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This review presents an overview of the current state-of-the-art in photonicscomputing, which leverages photons, photons coupled with matter, andoptics-related technologies for effective and efficient computational purposes.It covers the history and development of photonics computing and modernanalogue computing platforms and architectures, focusing on optimization tasksand neural network implementations. The authors examine special-purposeoptimizers, mathematical descriptions of photonics optimizers, and theirvarious interconnections. Disparate applications are discussed, includingdirect encoding, logistics, finance, phase retrieval, machine learning, neuralnetworks, probabilistic graphical models, and image processing, among manyothers. The main directions of technological advancement and associatedchallenges in photonics computing are explored, along with an assessment of itsefficiency. Finally, the paper discusses prospects and the field of opticalquantum computing, providing insights into the potential applications of thistechnology.

Analog Photonics Computing for Information Processing, Inference and Optimisation