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Academic Journal of Computing & Information Science, 2021, 4(3); doi: 10.25236/AJCIS.2021.040313.

Hybrid quantum genetic algorithm based on spin and its performance analysis

Author(s)

Feilong Ding

Corresponding Author:
Feilong Ding
Affiliation(s)

School of Science, East China University of Science and Technology, Shanghai, China

Abstract

Quantum computing is a new interdisciplinary science combining information science and quantum mechanics. This paper presents a hybrid quantum genetic algorithm based on spin, which implements quantum crossover on quantum individuals, which is beneficial to retain relatively good gene segments. The strategy of updating quantum gate and adaptively adjusting search grid by using quantum bit phase method; In this paper, the critical properties of quantum Heisenberg model with mixed spins on simple cubic lattice are studied by using the mean field approximation of two spin groups, and the hybrid quantum genetic algorithm based on spins is applied to solve knapsack problem. At present, many problems in the fields of industry and financial investment can be transformed into backpack problems to solve. The effectiveness of spin-based hybrid quantum genetic algorithm in solving knapsack problem has been proved by several groups of experiments.

Keywords

Spin, Hybrid quantum genetic algorithm, Backpack problem, performance analysis

Cite This Paper

Feilong Ding. Hybrid quantum genetic algorithm based on spin and its performance analysis. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 3: 83-87. https://doi.org/10.25236/AJCIS.2021.040313.

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