Quantum simulations of warm dense matter dynamics using Bohm's trajectories

Lead Research Organisation: University of Oxford
Department Name: Oxford Physics

Abstract

The projects intends to explore the possibility of using Bohm's interpretation of quantum mechanics in order to develop a numerical scheme for the dynamics of many-electron systems. The advantage is that the solutions would requires the solution of a classical trajectory problem (for which molecular dynamics is a good example) but with the addition of a quantum force that capture the non-local properties of quantum systems.

The projects deliverable is the calculation of static and dynamic structure factors in dense plasmas.

So far no one has implemented Bohm's quantum approach in a plasma code. Approaches along these lines have been attempted in condensed matter, but the full many-body finite-temperature problem has not yet been fully tackled. If successful, this would represent a major step forward, with a method that is competitive against density functional theory but has the advantage of keeping the full dynamical behavior.

This project falls within the Plasma and Lasers.

Any companies or collaborators involved - AWE plc.

Publications

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publication icon
Larder B (2019) Fast nonadiabatic dynamics of many-body quantum systems. in Science advances

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509711/1 01/10/2016 30/09/2021
1851214 Studentship EP/N509711/1 01/10/2016 10/04/2021 Brett Larder
 
Description A new computational approach for determining the properties of quantum systems was developed and implemented. This method will prove especially valuable for calculating the properties of specific types of plasma. As such, it has direct application to the study of planetary interiors, and will provide practical and detailed insights into the processes occurring in fusion reactors. The method will be a valuable tool for fusion researchers seeking to understand plasma dynamics in reactors, and has the potential to aid improved reactor design in the future.

Alongside this, several algorithms have been developed for inferring plasma properties from incomplete and noisy diagnostic measurements. In combination with the new predictive algorithm described above, researchers will be able to deploy our work to make accurate predictions about plasma behaviour before conducting experiments, and also obtain more accurate and complete insights from the resulting experimental data.
Exploitation Route Our method can be extended to more complex systems and materials, broadening it's utility. This work is underway, and has the potential to provide insight into complex material and drug design.

The algorithms we have developed can be put to use in order to make predictions about quantum plasmas in a range of contexts. Most notably, they open the door to improved modelling of fusion processes on the path to ignition - this has the potential to assist reactor design in the future, and aid progress towards reliable fusion energy.
Sectors Aerospace, Defence and Marine,Chemicals,Energy

 
Title Bohmian Trajectory Method for Quantum Simulations 
Description A new numerical technique and associated implementation for modelling many-body quantum systems at finite temperature, with dramatically reduced computational cost. Allows simulations to be performed non-adiabatically without prohibitive computational demands, enabling calculations that were not previously possible. The work on this software, in addition to a range of associated theoretical work on the dynamic structure of warm dense matter, is still largely in progress. 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact Publication of the core method and related algorithms is pending. Associated work is still ongoing. 
URL https://arxiv.org/abs/1811.08161
 
Title Multifidelity optimisation and sampling methods for inference of system properties from noisy measurements 
Description Multiple related algorithms have been developed that allow noisy experimental measurements and simulations to be combined in order to produce robust, accurate insights into physical properties. 
Type Of Material Improvements to research infrastructure 
Year Produced 2019 
Provided To Others? No  
Impact Two papers targeting high-impact journals are currently being produced to describe the methods and their applications. 
 
Description Collaboration on development of numerical methods 
Organisation Atomic Weapons Establishment
Country United Kingdom 
Sector Private 
PI Contribution Developed the core theory for quantum simulation using Bohmian trajectories, developed the associated algorithms, and wrote the implementation.
Collaborator Contribution Warwick: Provided specific advice for diagnosing issues with the computational implementation, and ideas for improving the code. AWE: Provided supporting Density Functional Theory calculations required for testing. Funding support.
Impact An implementation of a novel quantum simulation scheme, and associated paper (submitted, not yet published).
Start Year 2017
 
Description Collaboration on development of numerical methods 
Organisation University of Warwick
Country United Kingdom 
Sector Academic/University 
PI Contribution Developed the core theory for quantum simulation using Bohmian trajectories, developed the associated algorithms, and wrote the implementation.
Collaborator Contribution Warwick: Provided specific advice for diagnosing issues with the computational implementation, and ideas for improving the code. AWE: Provided supporting Density Functional Theory calculations required for testing. Funding support.
Impact An implementation of a novel quantum simulation scheme, and associated paper (submitted, not yet published).
Start Year 2017
 
Title Implementation of Bohmian Trajectory Method 
Description An implementation of the newly developed Bohmian Trajectory Method, which allows for fast, highly parallel calculations to be conducted using the new theory. The software is developed in Python and Cython/C++, and can be run using input decks or interactively through Python notebooks. 
Type Of Technology Software 
Year Produced 2018 
Impact Publication is pending (see URL). 
URL https://arxiv.org/abs/1811.08161
 
Company Name MACHINE DISCOVERY LIMITED 
Description Software company spun out to develop advanced optimisation, sampling, and materials modelling methods. 
Year Established 2019 
Impact Provides key software tools to multiple private and public research institutions associated with fusion and plasma physics. The company intends to build on work associated with this award to create further commercial modelling software in the near future.
Website https://machine-discovery.com