Pulsed Learning Enables Quantum Data Re-uploading Models On Noisy Intermediate-Scale Hardware, Addressing Variational Circuit Limitations

Pulsed Learning Enables Quantum Data Re-uploading Models On Noisy Intermediate-Scale Hardware, Addressing Variational Circuit Limitations

Researchers demonstrate that embedding learning directly into the control pulses of a quantum processor significantly improves the performance and resilience of machine learning models on today’s limited quantum hardware.