## Abstract This work is a generalization of the immersed interface method for discretization of a nondiagonal anisotropic Laplacian in 2D. This first‐order discretization scheme enforces weakly diagonal dominance of the numerical scheme whenever possible. A necessary and sufficient condition depen
On 2D Bisection Method for Double Eigenvalue Problems
✍ Scribed by Xingzhi Ji
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 339 KB
- Volume
- 126
- Category
- Article
- ISSN
- 0021-9991
No coin nor oath required. For personal study only.
✦ Synopsis
Ϫ( p 1 (x 1 ) yЈ 1 )Ј ϩ q 1 (x 1 ) y 1 ϭ (s 11 (x 1 ) ϩ Ȑs 12 (x 1 )) y 1 ,
The two-dimensional bisection method presented in (SIAM J. Matrix Anal. Appl. 13(4), 1085 (1992)) is efficient for solving a class
of double eigenvalue problems. This paper further extends the 2D bisection method to full matrix cases and analyses its stablity. As
in a single parameter case, the 2D bisection method is very stable for the tridiagonal matrix triples satisfying the symmetric-definite y 1 (b 1 ) cos ͱ 1 Ϫ ( p 1 yЈ 1 )(b 1 ) sin ͱ 1 ϭ 0, condition. Since the double eigenvalue problems arise from twoparameter boundary value problems, an estimate of the discretiza-
tion error in eigenpairs is also given. Some numerical examples are included. ᮊ 1996 Academic Press, Inc.
where 0 Յ Ͱ i Ͻ ȏ, 0 Ͻ ͱ i Յ ȏ, p i Ͼ 0 and pЈ i , q i , s ij are * The author thanks Professor P. A. Binding and Professor P. J. Browne BЉ(ͱ) ϩ ͕Ϫh ϩ ( ϩ 1)(1 Ϫ kЈ 2 sn 2 (ͱ, kЈ))͖B(ͱ) ϭ 0, for many stimulating discussions when he visited the University of Calgary.
B(ϪKЈ) ϭ BЈ(KЈ) ϭ 0, 91
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