search

ZhouHUB / pyIID

Monte Carlo Based Diffraction Simulation
Other
1 stars 0 forks source link

readme

Python Infinite Improbability Drive

Build Status Coverage Status

Is designed for the Monte Carlo modeling of nanomaterials using atomic pair distributuion functions, other experimental data, and ab-initio structural calculations.

Areas that need improvement:

  1. GPU based gradient and PDF potential energy functions: otherwise everything is very slow.
    1. Gradient: particularly expensive on single threaded systems, which makes Hamiltonian Monte Carlo glacially slow
    2. Generating PDFs: currently using diffpy.srreal for PDF generation, which is not GPU optimized
    3. PDF potential energy: this is quantified using the RW value which could also be put onto the GPU
  2. Ab-initio calculation support:while most of this is handled by ASE issues include
    1. Scaling and Units for PDF comparison: we need a way to effectively tune the relationship between the PDF and the ab-initio, otherwise one will dominate the refinement and dynamics
    2. Support for non-ASE calculators