Literature DB >> 26001438

Communication: Relation of centroid molecular dynamics and ring-polymer molecular dynamics to exact quantum dynamics.

Timothy J H Hele1, Michael J Willatt1, Andrea Muolo1, Stuart C Althorpe1.   

Abstract

We recently obtained a quantum-Boltzmann-conserving classical dynamics by making a single change to the derivation of the "Classical Wigner" approximation. Here, we show that the further approximation of this "Matsubara dynamics" gives rise to two popular heuristic methods for treating quantum Boltzmann time-correlation functions: centroid molecular dynamics (CMD) and ring-polymer molecular dynamics (RPMD). We show that CMD is a mean-field approximation to Matsubara dynamics, obtained by discarding (classical) fluctuations around the centroid, and that RPMD is the result of discarding a term in the Matsubara Liouvillian which shifts the frequencies of these fluctuations. These findings are consistent with previous numerical results and give explicit formulae for the terms that CMD and RPMD leave out.

Entities:  

Year:  2015        PMID: 26001438     DOI: 10.1063/1.4921234

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  5 in total

1.  Formulation of state projected centroid molecular dynamics: Microcanonical ensemble and connection to the Wigner distribution.

Authors:  Lindsay Orr; Lisandro Hernández de la Peña; Pierre-Nicholas Roy
Journal:  J Chem Phys       Date:  2017-06-07       Impact factor: 3.488

2.  Centroid Molecular Dynamics Can Be Greatly Accelerated through Neural Network Learned Centroid Forces Derived from Path Integral Molecular Dynamics.

Authors:  Timothy D Loose; Patrick G Sahrmann; Gregory A Voth
Journal:  J Chem Theory Comput       Date:  2022-09-14       Impact factor: 6.578

3.  The strengths and limitations of effective centroid force models explored by studying isotopic effects in liquid water.

Authors:  Ying Yuan; Jicun Li; Xin-Zheng Li; Feng Wang
Journal:  J Chem Phys       Date:  2018-05-14       Impact factor: 3.488

4.  A generalized class of strongly stable and dimension-free T-RPMD integrators.

Authors:  Jorge L Rosa-Raíces; Jiace Sun; Nawaf Bou-Rabee; Thomas F Miller
Journal:  J Chem Phys       Date:  2021-01-14       Impact factor: 3.488

5.  Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.

Authors:  John A Keith; Valentin Vassilev-Galindo; Bingqing Cheng; Stefan Chmiela; Michael Gastegger; Klaus-Robert Müller; Alexandre Tkatchenko
Journal:  Chem Rev       Date:  2021-07-07       Impact factor: 60.622

  5 in total

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