Spectral solution of the inverse Mie problem
Autor: | Konstantin V. Gilev, Valeri P. Maltsev, Ekaterina S. Yastrebova, Anastasiya I. Konokhova, Dmitry I. Strokotov, Andrei V. Chernyshev, Andrey V. Romanov, Maxim A. Yurkin |
---|---|
Rok vydání: | 2017 |
Předmět: |
Physics
Radiation 010504 meteorology & atmospheric sciences business.industry Mie scattering Mathematical analysis Inverse Inverse problem 01 natural sciences Atomic and Molecular Physics and Optics Light scattering 010309 optics Optics 0103 physical sciences SPHERES Particle size Spectral method business Refractive index Spectroscopy 0105 earth and related environmental sciences |
Zdroj: | Journal of Quantitative Spectroscopy and Radiative Transfer. 200:280-294 |
ISSN: | 0022-4073 |
Popis: | We developed a fast method to determine size and refractive index of homogeneous spheres from the power Fourier spectrum of their light-scattering patterns (LSPs), measured with the scanning flow cytometer. Specifically, we used two spectral parameters: the location of the non-zero peak and zero-frequency amplitude, and numerically inverted the map from the space of particle characteristics (size and refractive index) to the space of spectral parameters. The latter parameters can be reliably resolved only for particle size parameter greater than 11, and the inversion is unique only in the limited range of refractive index with upper limit between 1.1 and 1.25 (relative to the medium) depending on the size parameter and particular definition of uniqueness. The developed method was tested on two experimental samples, milk fat globules and spherized red blood cells, and resulted in accuracy not worse than the reference method based on the least-square fit of the LSP with the Mie theory. Moreover, for particles with significant deviation from the spherical shape the spectral method was much closer to the Mie-fit result than the estimated uncertainty of the latter. The spectral method also showed adequate results for synthetic LSPs of spheroids with aspect ratios up to 1.4. Overall, we present a general framework, which can be used to construct an inverse algorithm for any other experimental signals. |
Databáze: | OpenAIRE |
Externí odkaz: |