Nano-particle Transition Matrix code implementation

TL;DR

This paper introduces NP_TMcode, a high-performance parallel implementation of the T-matrix method for electromagnetic scattering by nano-particles, enabling complex modeling with reduced computational time.

Contribution

The paper presents a novel, optimized, parallel code for the T-matrix formalism, significantly improving computational efficiency for nano-particle scattering simulations.

Findings

Enhanced computational speed with parallel hardware

Successful modeling of complex nano-particle aggregates

Performance analysis demonstrates scalability and efficiency

Abstract

Electromagnetic scattering and absorption by material particles is a fundamental physical problem with a broad range of applications, going from laboratory experiments, biology and material sciences, all the way up to environmental studies and astrophysical investigations. In spite of its primary importance, an exact theoretical treatment is only possible for a limited range of ideal cases, while realistic situations require the development of numerical solutions. In the course of the years, several techniques were developed to model the effects of scattering and absorption in more general cases, using approaches such as the Discrete Dipole Approximation (DDA), the Finite Difference Time Domain (FDTD) method, the Transition Matrix formalism (T-matrix) or the Mean Field Theory (MFT). Among these possibilities, the T-matrix approach grants the highest degree of flexibility in modeling aggregates of spherically symmetric particles with arbitrary overall morphology and composition, but its application has been limited by the challenging computational requirements of the method in realistic cases. This paper describes the Nano-Particle Transition Matrix Code project (NP_TMcode), a new implementation of the T-matrix formalism that, taking advantage of high performance parallel hardware architectures, allows the solution of increasingly complex models, while substantially reducing the computing time. The paper describes the code structure, with a particular focus on the algorithm optimization, and it presents the results of the performance analysis for a set of development applications.