Skip to content

Latest commit

 

History

History
22 lines (13 loc) · 1.31 KB

README.md

File metadata and controls

22 lines (13 loc) · 1.31 KB
Raw

FunUQ

Functional Uncertainty Quantification with Python

Sam Reeve

This code enables FunUQ for MD with LAMMPS. More examples are under current investigation. If you use this code, please cite the FunUQ literature:

Reeve, S. T. & Strachan, A. Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies. Modelling Simul. Mater. Sci. Eng. 27, 044002 (2019). https://doi.org/10.1088/1361-651X/ab16fa

Reeve, S. T. & Strachan, A. Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification. J. Comput. Phys. 334, 207–220 (2017). https://doi.org/10.1016/j.jcp.2016.12.039

Strachan, A., Mahadevan, S., Hombal, V. & Sun, L. Functional derivatives for uncertainty quantification and error estimation and reduction via optimal high-fidelity simulations. Modelling Simul. Mater. Sci. Eng. 21, 065009 (2013). https://doi.org/10.1088/0965-0393/21/6/065009

Try an example through nanoHUB: https://nanohub.org/resources/funuq

Examples currently included:

  • One case from Reeve & Strachan J. Comput. Phys. 2017: correction between Lennard-Jones and a sine-modified LJ ("Sine 1")
  • Cases from Reeve & Strachan MSMSE 2019: correction between Morse and exponential-6
    • NVT (canonical ensemble)
    • NPT (isothermal-isobaric ensemble)