Inverse magneto-conductance design by automatic differentiation

Abstract

Magneto-conductance in thin wires often exhibits complicated patterns due to the quantum interference of conduction electrons. These patterns reflect microscopic structures in the wires, such as defects or potential distributions. In this study, we propose an inverse design method to automatically generate a microscopic structure that exhibits desired magneto-conductance patterns. We numerically demonstrate that our method accurately generates defect positions in wires and can be effectively applied to various complicated patterns. We also discuss techniques for designing structures that facilitate experimental investigation.

7 pages, 5 figures

References in corpus (7)

• Kwant: a software package for quantum transport
• Modeling Electronic Quantum Transport with Machine Learning
• Numerical Study of Universal Conductance Fluctuation in Three-dimensional Topological Semimetals
• Inverse Hamiltonian design by automatic differentiation
• AD-NEGF: An End-to-End Differentiable Quantum Transport Simulator for Sensitivity Analysis and Inverse Problems
• Deciphering quantum fingerprints in electric conductance
• Inverse Hamiltonian design of highly-entangled quantum systems