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A Ljusternik-Schnirelman minimax algorithm for finding equality constrained saddle points and its application for solving eigen problems: part I. Algorithm and global convergence

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Abstract

In Yao (J. Sci. Comput. 66, 19–40 2016), two Ljusternik-Schnirelman minimax algorithms for capturing multiple free saddle points are developed from well-known Ljusternik-Schnirelman critical point theory, numerical experiment is carried out and global convergence is established. In this paper, a Ljusternik-Schnirelman minimax algorithm for calculating multiple equality constrained saddle points is presented. The algorithm is applied to numerically solve eigen problems. Finally, global convergence for the algorithm is verified.

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Acknowledgments

The author would like to thank referees for their helpful comments.

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Correspondence to Xudong Yao.

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Communicated by: Stefan Volkwein

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Yao, X. A Ljusternik-Schnirelman minimax algorithm for finding equality constrained saddle points and its application for solving eigen problems: part I. Algorithm and global convergence. Adv Comput Math 45, 269–310 (2019). https://doi.org/10.1007/s10444-018-9616-6

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  • DOI: https://doi.org/10.1007/s10444-018-9616-6

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