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Paper · arXiv

Noise Models Impacts and Mitigation Strategies in Photonic Quantum Machine Learning

Photonic Quantum Machine Learning (PQML) is an emerging method to implement scalable, energy-efficient quantum information processing by combining photonic quantum computing technologies with machine learning techniques. The features of photonic technologies offer several benefits: room-temperature operation; fast (low delay) processing of signals; and the possibility of representing computations in high-dimensional (Hilbert) spaces. This makes photonic technologies a good candidate for the near-term development of quantum devices. However, noise is still a major limiting factor for the performance, reliability, and scalability of PQML implementations. This review provides a detailed and ...

AuthorsA. M. A. S. D. Alagiyawanna, Asoka Karunananda
Primary categoryquant-ph
Published10 March 2026
Last updated at source4 April 2026
quant-phcs.LG
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