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Direct quantum dynamics using grid-based wavefunction propagation and machine-learned potential energy surfaces
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Richings, Gareth and Habershon, Scott (2017) Direct quantum dynamics using grid-based wavefunction propagation and machine-learned potential energy surfaces. Journal of Chemical Theory and Computation, 13 (9). pp. 4017-4024. doi:10.1021/acs.jctc.7b00507 ISSN 1549-9618.
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WRAP-direct-quantum-dynamics-grid-based-wavefunction-propagation-Habershon-2017.pdf - Accepted Version - Requires a PDF viewer. Download (1090Kb) | Preview |
Official URL: http://dx.doi.org/10.1021/acs.jctc.7b00507
Abstract
We describe a method for performing nuclear quantum dynamics calculations using standard, grid-based algorithms, including the multi configurational time-dependent Hartree (MCTDH) method, where the potential energy surface (PES) is calculated “on-the-fly”. The method of Gaussian process regression (GPR) is used to construct a global representation of the PES using values of the energy at points distributed in molecular configuration space during the course of the wavepacket propagation. We demonstrate this direct dynamics approach for both an analytical PES function describing 3-dimensional proton transfer dynamics in malonaldehyde, and for 2- and 6-dimensional quantum dynamics simulations of proton transfer in salicylaldimine. In the case of salicylaldimine we also perform calculations in which the PES is constructed using Hartree-Fock calculations through an interface to an ab initio electronic structure code. In all cases, the results of the quantum dynamics simulations are in excellent agreement with previous simulations of both systems, yet do not require prior fitting of a PES at any stage. Our approach (implemented in a development version of the Quantics package) opens a route to performing accurate quantum dynamics simulations via wavefunction propagation of many-dimensional molecular systems in a direct and efficient manner.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QD Chemistry | ||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Chemistry Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing |
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| Type of Data: | Plain text data files | ||||||||
| Library of Congress Subject Headings (LCSH): | Potential energy surfaces, Proton transfer reactions | ||||||||
| Journal or Publication Title: | Journal of Chemical Theory and Computation | ||||||||
| Publisher: | American Chemical Society | ||||||||
| ISSN: | 1549-9618 | ||||||||
| Official Date: | 18 July 2017 | ||||||||
| Dates: |
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| Volume: | 13 | ||||||||
| Number: | 9 | ||||||||
| Page Range: | pp. 4017-4024 | ||||||||
| DOI: | 10.1021/acs.jctc.7b00507 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 3 January 2018 | ||||||||
| Date of first compliant Open Access: | 18 July 2018 | ||||||||
| RIOXX Funder/Project Grant: |
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