Smart Quantum Technologies using Photons
Narayan Bhusal

TL;DR
This paper reviews recent advances in quantum photonics, introduces smart methodologies combining quantum optics and machine learning, and demonstrates novel techniques for quantum metrology, light discrimination, and communication.
Contribution
It presents new theoretical schemes for quantum metrology, innovative AI-based methods for light discrimination, and neural network-based correction protocols for quantum communication.
Findings
Sub-shot-noise limited phase estimation using displaced-squeezed light
Camera-based squeezed-light detection as an efficient alternative
High-fidelity mode correction with convolutional neural networks
Abstract
The technologies utilizing quantum states of light have been in the spotlight for the last two decades. In this regard, quantum metrology, quantum imaging, quantum-optical communication are some of the important applications that exploit fascinating quantum properties like quantum superposition, quantum correlations, and nonclassical photon statistics. However, the state-of-art technologies operating at the single-photon level are not robust enough to truly realize a reliable quantum-photonic technology. In Chapter 1, I present a historical account of photon-based technologies. Furthermore, I discuss recent encouraging developments in the field of quantum-photonic technologies, and major challenges for the implementation of reliable quantum technologies, setting up a stage for unveiling our smart methodologies to cope with them. Similarly, in Chapter 2, I review the fundamental…
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Taxonomy
TopicsQuantum Information and Cryptography · Neural Networks and Reservoir Computing
