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Discovery of energy landscapes toward optimized quantum transport: Environmental effects and long-range tunneling

Maggie Lawrence1,2, Matthew Pocrnic1, Erin Fung1, Juan Carrasquilla3,2, Erik M. Gauger4, and Dvira Segal5,1,*

  • 1Department of Physics, 60 Saint George Street, University of Toronto, Toronto, Ontario M5S 1A7, Canada
  • 2Vector Institute, Toronto, Ontario M5S 1M1, Canada
  • 3Institute for Theoretical Physics, ETH Zürich, Zürich, Switzerland
  • 4SUPA, Institute of Photonics and Quantum Sciences, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom
  • 5Department of Chemistry and Centre for Quantum Information and Quantum Control, University of Toronto, 80 Saint George Street, Toronto, Ontario M5S 3H6, Canada

  • *Contact author: dvira.segal@utoronto.ca
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Phys. Rev. Research 8, 013163 – Published 12 February, 2026

DOI: https://doi.org/10.1103/ckfp-6jtd

Abstract

Carrier transport in quantum networks is governed by a variety of factors, including network dimensionality and connectivity, on-site energies, couplings between sites and whether they are short or long range, leakage processes, and environmental effects. In this work, we identify classes of quasi-one-dimensional chains with energy profiles that optimize carrier transport under such influences. Specifically, we optimize on-site energies using Optax’s optimistic gradient descent and AdaMax algorithms, enabled by the JAX automatic differentiation framework. Focusing on nonequilibrium steady-state transport, we study the system’s behavior under combined unitary and nonunitary (dephasing and dissipative) effects using the Lindblad quantum master equation. After validating our optimization scheme on short chains, we extend the study to larger systems where we identify systematic patterns in energy profiles. Our analysis reveals that different types of energy landscapes enhance transport, depending on whether intersite tunneling couplings in the chain are short or long range, the existence of environmental interactions, and the temperature of the environment. Our classification and insights of optimal energy landscapes offer guidance for designing efficient transport systems for electronic, photovoltaic, and quantum communication applications.

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Phys. Rev. Research 8, 013163– Published 12 February, 2026
  • Received 21 August 2025
  • Accepted 17 December 2025
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