IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v391y2012i4p1591-1601.html
   My bibliography  Save this article

Data compressor designed to improve recognition of magnetic phases

Author

Listed:
  • Vogel, E.E.
  • Saravia, G.
  • Cortez, L.V.

Abstract

Data compressors available in the web have been used to determine magnetic phases for two-dimensional (2D) systems [E. Vogel, G. Saravia, F. Bachmann, B. Fierro, J. Fischer, Phase transitions in Edwards-Anderson model by means of information theory, Physica A 388 2009 4075–4082]. In the present work, we push this line forward along four different directions. First, the compressor itself: we design a new data compressor, named wlzip, optimized for the recognition of information having physical (or scientific) information instead of the random digital information usually compressed. Second, for the first time we extend the data compression analysis to the 3D Ising ferromagnetic model using wlzip. Third, we discuss the tuning possibilities of wlzip in terms of the number of digits considered in the compression to yield maximum definition; in this way, the transition temperature of both 2D and 3D Ising ferromagnets can be reported with very good resolution. Fourth, the extension of the time window through which the data file is actually compressed is also considered to get optimum accuracy. The paper is focused on the new compressor, its algorithm in general and the way to apply it. Advantages and disadvantages of wlzip are discussed. Toward the end, we mention other possible applications of this technique to recognize stable and unstable regimes in the evolution of variables in meteorology (such as pollution content or atmospheric pressure), biology (blood pressure) and econophysics (prices of the stock market).

Suggested Citation

  • Vogel, E.E. & Saravia, G. & Cortez, L.V., 2012. "Data compressor designed to improve recognition of magnetic phases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1591-1601.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:4:p:1591-1601
    DOI: 10.1016/j.physa.2011.09.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437111007217
    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.2011.09.005?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. Vogel, E.E. & Saravia, G. & Bachmann, F. & Fierro, B. & Fischer, Janine, 2009. "Phase transitions in Edwards–Anderson model by means of information theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4075-4082.
    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. Vogel, E.E. & Saravia, G. & Kobe, S. & Schumann, R. & Schuster, R., 2018. "A novel method to optimize electricity generation from wind energy," Renewable Energy, Elsevier, vol. 126(C), pages 724-735.
    2. Posadas, A. & Morales, J. & Ibañez, J.M. & Posadas-Garzon, A., 2021. "Shaking earth: Non-linear seismic processes and the second law of thermodynamics: A case study from Canterbury (New Zealand) earthquakes," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    3. Pasten, Denisse & Saravia, Gonzalo & Vogel, Eugenio E. & Posadas, Antonio, 2022. "Information theory and earthquakes: Depth propagation seismicity in northern Chile," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).

    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. Vogel, E.E. & Saravia, G. & Kobe, S. & Schumann, R. & Schuster, R., 2018. "A novel method to optimize electricity generation from wind energy," Renewable Energy, Elsevier, vol. 126(C), pages 724-735.
    2. Pasten, Denisse & Saravia, Gonzalo & Vogel, Eugenio E. & Posadas, Antonio, 2022. "Information theory and earthquakes: Depth propagation seismicity in northern Chile," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).

    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:391:y:2012:i:4:p:1591-1601. 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.