标题: 在最优分割的分布下之非线性特征值问题
Nonlinear Eigenvalue Problems for the Distribution of Optimal Partitions
作者: 张书铭
Chang Shu-Ming
国立交通大学应用数学系(所)
关键字: 波色爱因斯坦冷凝现象;輪生;高斯塞德尔迭代法;Bose-Einstein condensate;verticillate multiplying;Gauss-Seidel-type iteration
公开日期: 2012
摘要: 在正的且大的排斥散射强度下,多种原子的玻色爱因斯坦凝聚现象之分布,是本研究专题所关注的。在排斥散射强度趋向无穷大后,數学理論上已经有严格的证明,不同种類的原子玻色爱因斯坦凝聚现象分布是呈现完全个别分开;在數值计算方面,模拟计算方法也已被发展了;同时观察到一种现象:輪生结构。但是,当原子种類个數相当大后,计算结果是差的,甚至是不可靠。因此,本研究专题首要目标是发展有效地數值计算演算法,求解描述多种原子玻色爱因斯坦凝聚现象的非线性薛丁格方程系统。然后,找出原子种類个數越來越大时的分布结构之准则。再者,我们希望探讨到三维空间下的多种原子之分布结构,并与二维空间下的情形进行比较。
In this project, we would like to study the distribution of segregated nodal domains of the mixture of Bose-Einstein condensates (BECs) under positive and large repulsive scattering lengths. It is shown that components of positive bound states may repel each other and form segregated nodal domains as the repulsive scattering lengths go to infinity. Numerical schemes, Gauss-Seidel-type iteration method and Jacobi-type iteration method, have been created to confirm the theoretical results. And a phenomenon, verticillate multiplying, is observed. But the numerical result is bad even unreliable when the number of segregated nodal domains of the mixture of BECs is large. Therefore, it is our first goal to develop an efficient numerical for simulating a multi-component BEC. Then, it is the second goal to find some principles in the distribution of segregated nodal domains of the mixture of multi-component BECs. Moreover, we hope to simulate multi-component BECs under a three dimensional domain and compare 2-dimensional and 3-dimensional cases.
官方说明文件#: NSC101-2115-M009-009
URI: http://hdl.handle.net/11536/98220
https://www.grb.gov.tw/search/planDetail?id=2592704&docId=392020
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