Inverse magneto-conductance design by automatic differentiation
Yuta Hirasaki, Koji Inui, and Eiji Saitoh

TL;DR
This paper introduces an inverse design approach using automatic differentiation to generate microscopic structures in thin wires that produce specific magneto-conductance patterns, aiding experimental studies.
Contribution
It presents a novel inverse design method leveraging automatic differentiation to control quantum interference effects in magneto-conductance patterns.
Findings
Accurately generates defect positions in wires.
Effectively applies to complex magneto-conductance patterns.
Facilitates experimental investigation of quantum effects.
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.
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Taxonomy
TopicsNeural Networks and Applications · Model Reduction and Neural Networks · Non-Destructive Testing Techniques
