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Quantum Computer Search Algorithms: Can We Outperform the Classical Search Algorithms?

机译:Quantum Computer搜索算法:我们可以擅长经典搜索算法吗?

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Quantum Computers are not limited to just two states. Qubits, the basic unit of quantum computing have the power to exist in more than one state at a time. While the classical computers only perform operations by manipulation of classical bits having two values 0 and 1, quantum bits can represent data in multiple states. This property of inheriting multiple states at a time is called superposition which gives quantum computers tremendous power over classical computers. With this power, the algorithms designed on quantum computers to solve search queries can yield result significantly faster than the classical algorithms. There are four types of problems that exist: Polynomial (P), Non-Deterministic Polynomial (NP), Non-Deterministic Polynomial Complete (NP-complete) and Non-Deterministic Polynomial hard (NP-hard). P problems can be solved in the polynomial amount of time like searching a database for an item. However, when the size of the search space grows, it becomes difficult to compute solutions even for P problems. Quantum algorithms like Grover's algorithm has reduced the time complexity of some of the classical algorithm problems from N to √N. Variants of Grover's algorithm like Quantum Partial Search propose changes that yield not exact but closer results in time even lesser than Grover's algorithm. NP problems are the problems whose solution if known can be verified in polynomial amount time. Factorization of prime numbers which is considered to be an NP problem took an exponential amount of time when solved using the classical computer while the Shor's quantum computing algorithm computes it in polynomial time. Factorization is also a class of bounded-error quantum polynomial time (BQP) problems which are decision problems solved by quantum computers in polynomial time. There are problems to which if a solution is found can solve every problem Of NP class, these are NP-complete problems. The power of Qubits could be exploited in the future to come up with
机译:量子计算机不仅限于两个状态。 QUBITS,量子计算的基本单元一次具有在多个状态中存在的功率。虽然经典计算机仅通过操纵具有两个值0和1的经典比特来执行操作,但是量子比特可以表示多个状态的数据。一次继承多个状态的属性称为叠加,使量子计算机在古典计算机上提供巨大的电源。通过这种功率,设计用于解决搜索查询的量子计算机上的算法可以产生比经典算法更快的结果。存在四种类型的问题:多项式(P),非确定性多项式(NP),非确定性多项式完全(NP-完全)和非确定性多项式硬(NP-HARD)。 p问题可以在搜索项目的多项式时间中解决,例如搜索项目的数据库。但是,当搜索空间的大小增长时,即使对于P问题也难以计算解决方案。 Quantum算法如GROVER的算法,从N到√N的一些经典算法问题的时间复杂度降低了。 Grover的算法等变体,如量子部分搜索提出了更改的变化,其不会精确但更接近的结果甚至比格罗弗的算法更小。 NP问题是如果可以在多项式量时间中验证已知的问题的问题。当Shor的量子计算算法在多项式时间中计算它时,被认为是NP问题的素数被认为是NP问题的序号占据了指数的时间。因子也是一类界限误差量子多项式时间(BQP)问题,其是多项式时间中量子计算机解决的决策问题。如果找到解决方案可以解决NP类的每个问题,存在问题,这些问题是NP完全的问题。 Qubits的力量可以在未来剥削

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