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Showing 1–7 of 7 results
Advanced filters: Author: Richard Kueng Clear advanced filters

  • Most of the current protocols for learning properties of quantum states are based on the assumption that the states are prepared in the same way over time. Here, the authors show a way to remove this assumption, while incurring only a polynomial increase in sample complexity.

    • Omar Fawzi
    • Richard Kueng
    • Aadil Oufkir
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-19

  • Recent work proposed a machine learning algorithm for predicting ground state properties of quantum many-body systems that outperforms any non-learning classical algorithm but requires extensive training data. Lewis et al. present an improved algorithm with exponentially reduced training data requirements.

    • Laura Lewis
    • Hsin-Yuan Huang
    • John Preskill
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-8

  • Randomized measurements provide a feasible procedure for probing properties of many-body quantum states realized in today’s quantum simulators and quantum computers. This Review covers implementation, classical post-processing and theoretical performance guarantees of randomized measurement protocols, surveying their many applications and discussing current challenges.

    • Andreas Elben
    • Steven T. Flammia
    • Peter Zoller
    Reviews
    Nature Reviews Physics
    Volume: 5, P: 9-24