Open Access

REVIEW

Research Progress of Reverse Monte Carlo and Its Application in Josephson Junction Barrier Layer

Junling Qiu^*, Huihui Sun, Shuya Wang

State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, 450001, China

* Corresponding Author: Junling Qiu. Email:

Computer Modeling in Engineering & Sciences 2023, 137(3), 2077-2109. https://doi.org/10.32604/cmes.2023.027353

Received 26 October 2022; Accepted 10 March 2023; Issue published 03 August 2023

Abstract

As indispensable components of superconducting circuit-based quantum computers, Josephson junctions determine how well superconducting qubits perform. Reverse Monte Carlo (RMC) can be used to recreate Josephson junction’s atomic structure based on experimental data, and the impact of the structure on junctions’ properties can be investigated by combining different analysis techniques. In order to build a physical model of the atomic structure and then analyze the factors that affect its performance, this paper briefly reviews the development and evolution of the RMC algorithm. It also summarizes the modeling process and structural feature analysis of the Josephson junction in combination with different feature extraction techniques for electrical characterization devices. Additionally, the obstacles and potential directions of Josephson junction modeling, which serves as the theoretical foundation for the production of superconducting quantum devices at the atomic level, are discussed.

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