Robust quantum dots charge autotuning using neural network uncertainty

1 code implementation • 7 Jun 2024 • Victor Yon, Bastien Galaup, Claude Rohrbacher, Joffrey Rivard, Clément Godfrin, Ruoyu Li, Stefan Kubicek, Kristiaan De Greve, Louis Gaudreau, Eva Dupont-Ferrier, Yann Beilliard, Roger G. Melko, Dominique Drouin

This study presents a machine-learning-based procedure to automate the charge tuning of semiconductor spin qubits with minimal human intervention, addressing one of the significant challenges in scaling up quantum dot technologies.

Efficient Exploration

A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction

no code implementations • 18 Jul 2023 • Victor Yon, Frédéric Marcotte, Pierre-Antoine Mouny, Gebremedhin A. Dagnew, Bohdan Kulchytskyy, Sophie Rochette, Yann Beilliard, Dominique Drouin, Pooya Ronagh

In simulations supported by experimental measurements, we investigate the impact of TiOx-based memristive devices' non-idealities on decoding fidelity.

Decoder

Hardware-aware Training Techniques for Improving Robustness of Ex-Situ Neural Network Transfer onto Passive TiO2 ReRAM Crossbars

no code implementations • 29 May 2023 • Philippe Drolet, Raphaël Dawant, Victor Yon, Pierre-Antoine Mouny, Matthieu Valdenaire, Javier Arias Zapata, Pierre Gliech, Sean U. N. Wood, Serge Ecoffey, Fabien Alibart, Yann Beilliard, Dominique Drouin

Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior to their active (1T1R) counterparts in terms of the integration density.