6 papers
Functional Interface Blocks for Neuromorphic Hardware: A Junction-Centered Framework
Wellington Avelino, Yann Beillard, Fabien Allibart +2
Heterogeneous neuromorphic hardware integrates devices with dissimilar electrical characteristics and dynamics, making functional compatibility at their interconnections a primary…
Unsupervised local learning based on voltage-dependent synaptic plasticity for resistive and ferroelectric synapses
Nikhil Garg, Ismael Balafrej, Joao Henrique Quintino Palhares +11
The deployment of AI on edge computing devices faces significant challenges related to energy consumption and functionality. These devices could greatly benefit from brain-inspired…
Experimental online quantum dots charge autotuning using neural networks
Victor Yon, Bastien Galaup, Claude Rohrbacher +11
Spin-based semiconductor qubits hold promise for scalable quantum computing, yet they require reliable autonomous calibration procedures. This study presents an experimental demons…
Towards a Cryogenic CMOS-Memristor Neural Decoder for Quantum Error Correction
Pierre-Antoine Mouny, Maher Benhouria, Victor Yon +6
This paper presents a novel approach utilizing a scalable neural decoder application-specific integrated circuit (ASIC) based on metal oxide memristors in a 180nm CMOS technology.…
Robust quantum dots charge autotuning using neural network uncertainty
Victor Yon, Bastien Galaup, Claude Rohrbacher +10
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…
A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction
Victor Yon, Frédéric Marcotte, Pierre-Antoine Mouny +6
Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to pr…