2008
DOI: 10.1063/1.2925681
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A stereographic projection path integral study of the coupling between the orientation and the bending degrees of freedom of water

Abstract: A Monte Carlo path integral method to study the coupling between the rotation and bending degrees of freedom for water is developed. It is demonstrated that soft internal degrees of freedom that are not stretching in nature can be mapped with stereographic projection coordinates. For water, the bending coordinate is orthogonal to the stereographic projection coordinates used to map its orientation. Methods are developed to compute the classical and quantum Jacobian terms so that the proper infinitely stiff spr… Show more

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Cited by 16 publications
(24 citation statements)
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“…In a series of works [63][64][65][66][67][68][69][70] we have extended the reweighted random series approach [104][105][106][107][108][109][110] to the imaginary time path integral in manifolds that are mappable by stereographic projections. The random series expansion of the path consists of k m core terms and an additional 3k m tail terms,…”
Section: A Stereographic Projection Path Integralmentioning
confidence: 99%
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“…In a series of works [63][64][65][66][67][68][69][70] we have extended the reweighted random series approach [104][105][106][107][108][109][110] to the imaginary time path integral in manifolds that are mappable by stereographic projections. The random series expansion of the path consists of k m core terms and an additional 3k m tail terms,…”
Section: A Stereographic Projection Path Integralmentioning
confidence: 99%
“…18 Additionally, we can ignore the difference between the Jacobian obtained from the manifold and the Jacobian obtained in R 9n , with infinitely stiff springs replacing the holonomic constraints, 115 since their ratio is a constant. 70 To implement the Metropolis algorithm, we move the center of mass or the orientation of a randomly selected molecule, and we translate one path variable for each coordinate moved, e.g.,…”
Section: A Stereographic Projection Path Integralmentioning
confidence: 99%
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