{"title":"求解电子-氢静态非交换散射的神经网络方法","authors":"Mohammad Shazri Bin Shahrir, Kurunathan Ratnavely","doi":"10.1109/CIMSIM.2013.11","DOIUrl":null,"url":null,"abstract":"In this present work is to numerically estimate via neural network the scattering elastic-collision phase shift from electron hydrogen interaction. Previous works have shown reliable results using runge-kutta 4th order (RK-4). This can be achieved by solving the 2nd Order Differential Equation (ODE) that is found commonly in physical scattering problem. A number of trial functions was tested that describe the Schrodinger Equation in which solves the static field approximation of the wave equation. Results have shown comparable but inferior results relatively to the RK-4 method. It can be said that NN approach shows promise with the advantage of continuous estimation but lack the accuracy that can be produced by RK-4.","PeriodicalId":249355,"journal":{"name":"2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Neural Network (NN) Approach to Solving a Static-non-exchange Scattering of Electron-Hydrogen\",\"authors\":\"Mohammad Shazri Bin Shahrir, Kurunathan Ratnavely\",\"doi\":\"10.1109/CIMSIM.2013.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this present work is to numerically estimate via neural network the scattering elastic-collision phase shift from electron hydrogen interaction. Previous works have shown reliable results using runge-kutta 4th order (RK-4). This can be achieved by solving the 2nd Order Differential Equation (ODE) that is found commonly in physical scattering problem. A number of trial functions was tested that describe the Schrodinger Equation in which solves the static field approximation of the wave equation. Results have shown comparable but inferior results relatively to the RK-4 method. It can be said that NN approach shows promise with the advantage of continuous estimation but lack the accuracy that can be produced by RK-4.\",\"PeriodicalId\":249355,\"journal\":{\"name\":\"2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMSIM.2013.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSIM.2013.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Neural Network (NN) Approach to Solving a Static-non-exchange Scattering of Electron-Hydrogen
In this present work is to numerically estimate via neural network the scattering elastic-collision phase shift from electron hydrogen interaction. Previous works have shown reliable results using runge-kutta 4th order (RK-4). This can be achieved by solving the 2nd Order Differential Equation (ODE) that is found commonly in physical scattering problem. A number of trial functions was tested that describe the Schrodinger Equation in which solves the static field approximation of the wave equation. Results have shown comparable but inferior results relatively to the RK-4 method. It can be said that NN approach shows promise with the advantage of continuous estimation but lack the accuracy that can be produced by RK-4.