Reconstructing the potential configuration in a high-mobility semiconductor heterostructure with scanning gate microscopy

The weak disorder potential seen by the electrons of a two-dimensional electron gas in high-mobility semiconductor heterostructures leads to fluctuations in the physical properties and can be an issue for nanodevices. In this paper, we show that a scanning gate microscopy (SGM) image contains inform...

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Published in:arXiv.org 2023-11
Main Authors: Percebois, Gaëtan J, Lacerda-Santos, Antonio, Brun, Boris, Hackens, Benoit, Waintal, Xavier, Weinmann, Dietmar
Format: Article
Language:English
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Electron gas
Electrons
Heterostructures
Machine learning
Microscopy
Nanotechnology devices
Physical properties
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creator Percebois, Gaëtan J
Lacerda-Santos, Antonio
Brun, Boris
Hackens, Benoit
Waintal, Xavier
Weinmann, Dietmar
description The weak disorder potential seen by the electrons of a two-dimensional electron gas in high-mobility semiconductor heterostructures leads to fluctuations in the physical properties and can be an issue for nanodevices. In this paper, we show that a scanning gate microscopy (SGM) image contains information about the disorder potential, and that a machine learning approach based on SGM data can be used to determine the disorder. We reconstruct the electric potential of a sample from its experimental SGM data and validate the result through an estimate of its accuracy.
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subjects Electron gas
Electrons
Heterostructures
Machine learning
Microscopy
Nanotechnology devices
Physical properties
title Reconstructing the potential configuration in a high-mobility semiconductor heterostructure with scanning gate microscopy
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