Quasi-polynomial time
In computational complexity theory and the analysis of algorithms, an algorithm is said to take quasi-polynomial time if its time complexity is quasi-polynomially bounded. That is, there should exist a constant such that the worst-case running time of the algorithm, on inputs of size , has an
The
Complexity class
The complexity class QP consists of all problems that have quasi-polynomial time algorithms. It can be defined in terms of DTIME as follows.[1]
Examples
An early example of a quasi-polynomial time algorithm was the Adleman–Pomerance–Rumely primality test;[2] however, the problem of testing whether a number is a prime number has subsequently been shown to have a polynomial time algorithm, the AKS primality test.[3]
In some cases, quasi-polynomial time bounds can be proven to be optimal under the
Other problems for which the best known algorithm takes quasi-polynomial time include:
- The planted clique problem, of determining whether a random graph has been modified by adding edges between all pairs of a subset of its vertices.[6]
- Monotone dualization, several equivalent problems of converting logical formulas between conjunctive and disjunctive normal form, listing all minimal hitting sets of a family of sets, or listing all minimal set covers of a family of sets, with time complexity measured in the combined input and output size.[7]
- Parity games, involving token-passing along the edges of a colored directed graph.[8] The paper giving a quasi-polynomial algorithm for these games won the 2021 Nerode Prize.[9]
- Computing the Vapnik–Chervonenkis dimension of a family of sets.[10]
- Finding the smallest dominating set in a tournament, a subset of the vertices of the tournament that has at least one directed edge to all other vertices.[11]
Problems for which a quasi-polynomial time algorithm has been announced but not fully published include:
- The graph isomorphism problem, determining whether two graphs can be made equal to each other by relabeling their vertices, announced in 2015 and updated in 2017 by László Babai.[12]
- The
In approximation algorithms
Quasi-polynomial time has also been used to study
More strongly, the problem of finding an approximate Nash equilibrium has a QPTAS, but cannot have a PTAS under the exponential time hypothesis.[16]
References
- Complexity Zoo: Class QP: Quasipolynomial-Time
- JSTOR 2006975
- JSTOR 3597229
- ISBN 978-1-61197-599-4
- MR 2765712
- MR 2437000
- MR 4413072
- ^ IPEC Nerode Prize, EATCS, retrieved 2023-12-03
- MR 1418886
- MR 0980249
- ^ Klarreich, Erica (January 14, 2017), "Graph isomorphism vanquished — again", Quanta Magazine
- ^ Marc Lackenby announces a new unknot recognition algorithm that runs in quasi-polynomial time, Mathematical Institute, University of Oxford, 2021-02-03, retrieved 2021-02-03
- ^ Braverman, Mark; Kun-Ko, Young; Weinstein, Omri (2015), "Approximating the best Nash equilibrium in -time breaks the Exponential Time Hypothesis", in