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首页> 外文期刊>Undergraduate Journal of Mathematical Modeling: One + Two >The Subset Sum Problem: Reducing Time Complexity of NP-Completeness with Quantum Search
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The Subset Sum Problem: Reducing Time Complexity of NP-Completeness with Quantum Search

机译:子集和问题:通过量子搜索降低NP完全性的时间复杂度

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The Subset Sum Problem is a member of the NP-complete class, so no known polynomial time algorithm exists for it. Although there are polynomial time approximations and heuristics, these are not always acceptable, yet exact-solution algorithms are unfeasible for large input. Quantum computation offers new insights for not only the Subset Sum Problem but also the entire NP-complete class; most notably, Grover's quantum algorithm for an unstructured database search can be tailored to identify solutions to problems within mathematics and computer science. This paper discusses the physical and conceptual feasibility of quantum computation and demonstrates the utility of quantum search by analyzing the time complexities of the classical dynamic programming algorithm and Grover's algorithm in solving the Subset Sum Problem, evincing the implications this has on the NP-complete class in general.
机译:子集和问题是NP-complete类的成员,因此不存在已知的多项式时间算法。尽管存在多项式时间近似和启发式算法,但它们并不总是可以接受的,但是对于大输入量,精确解算法是不可行的。量子计算不仅为子集和问题,而且为整个NP-完全类提供了新的见解。最值得注意的是,可以对用于非结构化数据库搜索的Grover量子算法进行定制,以识别数学和计算机科学领域的问题的解决方案。本文讨论了量子计算的物理和概念可行性,并通过分析经典动态规划算法和Grover算法在解决子集和问题上的时间复杂性,论证了量子搜索的效用,证明了其对NP-完全类的影响一般来说。

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