SpecSwap RMC: A novel reverse Monte Carlo approach using a discrete configuration space and pre-computed properties

TL;DR

SpecSwap RMC introduces a reverse Monte Carlo method that uses pre-computed property data and swap moves in a discrete configuration space, improving efficiency for disordered systems and complex properties.

Contribution

The paper presents a novel RMC approach using pre-computed data and swap moves, enabling efficient modeling of disordered systems and complex properties.

Findings

Successfully fitted EXAFS and XAS data for ice Ih

Achieved excellent agreement with FEFFIT on copper EXAFS data

Demonstrated efficiency for properties requiring significant computation

Abstract

We present a novel approach to reverse Monte Carlo (RMC) modeling, SpecSwap-RMC, which makes use of pre-computed property data from a discrete configuration space replacing atomistic moves with swap moves of contributions to a sample-set representing the average, or summed property. The approach is particularly suitable for disordered systems and properties which require significant computer time to compute. We demonstrate the approach by fitting jointly and separately the EXAFS signal and x-ray absorption spectrum (XAS) of ice Ih using as SpecSwap sample-set 80 configurations from a space of 1382 local structures with associated pre-computed spectra. As an additional demonstration we compare SpecSwap and FEFFIT fits of EXAFS data on crystalline copper finding excellent agreement.