IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v614y2023ics037843712300105x.html
   My bibliography  Save this article

An investigation of the background potential in quantum constrictions using scanning gate microscopy and a swarming algorithm

Author

Listed:
  • da Cunha, C.R.
  • Aoki, N.
  • Ferry, D.K.
  • Velasquez, A.
  • Zhang, Y.

Abstract

Scanning gate microscopy (SGM) is a valuable scanning probe technique for characterizing electronic transport in mesoscopic systems. However, the interpretation of the method is often limited by many experimental challenges. In this work, we propose an empirically-constrained optimization approach based on swarm search and Green’s functions to extract more information from SGM measurements. The approach is applied to a quantum point contact fabricated on an InAlAs/InGaAs/InAlAs quantum well, and the results indicate that the corresponding SGM could be generated, in a weak approximation, by a fluctuating background potential with features with radii in the order of 20 to 30 nm and a correlation length of 5.7 nm. Our method represents a data-driven tool for estimating solutions for inverse problems in mesoscopic physics, and can be used to generate estimates for the potential landscape experienced by free electrons in mesoscopic systems.

Suggested Citation

  • da Cunha, C.R. & Aoki, N. & Ferry, D.K. & Velasquez, A. & Zhang, Y., 2023. "An investigation of the background potential in quantum constrictions using scanning gate microscopy and a swarming algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    • Handle: RePEc:eee:phsmap:v:614:y:2023:i:c:s037843712300105x
    DOI: 10.1016/j.physa.2023.128550
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712300105X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.128550?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J. M. Elzerman & R. Hanson & L. H. Willems van Beveren & B. Witkamp & L. M. K. Vandersypen & L. P. Kouwenhoven, 2004. "Single-shot read-out of an individual electron spin in a quantum dot," Nature, Nature, vol. 430(6998), pages 431-435, July.
    2. da Cunha, C.R. & da Silva, R., 2020. "Relevant stylized facts about bitcoin: Fluctuations, first return probability, and natural phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    3. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    2. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    3. Shang, Lihui & Zhao, Mingming & Ai, Jun & Su, Zhan, 2021. "Opinion evolution in the Sznajd model on interdependent chains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    4. Lu, Xi & Mo, Hongming & Deng, Yong, 2015. "An evidential opinion dynamics model based on heterogeneous social influential power," Chaos, Solitons & Fractals, Elsevier, vol. 73(C), pages 98-107.
    5. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    6. Thomas Moore & Patrick Finley & Nancy Brodsky & Theresa Brown & Benjamin Apelberg & Bridget Ambrose & Robert Glass, 2015. "Modeling Education and Advertising with Opinion Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-7.
    7. George Butler & Gabriella Pigozzi & Juliette Rouchier, 2019. "Mixing Dyadic and Deliberative Opinion Dynamics in an Agent-Based Model of Group Decision-Making," Complexity, Hindawi, vol. 2019, pages 1-31, August.
    8. Huang, Changwei & Hou, Yongzhao & Han, Wenchen, 2023. "Coevolution of consensus and cooperation in evolutionary Hegselmann–Krause dilemma with the cooperation cost," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    9. María Cecilia Gimenez & Luis Reinaudi & Ana Pamela Paz-García & Paulo Marcelo Centres & Antonio José Ramirez-Pastor, 2021. "Opinion evolution in the presence of constant propaganda: homogeneous and localized cases," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(1), pages 1-11, January.
    10. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska, 2023. "On the Design of Public Debate in Social Networks," Operations Research, INFORMS, vol. 71(2), pages 626-648, March.
    11. Kułakowski, Krzysztof, 2009. "Opinion polarization in the Receipt–Accept–Sample model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 469-476.
    12. Guillaume Deffuant & Ilaria Bertazzi & Sylvie Huet, 2018. "The Dark Side Of Gossips: Hints From A Simple Opinion Dynamics Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-20, September.
    13. Schweitzer, Frank, 2021. "Social percolation revisited: From 2d lattices to adaptive networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    14. Toth, Gabor & Galam, Serge, 2022. "Deviations from the majority: A local flip model," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    15. G Jordan Maclay & Moody Ahmad, 2021. "An agent based force vector model of social influence that predicts strong polarization in a connected world," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-42, November.
    16. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.
    17. Lipiecki, Arkadiusz & Sznajd-Weron, Katarzyna, 2022. "Polarization in the three-state q-voter model with anticonformity and bounded confidence," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    18. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    19. Saggau, Volker, 2012. "Viele Köche Verderben Den Brei – Agentenbasierte Simulationen Zum Föderalismusdurcheinander Während Der Ehec-Krise," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 133052, German Association of Agricultural Economists (GEWISOLA).
    20. Jiangbo Zhang & Yiyi Zhao, 2023. "Dynamics Analysis for the Random Homogeneous Biased Assimilation Model," Mathematics, MDPI, vol. 11(7), pages 1-17, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:614:y:2023:i:c:s037843712300105x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.