2008
DOI: 10.1063/1.2837802
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Stereographic projection path integral simulations of (HCl)n clusters (n=2–5): Evidence of quantum induced melting in small hydrogen bonded networks

Abstract: We investigate the quantum thermodynamic properties of small (HCl)(n) clusters using stereographic projection path integral simulations. The HCl stretches are rigid, the orientations are mapped with stereographic projection coordinates, and we make use of the reweighted random series techniques to obtain cubic convergence with respect to the number of path coefficients. Path integral simulations are converged at and above 10 K for the pentamer and above 15 K for the dimer and the trimer. None of the systems di… Show more

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Cited by 18 publications
(25 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%
“…64,67,69 We extend the reweighted random series method [104][105][106][107][108][109][110] and the finite difference estimators 108 for cubically convergent path integral simulations to manifolds. 68 DMC simulations are nearly as straightforward to implement in curved spaces mapped with stereographic projection coordinates as they are with Cartesian coordinates. 72 As the only difference, the distribution of the diffusion step in curved spaces is generally not a simple Gaussian, and several straight-forward rejection techniques have been tested successfully.…”
Section: Introductionmentioning
confidence: 99%
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