Realization of a quantum neural network by repeat-until-success circuits in a superconducting quantum processor

ORAL

Abstract

We present the experimental realization of a quantum neural network capable of non-linear classification. By implementing control-flow feedback in a superconducting quantum processor, we synthesize non-linear activation functions using repeat-until-success circuits, demonstrating the elementary building blocks for quantum machine learning. In particular, we realize a quantum circuit that reproduces a variety of classical feed-forward neural network constructions and can learn from superpositions of training data.

*Research funded by Intel Corporation and IARPA (U.S. Army Research Office Grant No. W911NF-16-1-0071).

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Presenters

  • Miguel Moreira

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Techology
    • Delft University of Technology
    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology

Authors

  • Miguel Moreira

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Techology
    • Delft University of Technology
    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology

  • Gian Giacomo Guerreschi

    • Intel Labs, Intel Corporation, USA
    • Intel

  • Wouter J Vlothuizen

    • QuTech and Netherlands Organization for Applied Scientific Research, The Netherlands
    • Netherlands Organisation for Applied Scientific Research
    • Delft University of Technology,

  • Jeroen van Straten

    • QuTech and Quantum and Computer Engineering Department, Delft University of Technology, The Netherlands

  • Hans van Someren

    • QuTech and Quantum and Computer Engineering Department, Delft University of Technology, The Netherlands

  • Jorge F Marques

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Technology

  • Hany Ali

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Technology

  • Nandini Muthusubramanian

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands

  • Christos Zachariadis

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Technology
    • QuTech, Kavli Institute of Nanoscience, Delft University of Technology

  • Marc Beekman

    • QuTech and Netherlands Organisation for Applied Scientific Research, The Netherlands

  • Nadia Haider

    • QuTech and Netherlands Organisation for Applied Scientific Research, The Netherlands
    • Netherlands Organisation for Applied Scientific Research

  • Alessandro Bruno

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Technology
    • QuTech, Kavli Institute of Nanoscience, Delft University of Technology
    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, and Quantware, B.V., The Netherlands

  • Carmina G Almudever

    • QuTech and Quantum and Computer Engineering Department, Delft University of Technology, The Netherlands

  • Anne Y Matsuura

    • Intel Corporation, Hillsboro
    • Intel Corporation, Santa Clara
    • Intel Labs, Intel Corporation, USA

  • Leonardo DiCarlo

    • QuTech and Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands
    • Delft University of Technology