Quantum-enhanced imaging and sensing with spatially correlated biphotons

Toninelli, Ermes (2020) Quantum-enhanced imaging and sensing with spatially correlated biphotons. PhD thesis, University of Glasgow.

Abstract

In this thesis I discuss the experimental demonstration of quantum-enhanced imaging and sensing schemes able to surpass the performance of their classical counterparts. This is achieved by exploiting the spatial properties of quantum correlated biphotons. Over the next chapters I first discuss the production and detection of quantum correlated photons using a type-I nonlinear crystal and a single-photon sensitive electron-multiplying CCD camera. I then provide a simple yet powerful description of the spatially resolved detection of biphotons, allowing to accurately model and assess the performance of the quantum-enhanced schemes featured in this thesis. These consist of a shadow-sensing and an imaging scheme able to respectively beat the shot-noise-limit in the optical measurement of the position of a shadow and the diffraction limit in the full-field imaging of real-world objects. A combination of simulated and experimental results are used to investigate both the achieved and theoretically available quantum advantage. Optical losses and detector noise are found to limit the better-than-classical performance of the schemes, which rely on the ability to jointly detect an as high as possible number of spatially correlated biphotons.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: quantum enhanced imaging sensing spatially correlated biphotons.
• Subjects: Q Science > QC Physics
• Colleges/Schools: College of Science and Engineering > School of Physics and Astronomy
• Funder's Name: Scottish Funding Council (SFC), Engineering and Physical Sciences Research Council (EPSRC)
• Supervisor's Name: Padgett, Professor Miles
• Date of Award: 2020
• Depositing User: Dr Ermes Toninelli
• Unique ID: glathesis:2020-80288
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 26 Mar 2020 08:38
• Last Modified: 06 Oct 2022 15:32
• Thesis DOI: 10.5525/gla.thesis.80288
• URI: https://theses.gla.ac.uk/id/eprint/80288

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