NANAAPMar 10, 2016

Domain decomposition algorithms for two dimensional linear Schrödinger equation

arXiv:1506.056398 citationsh-index: 23
Originality Synthesis-oriented
AI Analysis

For researchers solving the Schrödinger equation numerically, this work offers incremental improvements to domain decomposition methods.

The paper proposes new domain decomposition algorithms for the 2D linear Schrödinger equation, including a preconditioned algorithm and a new absorbing transmission condition, which numerically accelerate convergence and reduce computation time.

This paper deals with two domain decomposition methods for two dimensional linear Schr{ö}dinger equation, the Schwarz waveform relaxation method and the domain decomposition in space method. After presenting the classical algorithms, we propose a new algorithm for the free Schr{ö}dinger equation and a preconditioned algorithm for the general Schr{ö}dinger equation. These algorithms are studied numerically, which shows that the two new algorithms could accelerate the convergence and reduce the computation time. Besides the traditional Robin transmission condition, we also propose to use a newly constructed absorbing condition as the transmission condition.

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