Circuit complexity | Computational complexity theory

Circuit complexity

In theoretical computer science, circuit complexity is a branch of computational complexity theory in which Boolean functions are classified according to the size or depth of the Boolean circuits that compute them. A related notion is the circuit complexity of a recursive language that is decided by a uniform family of circuits (see below). Proving lower bounds on size of Boolean circuits computing explicit Boolean functions is a popular approach to separating complexity classes. For example, a prominent circuit class P/poly consists of Boolean functions computable by circuits of polynomial size. Proving that would separate P and NP (see below). Complexity classes defined in terms of Boolean circuits include AC0, AC, TC0, NC1, NC, and P/poly. (Wikipedia).

Circuit complexity
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From playlist Physics - Electric Circuits

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From playlist Physics - Electric Circuits

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Related pages

AC (complexity) | Derandomization | Average-case complexity | AC0 | ACC0 | Boolean circuit | Theoretical computer science | TC0 | NOT gate | Recursive language | AND gate | Computational resource | Claude Shannon | Boolean function | Formal language | Natural proof | MA (complexity) | PP (complexity) | Computational problem | Clique problem | S2P (complexity) | Electronic Colloquium on Computational Complexity | NC (complexity) | Parity function | Turing machine equivalents | OR gate | Turing machine | Bit | NP (complexity) | Directed acyclic graph | P/poly | DLOGTIME | Abstract machine | Computational complexity theory | P (complexity) | Complexity class