Reservoir Computing Using Measurement-Controlled Quantum Dynamics
<|reference_start|>Reservoir Computing Using Measurement-Controlled Quantum Dynamics: Physical reservoir computing (RC) is a machine learning algorithm that employs the dynamics of a physical system to forecast highly nonlinear and chaotic phenomena. In this paper, we introduce a quantum RC system that employs the dynamics of a probed atom in a cavity. The atom experiences coherent driving at a particular rate, leading to a measurement-controlled quantum evolution. The proposed quantum reservoir can make fast and reliable forecasts using a small number of artificial neurons compared with the traditional RC algorithm. We theoretically validate the operation of the reservoir, demonstrating its potential to be used in error-tolerant applications, where approximate computing approaches may be used to make feasible forecasts in conditions of limited computational and energy resources.<|reference_end|>
@article{abbas2024reservoir,
    title={Reservoir Computing Using Measurement-Controlled Quantum Dynamics},
    author={A.H.Abbas and Ivan S.Maksymov},
    journal={arXiv preprint arXiv:2403.01024},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.01024},
    primaryClass={cs.NE cs.AI quant-ph}
}