PoS - Proceedings of Science
Volume 414 - 41st International Conference on High Energy physics (ICHEP2022) - Computing and Data Handling
A quantum analytical Adam descent through parameter shift rule using Qibo
S. Carrazza*, M. Robbiati, S. Efthymiou and A. Pasquale
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Pre-published on: November 13, 2022
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Abstract
In this proceedings we present quantum machine learning optimization experiments using stochastic gradient descent with the parameter shift rule algorithm. We first describe the gradient evaluation algorithm and its optimization procedure implemented using the Qibo framework. After numerically testing the implementation using quantum simulation on classical hardware, we perform successfully a full quantum hardware optimization exercise using a single superconducting qubit chip controlled by Qibo. We show results for a quantum regression model by comparing simulation to real hardware optimization.
DOI: https://doi.org/10.22323/1.414.0206
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