Complex Fluid Models of Mixed Quantum–Classical Dynamics.

Saved in:
Bibliographic Details
Title: Complex Fluid Models of Mixed Quantum–Classical Dynamics.
Authors: Gay-Balmaz, François1 (AUTHOR), Tronci, Cesare2 (AUTHOR) c.tronci@surrey.ac.uk
Source: Journal of Nonlinear Science. Oct2024, Vol. 34 Issue 5, p1-34. 34p.
Subjects: Complex fluids, Solvation, Solvents, Molecular dynamics, Quantum liquids, Electronic equipment, Hamiltonian systems
Abstract: Several methods in nonadiabatic molecular dynamics are based on Madelung's hydrodynamic description of nuclear motion, while the electronic component is treated as a finite-dimensional quantum system. In this context, the quantum potential leads to severe computational challenges and one often seeks to neglect its contribution, thereby approximating nuclear motion as classical. The resulting model couples classical hydrodynamics for the nuclei to the quantum motion of the electronic component, leading to the structure of a complex fluid system. This type of mixed quantum–classical fluid models has also appeared in solvation dynamics to describe the coupling between liquid solvents and the quantum solute molecule. While these approaches represent a promising direction, their mathematical structure requires a certain care. In some cases, challenging higher-order gradients make these equations hardly tractable. In other cases, these models are based on phase-space formulations that suffer from well-known consistency issues. Here, we present a new complex fluid system that resolves these difficulties. Unlike common approaches, the current system is obtained by applying the fluid closure at the level of the action principle of the original phase-space model. As a result, the system inherits a Hamiltonian structure and retains energy/momentum balance. After discussing some of its structural properties and dynamical invariants, we illustrate the model in the case of pure-dephasing dynamics. We conclude by presenting some invariant planar models. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Nonlinear Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
Be the first to leave a comment!
You must be logged in first