scholarly journals Inverse iteration for the Monge–Ampère eigenvalue problem

2020 ◽  
Vol 148 (11) ◽  
pp. 4875-4886
Author(s):  
Farhan Abedin ◽  
Jun Kitagawa
2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Qichao Zhao ◽  
Yidu Yang ◽  
Hai Bi

Combining the correction technique proposed by Lin and Xie and the shifted inverse iteration, a multilevel correction scheme for the Steklov eigenvalue problem is proposed in this paper. The theoretical analysis and numerical experiments indicate that the scheme proposed in this paper is efficient for both simple and multiple eigenvalues of the Steklov eigenvalue problem.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Stefano Giani ◽  
Luka Grubišić ◽  
Luca Heltai ◽  
Ornela Mulita

Abstract We present a perturbed subspace iteration algorithm to approximate the lowermost eigenvalue cluster of an elliptic eigenvalue problem. As a prototype, we consider the Laplace eigenvalue problem posed in a polygonal domain. The algorithm is motivated by the analysis of inexact (perturbed) inverse iteration algorithms in numerical linear algebra. We couple the perturbed inverse iteration approach with mesh refinement strategy based on residual estimators. We demonstrate our approach on model problems in two and three dimensions.


2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Feiyan Li ◽  
Hai Bi

For the Steklov eigenvalue problem, we establish a type of multigrid discretizations based on the fixed-shift inverse iteration and study in depth its a priori/a posteriori error estimates. In addition, we also propose an adaptive algorithm on the basis of the a posteriori error estimates. Finally, we present some numerical examples to validate the efficiency of our method.


Sign in / Sign up

Export Citation Format

Share Document