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Scalable quantum dynamics compilation via quantum machine learning

Yuxuan Zhang1,2,*, Roeland Wiersema2,3,*, Juan Carrasquilla4,†, Lukasz Cincio5,‡, and Yong Baek Kim1,§

  • 1Department of Physics and Centre for Quantum Information and Quantum Control, University of Toronto, 60 Saint George Street, Toronto, Ontario M5S 1A7, Canada
  • 2Vector Institute, W1140-108 College Street, Schwartz Reisman Innovation Campus, Toronto, Ontario M5G 0C6, Canada
  • 3Department of Physics and Astronomy, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
  • 4Institute for Theoretical Physics, ETH Zürich, 8093 Zurich, Switzerland
  • 5Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

  • *These authors contributed equally to this work.
  • †Contact author: jcarrasquill@ethz.ch
  • ‡Contact author: lcincio@lanl.gov
  • §Contact author: ybkim@physics.utoronto.ca

Operator learning for efficient quantum computation

Paul Over, Sergio Bengoechea, Leonardo Borello Busilacchi, Martin Kiffner, Thomas Rung, and Alexios A Michailidis

Quantum Sci. Technol. 11 045097 (2026)

Probing mixed-state phases on a quantum computer via Renyi correlators and variational decoding

Yuxuan Zhang, Timothy H. Hsieh, Yong Baek Kim, and Yijian Zou

Nat Commun 17 8047 (2026)

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