2022
DOI: 10.48550/arxiv.2205.07925
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Machine learning via relativity-inspired quantum dynamics

Zejian Li,
Valentin Heyraud,
Kaelan Donatella
et al.

Abstract: We present a machine-learning scheme based on the relativistic dynamics of a quantum system, namely a quantum detector inside a cavity resonator. An equivalent analog model can be realized for example in a circuit QED platform subject to properly modulated driving fields. We consider a reservoir-computing scheme where the input data are embedded in the modulation of the system (equivalent to the acceleration of the relativistic object) and the output data are obtained by linear combinations of measured observa… Show more

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