-time Boolean predicate R(x,y), and a polynomial bound on ∣y∣ in ∣x∣, one can construct in time polynomial in ∣x∣ formulas F∃(x;y,z) in 3CNF and F∀(x;y,z) in 3DNF such that, for every allowed y, R(x,y)  ⟺  ∃z F∃(x;y,z)  ⟺  ∀z F∀(x;y,z). Here clauses or terms have at most three literals. Both formula length and ∣z∣ are polynomially bounded. (Ph circuit matrix final block encoding).

[F3]

Let A⊆Σ∗ and B⊆Γ∗ be languages over finite alphabets. A polynomial-time many-one reduction from A to B is a total function f:Σ∗→Γ∗ such that: - f is computable by a deterministic Turing machine in polynomial time, and - for every x∈Σ∗, x∈A  ⟺  f(x)∈B. When such an f exists, write A≤pB. (Polynomial-time many-one reductions).

Proof

1.1F1

Parse the encoding deterministically; reject a malformed word. For a well-formed formula, quantify one polynomial-length assignment string per block and evaluate the matrix in polynomial time. Make the parsing test a conjunction in the matrix, so rejection remains valid for either starting polarity. This proves membership even when blocks have length zero.

1.2F2

Given a language at the desired level, take its fixed defining predicate. For each input x, apply the pointwise encoding to the whole tuple of quantified strings. If its last block is existential, use F∃ and merge z into that block. If it is universal, use F∀ instead. For every assignment to earlier blocks the replacement has exactly the original truth value, so iterating the outer quantifiers preserves truth in both directions.

2.1F3step 1.2∎

There are still k blocks and polynomially many symbols; compilation is polynomial-time. It outputs a well-formed instance on every input, with membership equivalent to the original language, which is exactly the required reduction. The construction applies separately to both starting polarities, including k=1.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Ph adaptive oracle transcript normal form

Statement

For fixed k≥1 and B∈Σkp, every nondeterministic polynomial-time B-oracle computation has a Σk+1p definition. More generally, for a fixed total base oracle A and B∈Σkp,A, polynomial nondeterministic access to both A and B has a Σk+1p,A definition.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

Fix a total language A⊆{0,1}∗. An oracle machine writes a query word and receives its membership bit in A in one answer step. Query writing counts toward time and the query tape toward space. A polynomial time clock bounds every branch for every oracle. PA and NPA are deterministic and nondeterministic polynomial-time oracle classes, respectively; the latter equivalently uses a polynomial-length witness and a deterministic polynomial-time A-oracle verifier. Use the conventions of the stated convention and the stated convention. For Σkp,A and Πkp,A, replace the deterministic predicate in the stated convention by a PA predicate; level zero is PA. Define PSPACEA by deterministic polynomial space under the charged-query convention. For a language class D, PD=⋃B∈DPB and NPD=⋃B∈DNPB. Finally Δk+1p=PΣkp. With a fixed base oracle, a machine may query both A and a language B; encode this by the tagged union A⊕B={0x:x∈A}∪{1x:x∈B}. (Relativized complexity class).

[F2]

For each fixed k≥0, both Σkp and Πkp are closed under polynomial-time many-one preimages and polynomially many uniformly indexed conjunctions and disjunctions. Precisely, if the language of pairs (x,i) lies in the class and 0≤i<q(∣x∣) for a polynomial-time computable polynomial bound q, then both “every such i” and “some such i” define languages in that class. Complements interchange Σkp and Πkp, and each is contained in both classes at level k+1. These assertions also hold with one fixed base oracle. (Ph quantifier block closure).

Proof

1.1F1

Use the oracle-independent polynomial clock to bound the branch string, number and lengths of queries, and the entire transcript. Guess in a first existential block a branch and all answers to B queries. Replay the machine using these answers, making any A calls directly; reject if the replay does not accept. Thus the replay test is in PA.

2.1F2step 1.1

Write B(q)=∃u1∀u2⋯QkukR(q,u1,…,uk) with R∈PA. For each guessed YES answer, guess its u1 in the first block too; its remaining condition starts universally and has k−1 blocks. For each NO answer, use the complementary k-block universal-first formula. Pad YES conditions with an unused last block, and combine the conditions in parallel into k alternating universal-first blocks by tuple conjunction closure. Unused transcript slots impose the constant true condition. At k=1, a YES condition has no remaining quantified variable.

3.1step 2.1algebra∎

An actually accepting branch supplies its correct transcript and YES witnesses, so the constructed formula is true. Conversely a true formula certifies every YES and every NO answer, and the replay is therefore an actual accepting branch. Tuple lengths are polynomial because both query count and query length are polynomially bounded. Prefixing the guessed first block gives exactly k+1 alternating blocks over PA. For the unrelativized assertion take A=∅.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Quantifier and oracle characterizations of ph

Statement

For every k≥0, Σk+1p=NPΣkp,Πk+1p=coNPΣkp,Δk+1p=PΣkp. For k≥1 a fixed complete bounded-alternation QBF language can replace the class oracle. At k=1, this gives the usual satisfiability oracle. The quantifier levels also equal polynomial-time alternating computations with at most k blocks of existential/universal choices, beginning with the indicated polarity. With a fixed base oracle A, the same oracle characterization holds using access to both A and a language in Σkp,A.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

For fixed k≥1 and B∈Σkp, every nondeterministic polynomial-time B-oracle computation has a Σk+1p definition. More generally, for a fixed total base oracle A and B∈Σkp,A, polynomial nondeterministic access to both A and B has a Σk+1p,A definition. (Ph adaptive oracle transcript normal form).

[F2]

For every fixed k≥1, truth of prenex Boolean formulas with k alternating blocks beginning existentially is Σkp-complete under polynomial-time many-one reductions. The universally starting version is Πkp-complete. The matrix is a general Boolean formula, empty blocks are allowed, and malformed encodings are rejected. (Bounded alternation qbf is level complete).

[F3]

Σ1p=NP and Π1p=coNP. (Np and conp are the first levels).

Proof

1.1F1F3

For k≥1, transcript normal form gives NPΣkp⊆Σk+1p. Conversely, guess the first block of a Σk+1p predicate. The remaining language of pairs is in Πkp; query its complementary Σkp language and flip the answer. The two procedures give both inclusions. For k=0, polynomial-time oracle calls can be simulated directly in polynomial time, and the first-level verifier identity gives the result.

2.1F2step 1.1

Every language at positive level reduces to the fixed complete QBF language; replace each adaptive query by its reduction. Query lengths and query counts remain polynomial. Negating the oracle machine's acceptance convention gives the complementary nondeterministic class; the displayed Delta equality is its definition. The first-level complete QBF language is simply formula satisfiability with its assignment block made explicit.

2.2step 1.1algebra

For an alternating machine, replace each existential or universal choice block by a polynomial-length string of its branch choices, ignoring unused bits. Deterministic steps between changes of polarity are simulated by the final predicate. Conversely, realize each quantified string by successive binary choices of the required polarity and then evaluate the predicate. Acceptance at an existential node means some child accepts, and at a universal node every child accepts; recursive evaluation of the finite tree proves the equivalence. Halted branches can be padded with ignored choices.

3.1F1step 1.1∎

The first inclusion and the guess-and-complement-query construction work identically with a fixed base A, using the relative part of transcript normal form. Both the outer machine and its predicate retain access to that same A; this is the claimed relative oracle characterization. It does not assert unrelativized formula completeness for arbitrary A.

PropositionStatement: AI-adaptedProof: AI-adaptedprecheck passverified 2026-09-08 (gpt-6-astra)Open item page →

PH containments and polynomial space

Statement

For every k≥0, Σkp∪Πkp⊆Δk+1p⊆Σk+1p∩Πk+1p. Moreover PH⊆PSPACE, where PSPACE:=⋃c≥1DSPACE(nc), with DSPACE as in The classes DTIME, NTIME, DSPACE, and NSPACE.

Facts & Assumptions

Given: a fixed level k≥0.

[F1]

Hierarchy levels use a fixed number of polynomial-length alternating blocks over a polynomial-time matrix; level zero is P and PH is their union. Polynomial hierarchy levels

[F2]

Δk+1p=PΣkp is a union over fixed total oracle languages, with polynomial clocks counting query writing. Relativized complexity class

[F3]

Complements interchange Σkp and Πkp, and each level-zero language belongs to both first-level classes. Ph quantifier block closure

[F4]

For k≥1 and B∈Σkp, a nondeterministic polynomial-time B-oracle computation has a Σk+1p definition. Ph adaptive oracle transcript normal form

Proof

1.1F2F3construct

For L∈Σkp, query oracle L once on the input. For L∈Πkp, query its complementary Σkp language and flip the answer. Both are deterministic polynomial-time oracle deciders, proving the first containment for every k.

1.2F2F3F4algebra

For k≥1, let L∈PB with B∈Σkp. Its deterministic machine is also a nondeterministic machine, so L∈Σk+1p by [F4]. Reversing its accepting and rejecting outcomes gives a deterministic B-oracle decider for the complement; hence the complement is in Σk+1p as well, and L∈Πk+1p by [F3]. For k=0, replace each query to the fixed P oracle by its polynomial-time decider. Polynomial query lengths and counts keep the total time polynomial, so PP=P, and [F3] places it in both first-level classes.

1.3F1construct

For any language at a fixed quantifier level, evaluate its quantified predicate by enumerating block assignments depth first. Keep one assignment and enumeration counter for each of the finitely many blocks, plus the polynomial workspace of the matrix decider. Existential blocks OR their child values and universal blocks AND them; a length-zero block has the one empty assignment. The resulting finite computation halts on every input, including false predicates. Because the level and length polynomials are fixed for the language, all input and work cells together number at most a polynomial in input length. Level-zero polynomial-time computation also uses polynomial space.

2.1step 1.1step 1.2step 1.3algebra∎

Step 1.3 places each fixed-level language in some DSPACE(nc), hence in the stated PSPACE union. Taking the union over levels gives PH contained in PSPACE, while steps 1.1--1.2 give all displayed level containments.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Collapse at one level propagates

Statement

If k≥1 and Σkp=Πkp, then Σk+1p=Πk+1p=Σkp.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

For each fixed k≥0, both Σkp and Πkp are closed under polynomial-time many-one preimages and polynomially many uniformly indexed conjunctions and disjunctions. Precisely, if the language of pairs (x,i) lies in the class and 0≤i<q(∣x∣) for a polynomial-time computable polynomial bound q, then both “every such i” and “some such i” define languages in that class. Complements interchange Σkp and Πkp, and each is contained in both classes at level k+1. These assertions also hold with one fixed base oracle. (Ph quantifier block closure).

Proof

1.1givenalgebra

A language in Σk+1p has a leading existential block followed by a Πkp predicate on the pair consisting of the input and that block. By hypothesis this single language of pairs has a uniform Σkp definition. Substitute it and merge its first existential block with the leading one. Because k≥1, this gives k blocks with polynomial bounds. No input-dependent selection of machines is made.

2.1F1step 1.1∎

The reverse containment follows by dummy-block padding. Complement the containment just proved; complements interchange the two polarities, and the assumed level is complement closed. Consequently both classes at level k+1 equal Σkp. Zero-length witness blocks remain nonempty domains.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Sigma k equals pi k implies ph collapse

Statement

For fixed k≥1, Σkp=Πkp implies PH=Σkp=Πkp. Also P=NP implies PH=P.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

If k≥1 and Σkp=Πkp, then Σk+1p=Πk+1p=Σkp. (Collapse at one level propagates).

Proof

1.1F1

Start at level k and repeatedly apply the propagation lemma. After each application the next two polarities equal the same class, so the hypothesis needed for the following application holds. By finite induction all levels at least k equal Σkp; lower levels embed by unused quantifier blocks. Taking their union proves the first assertion.

2.1step 1.1given∎

If P=NP, a one-block existential verifier defines a P language, and every P language has an unused existential witness. Deterministic P is complement closed by flipping a halting decider's bit, so Σ1p=Π1p=P. Apply the first assertion at level one. Empty inputs and unused witnesses cause no exception.

CorollaryStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Ph complete language forces collapse

Statement

If a language C∈PH is polynomial-time many-one hard for all of PH, then PH collapses to a finite level. In particular, PH=PSPACE implies such a collapse.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

For each fixed k≥0, both Σkp and Πkp are closed under polynomial-time many-one preimages and polynomially many uniformly indexed conjunctions and disjunctions. Precisely, if the language of pairs (x,i) lies in the class and 0≤i<q(∣x∣) for a polynomial-time computable polynomial bound q, then both “every such i” and “some such i” define languages in that class. Complements interchange Σkp and Πkp, and each is contained in both classes at level k+1. These assertions also hold with one fixed base oracle. (Ph quantifier block closure).

[F2]

For fixed k≥1, Σkp=Πkp implies PH=Σkp=Πkp. Also P=NP implies PH=P. (Sigma k equals pi k implies ph collapse).

[F3]

TQBF lies in PSPACE, and every language in PSPACE polynomial-time many-one reduces to TQBF. Therefore TQBF is PSPACE-complete. (TQBF is PSPACE-complete).

Proof

1.1F1F2

Choose a fixed k≥1 with C∈Σkp, padding upward if necessary. Every L∈Πkp belongs to PH by padding and reduces to C, hence lies in Σkp by preimage closure. Complementing gives the reverse inclusion, so the finite-level collapse theorem applies.

2.1F3step 1.1∎

Under PH=PSPACE, TQBF belongs to PH and every PH language reduces to it, by its exact PSPACE-completeness statement. It therefore serves as C in the first step. No strict containment between PH and PSPACE is assumed.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Standard containments relativize

Statement

For every fixed total oracle A, PA⊆NPA, NPA∪coNPA⊆PSPACEA, and PHA⊆PSPACEA. The verifier characterization, bounded-level oracle characterization, and implication Σkp,A=Πkp,A⇒PHA=Σkp,A for k≥1 all hold using the same A throughout.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

Fix a total language A⊆{0,1}∗. An oracle machine writes a query word and receives its membership bit in A in one answer step. Query writing counts toward time and the query tape toward space. A polynomial time clock bounds every branch for every oracle. PA and NPA are deterministic and nondeterministic polynomial-time oracle classes, respectively; the latter equivalently uses a polynomial-length witness and a deterministic polynomial-time A-oracle verifier. Use the conventions of the stated convention and the stated convention. For Σkp,A and Πkp,A, replace the deterministic predicate in the stated convention by a PA predicate; level zero is PA. Define PSPACEA by deterministic polynomial space under the charged-query convention. For a language class D, PD=⋃B∈DPB and NPD=⋃B∈DNPB. Finally Δk+1p=PΣkp. With a fixed base oracle, a machine may query both A and a language B; encode this by the tagged union A⊕B={0x:x∈A}∪{1x:x∈B}. (Relativized complexity class).

[F2]

For every k≥0, Σk+1p=NPΣkp,Πk+1p=coNPΣkp,Δk+1p=PΣkp. For k≥1 a fixed complete bounded-alternation QBF language can replace the class oracle. At k=1, this gives the usual satisfiability oracle. The quantifier levels also equal polynomial-time alternating computations with at most k blocks of existential/universal choices, beginning with the indicated polarity. With a fixed base oracle A, the same oracle characterization holds using access to both A and a language in Σkp,A. (Quantifier and oracle characterizations of ph).

[F3]

For every k≥0, Σkp∪Πkp⊆Δk+1p⊆Σk+1p∩Πk+1p. Moreover PH⊆PSPACE. (PH containments and polynomial space).

Proof

1.1F1

A polynomially clocked branch is encoded by polynomially many bits; a deterministic A-verifier replays it with the original oracle queries. Conversely a nondeterministic machine guesses the verifier witness and executes that verifier. A deterministic machine is a special case. All query writing is charged.

1.2F2F3

The relative oracle characterization is supplied with access to that same base oracle. For space containment, use the depth-first assignment evaluation from the unrelativized containment proof; each matrix predicate makes only polynomial-length A queries and uses polynomial space including the query tape. Query buffers are reused. This treats both starting polarities and hence NP and coNP as well.

2.1step 1.1step 1.2algebra∎

For collapse, substitute a uniform Σkp,A definition for the inner Πkp,A language of pairs and merge existential blocks. The final predicate still lies in PA; no new oracle is introduced. Complementation flips its answer and preserves A. Iterate this argument over the finite levels, then take their union. Zero-length blocks and immediately halting computations are preserved in each simulation.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Relativizing proof technique

Definition

An argument about complexity classes relativizes if its asserted reasoning remains valid when every machine in it receives the same arbitrary total membership oracle, using the resource conventions of Relativized complexity class. This is a property of an argument, not a claimed algorithm for classifying all proofs.

LemmaStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Oracle diagonalization finite extension

Statement

Let c be a finite partial assignment of membership bits to binary words, and let M be a deterministic oracle machine with a fixed polynomial clock p(n). There exist n≥1 and a finite extension c′ of c such that every total oracle B extending c′ makes MB(1n) disagree with membership in LB={1j:B∩{0,1}j≠∅}.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

Fix a total language A⊆{0,1}∗. An oracle machine writes a query word and receives its membership bit in A in one answer step. Query writing counts toward time and the query tape toward space. A polynomial time clock bounds every branch for every oracle. PA and NPA are deterministic and nondeterministic polynomial-time oracle classes, respectively; the latter equivalently uses a polynomial-length witness and a deterministic polynomial-time A-oracle verifier. Use the conventions of the stated convention and the stated convention. For Σkp,A and Πkp,A, replace the deterministic predicate in the stated convention by a PA predicate; level zero is PA. Define PSPACEA by deterministic polynomial space under the charged-query convention. For a language class D, PD=⋃B∈DPB and NPD=⋃B∈DNPB. Finally Δk+1p=PΣkp. With a fixed base oracle, a machine may query both A and a language B; encode this by the tagged union A⊕B={0x:x∈A}∪{1x:x∈B}. (Relativized complexity class).

Proof

1.1F1

Choose n larger than every committed word length, with 2n>p(n). Such integers exist: for a fixed degree a, the ratio (n+1)a/2n+1 divided by na/2n tends to 1/2, and is eventually bounded below one, so any polynomial is eventually smaller than 2n. Simulate the clocked machine; answer committed queries consistently and commit every previously unassigned queried word to NO. The clock bounds both query length and count.

2.1step 1.1algebra

If it accepts, commit all n-bit words to NO. If it rejects (including clock expiration), choose an unqueried n-bit word and commit it to YES, committing every other n-bit word to NO. There is an unqueried word because fewer than 2n queries occurred and no earlier commitment had length n. Each extension is finite and consistent.

3.1step 2.1algebra∎

Every total extension retains all answers on the simulated path, including queries longer than n, so the deterministic path is unchanged. In the accepting case 1n∉LB; in the rejecting case 1n∈LB. Thus both outcomes defeat the machine for every total extension.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

An oracle separates p from np

Statement

There is a total oracle B for which PB≠NPB. In fact LB={1n:B∩{0,1}n≠∅} lies in NPB∖PB.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

Let c be a finite partial assignment of membership bits to binary words, and let M be a deterministic oracle machine with a fixed polynomial clock p(n). There exist n≥1 and a finite extension c′ of c such that every total oracle B extending c′ makes MB(1n) disagree with membership in LB={1j:B∩{0,1}j≠∅}. (Oracle diagonalization finite extension).

Proof

1.1F1

Enumerate all deterministic oracle programs paired with clocks (n+2)a+a, for positive integers a. Every polynomial-time oracle decider agrees with some clocked program for its oracle. Starting with no commitments, apply the finite-extension lemma once to each pair, always preserving all prior commitments. Let B have precisely the words ever assigned YES; all other words receive NO. This is a consistent total extension of every stage.

2.1F1step 1.1∎

At the assigned input the corresponding clocked program fails by the lemma, so no polynomial-time B decider decides LB. A nondeterministic machine rejects nonunary inputs, guesses one n-bit word on 1n, and asks whether it belongs to B. It accepts exactly LB within polynomial time; at n=0 it queries the empty word. Thus the separation follows.

LemmaStatement: AI-adaptedProof: AI-adaptedaudited 2026-09-07Open item page →

Polynomial space oracle absorption

Statement

NPTQBF⊆PSPACE⊆PTQBF.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

Fix a total language A⊆{0,1}∗. An oracle machine writes a query word and receives its membership bit in A in one answer step. Query writing counts toward time and the query tape toward space. A polynomial time clock bounds every branch for every oracle. PA and NPA are deterministic and nondeterministic polynomial-time oracle classes, respectively; the latter equivalently uses a polynomial-length witness and a deterministic polynomial-time A-oracle verifier. Use the conventions of the stated convention and the stated convention. For Σkp,A and Πkp,A, replace the deterministic predicate in the stated convention by a PA predicate; level zero is PA. Define PSPACEA by deterministic polynomial space under the charged-query convention. For a language class D, PD=⋃B∈DPB and NPD=⋃B∈DNPB. Finally Δk+1p=PΣkp. With a fixed base oracle, a machine may query both A and a language B; encode this by the tagged union A⊕B={0x:x∈A}∪{1x:x∈B}. (Relativized complexity class).

[F2]

The class PSPACE is the union of all deterministic polynomial-space classes: PSPACE:=⋃p polynomialDSPACE(p(n)). The class NPSPACE is the union of all nondeterministic polynomial-space classes: NPSPACE:=⋃p polynomialNSPACE(p(n)). Equivalently, a language L lies in PSPACE when there is a deterministic multitape Turing machine deciding L using at most O(nc) space for some constant c, and similarly L lies in NPSPACE when there is such a nondeterministic decider. The meanings of DSPACE(s(n)) and NSPACE(s(n)) are those of the stated convention. (The classes PSPACE and NPSPACE).

[F3]

TQBF lies in PSPACE, and every language in PSPACE polynomial-time many-one reduces to TQBF. Therefore TQBF is PSPACE-complete. (TQBF is PSPACE-complete).

Proof

1.1F1F3F2

For a nondeterministic oracle machine with clock p(n), enumerate all branch-choice strings of the bounded length and replay each branch. Each TQBF query has length at most p(n) under the charged-query convention. Decide it by the polynomial-space algorithm supplied by TQBF membership in PSPACE, then reuse that workspace. A branch counter, a machine configuration and the query workspace all have polynomial size; accepting when one replay accepts yields a deterministic polynomial-space decider. Zero-query branches use the same procedure.

2.1F3∎

For any PSPACE language, its polynomial-time many-one reduction to TQBF computes one polynomial-length query. Accept exactly when the oracle answers YES. This is a deterministic polynomial-time oracle decider on every input, proving the other containment.

TheoremStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

An oracle collapses p and np

Statement

For A=TQBF, PA=NPA=PSPACE.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

NPTQBF⊆PSPACE⊆PTQBF. (Polynomial space oracle absorption).

Proof

1.1F1

Oracle absorption supplies PSPACE⊆PA and NPA⊆PSPACE. A deterministic oracle computation is a nondeterministic one with no choices, so PA⊆NPA.

2.1step 1.1algebra∎

The inclusions form a closed chain, giving equality of all three classes. The same fixed total TQBF language is used throughout; it is not required to belong to P.

CorollaryStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Relativization alone cannot resolve p versus np

Statement

Neither an argument for P=NP nor an argument for P≠NP can be valid unchanged relative to every total oracle.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

An argument about complexity classes relativizes if its asserted reasoning remains valid when every machine in it receives the same arbitrary total membership oracle, using the resource conventions of the stated convention. This is a property of an argument, not a claimed algorithm for classifying all proofs. (Relativizing proof technique).

[F2]

There is a total oracle B for which PB≠NPB. In fact LB={1n:B∩{0,1}n≠∅} lies in NPB∖PB. (An oracle separates p from np).

[F3]

For A=TQBF, PA=NPA=PSPACE. (An oracle collapses p and np).

Proof

1.1F1F2

By the definition of relativization, an argument for equality with this property would prove PB=NPB for every total B. The separating oracle supplies a counterinstance.

2.1F1F3∎

An argument for inequality with this property would prove PA≠NPA for every total A. The TQBF oracle instead gives equality. These two obstructions concern the property of the argument, and imply neither an unrelativized equality nor an unrelativized separation.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Lowness and highness

Definition

For a language A∈NP and an integer k≥0, define Lowk={A∈NP:Σkp,A=Σkp},Highk={A∈NP:Σkp,A=Σkp,SAT}. The relativized levels and Σ0p,A=PA use Relativized complexity class; SAT denotes satisfiability of general Boolean formulas, the first-level complete language supplied in Quantifier and oracle characterizations of ph. At k=0 the highness benchmark is PSAT; no identification of that class with NP is assumed. At positive levels the oracle characterization identifies Σkp,SAT with Σk+1p. More generally, lowness for a specified oracle machine class C means CA=C. Highness here concerns polynomial-time oracle access, not many-one completeness or computability-theoretic jumps.

PropositionStatement: AI-adaptedProof: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Elementary high low identities

Statement

For the NP high/low classes, Low0=P, Low1=NP∩coNP, and High0 consists exactly of NP languages polynomial-time Turing complete for NP. Both Lowk⊆Lowk+1 and Highk⊆Highk+1 hold for every k≥0.

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

For a language A∈NP and an integer k≥0, define Lowk={A∈NP:Σkp,A=Σkp},Highk={A∈NP:Σkp,A=Σkp,SAT}. The relativized levels and Σ0p,A=PA use the stated convention; SAT denotes satisfiability of general Boolean formulas, the first-level complete language supplied in the stated convention. At k=0 the highness benchmark is PSAT; no identification of that class with NP is assumed. At positive levels the oracle characterization identifies Σkp,SAT with Σk+1p. More generally, lowness for a specified oracle machine class C means CA=C. Highness here concerns polynomial-time oracle access, not many-one completeness or computability-theoretic jumps. (Lowness and highness).

[F2]

Σ1p=NP and Π1p=coNP. (Np and conp are the first levels).

[F3]

For fixed k≥1 and B∈Σkp, every nondeterministic polynomial-time B-oracle computation has a Σk+1p definition. More generally, for a fixed total base oracle A and B∈Σkp,A, polynomial nondeterministic access to both A and B has a Σk+1p,A definition. (Ph adaptive oracle transcript normal form).

Proof

1.1F1

If PA=P, one query decides A, so A∈P. Conversely a P decider for A replaces each of polynomially many polynomial-length queries, giving PA=P. This proves the level-zero low identity under the restriction A∈NP.

1.2F2F3

If NPA=NP, deterministic queries decide both A and its complement in NPA, so A∈NP∩coNP. Conversely assume both have NP verifiers. Guess an accepting branch and its adaptive query transcript, and an appropriate NP witness for every YES or NO answer. Deterministic replay and verification accepts exactly the real accepting transcripts; the total certificate length is polynomial. Therefore NPA⊆NP, while ignoring the oracle gives the reverse containment. The first-level identity identifies this with lowness at level one.

1.3F1

Every A∈NP has a polynomial-time many-one reduction to SAT, so PA⊆PSAT. Equality implies SAT∈PA, which implies every NP language belongs to PA by composing its SAT reduction. Conversely that Turing completeness gives SAT∈PA and allows every SAT query to be simulated using A, proving PSAT⊆PA. These reductions use the first-level complete language in the highness convention.

2.1F1F3step 1.2∎

For k≥1, the relative oracle characterization gives Σk+1p,A=NPΣkp,A: the base oracle may be absorbed into the inner language by a tagged union, since A∈PA⊆Σkp,A and that class is closed under tagged unions. For k=0 the same identity holds as NPPA=NPA, by replacing each PA subroutine with its deterministic oracle simulation. Thus equality of the inner classes, either with the unrelativized class or with the SAT-relativized class, propagates one level. This proves both nestings, including the zero-to-one transition. Empty transcripts and constant oracles are included by these simulations.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Promise problem

Definition

A promise problem is a pair (Y,N) of disjoint subsets of {0,1}∗. Its promise is Y∪N. A deterministic solver must accept every word of Y and reject every word of N, with either answer allowed elsewhere. The pair belongs to PromiseP if such a solver has a polynomial time bound on every input.

It belongs to PromiseNP if there are a polynomial p and a deterministic polynomial-time predicate V(x,w) such that every x∈Y has some w with ∣w∣≤p(∣x∣) and V(x,w)=1, whereas for every x∈N every such w has V(x,w)=0. The promise need not be decidable; either side or both sides may be empty. When Y∪N={0,1}∗, this is the ordinary language decision convention.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Promise preserving reduction

Definition

For promise problems (Y,N) and (Y′,N′) in Promise problem, a polynomial-time many-one promise reduction is a total polynomial-time function f satisfying f(Y)⊆Y′ and f(N)⊆N′. There is no condition on f outside Y∪N.

A polynomial-time oracle promise reduction is a polynomially clocked deterministic oracle machine M which solves (Y,N) for every total language B satisfying Y′⊆B and B∩N′=∅. This uses binary, consistent membership completions: an off-promise word may have either bit, but repeated queries to that word receive the same bit. The clock is uniform over all completions.

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Oracle and promise conventions are distinct

Statement

A total membership oracle in Relativized complexity class fixes the answer on every query word. A promise target in Promise preserving reduction describes a collection of total completions. Correctness of a promise reduction must hold for each completion, including its arbitrary answers outside the target promise. A promised input to the caller does not by itself guarantee that the caller's queries satisfy the target promise.

5 · Examples, counterexamples and false statements

False statementConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Relativized separations prove unrelativized separations

Statement

False inference schema: a separation PB≠NPB for one total oracle can be transferred independently of the oracle, yielding PA≠NPA for every total oracle A (and in particular for the empty oracle).

Facts & Assumptions

Given: the objects and hypotheses in the statement above.

[F1]

There is a total oracle B for which PB≠NPB. In fact LB={1n:B∩{0,1}n≠∅} lies in NPB∖PB. (An oracle separates p from np).

[F2]

For A=TQBF, PA=NPA=PSPACE. (An oracle collapses p and np).

Refutation

1.1F1

There exists a total B with PB≠NPB, so the premise of the proposed rule is realized.

2.1F2step 1.1∎

For A=TQBF, however, PA=NPA. This violates the universally quantified conclusion and refutes the rule. The isolated implication from the separating world to P≠NP is not here called a known false proposition: determining its truth would require settling the unrelativized question.

Remark

The refutation supplies total oracles B and A=TQBF with PB≠NPB and PA=NPA, respectively. These are counterinstances to the universal transfer rule; no conclusion about the empty oracle follows.

Sources