Memristor-Based Cryogenic Programmable DC Sources for Scalable In Situ Quantum-Dot Control

Pierre-Antoine, Mouny,; Beilliard, Yann; Graveline, Sebastien; Roux, Marc-Antoine; Mesoudy, Abdelouadoud El; Raphaël, Dawant,; Gliech, Pierre; Ecoffey, Serge; Alibart, Fabien; Pioro‐Ladrière, Michel; Drouin, Dominique

doi:10.1109/ted.2023.3244133

Cited by 4 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Same as CPU, a Quantum chip will be acting as the processing unit of a Quantum computer. The chip equips the Qubits [3] , which are made up of 'Quantum dots' in it, they are designed in such a manner to handle trillions of operations within the stipulated time. Using the qubits, Quantum computers run complex multidimensional algorithms.…”

Section: Quantum Computing Systemsmentioning

confidence: 99%

Drug Discovery using Quantum Simulation

Kathiresan

2023

IJSREM

View full text Add to dashboard Cite

Health care Analysis spread wider throughout the globe enables proper structured resolutions for preventing the avalanche of health-related issues. The foremost goal lies in ensuring the proper safety and security of the patients. Talking about Patient safety, early diagnosis is the predominant key in finding any deadly diseases at an earlier stage, reducing the treatment costs, and increasing the overall survival rates. Also, an important factor that comes in parallel along with patient safety is ‘Drug Discovery’. In current day scenario, Pharma industries are striving a lot to improvise clinical development productivity by examining important potential strategies. The main point of optimization lies in the ‘Drug Discovery’ process. Drug Discovery plays a crucial role in clinical programs, as it helps towards diagnosis of illnesses. When a drug of satisfactory evidence is administered to a target it should ensure sufficient safety of the target. One of the foremost risks here is the availability of better drugs for a disease, or in other words appropriate potency should be ensured by the drug over a target. Despite investing very huge amount over a drug, 90% of it gets failed in clinical trials. In order to overcome the above-mentioned issue with Drug discovery, many pharma industries are relying on AI technologies to ensure, the drug actively engages the target and produce expected therapeutic effect. Along AI another promising technology which is set to revolutionize a wide range of health industry is Quantum Computing. As pharma industries are in urge to provide quality efficient and easily accessible drugs within reach, Quantum computing with built in Quantum mechanics perfectly fits in to derive proper compositions of drugs by trying out various drug-protein-gene interactions and in forecasting drug’s development using quantum algorithms and simulation techniques.

show abstract

Section: Quantum Computing Systemsmentioning

confidence: 99%

Drug Discovery using Quantum Simulation

Kathiresan

2023

IJSREM

View full text Add to dashboard Cite

show abstract

Towards scalable cryogenic quantum dot biasing using memristor-based DC sources

Mouny,

Dawant,

Dufour

et al. 2024

Cryogenics

View full text Add to dashboard Cite

Analog programming of CMOS-compatible Al2O3/TiO2−x memristor at 4.2 K after metal-insulator transition suppression by cryogenic reforming

Mouny,

Dawant,

Galaup

et al. 2023

Applied Physics Letters

View full text Add to dashboard Cite

Exploration of memristors' behavior at cryogenic temperatures has become crucial due to the growing interest in quantum computing and cryogenic electronics. In this context, our study focuses on the characterization at cryogenic temperatures (4.2 K) of TiO2−x-based memristors fabricated with a CMOS-compatible etch-back process. We demonstrate a so-called cryogenic reforming (CR) technique performed at 4.2 K to overcome the well-known metal-insulator transition (MIT), which limits the analog behavior of memristors at low temperatures. This cryogenic reforming process was found to be reproducible and led to a durable suppression of the MIT. This process allowed to reduce by ∼20% the voltages required to perform DC resistive switching at 4.2 K. Additionally, conduction mechanism studies of memristors before and after cryogenic reforming from 4.2 to 300 K revealed different behaviors above 100 K, indicating a potential change in the conductive filament stoichiometry. The reformed devices exhibit a conductance level that is 50 times higher than ambient-formed memristor, and the conduction drop between 300 and 4.2 K is 100 times smaller, indicating the effectiveness of the reforming process. More importantly, CR enables analog programming at 4.2 K with typical read voltages allowing to store up to 4 bits of information on a single CR memristor. Suppressing the MIT improved the analog switching dynamics of the memristor leading to ∼250% larger on/off ratios during long-term depression (LTD)/long-term potentiation (LTP) resistance tuning. This enhancement opens up the possibility of using TiO2−x-based memristors to be used as synapses in neuromorphic computing at cryogenic temperatures.

show abstract

Memristor-Based Cryogenic Programmable DC Sources for Scalable In Situ Quantum-Dot Control

Cited by 4 publications

References 20 publications

Drug Discovery using Quantum Simulation

Drug Discovery using Quantum Simulation

Towards scalable cryogenic quantum dot biasing using memristor-based DC sources

Analog programming of CMOS-compatible Al2O3/TiO2−x memristor at 4.2 K after metal-insulator transition suppression by cryogenic reforming

Contact Info

Product

Resources

About