| 量子力学基态能量计算的改进蚁群优化算法 |
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| 引用本文： | 陈霞,唐晨.量子力学基态能量计算的改进蚁群优化算法[J].计算物理,2010,27(4):624-632. |
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| 作者姓名： | 陈霞 唐晨 |
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| 作者单位： | 天津大学应用物理系, 天津 300072 |
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| 基金项目： | Supported by the national natural science foundation of China (grant 60877001) |
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| 摘 要： | 为进一步减少迭代次数和改善解的质量,对蚁群优化方法进行改进.在求解体系基态能上与传统的变分法相比有很大的优势.求解了氦原子基态能量,并应用于不同半径量子点中砷化镓类氢施主基态能量的计算.通过与变分法和遗传算法的比较,展示了算法的性能.
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| 关 键 词： | 基态能量 量子点 蚁群优化算法 |
| 收稿时间： | 2009-04-10 |
| 修稿时间： | 2009-08-25 |
Improved Ant Colony Optimization Algorithms for Ground State Energy of Quantum Mechanical Systems |
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| CHEN Xia,TANG Chen.Improved Ant Colony Optimization Algorithms for Ground State Energy of Quantum Mechanical Systems[J].Chinese Journal of Computational Physics,2010,27(4):624-632. |
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| Authors: | CHEN Xia TANG Chen |
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| Institution: | Department of Applied Physics, University of Tianjin, Tianjin 300072, China |
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| Abstract: | Ant colony optimization (ACO),a global optimization method,is proposed to analyze ground state energy of quantum mechanical systems.It simulates the way that real ants find a shortest path from nest to food source and back.In order to reduce iterations and improve solutions,ACO algorithm for ground state energy is modified.The proposed method exhibits advantage compared with traditional variation method.Ground state energy of helium atom and hydrogenic donors in GaAs-(Ga,Al)As quantum dot are calculated.The algorithm is demonstrated via comparison with variational method and genetic algorithms (GAs). |
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| Keywords: | ground state energy quantum dots ant colony optimization algorithms |
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