IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v455y2016icp11-26.html
   My bibliography  Save this article

Application of the maximum relative entropy method to the physics of ferromagnetic materials

Author

Listed:
  • Giffin, Adom
  • Cafaro, Carlo
  • Ali, Sean Alan

Abstract

It is known that the Maximum relative Entropy (MrE) method can be used to both update and approximate probability distributions functions in statistical inference problems. In this manuscript, we apply the MrE method to infer magnetic properties of ferromagnetic materials. In addition to comparing our approach to more traditional methodologies based upon the Ising model and Mean Field Theory, we also test the effectiveness of the MrE method on conventionally unexplored ferromagnetic materials with defects.

Suggested Citation

  • Giffin, Adom & Cafaro, Carlo & Ali, Sean Alan, 2016. "Application of the maximum relative entropy method to the physics of ferromagnetic materials," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 455(C), pages 11-26.
    • Handle: RePEc:eee:phsmap:v:455:y:2016:i:c:p:11-26
    DOI: 10.1016/j.physa.2016.02.069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116002478
    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.2016.02.069?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. Cafaro, C. & Ali, S.A., 2008. "Can chaotic quantum energy levels statistics be characterized using information geometry and inference methods?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6876-6894.
    2. Tseng, Chih-Yuan & Caticha, Ariel, 2008. "Using relative entropy to find optimal approximations: An application to simple fluids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6759-6770.
    3. Adom Giffin, 2009. "From Physics to Economics: An Econometric Example Using Maximum Relative Entropy," Papers 0901.0401, arXiv.org.
    4. Giffin, Adom, 2009. "From physics to economics: An econometric example using maximum relative entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1610-1620.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Daoqing & He, Jingjing & Du, Yi-Mu & Sun, C.P. & Guan, Xuefei, 2021. "Probabilistic information fusion with point, moment and interval data in reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

    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. Secrest, J.A. & Conroy, J.M. & Miller, H.G., 2020. "A unified view of transport equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    2. Zhou, Daoqing & He, Jingjing & Du, Yi-Mu & Sun, C.P. & Guan, Xuefei, 2021. "Probabilistic information fusion with point, moment and interval data in reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Cafaro, Carlo & Mancini, Stefano, 2012. "On Grover’s search algorithm from a quantum information geometry viewpoint," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1610-1625.
    4. Ali, S.A. & Cafaro, C. & Kim, D.-H. & Mancini, S., 2010. "The effect of microscopic correlations on the information geometric complexity of Gaussian statistical models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3117-3127.

    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:455:y:2016:i:c:p:11-26. 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.