有界背包优化问题的量子算法与电路设计

Wenjun Hou, M. Perkowski
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引用次数: 0

摘要

背包问题是资源分配和密码学中的一个突出问题。本文给出了一个验证有界背包问题决策问题形式解的程序和电路设计。该算法可用于格罗弗搜索求解有界背包问题的优化问题形式。该算法利用Grover Search提供的二次加速来实现背包问题的量子算法,该算法在经典算法方面显示出改进。采用微软q#编程语言设计了量子电路,并在其本地量子模拟器上进行了验证。本文还对所提出的oracle的复杂性和gate cost进行了分析。本文的工作是第一个针对背包优化问题提出的这种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum-based algorithm and circuit design for bounded Knapsack optimization problem
The Knapsack Problem is a prominent problem that is used in resource allocation and cryptography. This paper presents an oracle and a circuit design that verifies solutions to the decision problem form of the Bounded Knapsack Problem. This oracle can be used by Grover Search to solve the optimization problem form of the Bounded Knapsack Problem. This algorithm leverages the quadratic speed-up offered by Grover Search to achieve a quantum algorithm for the Knapsack Problem that shows improvement with regard to classical algorithms. The quantum circuits were designed using the Microsoft Q# Programming Language and verified on its local quantum simulator. The paper also provides analyses of the complexity and gate cost of the proposed oracle. The work in this paper is the first such proposed method for the Knapsack Optimization Problem.
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