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P (complexity) and P/poly

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between P (complexity) and P/poly

P (complexity) vs. P/poly

In computational complexity theory, P, also known as PTIME or DTIME(nO(1)), is a fundamental complexity class. In computational complexity theory, P/poly is the complexity class of languages recognized by a polynomial-time Turing machine with a polynomial-bounded advice function.

Similarities between P (complexity) and P/poly

P (complexity) and P/poly have 11 things in common (in Unionpedia): Advice (complexity), BPP (complexity), Complexity class, Computational complexity theory, EXPTIME, NP (complexity), Polynomial hierarchy, PSPACE, Sparse language, Turing machine, Undecidable problem.

Advice (complexity)

In computational complexity theory, an advice string is an extra input to a Turing machine that is allowed to depend on the length n of the input, but not on the input itself.

Advice (complexity) and P (complexity) · Advice (complexity) and P/poly · See more »

BPP (complexity)

In computational complexity theory, BPP, which stands for bounded-error probabilistic polynomial time is the class of decision problems solvable by a probabilistic Turing machine in polynomial time with an error probability bounded away from 1/2 for all instances.

BPP (complexity) and P (complexity) · BPP (complexity) and P/poly · See more »

Complexity class

In computational complexity theory, a complexity class is a set of problems of related resource-based complexity.

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Computational complexity theory

Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.

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EXPTIME

In computational complexity theory, the complexity class EXPTIME (sometimes called EXP or DEXPTIME) is the set of all decision problems that have exponential runtime, i.e., that are solvable by a deterministic Turing machine in O(2p(n)) time, where p(n) is a polynomial function of n. In terms of DTIME, We know and also, by the time hierarchy theorem and the space hierarchy theorem, that so at least one of the first three inclusions and at least one of the last three inclusions must be proper, but it is not known which ones are.

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NP (complexity)

In computational complexity theory, NP (for nondeterministic polynomial time) is a complexity class used to describe certain types of decision problems.

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Polynomial hierarchy

In computational complexity theory, the polynomial hierarchy (sometimes called the polynomial-time hierarchy) is a hierarchy of complexity classes that generalize the classes P, NP and co-NP to oracle machines.

P (complexity) and Polynomial hierarchy · P/poly and Polynomial hierarchy · See more »

PSPACE

In computational complexity theory, PSPACE is the set of all decision problems that can be solved by a Turing machine using a polynomial amount of space.

P (complexity) and PSPACE · P/poly and PSPACE · See more »

Sparse language

In computational complexity theory, a sparse language is a formal language (a set of strings) such that the complexity function, counting the number of strings of length n in the language, is bounded by a polynomial function of n. They are used primarily in the study of the relationship of the complexity class NP with other classes.

P (complexity) and Sparse language · P/poly and Sparse language · See more »

Turing machine

A Turing machine is a mathematical model of computation that defines an abstract machine, which manipulates symbols on a strip of tape according to a table of rules.

P (complexity) and Turing machine · P/poly and Turing machine · See more »

Undecidable problem

In computability theory and computational complexity theory, an undecidable problem is a decision problem for which it is known to be impossible to construct a single algorithm that always leads to a correct yes-or-no answer.

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The list above answers the following questions

P (complexity) and P/poly Comparison

P (complexity) has 58 relations, while P/poly has 33. As they have in common 11, the Jaccard index is 12.09% = 11 / (58 + 33).

References

This article shows the relationship between P (complexity) and P/poly. To access each article from which the information was extracted, please visit:

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