Quantum optimal control of superconducting qubits with Q-PRONTO

ORAL

Abstract

Standard methods of Quantum Optimal Control (QOC) have linear convergence in the cost per iteration. In this talk I will describe Q-PRONTO [1,2], a new method for QOC that can achieve quadratic convergence. After briefly describing the method, I will illustrate its use to design gates on two typical superconducting qubits: the transmon and the fluxonium. I will compare Q-PRONTO to other QOC methods and show its advantages in terms of performance. Finally, I will briefly describe the open-source Julia package we have developed to enable anyone to use Q-PRONTO.



[1] J. Shao, J. Combes, J. Hauser, and M. Nicotra, arXiv:2111.08795

[2] J. Shao, M. Naris, J. Hauser, M. Nicotra, arXiv:2305.17630

–

Publication: Phys. Rev. A 105, 032605 (2022)
arXiv:2305.17630

Presenters

  • Jieqiu Shao

    University of Colorado, Boulder

Authors

  • Jieqiu Shao

    University of Colorado, Boulder

  • Marco M Nicotra

    Univerisity of Colorado, Boulder

  • Andras Gyenis

    CU Boulder, University of Colorado Boulder, University of Colorado, Boulder

  • Brian Isakov

    University of Colorado, Boulder

  • Mantas Naris

    University of Colorado, Boulder