A genetic-algorithm framework searches 19 photonic hybrid-network design choices and reports 99.44% (Digits) and 98.78% (MNIST) validation accuracy in simulation.
Experimental quantum-enhanced kernels on a photonic processor
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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quant-ph 2years
2026 2representative citing papers
Logical quantum kernels outperform physical ones when solving differential equations on a neutral-atom processor, with gains traced to noise error detection in the logical encoding.
citing papers explorer
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Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices
A genetic-algorithm framework searches 19 photonic hybrid-network design choices and reports 99.44% (Digits) and 98.78% (MNIST) validation accuracy in simulation.
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Benchmarking a machine-learning differential equations solver on a neutral-atom logical processor
Logical quantum kernels outperform physical ones when solving differential equations on a neutral-atom processor, with gains traced to noise error detection in the logical encoding.