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Optimizing quantum transport in multibarrier graphene systems using differential evolution

Leon Browne* and Stephen R. Power†

  • *Contact author: leon.browne26@mail.dcu.ie
  • †Contact author: stephen.r.power@dcu.ie
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Phys. Rev. Applied 25, 044049 – Published 20 April, 2026

DOI: https://doi.org/10.1103/m4kr-dvkq

Abstract

Potential and mass barriers in graphene introduce electron scattering, modulating transmission probabilities. Complex multibarrier setups allow electron transmission to be controlled with high precision, but they have a huge design space of possible barrier geometries. This work presents a framework to optimize electronic transport in such systems using differential-evolution algorithms. First, transfer-matrix methods are employed to efficiently compute quantum transport through multibarrier structures, and optimization is then applied to find barrier configurations whose transmission profiles closely match a predefined target profile. To address the trade-off between the accuracy and complexity of the resulting barrier configurations, regularization techniques are incorporated into the optimization process. Our approach demonstrates the potential for highly tunable electronic transport in graphene-based systems by exploiting evolution-inspired optimization techniques.

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Phys. Rev. Applied 25, 044049– Published 20 April, 2026
  • Received 28 August 2025
  • Revised 23 February 2026
  • Accepted 19 March 2026
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