The European Physical Journal Special Topics

, Volume 226, Issue 9, pp 1971–1977 | Cite as

Predictability of extreme intensity pulses in optically injected semiconductor lasers

  • Nuria Martinez Alvarez
  • Saurabh Borkar
  • Cristina MasollerEmail author
Regular Article
Part of the following topical collections:
  1. Recent Advances in Nonlinear Dynamics and Complex Structures: Fundamentals and Applications


The predictability of extreme intensity pulses emitted by an optically injected semiconductor laser is studied numerically, by using a well-known rate equation model. We show that symbolic ordinal time-series analysis allows to identify the patterns of intensity oscillations that are likely to occur before an extreme pulse. The method also gives information about patterns which are unlikely to occur before an extreme pulse. The specific patterns identified capture the topology of the underlying chaotic attractor and depend on the model parameters. The methodology proposed here can be useful for analyzing data recorded from other complex systems that generate extreme fluctuations in their output signals.


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  1. 1.
    S. Albeverio, V. Jentsch, H. Kantz, Extreme Events in Nature and Society, The Frontiers Collection (Springer, Berlin, 2006)Google Scholar
  2. 2.
    D.R. Solli, C. Ropers, P. Koonath, B. Jalali, Nature 450, 1054 (2007)ADSCrossRefGoogle Scholar
  3. 3.
    M. Onorato, S. Residori, U. Bortolozzo, A. Montina, F.T. Arecchi, Phys. Rep. 528, 47 (2013)ADSMathSciNetCrossRefGoogle Scholar
  4. 4.
    G. Ansmann, R. Karnatak, K. Lehnertz, U. Feudel, Phys. Rev. E 88, 052911 (2013)ADSCrossRefGoogle Scholar
  5. 5.
    R. Karnatak, G. Ansmann, U. Feudel, K. Lehnertz, Phys. Rev. E 90, 022917 (2014)ADSCrossRefGoogle Scholar
  6. 6.
    H. Degueldre, J.J. Metzger, T. Geisel, R. Fleischmann, Nat. Phys. 12, 259 (2016)CrossRefGoogle Scholar
  7. 7.
    L. de Haan, A. Ferreira, Extreme Value Theory: An Introduction (Springer, New York, 2006)Google Scholar
  8. 8.
    E.G. Altmann, H. Kantz, Phys. Rev. E 71, 056106 (2005)ADSMathSciNetCrossRefGoogle Scholar
  9. 9.
    J.J. Metzger, R. Fleischmann, T. Geisel, Phys. Rev. Lett. 112, 203903 (2014)ADSCrossRefGoogle Scholar
  10. 10.
    M.-R. Alam, Geophys. Research Lett. 41, 8477 (2014)ADSCrossRefGoogle Scholar
  11. 11.
    S. Birkholz, C. Bree, A. Demircan, G. Steinmeyer, Phys. Rev. Lett. 114, 213901 (2015)ADSCrossRefGoogle Scholar
  12. 12.
    A. Deluca, N.R. Moloney, A. Corral, Phys. Rev. E 91, 052808 (2015)ADSCrossRefGoogle Scholar
  13. 13.
    H.L.D. de, S. Cavalcante, M. Oria, D. Sornette, E. Ott, D.J. Gauthier, Phys. Rev. Lett. 111, 198701 (2013)ADSCrossRefGoogle Scholar
  14. 14.
    D. Sornette, Proc. Natl. Acad. Sci. USA 99, 2522 (2002)ADSCrossRefGoogle Scholar
  15. 15.
    P. Embrechts, C. Kluppelberg, T. Mikosch, Modelling Extremal Events for Insurance and Finance (Springer, Berlin, 2004)Google Scholar
  16. 16.
    J. Davidsen, G. Kwiatek, Phys. Rev. Lett. 111, 068501 (2013)ADSCrossRefGoogle Scholar
  17. 17.
    C.B. Field et al., Eds., Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, IPCC Special Report (Cambridge University Press, New York, 2012)Google Scholar
  18. 18.
    A.N. Pisarchik, R. Jaimes-Reategui, R. Sevilla-Escoboza, G. Huerta-Cuellar, M. Taki, Phys. Rev. Lett. 107, 274101 (2011)ADSCrossRefGoogle Scholar
  19. 19.
    F. Marino, M. Ciszak, S.F. Abdalah, K. Al-Naimee, R. Meucci, F.T. Arecchi, Phys. Rev. E 84, 047201 (2011)ADSCrossRefGoogle Scholar
  20. 20.
    C. Bonatto, M. Feyereisen, S. Barland, M. Giudici, C. Masoller, J.R. Rios Leite, J.R. Tredicce, Phys. Rev. Lett. 107, 053901 (2011)ADSCrossRefGoogle Scholar
  21. 21.
    J. Zamora-Munt, B. Garbin, S. Barland, M. Giudici, J.R. Rios Leite, C. Masoller, J.R. Tredicce, Phys. Rev. A 87, 035802 (2013)ADSCrossRefGoogle Scholar
  22. 22.
    S. Perrone, R. Vilaseca, J. Zamora-Munt, C. Masoller, Phys. Rev. A 89, 033804 (2014)ADSCrossRefGoogle Scholar
  23. 23.
    C. Metayer, A. Serres, E.J. Rosero, W.A.S. Barbosa, F.M. de Aguiar, J.R. Rios Leite, J.R. Tredicce, Opt. Express 22, 19850 (2014)ADSCrossRefGoogle Scholar
  24. 24.
    E.G. Turitsyna, S.V. Smirnov, S. Sugavanam, N. Tarasov, X. Shu, S.A. Babin, E.V. Podivilov, D.V. Churkin, G.E. Falkovich, S.K. Turitsyn, Nat. Photon. 7, 783 (2013)ADSCrossRefGoogle Scholar
  25. 25.
    A. Aragoneses, L. Carpi, N. Tarasov, D.V. Churkin, M.C. Torrent, C. Masoller, S.K. Turitsyn, Phys. Rev. Lett. 116, 033902 (2016)ADSCrossRefGoogle Scholar
  26. 26.
    C. Bandt, B. Pompe, Phys. Rev. Lett. 88, 174102 (2002)ADSCrossRefGoogle Scholar
  27. 27.
    O.A. Rosso, H.A. Larrondo, M.T. Martin, A. Plastino, M.A. Fuentes, Phys. Rev. Lett. 99, 154102 (2007)ADSCrossRefGoogle Scholar
  28. 28.
    M. Zanin, L. Zunino, O.A. Rosso, D. Papo, Entropy 14, 15531577 (2012)CrossRefGoogle Scholar
  29. 29.
    S. Wieczorek, B. Krauskopf, T.B. Simpson, D. Lenstra, Phys. Rep. 416, 1 (2005)ADSCrossRefGoogle Scholar
  30. 30.
    V. Kovanis, A. Gavrielides, J.A.C. Gallas, Eur. Phys. J. D 58, 181186 (2010)CrossRefGoogle Scholar
  31. 31.
    P. Grassberger, I. Procaccia, Phys. Rev. Lett. 50, 346 (1983)ADSMathSciNetCrossRefGoogle Scholar

Copyright information

© EDP Sciences and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Departament de Fisica, Universitat Politecnica de CatalunyaTerrassa, BarcelonaSpain
  2. 2.Indian Institute of TechnologyGuwahati, AssamIndia

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