Experimental graybox quantum identification and control

ORAL

Abstract

Modeling and controlling a quantum system are crucial for developing useful quantum devices to overcome errors that come from environmental noise or fabrication imperfections. Many methods have been developed to tackle this challenge. However, they are either limited by the system model such as traditional curve fitting, or lack of physics insights such as machine learning methods. Here we experimentally demonstrate a 'graybox' method on a reconfigurable photonic circuit. Our results show that the 'graybox' method outperforms the traditional model fitting method while holding the capability of providing physics insights. This new method is effective in modeling devices whose properties cannot be measured directly and can be applied to time-dependent and open quantum systems.

*AP acknowledges an RMIT University Vice-Chancellor's Senior Research Fellowship and a Google Faculty Research Award. ML was supported by the Australian Research Council (ARC) Future Fellowship (FT180100055). BH was supported by the Griffith University Postdoctoral Fellowship. This work was supported by the Australian Government through the Australian Research Council under the Centre of Excellence scheme (No: CE170100012), and the Griffith University Research Infrastructure Program. This work was performed in part at the Queensland node of the Australian National Fabrication Facility, a company established under the National Collaborative Research Infrastructure Strategy to provide nano- and micro-fabrication facilities for Australia's researchers. This research was also undertaken with the assistance of resources from the National Computational Infrastructure (NCI Australia), an NCRIS enabled capability supported by the Australian Government.

Publication: https://arxiv.org/abs/2206.12201

Presenters

  • Yang Yang

    • RMIT University

Authors

  • Yang Yang

    • RMIT University

  • Akram Youssry

    • RMIT University

  • Robert J Chapman

    • ETH Zurich

  • Ben Haylock

    • Heriot-Watt University

  • Francesco Lenzini

    • niversity of Muenster
    • University of Muenster

  • Mirko Lobino

    • Griffith Univ
    • University of Trento

  • Alberto Peruzzo

    • RMIT University