{"title":"用量子粒子群算法计算球形量子点中类氢杂质的基态能量","authors":"M. Omran","doi":"10.4018/IJEOE.2016100103","DOIUrl":null,"url":null,"abstract":"In this work, quantum particle swarm optimization (QPSO1) algorithm method is applied to the problem of impurity at the center of a spherical quantum dot for infinite confining potential case. For this purpose, a trial variational wave function is considered for ground state, and then energy values are calculated as a function of the radius of a spherical quantum dot. Also, the evolution of the energy eigenvalue for different dot radii and different optimized parameter is determined. The energy converges remarkably fast, after a few numbers of iteration. In comparison with the two other available methods, standard variational procedure and genetic algorithm method (GA), the results coming out from QPSO algorithm are in more satisfactory agreement with the real values.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computing of the Ground State Energy of a Hydrogen Like Impurity in a Spherical Quantum Dot using QPSO Algorithm\",\"authors\":\"M. Omran\",\"doi\":\"10.4018/IJEOE.2016100103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, quantum particle swarm optimization (QPSO1) algorithm method is applied to the problem of impurity at the center of a spherical quantum dot for infinite confining potential case. For this purpose, a trial variational wave function is considered for ground state, and then energy values are calculated as a function of the radius of a spherical quantum dot. Also, the evolution of the energy eigenvalue for different dot radii and different optimized parameter is determined. The energy converges remarkably fast, after a few numbers of iteration. In comparison with the two other available methods, standard variational procedure and genetic algorithm method (GA), the results coming out from QPSO algorithm are in more satisfactory agreement with the real values.\",\"PeriodicalId\":246250,\"journal\":{\"name\":\"Int. J. Energy Optim. Eng.\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Energy Optim. Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJEOE.2016100103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Energy Optim. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJEOE.2016100103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computing of the Ground State Energy of a Hydrogen Like Impurity in a Spherical Quantum Dot using QPSO Algorithm
In this work, quantum particle swarm optimization (QPSO1) algorithm method is applied to the problem of impurity at the center of a spherical quantum dot for infinite confining potential case. For this purpose, a trial variational wave function is considered for ground state, and then energy values are calculated as a function of the radius of a spherical quantum dot. Also, the evolution of the energy eigenvalue for different dot radii and different optimized parameter is determined. The energy converges remarkably fast, after a few numbers of iteration. In comparison with the two other available methods, standard variational procedure and genetic algorithm method (GA), the results coming out from QPSO algorithm are in more satisfactory agreement with the real values.