کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5372784 | 1504186 | 2017 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Towards a systematic convergence of Multi-Layer (ML) Multi-Configuration Time-Dependent Hartree nuclear wavefunctions: The ML-spawning algorithm Towards a systematic convergence of Multi-Layer (ML) Multi-Configuration Time-Dependent Hartree nuclear wavefunctions: The ML-spawning algorithm](/preview/png/5372784.png)
The Multi-Layer (ML) variant of the Multi-Configuration Time-Dependent Hartree (MCTDH) method is a powerful tool for the efficient computation of nuclear quantum dynamics in high-dimensional systems. By providing an optimal choice of layered effective degrees of freedom in form of the so-called ML tree, one is able to reduce the computational cost to an amenable number of configurations. Nevertheless, the fact that one must also make a series of ad hoc decisions often based on intuition or experience at the outset - such as the number of configurations per node and the branching of the ML tree - directly affect the efficiency of the computation and make its use less straightforward than the standard MCTDH method. Therefore, herein we detail a new algorithm for adaptively expanding the size of every node on-the-fly (i.e. spawning) and a derived criterion for the selection of an efficient tree's branching.
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Journal: Chemical Physics - Volume 482, 12 January 2017, Pages 113-123