Concept

P (complexity)

Summary
In computational complexity theory, P, also known as PTIME or DTIME(nO(1)), is a fundamental complexity class. It contains all decision problems that can be solved by a deterministic Turing machine using a polynomial amount of computation time, or polynomial time. Cobham's thesis holds that P is the class of computational problems that are "efficiently solvable" or "tractable". This is inexact: in practice, some problems not known to be in P have practical solutions, and some that are in P do not, but this is a useful rule of thumb. A language L is in P if and only if there exists a deterministic Turing machine M, such that M runs for polynomial time on all inputs For all x in L, M outputs 1 For all x not in L, M outputs 0 P can also be viewed as a uniform family of boolean circuits. A language L is in P if and only if there exists a polynomial-time uniform family of boolean circuits , such that For all , takes n bits as input and outputs 1 bit For all x in L, For all x not in L, The circuit definition can be weakened to use only a logspace uniform family without changing the complexity class. P is known to contain many natural problems, including the decision versions of linear programming, and finding a maximum matching. In 2002, it was shown that the problem of determining if a number is prime is in P. The related class of function problems is FP. Several natural problems are complete for P, including st-connectivity (or reachability) on alternating graphs. The article on P-complete problems lists further relevant problems in P. A generalization of P is NP, which is the class of decision problems decidable by a non-deterministic Turing machine that runs in polynomial time. Equivalently, it is the class of decision problems where each "yes" instance has a polynomial size certificate, and certificates can be checked by a polynomial time deterministic Turing machine. The class of problems for which this is true for the "no" instances is called co-NP.
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