Speeding up quantum perceptron via shortcuts to adiabaticity Articles uri icon

publication date

  • March 2020

start page

  • 1

end page

  • 8

issue

  • 5783

volume

  • 11

International Standard Serial Number (ISSN)

  • 2045-2322

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.

keywords

  • speed limit; qubits; quantum control; adiabaticity; perceptron