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Home   /   Post Doctorat   /   Multi-scale modeling of the electromagnetic quantum dot environment

Multi-scale modeling of the electromagnetic quantum dot environment

Electronics and microelectronics - Optoelectronics Engineering sciences New computing paradigms, circuits and technologies, incl. quantum Technological challenges


In the near future, emerging quantum information technologies are expected to lead to global breakthroughs in high performance computing and secure communication. Among semiconductor approaches, silicon-based spin quantum bits (qubits) are promising thanks to their compactness featuring long coherence time, high fidelity and fast qubit rotation [Maurand2016], [Meunier2019]. A main challenge is now to achieve individual qubit control inside qubit arrays.

Qubit array constitutes a compact open system, where each qubit cannot be considered as isolated since it depends on the neighboring qubit placement, their interconnection network and the back-end-line stack. The main goal of this post-doctoral position is to develop various implementation of spin control on 2D qubit array using multi-scale electromagnetic (EM) simulation ranging from nanometric single qubit up to millimetric interconnect network.

The candidate will i) characterize radio-frequency (RF) test structures at cryogenic temperature using state-of-the-art equipment and compare results with dedicated EM simulations, ii) evaluate the efficiency of spin control and allow multi-scale optimization from single to qubit arrays [Niquet2020], iii) integrate RF spin microwave control for 2D qubit array using CEA-LETI silicon technologies.

The candidate need to have a good RF and microelectronic background and experience in EM simulation, and/or design of RF test structures and RF characterization. This work takes place in a dynamic tripartite collaborative project between CEA-LETI, CEA-IRIG and CNRS-Institut Néel (ERC “Qucube”).


Département Composants Silicium (LETI)
Service Caractérisation, Conception et Simulation
Laboratoire de Simulation et Modélisation
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