Supervision : Elham KASHEFI

Co-supervision : HENRIET Loïc (Pasqal)

Analogue randomized benchmarking of Pasqal quantum processors

The PhD student will work towards extending these existing benchmarking tools to a quantum processor made of neutral atoms working in the analogue setting (i.e. whose time-evolution is described with a Hamiltonian rather than a sequence of gates), building on previous work done in the group of Prof. Elham Kashefi[4] at LIP6, the computer science laboratory of Sorbonne University’s Faculty of Science and Engineering. To achieve this goal, the PhD student will both need an in-depth understanding of the hardware capabilities as well as solid theoretical understanding of the mathematical tools developed for randomized benchmarking. The complementarity of the two teams at Pasqal and LIP6, both based in the Paris region, is a strong asset in the development of a durable and robust French quantum computing ecosystem.

2021-2022 Publications

• 2022
  • J. Landman, S. Thabet, C. Dalyac, H. Mhiri, E. Kashefi : “Classically Approximating Variational Quantum Machine Learning with Random Fourier Features”, (2022)
  • C. Dalyac, L. Henriet, E. Jeandel, W. Lechner, S. Perdrix, M. Porcheron, M. Veshchezerova : “Qualifying quantum approaches for hard industrial optimization problems. A case study in the field of smart-charging of electric vehicles”, ROADEF 2022 - 23^e congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France (2022)
• 2021
  • C. Dalyac, L. Henriet, E. Jeandel, W. Lechner, S. Perdrix, M. Porcheron, M. Veshchezerova : “Qualifying quantum approaches for hard industrial optimization problems. A case study in the field of smart-charging of electric vehicles”, (2021)