2002
DOI: 10.1063/1.1473811
|View full text |Cite
|
Sign up to set email alerts
|

A general framework for discrete variable representation basis sets

Abstract: A framework for discrete variable representation ͑DVR͒ basis sets is developed that is suitable for multidimensional generalizations. Those generalizations will be presented in future publications. The new axiomatization of the DVR construction places projection operators in a central role and integrates semiclassical and phase space concepts into the basic framework. Rates of convergence of basis set expansions are emphasized, and it is shown that the DVR method gives exponential convergence, assuming conditi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
130
0

Year Published

2005
2005
2019
2019

Publication Types

Select...
4
3
1

Relationship

0
8

Authors

Journals

citations
Cited by 135 publications
(132 citation statements)
references
References 54 publications
2
130
0
Order By: Relevance
“…However, the components of V (x) x| n which lie outside of S K are typically O(1/N ) and this error is concentrated in the basis elements near the boundary n N . For wave functions well converged with a basis size N , the weight on the basis functions with n near N is exponentially small, and hence we recover exponential accuracy [21].…”
Section: Exactmentioning
confidence: 95%
See 2 more Smart Citations
“…However, the components of V (x) x| n which lie outside of S K are typically O(1/N ) and this error is concentrated in the basis elements near the boundary n N . For wave functions well converged with a basis size N , the weight on the basis functions with n near N is exponentially small, and hence we recover exponential accuracy [21].…”
Section: Exactmentioning
confidence: 95%
“…Hence, the loss in sparsity of the DVR compared to finite-order finite-differencing methods is more than compensated by the increase in accuracy. Generally speaking, exponential convergence comes only from using an analytic basis set for expansion [21], and so methods based on nonanalytic wave functions, such as Haar wavelets, B splines, and finite differencing, will not display exponential convergence.…”
Section: Exactmentioning
confidence: 99%
See 1 more Smart Citation
“…For W(x)=x 3 , and thus V(x)=x 6 − 3x 2 , we carried out a variational calculation using the system-specific coherent states defined above and compared the accuracy in the approximation of the first three excited state energy eigenvalues with that achieved using the standard harmonic oscillator basis and the harmonic oscillator coherent states. To evaluate the accuracy of each method, we compare the results with a Chebyshev polynomial DVR (Discrete Variable Representation) calcuation using 1000 points Littlejohn (2002). The number of decimal places reported in Tables 7-10 correspond to the number of decimal places of agreement with the DVR plus an additional significant figure which is either rounded up or down.…”
Section: Computational Examplesmentioning
confidence: 99%
“…This paper was born out of an attempt to extend the DVR method to higher dimensions; other, recent progress on this subject has been made by Dawes and Carrington [9]. Another interesting perspective on DVR can be found in the paper [10].…”
Section: Introductionmentioning
confidence: 99%