Publication: Speeding up quantum perceptron via shortcuts to adiabaticity
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2020-03-11
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Nature Portfolio
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Abstract
The quantum perceptron is a fundamental building block for quantum machine learning. This is a multidisciplinary field that incorporates abilities of quantum computing, such as state superposition and entanglement, to classical machine learning schemes. Motivated by the techniques of shortcuts to adiabaticity, we propose a speed-up quantum perceptron where a control field on the perceptron is inversely engineered leading to a rapid nonlinear response with a sigmoid activation function. This results in faster overall perceptron performance compared to quasi-adiabatic protocols, as well as in enhanced robustness against imperfections in the controls.
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Speed limit, Qubits, Quantum control, Adiabaticity, Perceptron
Bibliographic citation
Scientific reports, 11, article number 5783, March 2021, 8 pp.