求解电子-氢静态非交换散射的神经网络方法

Mohammad Shazri Bin Shahrir, Kurunathan Ratnavely
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引用次数: 2

摘要

本文利用神经网络对电子-氢相互作用的散射弹性-碰撞相移进行了数值估计。以前的研究已经用龙格-库塔四阶(RK-4)得到了可靠的结果。这可以通过求解物理散射问题中常见的二阶微分方程(ODE)来实现。对描述薛定谔方程的若干试函数进行了测试,其中薛定谔方程求解了波动方程的静态场近似。结果显示与RK-4方法相当,但效果较差。可以说,NN方法具有连续估计的优点,但缺乏RK-4方法所能产生的精度。
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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.
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