نویسنده
Zhu, Y., Liu, C., Yurkin, Maxim A.
تاریخ انتشار
2023-12-18
محل انتشار
-
Optica Publishing Group
نوع
دوره ای
زبان
انگلیسی
دیجیتال
بله
نسخه خطی
خیر
کتابخانه
دانشگاه اوزیغین
شناسه دارایی کتابخانه
1094-4087
شماره ثبت
15d8bfec-433d-4d9b-91dd-b7afbe10b24d
تاریخ
2023-12-18
یادداشتها
National Natural Science Foundation of China ; Nanjing University of Information Science and Technology ; Graduate Research and Innovation Projects of Jiangsu Province
متن نمونه
The discrete dipole approximation (DDA) simulates optical properties of particles with any given shape based on the volume discretization. These calculations cost a large amount of time and memory to achieve high accuracy, especially for particles with large sizes and complex geometric structures, such as mixed black-carbon aerosol particles. We systematically study the smoothing of the DDA discretization using the effective medium approximation (EMA) for boundary dipoles. This approach is tested for optical simulations of spheres and coated black-carbon (BC) aggregates, using the Lorenz-Mie and multiple-sphere T-Matrix as references. For spheres, EMA significantly improves the DDA accuracy of integral scattering quantities (up to 60 times), when the dipole size is only several times smaller than the sphere diameter. In these cases, the application of the EMA is often comparable to halving the dipole size in the original DDA, thus reducing the simulation time by about an order of magnitude for the same accuracy. For a coated BC model based on transmission electron microscope observations, the EMA (specifically, the Maxwell Garnett variant) significantly improves the accuracy when the dipole size is larger than ¼ of the monomer diameter. For instance, the relative error of extinction efficiency is reduced from 4.7% to 0.3% when the dipole size equals that of the spherical monomer. Moreover, the EMA-DDA achieves the accuracy of 1% for extinction, absorption, and scattering efficiencies using three times larger dipoles than that with the original DDA, corresponding to about 30 times faster simulations.
DOI
10.1364/OE.509479
Cilt
31
