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    If P = NP, deciding and verifying coincide up to a polyno... — Carmelics
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    Supports→If P = NP, then finding a satisfying valuation for a propositional formula would be no harder than constructing its truth table

    If P = NP, deciding and verifying coincide up to a polynomial factor for all NP problems

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    If P = NP, then finding a satisfying valuation for a propositional formula would...NP is the class of problems verifiable efficiently given a certificateP is the class of problems decidable efficiently

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    If P = NP, then the difficulty of deciding and verifying coincide (up ...95%If P equals NP, the difficulty of deciding and verifying coincides up ...93%Some problems can be verified in polynomial time80%If P equals NP, the difficulty of finding and verifying solutions to a...79%

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    Among these are Grover’s algorithm (Grover 1996) for searching an unsorted database (which runs in time \(O(n^{1/2})\), whereas the best possible classical algorithm is \(O(n)\)) and Shor’s algorithm (Shor 1999) for integer factorization (which runs in \(O(\log_2(n)^3)\), whereas the best known classical algorithm is \(O(2^{\log_2(\log_2(n))^{1/3})}\)). Since it can be shown that quantum models can simulate models such as the classical Turing machine, \(\textbf{BQP}\) contains \(\textbf{P}\) and

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