Can you explain the difference between BPP (Bounded-Error Probabilistic Polynomial-Time) and BQP (Bounded-Error Quantum Polynomial-Time)? I feel like they are both in the P polynomial time area of solvability, just one deals with quantum and the other with a slightly higher level above just P.
Can you explain the difference between BPP (Bounded-Error Probabilistic Polynomial-Time) and BQP (Bounded-Error Quantum Polynomial-Time)? I feel like they are both in the P polynomial time area of solvability, just one deals with quantum and the other with a slightly higher level above just P.
In computational intricacy hypothesis, a part of software engineering, bounded-error probabilistic polynomial time (BPP) is the class of choice issues resolvable by a probabilistic Turing machine in polynomial time with an error likelihood bounded by 1/3 for all occasions. BPP is one of the biggest pragmatic classes of issues, meaning most issues of interest in BPP have effective probabilistic calculations that can be run rapidly on genuine present day machines. BPP likewise contains P, the class of issues reasonable in polynomial time with a deterministic machine, since a deterministic machine is an exceptional instance of a probabilistic machine.
Casually, an issue is in BPP assuming there is a calculation for it that has the accompanying properties:
- Flipping coins and pursue arbitrary choices is permitted.
- Running in polynomial time is ensured.
- On some random run of the calculation, it has a likelihood of at generally 1/3 of offering some unacceptable response, whether the response is YES or NO.
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