Skip to main content
Log in

StructuRal Derivative Based on Inverse Mittag-Leffler Function for Modeling Ultraslow Diffusion

  • Research Paper
  • Published:
Fractional Calculus and Applied Analysis Aims and scope Submit manuscript

Abstract

This paper proposes a novel structural derivative approach to tackle the perplexing modeling problem of ultraslow diffusion. The structural function plays a central role in this new strategy as a kernel transform of underlying time-space fabric of physical systems. Ultraslow diffusion has been observed in numerous lab experiments and field observations, whose behaviors deviate dramatically from the standard anomalous diffusion models characterizing power function of time. The logarithmic diffusion model has since been used to describe bizarre process of ultraslow diffusion but with very limited success. This study applies the inverse Mittag-Leffler function as the structural function in the structural derivative modeling ultraslow diffusion of a random system of two interacting particles. It is observed that the dynamics of two interacting particles are respectively the ballistic motion at the short time scale and the Sinai ultraslow diffusion at the long time scale. Compared with the logarithmic diffusion model, the inverse Mittag-Leffler diffusion model has higher accuracy and manifests clearer physical mechanism. Numerical experiments show that the structural derivative is a feasible mathematical tool to model the ultraslow diffusion using the inverse Mittag-Leffler function as its structural function.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. S.D.T. Arias, X. Waintal, J.L. Pichard, Two interacting particles in a disordered chain III: Dynamical aspects of the interplay disorderinteraction. Eur. Phys. J. B 10 (1999), 149–158.

    Article  Google Scholar 

  2. F. Bowman, Introduction to Bessel Functions. Courier Corporation (2012).

    MATH  Google Scholar 

  3. C.B. Boyer, U.C. Merzbach, A History of Mathematics. John Wiley Sons (2011).

    MATH  Google Scholar 

  4. E.B. Brauns, M.L. Madaras, R.S. Coleman, et al., Complex local dynamics in DNA on the picosecond and nanosecond time scales. Phys. Rev. Lett. 88 (2002), Article # 158101.

  5. M. Caputo, M. Fabrizio, A new definition of fractional derivative without singular kernel. Progr. Fract. Differ. Appl. 1 (2015), 73–85.

    Google Scholar 

  6. W. Chen, Time-space fabric underlying anomalous diffusion. Chaos Soliton. Fract. 28 (2006), 923–929.

    Article  Google Scholar 

  7. W. Chen, Implicit calculus modeling for simulation of complex scientific and engineering problems. Comput. Aided E 23 (2014), 1–6 (In Chinese).

    Google Scholar 

  8. W. Chen, X. Hei, Y. Liang, Fractional kernel derivative model for ultraslow diffusion. Appl. Math. Mech. 37, No 6 (2016), 599–608 (In Chinese).

    Google Scholar 

  9. W. Chen, Y. Liang, S. Hu S, et al., Fractional derivative anomalous diffusion equation modeling prime number distribution. Fract. Calc. Appl. Anal. 18, No 3 (2015), 789–798; DOI: 10.1515/fca-2015-0047; https://www.degruyter.com/view/j/fca.2015.18.issue-3/issue-files/fca.2015.18.issue-3.xml.

    Article  MathSciNet  Google Scholar 

  10. W. Chen, Y. Liang, X. Hei, Local structural derivative and its applications. Chinese J. Solid Mech. 37, No 5 (2016), 1–5 (in Chinese).

    Google Scholar 

  11. W. Chen, G. Pang, A new definition of fractional Laplacian with application to modeling three-dimensional nonlocal heat conduction. J. Comput. Phys. 309 (2016), 350–367.

    Article  MathSciNet  Google Scholar 

  12. M. Cardona, R.V. Chamberlin, W. Marx, The history of the stretched exponential function. Ann. Phys.-Berlin 16 (2007), 842–845.

    Article  Google Scholar 

  13. A. Ehsani, M.G. Mahjani, M. Bordbar, et al., Electrochemical study of anomalous diffusion and fractal dimension in poly ortho aminophenol electroactive film: Comparative study. J. Electroanal. Chem. 710 (2013), 29–35.

    Article  Google Scholar 

  14. R. Gorenflo, A.A. Kilbas, F. Mainardi, S. Rogosin, Mittag-Leffler Functions, Related Topics and Applications. Springer, Berlin (2014).

    Book  Google Scholar 

  15. J.W. Hanneken, B.N. Achar, Finite series representation of the inverse Mittag-Leffler function. Math. Probl. Eng. 2014 (2014), Article # 252393.

  16. G.H. Hardy, Gosta Mittag-Leffler. J. Lond. Math. Soc. 1 (1928), 156–160.

    Article  MathSciNet  Google Scholar 

  17. R. Hilfer, H.J. Seybold, Computation of the generalized Mittag-Leffler function and its inverse in the complex plane. Integr. Transf. Spec. Func. 17 (2006), 637–652.

    Article  MathSciNet  Google Scholar 

  18. F. Hofling, T. Franosch, Anomalous transport in the crowded world of biological cells. Rep. Prog. Phys. 76 (2013), Article # 046602.

  19. C. Ingo, R.L. Magin, L. Colon-Perez, et al., On random walks and entropy in diffusion-weighted magnetic resonance imaging studies of neural tissue. Magnetic Reson. Med. 71 (2014), 617–627.

    Article  Google Scholar 

  20. I. Karatzas, S. Shreve, Brownian Motion and Stochastic Calculus. Springer Science Business Media (2012).

    MATH  Google Scholar 

  21. Y. Liang, W. Chen, R.L. Magin, Connecting complexity with spectral entropy using the Laplace transformed solution to the fractional diffusion equation. Physica A 453 (2016), 327–335.

    Article  MathSciNet  Google Scholar 

  22. Y. Liang, A.Q. Ye, W. Chen, et al., A fractal derivative model for the characterization of anomalous diffusion in magnetic resonance imaging. Commun. Nonlinear Sci. Numer. Simulat. 39 (2016), 529–537.

    Article  MathSciNet  Google Scholar 

  23. M.A. Lomholt, L. Lizana, R. Metzler, et al., Microscopic origin of the logarithmic time evolution of aging processes in complex systems. Phys. Rev. Lett. 110 (2013), Article # 208301.

  24. F. Mainardi, Fractional Calculus and Waves in Linear Viscoelasticity: An Introduction to Mathematical Models. World Scientific (2010).

    Book  Google Scholar 

  25. K. Matan, R.B. Williams, T.A. Witten, et al., Crumpling a thin sheet. Phys. Rev. Lett. 88 (2002), Article # 076101.

  26. R. Metzler, J.H. Jeon, A.G. Cherstvy, et al., Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking. Phys. Chem. Chem. Phys. 16 (2014), Article # 24128.

  27. R. Metzler, J. Klafter, The random walk’s guide to anomalous diffusion: a fractional dynamics approach. Phys. Rep. 339 (2000), 1–77.

    Article  MathSciNet  Google Scholar 

  28. M.D. Ortigueira, J.A.T. Machado, Fractional signal processing and applications. Signal Process. 83 (2003), 2285–2286.

    Article  Google Scholar 

  29. L.P. Sanders, M.A. Lomholt, L. Lizana, et al., Severe slowing-down and universality of the dynamics in disordered interacting many-body systems: ageing and ultraslow diffusion. New J. Phys. 16 (2014), Article # 113050.

  30. R. Schumer, M.M. Meerschaert, B. Baeumer, Fractional advection dispersion equations for modeling transport at the Earth surface. J. Geophys. Res: Earth Surf. 114 (2009), Article # F00A07.

  31. Y.G. Sinai, The limiting behavior of a one-dimensional random walk in a random medium. Theor. Probab. Appl. 27 (1983), 256–268.

    Article  Google Scholar 

  32. H.E. Stanley, S. Havlin, Generalisation of the Sinai anomalous diffusion law. J. Phys. A-Math. Theor. 20 (1987), Article # L615.

  33. A. Vaknin, Z. Ovadyahu, M. Pollak, Aging effects in an Anderson insulator. Phys. Rev. Lett. 84 (2000), Article #3402.

  34. Y. Zhou, Basic Theory of Fractional Differential Equations. World Scientific, Singapore (2014).

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, W., Liang, Y. & Hei, X. StructuRal Derivative Based on Inverse Mittag-Leffler Function for Modeling Ultraslow Diffusion. FCAA 19, 1250–1261 (2016). https://doi.org/10.1515/fca-2016-0064

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1515/fca-2016-0064

MSC 2010

Key Words and Phrases

Navigation