Simulation of Cryogenic Cmos-oxram Neuromorphic - Sherbrooke, Canada - Institut interdisciplinaire d'innovation technologique - Université de Sherbrooke
2 weeks ago
Description
Simulation of Cryogenic CMOS-OxRAM Neuromorphic Circuits for Quantum Technologies:
- Réf
ABG-115248
- Sujet de Thèse 14/06/2023
- Contrat doctoral
- Institut interdisciplinaire d'innovation technologique
- Université de Sherbrooke
- Lieu de travail
- Sherbrooke
- Canada
- Intitulé du sujet
- Simulation of Cryogenic CMOS-OxRAM Neuromorphic Circuits for Quantum Technologies
- Champs scientifiques
- Electronique
- Electronique
- Physique
Description du sujet:
Context:
The latest major breakthrough in quantum computing (QC) has been the demonstration of quantum systems with more than 50 superconducting qubits allowing quantum supremacy for the first time.
Other very promising qubit technologies include spin qubits based on solid-state quantum dots (QDs). They leverage the great maturity of CMOS technologies to offer low cost and highly scalable quantum devices.Major research centers like CEA, QuTech and Intel have started to report high quality spin qubits based on advanced CMOS technologies.
However, the tuning and control of QDs are still performed mostly by hand with bulky classical electronics located outside the cryostat.
The absence of fully integrated cryo-electronics capable of automatically tuning the QDs makes it currently impossible to build a large-scale quantum computer due to the "wiring bottleneck" between the quantum devices and the control electronics.
In that scope, a 3IT-1QBit consortium composed of 10 world-class researchers and engineers in Canada is starting an ambitious research program to develop innovative solutions to that problem.
We propose a PhD project focused on the development of a simulation framework of cryogenic-compatible neuromorphic circuits based on TiO2 memristors (i.e. OxRAM) and CMOS components interconnected with superconducting materials. These CMOS-OxRAM circuits will allow to implement neural networks and in-memory computing dedicated to low-power QD auto-tuning.Research p
roject:
In collaboration with 2 postdoc fellows, 2 PhD students and 1 Master's student, the PhD student recruited will be in charge of developing a framework for system-level and circuit-level simulations of in-memory computing implemented in cryogenic CMOS-OxRAM circuits.
The impact of temperature and hardware constrains/non-idealities will be considered thanks to experimental measurements of CMOS-OxRAM circuits fabricated in the scope of the program.
This project will build upon the work of Pr. Dominique Drouin's group at 3IT on TiO2-based memristors and neural networks for QD auto-tuning:Fully CMOS-compatible passive TiO2-based memristor crossbars for in-memory computing - ScienceDirect- Miniaturizing neural networks for charge state autotuning in quantum dots
- IOPscience
- Supported by the expertise of 3IT, 1QBit and IQ in the fields of neural network simulations, neuromorphic engineering and cryogenic electronics, the student will have to
- and circuit-level simulations of OxRAM-based neural networks trained to recognize specific patterns in stability diagrams of QDs,
- _ii_) implement at the system-level auto-tuning algorithms of single and double QDs, then design the CMOS-OxRAM circuit to run them,
- _i_
- ii_) investigate the impact of circuit non-idealities on the accuracy of the auto-tuning process,
- _i_
- v_) participate to in-depth electrical characterizations of the CMOS-OxRAM circuits at room and cryogenic temperatures in the Quantum Fab Lab of the IQ of UdeS,
Nature du financement:
- Contrat doctoral
Précisions sur le financement:
Présentation établissement et labo d'accueil:
- Institut interdisciplinaire d'innovation technologique
- Université de Sherbrooke
Site web:
Researched profile:
Specialization in electrical and computer engineering
Strengths:
knowledge in neural networks, in-memory computing, analog circuit design, device modeling
Excellent adaptability, autonomy, teamwork, problem solving skills, strong taste for interdisciplinary R&D- 14/07/2023
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