An Accelerated Method for Investigating Spectral Properties of Dynamically Evolving Nanostructures

The discrete-dipole approximation (DDA) is widely applied to study the spectral properties of plasmonic nanostructures. However, the high computational cost limits the application of DDA in static geometries, making it impractical for investigating spectral properties during structural transformations. Here we developed an efficient method to simulate spectra of dynamically evolving structures by formulating an iterative calculation process based on the rankone decomposition of matrices and DDA. By representing structural transformation as the change of dipoles and their properties, the updated polarizations can be computed efficiently. The improvement in computational efficiency was benchmarked, demonstrating up to several hundred times acceleration for a system comprising ca. 4000 dipoles. The rank-one decomposition accelerated DDA method (RD-DDA) can be used directly to investigate the optical properties of nanostructural transformations defined by atomic- or continuum-scale processes, which is essential for understanding the growth mechanisms of nanoparticles and algorithm-driven structural optimization toward enhanced optical properties.

Automated summary

The discrete-dipole approximation (DDA) is widely used for studying the spectral properties of plasmonic nanostructures. However, its high computational cost limits its application in static geometries and makes it impractical for investigating spectral properties during structural transformations. In this study, we developed an efficient method called rank-one decomposition accelerated DDA (RD-DDA) to simulate spectra of dynamically evolving structures. The RD-DDA method can be used to directly investigate the optical properties of nanostructural transformations defined by atomic- or continuum-scale processes, which is crucial for understanding the growth mechanisms of nanoparticles and optimizing their optical properties.