A reconfigurable silicon quantum photonic device for machine learning applications

Alberto Beccari

Lingxiao Wan, Hui Zhang, J. G. Huang +13 more

A method of tuning a reconfigurable silicon photonic circuit into an arbitrary unitary operator with machine learning was proposed to bypass the traditional phase-voltage calibration process and make the prediction of applied heating voltage directly.

Mariam Zomorodi Moghadam, Keivan Navi

Konstantina I. Koteva, Antonio A. Gentile, Brian Flynn +7 more

We present a fully reconfigurable silicon quantum photonic device capable of performing controlled four-dimensional unitary operations with 0.84 ± 0.02 fidelity. We report its characterisation by process tomography and deploy it to successfully perform a quantum model learning protocol.

Stefano Paesani, Antonio A. Gentile, Raffaele Santagati +13 more

We demonstrate a Bayesian approach for practical and robust implementation of the quantum phase estimation algorithm. We implement it on a reconfigurable Silicon quantum photonic device, demonstrating its importance for future quantum applications.

Jeremy L. O’Brien