A residual neural network trained on one quantum device's noise data can be fine-tuned with 20 samples from a second device to improve prediction of ideal circuit outputs, recovering 34.9% of the performance gap.
Error mitigation with clifford quantum-circuit data
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Few-Shot Cross-Device Transfer for Quantum Noise Modeling on Real Hardware
A residual neural network trained on one quantum device's noise data can be fine-tuned with 20 samples from a second device to improve prediction of ideal circuit outputs, recovering 34.9% of the performance gap.