Karp–Lipton theorem

In complexity theory, the Karp–Lipton theorem states that if the Boolean satisfiability problem (SAT) can be solved by Boolean circuits with a polynomial number of logic gates, then

${\displaystyle \Pi _{2}=\Sigma _{2}\,}$ and therefore ${\displaystyle {\mathsf {PH}}=\Sigma _{2}.\,}$

That is, if we assume that NP, the class of nondeterministic polynomial time problems, can be contained in the non-uniform polynomial time complexity class P/poly, then this assumption implies the collapse of the polynomial hierarchy at its second level. Such a collapse is believed unlikely, so the theorem is generally viewed by complexity theorists as evidence for the nonexistence of polynomial size circuits for SAT or for other NP-complete problems. A proof that such circuits do not exist would imply that P ≠ NP. As P/poly contains all problems solvable in randomized polynomial time (Adleman's theorem), the theorem is also evidence that the use of randomization does not lead to polynomial time algorithms for NP-complete problems.

The Karp–Lipton theorem is named after Richard M. Karp and Richard J. Lipton, who first proved it in 1980. (Their original proof collapsed PH to ${\displaystyle \Sigma _{3}}$, but Michael Sipser improved it to ${\displaystyle \Sigma _{2}}$.)

Variants of the theorem state that, under the same assumption, MA = AM, and PH collapses to S^P
₂ complexity class. There are stronger conclusions possible if PSPACE, or some other complexity classes are assumed to have polynomial-sized circuits; see P/poly. If NP is assumed to be a subset of BPP (which is a subset of P/poly), then the polynomial hierarchy collapses to BPP. If coNP is assumed to be subset of NP/poly, then the polynomial hierarchy collapses to its third level.