Machine-learning recognition of light orbital-angular-momentum superpositions
| العنوان: | Machine-learning recognition of light orbital-angular-momentum superpositions |
|---|---|
| المؤلفون: | Bruno Augusto Dorta Marques, Antonio Z. Khoury, P. H. Souto Ribeiro, R. B. Rodrigues, B. Pinheiro da Silva |
| المصدر: | Physical Review A. 103 |
| بيانات النشر: | American Physical Society (APS), 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Physics, Quantum Physics, FOS: Physical sciences, Physics::Optics, Order (ring theory), Invariant (physics), 01 natural sciences, Convolutional neural network, 010305 fluids & plasmas, Image (mathematics), Superposition principle, Classical mechanics, Transformation (function), 0103 physical sciences, Orbital angular momentum of light, Quantum Physics (quant-ph), 010306 general physics, Beam (structure), Physics - Optics, Optics (physics.optics) |
| الوصف: | We develop a method to characterize arbitrary superpositions of light orbital angular momentum (OAM) with high fidelity by using astigmatic transformation and machine-learning processing. In order to identify each superposition unequivocally, we combine two intensity measurements. The first one is the direct image of the input beam, which is invariant for positive and negative OAM components. The second one is an image obtained using an astigmatic transformation, which allows distinguishing between positive and negative topological charges. Samples of these image pairs are used to train a convolution neural network and achieve high-fidelity recognition of arbitrary OAM superpositions. |
| تدمد: | 2469-9934 2469-9926 |
| DOI: | 10.1103/physreva.103.063704 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83bf179a2a44e99b2a975933eb7e7f6b https://doi.org/10.1103/physreva.103.063704 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....83bf179a2a44e99b2a975933eb7e7f6b |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 24699934 24699926 |
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| DOI: | 10.1103/physreva.103.063704 |