IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v93y2020i3d10.1140_epjb_e2020-100445-1.html
   My bibliography  Save this article

Order parameter dynamics of the non-linear sigma model in the large N limit

Author

Listed:
  • Sebastian Gemsheim

    (Fakultät Physik, Technische Universität Dresden)

  • Ipsita Mandal

    (Laboratory of Atomic And Solid State Physics, Cornell University
    Faculty of Science and Technology, University of Stavanger)

  • Krishnendu Sengupta

    (School of Physical Sciences, Indian Association for the Cultivation of Science)

  • Zhiqiang Wang

    (McMaster University)

Abstract

We study non-equilibrium order parameter dynamics of the non-linear sigma model in the large N limit, using Keldysh formalism. We provide a scheme for obtaining stable numerical solution of the Keldysh saddle point equations and use them to study order parameter dynamics of the model either following a ramp, or in the presence of a periodic drive. We find that the transient dynamics of the order parameter in the presence of a periodic drive is controlled by the drive frequency displaying the phenomenon of synchronization. We also study the approach of the order parameter to its steady state value following a ramp and find out the effective temperature of the steady state. We chart out the steady state temperature of the ordered phase as a function of ramp time and amplitude, and discuss the relation of our results to experimentally realizable spin models. Graphical abstract

Suggested Citation

  • Sebastian Gemsheim & Ipsita Mandal & Krishnendu Sengupta & Zhiqiang Wang, 2020. "Order parameter dynamics of the non-linear sigma model in the large N limit," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(3), pages 1-8, March.
  • Handle: RePEc:spr:eurphb:v:93:y:2020:i:3:d:10.1140_epjb_e2020-100445-1
    DOI: 10.1140/epjb/e2020-100445-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/e2020-100445-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1140/epjb/e2020-100445-1?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.

    More about this item

    Keywords

    Statistical and Nonlinear Physics;

    Statistics

    Access and download statistics

    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:spr:eurphb:v:93:y:2020:i:3:d:10.1140_epjb_e2020-100445-1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.