This paper introduces NISQRC, a machine learning algorithm designed for qubit-based quantum systems to perform inference on temporal data without coherence time limitations. NISQRC uses mid-circuit measurements and deterministic reset operations to minimize circuit executions while maintaining persistent temporal memory. The algorithm's effectiveness is validated through simulations and experiments on a 7-qubit quantum processor, successfully recovering arbitrarily long test signals unaffected by coherence time constraints. The paper also presents a Quantum Volterra Theory for analyzing the memory properties of quantum systems.

Fangjun Hu, Saeed A. Khan, Nicholas T. Bronn, Gerasimos Angelatos, Graham E. Rowlands, Guilhem J. Ribeill, Hakan E. Türeci