Loughborough University
Browse
spin-ice.pdf (547.3 kB)

Thermodynamics of the classical spin-ice model with nearest neighbour interactions using the Wang-Landau algorithm

Download (547.3 kB)
journal contribution
posted on 2015-10-01, 10:19 authored by M.V. Ferreyra, G. Giordano, R.A. Borzi, Joseph BetourasJoseph Betouras, S.A. Grigera
In this article we study the classical nearest-neighbour spin-ice model (nnSI) by means of Monte Carlo simulations, using the Wang-Landau algorithm. The nnSI describes several of the salient features of the spin-ice materials. Despite its simplicity it exhibits a remarkably rich behaviour. The model has been studied using a variety of techniques, thus it serves as an ideal benchmark to test the capabilities of the Wang Landau algorithm in magnetically frustrated systems. We study in detail the residual entropy of the nnSI and, by introducing an applied magnetic field in two different crystallographic directions ([111] and [100],) we explore the physics of the kagome-ice phase, the transition to full polarisation, and the three dimensional Kasteleyn transition. In the latter case, we discuss how additional constraints can be added to the Hamiltonian, by taking into account a selective choice of states in the partition function and, then, show how this choice leads to the realization of the ideal Kasteleyn transition in the system.

History

School

  • Science

Department

  • Physics

Citation

FERREYRA, M.V. ... et al., 2015. Thermodynamics of the classical spin-ice model with nearest neighbour interactions using the Wang-Landau algorithm. The European Physical Journal B, 89 (2), article 51.

Publisher

Springer / © The Authors

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0

Publication date

2015

Notes

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Language

  • en

Usage metrics

    Loughborough Publications

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC