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An imperfect quantum photonic neural network-based Bell-state analyzer with fabrication imperfections modelled after state-of-the-art silicon-on-insulator photonic elements (U, inset) and weak optical Kerr nonlinearities (Σ(π/4)). The network is trained to perform the input-output mapping of the Bell-state analyzer (see truth table) in the presence of all component-by-component errors, and thus learns to both overcome fabrication imperfections and get the most out of the available nonlinearities.

Imperfect Quantum Photonic Neural Networks

Date Published: Jan 31, 2023

Jacob Ewaniuk, a MASC candidate has his work published in Advanced Quantum Technologies

The photonic chip used for teaching hardware

Teaching photonic chips to learn

Date Published: Nov 22, 2022

Prof. Shastri and multi-institution team has developed an optical chip that can train machine learning hardware

The skymap of high-energy neutrinos around NGC 1068 vicinity

Evidence of Neutrino Emission from NGC1068

Date Published: Nov 03, 2022

Prof. Park and colleagues, part of the IceCUBE Neutrino Observatory, find evidence of neutrino emission in their latest research