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CPDDA: A Python Package for Discrete Dipole Approximation Accelerated by CuPy
Dibo Xu1, Paerhatijiang Tuersun1, Shuyuan Li1
1Xinjiang Key Laboratory for Luminescence Minerals and Optical Functional Materials, School of Physics and Electronic Engineering, Xinjiang Normal University, Urumqi 830054, China.
Abstract:
Discrete Dipole Approximation (DDA) is a rapidly developing numerical method in recent years. DDA has found wide application in many research fields including plasmonics and atmospheric optics. Currently, few DDA packages based on Python have been reported. In this work, a Python package called CPDDA is developed. It can be used to simulate the light-scattering and -absorption properties of arbitrarily shaped particles. CPDDA uses object-oriented programming, offers high flexibility and extensibility, and provides a comprehensive database of refractive indices. The package uses the biconjugate gradient method and fast Fourier transform for program acceleration and memory optimization, and it uses parallel computation with graphics processing units to enhance program performance. The accuracy and performance of CPDDA were demonstrated by comparison with Mie theory, the MATLAB package MPDDA, and the Python package pyGDM2. Finally, CPDDA was used to simulate the variations in light-absorption and -scattering properties of ZnO@Au core-shell nanorods based on the particle size. CPDDA is useful for calculating light-scattering and -absorption properties of small particles and selecting materials with excellent optical properties.
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