Quantum complexity theory | Quantum computing | Probabilistic complexity classes

BQP

In computational complexity theory, bounded-error quantum polynomial time (BQP) is the class of decision problems solvable by a quantum computer in polynomial time, with an error probability of at most 1/3 for all instances. It is the quantum analogue to the complexity class BPP. A decision problem is a member of BQP if there exists a quantum algorithm (an algorithm that runs on a quantum computer) that solves the decision problem with high probability and is guaranteed to run in polynomial time. A run of the algorithm will correctly solve the decision problem with a probability of at least 2/3. (Wikipedia).

BQP
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Path integral formulation | BPP (complexity) | Jones polynomial | Integer factorization | IP (complexity) | Probabilistic Turing machine | Complete (complexity) | With high probability | Quantum Turing machine | Circuit complexity | PostBQP | QIP (complexity) | Postselection | Oracle machine | PSPACE | Low (complexity) | Quantum algorithm | Chernoff bound | PP (complexity) | Quantum complexity theory | Deferred Measurement Principle | Polynomial hierarchy | Discrete logarithm | Grover's algorithm | Hidden subgroup problem | Quantum algorithm for linear systems of equations | NP (complexity) | Quantum logic gate | QMA | Controlled NOT gate | P versus NP problem | Computational complexity theory | P (complexity) | Richard Feynman | Quantum circuit | Algorithm | NP-completeness | Complexity class | Shor's algorithm