General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
SL-DRT-24-0734
Direction
DRT
Thesis topic details
Category
Technological challenges
Thesis topics
Quantum Machine Learning in the era of NISQ: can QML provide an advantage for the learning part of Neural Networks?
Contract
Thèse
Job description
Quantum computing is believed to offer a future advantage in a variety of algorithms, including those challenging for traditional computers (e.g., Prime Factorization). However, in an era where Noisy Quantum Computers (QCs) are the norm, practical applications of QC would be centered around optimization approaches and energy efficiency rather than purely algorithmic performance.
In this context, this PhD thesis aims to address the utilization of QC to enhance the learning process of Neural Networks (NN). The learning phase of NN is arguably the most power-hungry aspect with traditional approaches. Leveraging quantum optimization techniques or quantum linear system solving could potentially yield an energy advantage, coupled with the ability to perform the learning phase with a less extensive set of training examples.
University / doctoral school
Sciences et Technologies de l’Information et de la Communication (STIC)
Paris-Saclay
Thesis topic location
Site
Saclay
Requester
Position start date
01/10/2024
Person to be contacted by the applicant
LOUISE Stéphane stephane.louise@cea.fr
CEA
DRT/DSCIN/DSCIN/LCYL
Pièce 2019, Bat 862 Nano-INNOV
PC 174
01 69 08 64 12
Tutor / Responsible thesis director
LOUISE Stéphane stephane.louise@cea.fr
CEA
DRT/DSCIN/DSCIN/LCYL
Pièce 2019, Bat 862 Nano-INNOV
PC 174
01 69 08 64 12
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