Abstract

Inelastic neutron scattering is an experimental technique widely used to investigate the vibrational characteristics of materials in condensed matter research. While coherent inelastic neutron scattering is typically restricted to single-crystal samples, analysis of the complex datasets obtained on polycrystalline samples remains challenging, even for the simplest of structures. However, given the common availability of high performance computing platforms, it is becoming feasible to apply computationally intensive calculation methods that sample millions of q-points to the simulation of polycrystalline models of increasing complexity, a technique referred to as poly-CINS analysis. This approach allows the interpretation of experimental results by comparison and fitting against theoretical models. This paper describes a new high-performance implementation of the Scatter code, a modelling package developed for the General Utility Lattice Program (Gulp) for heterogenous CPU-GPU computing architectures. It provides the ability to generate theoretical poly-CINS data sets from semi-empirical and ab-initio models. We present the computational framework behind its implementation, applying an example of a semi-empirical model for the dynamics of a large unit-cell system, namely the two (low and ambient temperature) phases of solid C60 to illustrate the methodology and its scalability characteristics.

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