Quasi-polynomial time

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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

upper bound
of the form

The

NP-hard
.

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

hyperbolic plane,[4] and for finding a graph with the fewest vertices that does not appear as an induced subgraph of a given graph.[5]

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:

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

  1. ^ IPEC Nerode Prize, EATCS, retrieved 2023-12-03
  2. ^ Klarreich, Erica (January 14, 2017), "Graph isomorphism vanquished — again", Quanta Magazine
  3. ^ 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
  4. ^ Braverman, Mark; Kun-Ko, Young; Weinstein, Omri (2015), "Approximating the best Nash equilibrium in -time breaks the Exponential Time Hypothesis", in