Presentation + Paper
5 March 2021 Engineering and characterization of high-dimensional states
Alessia Suprano, Taira Giordani, Emanuele Polino, Danilo Zia, Sabrina Emiliani, Francesca Acanfora, Luca Innocenti, Helena Majury, Lorenzo Marrucci, Alessandro Ferraro, Mauro Paternostro, Nicolò Spagnolo, Fabio Sciarrino
Author Affiliations +
Abstract
The capability to engineer and characterize high dimensional states has become a crucial request in the quantum information field. The quantum walk dynamics proved to be a suitable resource for developing general quantumstate engineering protocols. Here, we experimentally verified the flexibility of an engineering protocol based on a one-dimensional quantum walk in the Orbital Angular Momentum (OAM). Although this degree of freedom has found several applications in the quantum information field, extract the information stored in them appears to be difficult. Therefore, we employ machine learning protocols to classify and characterize particularly structured beams endowed with a not uniform distribution of the polarization on the transverse plane. Moreover, we prove that by modeling the engineering process through a refined model it is possible to improve the performances of measurement techniques such as holographic projection and machine-learning based classification. These results represent a further investigation in the manipulation and detection of OAM modes coupling the photonics platforms with machine-learning protocols.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alessia Suprano, Taira Giordani, Emanuele Polino, Danilo Zia, Sabrina Emiliani, Francesca Acanfora, Luca Innocenti, Helena Majury, Lorenzo Marrucci, Alessandro Ferraro, Mauro Paternostro, Nicolò Spagnolo, and Fabio Sciarrino "Engineering and characterization of high-dimensional states", Proc. SPIE 11699, Quantum Computing, Communication, and Simulation, 1169917 (5 March 2021); https://doi.org/10.1117/12.2582668
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KEYWORDS
Polarization

Principal component analysis

Machine learning

Structured light

Photons

Quantum communications

Quantum state engineering

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