2015
DOI: 10.1016/j.chemphys.2015.07.009
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An improved Lobatto discrete variable representation by a phase optimisation and variable mapping method

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Cited by 6 publications
(2 citation statements)
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References 70 publications
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“…This fact not only leads to low grid efficiency but also makes the iterative propagator, such as short-time iterative Lanczos (SIL) method, converge slowly [23]. To overcome this difficulty, one can use the variable mapping method or prolate spheroidal wave functions to get a more uniform spatial grid far from the origin and dense spatial grid around the origin, to increase the numerical efficiency [24,25]. In the bottom panels of Figure 2, the gird distribution becomes nearly even after optimization, which improves the efficiency of the grid.…”
Section: Multidomain Spectral Element Methodsmentioning
confidence: 99%
“…This fact not only leads to low grid efficiency but also makes the iterative propagator, such as short-time iterative Lanczos (SIL) method, converge slowly [23]. To overcome this difficulty, one can use the variable mapping method or prolate spheroidal wave functions to get a more uniform spatial grid far from the origin and dense spatial grid around the origin, to increase the numerical efficiency [24,25]. In the bottom panels of Figure 2, the gird distribution becomes nearly even after optimization, which improves the efficiency of the grid.…”
Section: Multidomain Spectral Element Methodsmentioning
confidence: 99%
“…[15] To solve this problem, Patchkovskii et al have proposed a parallel method, [18] and achieved the spa-tial derivatives of the radial coordinate by using the finitedifference method (FDM), which leads to an increase in the grids for the larger sized problem, [17] and finally significantly increasing the amount of computation in the case of higher accuracy. [19] Guan et al solved TDSE of two-electron quantum system in spherical coordinates efficiently based on the finite-element (FE) discrete-variable-representation (DVR) and Short-Iteration-Lanczos (SIL) propagator, [20] because the FE-DVR can offer higher computing accuracy [21] and make the Hamiltonian matrix very sparse, whose effects are similar to those provided by the B-spline [22,23] and sine-DVR, [24] and the efficiency of the wave function evolution strongly relies on the sparsity of the Hamiltonian matrix for the SIL propagator. [25] The most ideal structure of the Hamiltonian matrix is expected to have diagonal or similarly sparse elements for the SIL propagator.…”
Section: Introductionmentioning
confidence: 99%