Qubit pulse optimization using machine learning

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Exploration of machine learning algorithms for discovery of novel pulse shapes that will considerably increase fidelity of single qubit gates in quantum computers.

We are looking for a highly motivated student with a strong background in software development, preferably in python. Prior experiences with machine learning algorithms are desired. The student will initially test algorithms, such as reinforced learning etc., first on quantum simulators, e.g. QuTiP, and later test the best algorithms on ​the actual experiment. The aim of this project is to the develop a method for fast microwave ​pulse calibration for achieving high-fidelity single qubit gates. ​



Type of project: Thesis

Required degree: Master of Engineering Technology, Master of Science, Master of Engineering Science

Required background: Computer Science, Electrotechnics/Electrical Engineering, Nanoscience & Nanotechnology, Physics

Supervising scientist(s): For further information or for application, please contact: Anton Potocnik (Anton.Potocnik@imec.be) and Massimo Mongillo (Massimo.Mongillo@imec.be)

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