A free-space PELM achieves 96.56% on MNIST, 95.67% on spoken digit spectrograms, 100% on mushroom classification, and 0.0699 NRMSE on abalone regression using the same optical setup, claimed as the first multimodal free-space PELM.
J.et al.Photonics for artificial intelligence and neuromorphic computing.Nat
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Monolithic Si3N4 platform achieves EPR fidelity 0.9875(3), HOM visibility 0.990(6), and four-photon GHZ fidelity 0.943(8) at 27 Hz—more than 100x prior silicon-photonic rates—using CMOS-compatible 150 mm wafer fabrication.
PaNO neural operator improves port-power readout fidelity in photonic design surrogates over global-field baselines on a 3x3 MMI benchmark.
Koopman theory plus knowledge distillation yields linearized models from pre-trained nets that outperform standard least-squares Koopman approximations on MNIST and Fashion-MNIST in accuracy and stability.
Clockless FPGA circuits produce autonomous spiking neuron networks that achieve competitive audio classification accuracy with significantly lower power than conventional digital implementations.
An experimental 4-channel TSWDM silicon photonic crossbar achieves 0.96 TOPS for hyperdimensional tensor operations with 3.9% average error and 93.3% Iris accuracy at 10-30 GBd.
citing papers explorer
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Multimodal Optical Feature Extraction with a Free-Space Photonic Extreme Learning Machine
A free-space PELM achieves 96.56% on MNIST, 95.67% on spoken digit spectrograms, 100% on mushroom classification, and 0.0699 NRMSE on abalone regression using the same optical setup, claimed as the first multimodal free-space PELM.
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An ultralow-loss integrated photonic platform for discrete-variable quantum information processing
Monolithic Si3N4 platform achieves EPR fidelity 0.9875(3), HOM visibility 0.990(6), and four-photon GHZ fidelity 0.943(8) at 27 Hz—more than 100x prior silicon-photonic rates—using CMOS-compatible 150 mm wafer fabrication.
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Will Accurate Fields Mislead Photonic Design? FromGlobal Accuracy to Port Readout
PaNO neural operator improves port-power readout fidelity in photonic design surrogates over global-field baselines on a 3x3 MMI benchmark.
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Extraction of linearized models from pre-trained networks via knowledge distillation
Koopman theory plus knowledge distillation yields linearized models from pre-trained nets that outperform standard least-squares Koopman approximations on MNIST and Fashion-MNIST in accuracy and stability.
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Scalable neuromorphic computing from autonomous spiking dynamics in a clockless reconfigurable chip
Clockless FPGA circuits produce autonomous spiking neuron networks that achieve competitive audio classification accuracy with significantly lower power than conventional digital implementations.
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On-chip 1 TOPS Hyperdimensional Photonic Tensor Core using a WDM Silicon Photonic Coherent Crossbar
An experimental 4-channel TSWDM silicon photonic crossbar achieves 0.96 TOPS for hyperdimensional tensor operations with 3.9% average error and 93.3% Iris accuracy at 10-30 GBd.
- Beyond Silicon: Materials, Mechanisms, and Methods for Physical Neural Computing