True and false symmetries in the classification of optical scatterers

Giovanni F. Crosta; Gorden Videen

doi:10.1117/12.2049577

28 May 2014 True and false symmetries in the classification of optical scatterers

Giovanni F. Crosta, Gorden Videen

Proceedings Volume 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014; 91210I (2014) https://doi.org/10.1117/12.2049577
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

A plane wave is scattered by a potential of bounded support. Translation, rotation and reflection of the potential, q0 induce transformations of the scattered wave. The latter can be represented by means of Born sequences, where q0 appears under the integral sign: non-local formulas are thus derived, the properties of which are discussed. Next, the symmetries induced by the 1^st BORN approximation are addressed. Invariance of the squared modulus of the scattering amplitude holds for translation and reflection. The transformation T_ε := 1₃ +Σ³ℓ=1ε_ℓA_ℓ,with {ε_ℓ;} real and {A_ℓ} the generators of rotations in IR³, is investigated. Conditions on the {ε_ℓ} are derived, by which the scattering amplitude coming from the first BORN approximation is invariant to T_ε. As an application, these “false symmetries” are compared to those induced by limited angular resolution of a detector in light scattering experiments. Namely, scattering patterns are made available by the TAOS (Two-dimensional Angle-resolved Optical Scattering) method, which consists of detecting single airborne aerosol particles and collecting the intensity of the light they scatter from a pulsed, monochromatic laser beam. The optics and the detector properties determine the resolution at which a pattern is saved. The implications on the performance of TAOS pattern analysis are briefly discussed.

Citation Download Citation

Giovanni F. Crosta and Gorden Videen "True and false symmetries in the classification of optical scatterers", Proc. SPIE 9121, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014, 91210I (28 May 2014); https://doi.org/10.1117/12.2049577

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