Yue Ruan1, *, Samuel Marsh2, Xilin Xue1, Zhihao Liu3, Jingbo Wang2, *
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1237-1247, 2020, DOI:10.32604/cmc.2020.010001
- 30 April 2020
Abstract The Quantum Approximate Optimization Algorithm (QAOA) is an
algorithmic framework for finding approximate solutions to combinatorial optimization
problems. It consists of interleaved unitary transformations induced by two operators
labelled the mixing and problem Hamiltonians. To fit this framework, one needs to
transform the original problem into a suitable form and embed it into these two
Hamiltonians. In this paper, for the well-known NP-hard Traveling Salesman Problem
(TSP), we encode its constraints into the mixing Hamiltonian rather than the conventional
approach of adding penalty terms to the problem Hamiltonian. Moreover, we map edges
(routes) connecting each More >
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