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  2. Padding argument - Wikipedia

    en.wikipedia.org/wiki/Padding_argument

    The proof that P = NP implies EXP = NEXP uses "padding".. by definition, so it suffices to show .. Let L be a language in NEXP. Since L is in NEXP, there is a non-deterministic Turing machine M that decides L in time for some constant c.

  3. EXPTIME - Wikipedia

    en.wikipedia.org/wiki/EXPTIME

    EXPTIME is one intuitive class in an exponential hierarchy of complexity classes with increasingly more complex oracles or quantifier alternations. For example, the class 2-EXPTIME is defined similarly to EXPTIME but with a doubly exponential time bound. This can be generalized to higher and higher time bounds.

  4. List of complexity classes - Wikipedia

    en.wikipedia.org/wiki/List_of_complexity_classes

    NP "YES" answers checkable in polynomial time (see complexity classes P and NP) NP-complete: The hardest or most expressive problems in NP NP-easy: Analogue to P NP for function problems; another name for FP NP: NP-equivalent: The hardest problems in FP NP: NP-hard: At least as hard as every problem in NP but not known to be in the same ...

  5. P versus NP problem - Wikipedia

    en.wikipedia.org/wiki/P_versus_NP_problem

    It is in NP because (given an input) it is simple to check whether M accepts the input by simulating M; it is NP-complete because the verifier for any particular instance of a problem in NP can be encoded as a polynomial-time machine M that takes the solution to be verified as input. Then the question of whether the instance is a yes or no ...

  6. NP (complexity) - Wikipedia

    en.wikipedia.org/wiki/NP_(complexity)

    NP is the set of decision problems solvable in polynomial time by a nondeterministic Turing machine. NP is the set of decision problems verifiable in polynomial time by a deterministic Turing machine. The first definition is the basis for the abbreviation NP; "nondeterministic, polynomial time". These two definitions are equivalent because the ...

  7. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    An algorithm is said to be exponential time, if T(n) is upper bounded by 2 poly(n), where poly(n) is some polynomial in n. More formally, an algorithm is exponential time if T(n) is bounded by O(2 n k) for some constant k. Problems which admit exponential time algorithms on a deterministic Turing machine form the complexity class known as EXP.

  8. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

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  9. Boolean satisfiability problem - Wikipedia

    en.wikipedia.org/wiki/Boolean_satisfiability_problem

    For example, the formula "a AND NOT b" is satisfiable because one can find the values a = TRUE and b = FALSE, which make (a AND NOT b) = TRUE. In contrast, "a AND NOT a" is unsatisfiable. SAT is the first problem that was proven to be NP-complete—this is the Cook–Levin theorem.