RP000, a room-temperature CMOS photonic three-qubit processor, delivers higher or comparable accuracy to parameter-matched classical nets on ML classification and better noise tolerance than a superconducting processor.
Data re-uploading for a universal quantum classifier
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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Diagonal ANOs are mathematically equivalent to full ANOs modulo unitary similarity, reducing k-local observable complexity from O(4^k) to O(2^k) and lowering measurement-side classical computation while including conventional VQCs as a special case.
Magnitude-only encoding reaches 99.57% accuracy on 3-class and 71.19% on 8-class SAR tasks in hybrid models, beating phase-inclusive alternatives, while phase boosts pure quantum models by up to 21.65 points.
Empirical comparison of angle and amplitude encoding in VQCs on Wine and Diabetes datasets shows rotational gate selection in the encoding layer changes accuracy by 10-41 percent and treats embedding as a tunable hyperparameter.
citing papers explorer
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Design and Benchmarking of a Quantum Photonic Chip
RP000, a room-temperature CMOS photonic three-qubit processor, delivers higher or comparable accuracy to parameter-matched classical nets on ML classification and better noise tolerance than a superconducting processor.
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Diagonal Adaptive Non-local Observables on Quantum Neural Networks
Diagonal ANOs are mathematically equivalent to full ANOs modulo unitary similarity, reducing k-local observable complexity from O(4^k) to O(2^k) and lowering measurement-side classical computation while including conventional VQCs as a special case.
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Magnitude Is All You Need? Rethinking Phase in Quantum Encoding of Complex SAR Data
Magnitude-only encoding reaches 99.57% accuracy on 3-class and 71.19% on 8-class SAR tasks in hybrid models, beating phase-inclusive alternatives, while phase boosts pure quantum models by up to 21.65 points.
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Evaluating Angle and Amplitude Encoding Strategies for Variational Quantum Machine Learning: their impact on model's accuracy
Empirical comparison of angle and amplitude encoding in VQCs on Wine and Diabetes datasets shows rotational gate selection in the encoding layer changes accuracy by 10-41 percent and treats embedding as a tunable hyperparameter.