Conjecture · version 3

P ≠ NP

Statement

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

Assumptions

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope

The conjectural negative answer to the same canonical question.

Evidence

Connections

In this problem · publication v13 · Selected context

P versus NP →

Alternative answer · Open

Equality and inequality are competing answers to one question, not separate canonical Problems.

Separation is the alternative answer to the same P versus NP question.

One-way implication

Nonuniform general NP circuit lower bounds would suffice for P ≠ NP.

The reverse implication is not established; restricted gates or larger target classes do not satisfy this premise.

Details & sources
NP lacks polynomial-size general circuits →

Open · version 2

NP is not contained in P/poly.

  • Nonuniform families of polynomial-size unrestricted Boolean circuits.

Scope: A stronger circuit-complexity target than P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

General NP circuit lower bounds would separate P and NP →

Relationship statement · Proved · version 2

If NP is not contained in P/poly, then P ≠ NP.

  • Uniform polynomial-time algorithms have polynomial-size nonuniform circuits.

Scope: A one-direction sufficient condition; the converse is not established.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

Separating NP from coNP would also separate P from NP.

The converse is not established; short proofs in one particular proof system are a narrower question.

Details & sources
NP ≠ coNP →

Open · version 2

NP and coNP are distinct.

  • Classical NP and complements of NP languages.

Scope: A stronger related separation; not equivalent to P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

NP versus coNP would separate P and NP →

Relationship statement · Proved · version 2

If NP ≠ coNP, then P ≠ NP.

  • P is closed under complementation.

Scope: The implication does not establish its premise.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

Average-case one-wayness is a stronger sufficient hardness premise.

P ≠ NP alone does not establish one-way functions or the security of a particular cryptosystem.

Details & sources
Standard one-way functions exist →

Open · version 2

There exists a polynomial-time-computable function that is hard to invert on average for probabilistic polynomial-time algorithms.

  • The standard asymptotic cryptographic definition, efficient sampling and polynomially bounded encodings.

Scope: Average-case cryptographic hardness; stronger than merely worst-case NP hardness.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

One-way functions would separate P and NP →

Relationship statement · Proved · version 2

If standard one-way functions exist, then P ≠ NP.

  • Standard polynomially bounded one-way functions; classical polynomial-time computation.

Scope: The reverse implication is not established; P ≠ NP alone is not a security guarantee.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

ETH rules out even subexponential 3SAT algorithms in the stated model.

P ≠ NP does not by itself establish exponential runtime lower bounds.

Details & sources
Exponential Time Hypothesis →

Open · version 2

3SAT cannot be decided in deterministic time 2^{o(n)} times a polynomial in the input length, where n is the number of variables.

  • Classical deterministic algorithms; finite CNF input; parameter is variables, not encoded bit length.

Scope: A stronger quantitative hypothesis than P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

ETH would separate P and NP →

Relationship statement · Proved · version 2

If ETH holds, then P ≠ NP.

  • ETH in the stated variable-parameter deterministic model; 3SAT is NP-complete.

Scope: A sufficient stronger hardness hypothesis; P ≠ NP does not establish ETH.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

The cited randomized SETH excludes even fixed-base exponential improvements for some clause width, and therefore excludes polynomial deterministic algorithms.

This version is stronger than deterministic SETH; neither is implied by P ≠ NP.

Details & sources
Strong Exponential Time Hypothesis — randomized version →

Open · version 2

For every fixed α in (0,1), there is a fixed clause width k such that k-CNF-SAT on n variables has no bounded-error randomized O(2^{αn})-time algorithm.

  • The bounded-error randomized convention explicitly used in Cygan et al., §1; width k depends on α.
  • Parameter is the number of variables; fixed-width formulas can be normalized to polynomial input length.

Scope: A fine-grained hardness premise stronger than the deterministic version; neither version follows from P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

Randomized SETH would separate P and NP →

Relationship statement · Proved · version 2

If the stated bounded-error randomized SETH holds, then P ≠ NP.

  • The stated SETH formulation; deterministic algorithms are a special case of bounded-error randomized algorithms; fixed-width SAT is in NP.

Scope: Only a sufficient stronger premise; P ≠ NP gives no such exponent or randomized lower bound.

Relationship not independently reviewed.

Connection in P versus NP →

Analogue

VP versus VNP is an algebraic complexity analogue, with field operations and polynomial families.

No equivalence or implication to the classical Boolean question is asserted.

Details & sources
VP versus VNP →

Open · version 2

Over a field of characteristic zero, VP and VNP are distinct.

  • Polynomial families with polynomially bounded degree; nonuniform algebraic circuits; arithmetic operation complexity over the field.

Scope: An algebraic analogue; no equivalence to Boolean P versus NP is asserted.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

Relationship not independently reviewed.

Connection in P versus NP →

Relationship not independently reviewed. This concerns its use in this problem.

In this problem · publication v14

P versus NP →

Alternative answer · Open

Equality and inequality are competing answers to one question, not separate canonical Problems.

Separation is the alternative answer to the same P versus NP question.

One-way implication

Nonuniform general NP circuit lower bounds would suffice for P ≠ NP.

The reverse implication is not established; restricted gates or larger target classes do not satisfy this premise.

Details & sources
NP lacks polynomial-size general circuits →

Open · version 2

NP is not contained in P/poly.

  • Nonuniform families of polynomial-size unrestricted Boolean circuits.

Scope: A stronger circuit-complexity target than P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

General NP circuit lower bounds would separate P and NP →

Relationship statement · Proved · version 2

If NP is not contained in P/poly, then P ≠ NP.

  • Uniform polynomial-time algorithms have polynomial-size nonuniform circuits.

Scope: A one-direction sufficient condition; the converse is not established.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

Separating NP from coNP would also separate P from NP.

The converse is not established; short proofs in one particular proof system are a narrower question.

Details & sources
NP ≠ coNP →

Open · version 2

NP and coNP are distinct.

  • Classical NP and complements of NP languages.

Scope: A stronger related separation; not equivalent to P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

NP versus coNP would separate P and NP →

Relationship statement · Proved · version 2

If NP ≠ coNP, then P ≠ NP.

  • P is closed under complementation.

Scope: The implication does not establish its premise.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

Average-case one-wayness is a stronger sufficient hardness premise.

P ≠ NP alone does not establish one-way functions or the security of a particular cryptosystem.

Details & sources
Standard one-way functions exist →

Open · version 2

There exists a polynomial-time-computable function that is hard to invert on average for probabilistic polynomial-time algorithms.

  • The standard asymptotic cryptographic definition, efficient sampling and polynomially bounded encodings.

Scope: Average-case cryptographic hardness; stronger than merely worst-case NP hardness.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

One-way functions would separate P and NP →

Relationship statement · Proved · version 2

If standard one-way functions exist, then P ≠ NP.

  • Standard polynomially bounded one-way functions; classical polynomial-time computation.

Scope: The reverse implication is not established; P ≠ NP alone is not a security guarantee.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

ETH rules out even subexponential 3SAT algorithms in the stated model.

P ≠ NP does not by itself establish exponential runtime lower bounds.

Details & sources
Exponential Time Hypothesis →

Open · version 2

3SAT cannot be decided in deterministic time 2^{o(n)} times a polynomial in the input length, where n is the number of variables.

  • Classical deterministic algorithms; finite CNF input; parameter is variables, not encoded bit length.

Scope: A stronger quantitative hypothesis than P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

ETH would separate P and NP →

Relationship statement · Proved · version 2

If ETH holds, then P ≠ NP.

  • ETH in the stated variable-parameter deterministic model; 3SAT is NP-complete.

Scope: A sufficient stronger hardness hypothesis; P ≠ NP does not establish ETH.

Relationship not independently reviewed.

Connection in P versus NP →

One-way implication

The cited randomized SETH excludes even fixed-base exponential improvements for some clause width, and therefore excludes polynomial deterministic algorithms.

This version is stronger than deterministic SETH; neither is implied by P ≠ NP.

Details & sources
Strong Exponential Time Hypothesis — randomized version →

Open · version 2

For every fixed α in (0,1), there is a fixed clause width k such that k-CNF-SAT on n variables has no bounded-error randomized O(2^{αn})-time algorithm.

  • The bounded-error randomized convention explicitly used in Cygan et al., §1; width k depends on α.
  • Parameter is the number of variables; fixed-width formulas can be normalized to polynomial input length.

Scope: A fine-grained hardness premise stronger than the deterministic version; neither version follows from P ≠ NP.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

Randomized SETH would separate P and NP →

Relationship statement · Proved · version 2

If the stated bounded-error randomized SETH holds, then P ≠ NP.

  • The stated SETH formulation; deterministic algorithms are a special case of bounded-error randomized algorithms; fixed-width SAT is in NP.

Scope: Only a sufficient stronger premise; P ≠ NP gives no such exponent or randomized lower bound.

Relationship not independently reviewed.

Connection in P versus NP →

Analogue

VP versus VNP is an algebraic complexity analogue, with field operations and polynomial families.

No equivalence or implication to the classical Boolean question is asserted.

Details & sources
VP versus VNP →

Open · version 2

Over a field of characteristic zero, VP and VNP are distinct.

  • Polynomial families with polynomially bounded degree; nonuniform algebraic circuits; arithmetic operation complexity over the field.

Scope: An algebraic analogue; no equivalence to Boolean P versus NP is asserted.

P ≠ NP →

Open · version 3

There exists a language in NP that is not decidable by any deterministic polynomial-time algorithm.

  • Finite binary inputs; uniform classical computation; polynomial time in bit length.

Scope: The conjectural negative answer to the same canonical question.

Relationship not independently reviewed.

Connection in P versus NP →

Relationship not independently reviewed. This concerns its use in this problem.

Sources

Stephen Cook · The P versus NP problem →

Stephen Cook · Published

Published author exposition or original paper.

Revision & attribution

Source revision: official-description-sha256-018f3d473d16. Observed Oct 10, 2026.

AI involvement is not reported by this cited source; this is not a claim of its absence.

Stephen Cook · The P versus NP problem — proof text: official-description-sha256-018f3d473d16. External source text. Its mathematical claims and independent OpenMath review are assessed separately.

Avi Wigderson · Mathematics and Computation →

Avi Wigderson · Published · Publication date 2019

Published author exposition or original paper.

Revision & attribution

Source revision: author-draft-2019-08-06. Observed Oct 10, 2026.

AI involvement is not reported by this cited source; this is not a claim of its absence.

Impagliazzo–Paturi · On the complexity of k-SAT →

Russell Impagliazzo · Ramamohan Paturi · Published · Publication date Mar 2001

Published author exposition or original paper.

Revision & attribution

Source revision: JCSS-2001. Observed Oct 10, 2026.

AI involvement is not reported by this cited source; this is not a claim of its absence.

Cygan et al. · On problems as hard as CNF-SAT →

Marek Cygan · Holger Dell · Daniel Lokshtanov · Dániel Marx · Jesper Nederlof · Yoshio Okamoto · Ramamohan Paturi · Saket Saurabh · Magnus Wahlström · Preprint · Publication date Mar 27, 2014

Author full version dated March 2014; an extended abstract appeared at CCC 2012. The paper explicitly uses a bounded-error randomized formulation of SETH.

Revision & attribution

Source revision: arXiv-1112.2275v3. Observed Oct 10, 2026.

AI involvement is not reported by this cited source; this is not a claim of its absence.

History

Statement versions

Statement versions and problem publication versions are separate. A new publication can update context or sources while retaining the same statement.

Assessment history · 1

Assessments retained in these publication records. Earlier statement versions retain their own source histories.

Record details
Claim ID
claim-pnp-inequality
Statement version
3
SHA-256
e3c33603bd67787399a6837a5997ced659050ea38d7743545cdf081f43f545ac

Publication records