A Density Matrix-based Algorithm for Solving Eigenvalue Problems
A Density Matrix-based Algorithm for Solving Eigenvalue Problems
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DOI：
10.1103/physrevb.79.115112
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发表时间：
2009-01
期刊：
影响因子：
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通讯作者：
E. Polizzi
中科院分区：
文献类型：
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作者：
E. Polizzi
提出了一种用于解决对称特征值问题的新数值算法。该技术从根本上偏离了传统的Krylov子空间迭代技术（Arnoldi和Lanczos算法）或其他Davidson-Jacobi技术，并从量子力学中的轮廓整合和密度矩阵表示中汲取灵感。可以证明，这种新算法（称为盛宴）在并行体系结构上表现出高效率，鲁棒性，准确性和可扩展性。提出了来自碳纳米管（CNT）的电子结构计算的示例，并讨论了数值性能和能力。
A new numerical algorithm for solving the symmetric eigenvalue problem is presented. The technique deviates fundamentally from the traditional Krylov subspace iteration based techniques (Arnoldi and Lanczos algorithms) or other Davidson-Jacobi techniques, and takes its inspiration from the contour integration and density matrix representation in quantum mechanics. It will be shown that this new algorithm - named FEAST - exhibits high efficiency, robustness, accuracy and scalability on parallel architectures. Examples from electronic structure calculations of Carbon nanotubes (CNT) are presented, and numerical performances and capabilities are discussed.