A programmable silicon photonic chip excited with single photons implements quantum reservoir computing for quantum state tomography, entanglement measurement via negativity, and classical tasks, with an imperfection mitigation technique that improves accuracy over the classical regime.
arXiv preprint arXiv:2512.08318 (2025)
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MerLin is a new open-source discovery engine for photonic and hybrid quantum machine learning that integrates circuit simulations into standard ML frameworks and reproduces 18 prior works as reusable benchmarks.
Q-PhotoNAS applies genetic algorithm search to jointly optimize classical preprocessing, phase encoding, and photonic circuit structure for hybrid quantum-classical models, reporting 99.44% and 98.78% accuracy on Digits and MNIST with projected photonic QPU inference times.
citing papers explorer
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Quantum and classical processing with photonic quantum machine learning
A programmable silicon photonic chip excited with single photons implements quantum reservoir computing for quantum state tomography, entanglement measurement via negativity, and classical tasks, with an imperfection mitigation technique that improves accuracy over the classical regime.
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MerLin: A Discovery Engine for Photonic and Hybrid Quantum Machine Learning
MerLin is a new open-source discovery engine for photonic and hybrid quantum machine learning that integrates circuit simulations into standard ML frameworks and reproduces 18 prior works as reusable benchmarks.
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Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices
Q-PhotoNAS applies genetic algorithm search to jointly optimize classical preprocessing, phase encoding, and photonic circuit structure for hybrid quantum-classical models, reporting 99.44% and 98.78% accuracy on Digits and MNIST with projected photonic QPU inference times.