17,794 research outputs found
Recursive integral method for transmission eigenvalues
Recently, a new eigenvalue problem, called the transmission eigenvalue
problem, has attracted many researchers. The problem arose in inverse
scattering theory for inhomogeneous media and has important applications in a
variety of inverse problems for target identification and nondestructive
testing. The problem is numerically challenging because it is non-selfadjoint
and nonlinear. In this paper, we propose a recursive integral method for
computing transmission eigenvalues from a finite element discretization of the
continuous problem. The method, which overcomes some difficulties of existing
methods, is based on eigenprojectors of compact operators. It is
self-correcting, can separate nearby eigenvalues, and does not require an
initial approximation based on some a priori spectral information. These
features make the method well suited for the transmission eigenvalue problem
whose spectrum is complicated. Numerical examples show that the method is
effective and robust.Comment: 18 pages, 8 figure
A spectral projection method for transmission eigenvalues
In this paper, we consider a nonlinear integral eigenvalue problem, which is
a reformulation of the transmission eigenvalue problem arising in the inverse
scattering theory. The boundary element method is employed for discretization,
which leads to a generalized matrix eigenvalue problem. We propose a novel
method based on the spectral projection. The method probes a given region on
the complex plane using contour integrals and decides if the region contains
eigenvalue(s) or not. It is particularly suitable to test if zero is an
eigenvalue of the generalized eigenvalue problem, which in turn implies that
the associated wavenumber is a transmission eigenvalue. Effectiveness and
efficiency of the new method are demonstrated by numerical examples.Comment: The paper has been accepted for publication in SCIENCE CHINA
Mathematic
Recursive Integral Method with Cayley Transformation
Recently, a non-classical eigenvalue solver, called RIM, was proposed to
compute (all) eigenvalues in a region on the complex plane. Without solving any
eigenvalue problem, it tests if a region contains eigenvalues using an
approximate spectral projection. Regions that contain eigenvalues are
subdivided and tested recursively until eigenvalues are isolated with a
specified precision. This makes RIM an eigensolver distinct from all existing
methods. Furthermore, it requires no a priori spectral information. In this
paper, we propose an improved version of {\bf RIM} for non-Hermitian eigenvalue
problems. Using Cayley transformation and Arnoldi's method, the computation
cost is reduced significantly. Effectiveness and efficiency of the new method
are demonstrated by numerical examples and compared with 'eigs' in Matlab
- …