In computational complexity theory, the complexity class NTIME(f(n)) is the set of decision problems that can be solved by a non-deterministic Turing machine that runs in time O(f(n)), where O is the big O notation, f is some function, and n is the size of the input (for which the problem is to be decided).

Meaning

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This means that there is a non-deterministic machine that, for a given input of size n, will, for all computation paths, run in time O(f(n)) (i.e. within a fixed constant multiple of f(n), for n greater than some value), and will always "reject" the input if the answer to the decision problem is "no" for that input, while if the answer is "yes" the machine will "accept" that input for at least one computation path. Equivalently, there is a deterministic Turing machine M that runs in time O(f(n)) and is able to check an O(f(n))-length certificate for an input; if the input is a "yes" instance, then at least one certificate is accepted, if the input is a "no" instance, no certificate can make the machine accept.

Space constraints

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The space available to the machine is not limited, although it cannot exceed O(f(n)), because the time available limits how much of the tape is reachable.

Relation to other complexity classes

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The well-known complexity class NP can be defined in terms of NTIME as follows:

Similarly, the class NEXP is defined in terms of NTIME:

The non-deterministic time hierarchy theorem says that nondeterministic machines can solve more problems in asymptotically more time.

NTIME is also related to DSPACE in the following way. For any time constructible function t(n), we have

.

A generalization of NTIME is ATIME, defined with alternating Turing machines. It turns out that

.

References

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Complexity Zoo: NTIME(f(n)).

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NP (complexity)

in terms of NTIME as follows: N P = โ‹ƒ k โˆˆ N N T I M E ( n k ) , {\displaystyle {\mathsf {NP}}=\bigcup _{k\in \mathbb {N} }{\mathsf {NTIME}}(n^{k}),} where

Time hierarchy theorem

) ) โŠŠ N T I M E ( g ( n ) ) . {\displaystyle {\mathsf {NTIME}}(f(n))\subsetneq {\mathsf {NTIME}}(g(n)).} The analogous theorems for space are the space

Network Time Protocol

"statime". Both projects are available under Apache and MIT software licenses. Ntimed was started by Poul-Henning Kamp of FreeBSD in 2014 and abandoned in 2015

DTIME

example, if we use a nondeterministic Turing machine, we have the resource NTIME. The relationship between the expressive powers of DTIME and other computational

Computational complexity theory

( n ) ) {\displaystyle O(2^{{\text{poly}}(n)})} Time Non-Deterministic NTIME( f ( n ) {\displaystyle f(n)} ) O ( f ( n ) ) {\displaystyle O(f(n))} NP

NEXPTIME

terms of NTIME, N E X P T I M E = โ‹ƒ k โˆˆ N N T I M E ( 2 n k ) {\displaystyle {\mathsf {NEXPTIME}}=\bigcup _{k\in \mathbb {N} }{\mathsf {NTIME}}(2^{n^{k}})}

Complexity class

often defined using granular sets of complexity classes called DTIME and NTIME (for time complexity) and DSPACE and NSPACE (for space complexity). Using

Space complexity

space complexity. Analogously to time complexity classes DTIME(f(n)) and NTIME(f(n)), the complexity classes DSPACE(f(n)) and NSPACE(f(n)) are the sets