Quantum natural language processing applications on high-performance computing systems and quantum devices

ORAL

Abstract

Quantum natural language processing (QNLP) is a cutting-edge application aiming to develop NLP models to be executed on quantum computers. We assess the feasibility and accuracy of QNLP models using numerical simulators on HPC systems and actual quantum hardware. In particular, we use classical simulators and an hybrid HPC-quantum workflow to implement quantum pipelines and neural networks in combination with default datasets to demonstrate a QNLP application on HPC and NISQ devices.

*This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

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Presenters

  • Eduardo A Coello Perez

    • Oak Ridge National Laboratory

Authors

  • Eduardo A Coello Perez

    • Oak Ridge National Laboratory

  • In-Saeng Suh

    • Oak Ridge National Laboratory

  • Prasanna Date

    • Oak Ridge National Lab
    • Oak Ridge National Laboratory

  • John P Gounley

    • Oak Ridge National Laboratory

  • Mayanka Chandra Shekar

    • Oak Ridge National Laboratory

  • Kathleen Hamilton

    • Oak Ridge National Laboratory