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Proper Cost Hamiltonian Design for Combinatorial Optimization Problems: A Boolean Function Approach

机译:适当的成本哈密顿设计用于组合优化问题:布尔函数方法

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Advanced researches on the variational quantum algorithms are actively conducted. In particular, the quantum approximate optimization algorithm (QAOA) is one of the promising variational quantum algorithms and can be applied to various graph-based problems, and is a promising algorithm that shows good performance even in small quantum computers. As is widely known, QAOA obtains the approximate solution via the expectation value of the cost Hamiltonian on the parameterized state. Therefore, in addition to finding the optimal parameters, the proper design of the cost Hamiltonian is important. This paper designs the cost function of the combinatorial optimization problem via Boolean function and maps it to the proper cost Hamiltonian. The proposed cost Hamiltonian design method is applied to the maximum independent set (MIS) and minimum dominating set (MDS) problems.
机译:积极进行对变分量子算法的高级研究。特别地,量子近似优化算法(qaoa)是有前途的变分量子算法之一,并且可以应用于各种基于图形的问题,并且即使在小量子计算机中也显示出良好的性能的有希望的算法。如众所周知,QAOA通过参数化状态的成本哈密顿人的期望值获得近似解。因此,除了寻找最佳参数之外,正常设计的成本哈密顿是重要的。本文通过布尔函数设计了组合优化问题的成本函数,并将其映射到正确的成本哈密顿人。拟议的成本哈密尔顿设计方法应用于最大独立集(MIS)和最低主导集(MDS)问题。

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