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Oscillatory Systems with Three Separated Time Scales: Analysis and Computation

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Numerical Analysis of Multiscale Computations

Abstract

We study a few interesting issues that occur in multiscale modeling and computation for oscillatory dynamical systems that involve three or more separated scales. A new type of slow variables which do not formally have bounded derivatives emerge from averaging in the fastest time scale. We present a few systems which have such new slow variables and discuss their characterization. The examples motivate a numerical multiscale algorithm that uses nested tiers of integrators which numerically solve the oscillatory system on different time scales. The communication between the scales follows the framework of the Heterogeneous Multiscale Method. The method’s accuracy and efficiency are evaluated and its applicability is demonstrated by examples.

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References

  1. G. Ariel, B. Engquist, and R. Tsai. A multiscale method for highly oscillatory ordinary differential equations with resonance. Math. Comp., 78:929–956, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  2. G. Ariel, B. Engquist, and R. Tsai. Numerical multiscale methods for coupled oscillators. Multi. Mod. Simul., 7:1387–1404, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  3. G. Ariel, B. Engquist, and R. Tsai. A reversible multiscale integration method. Comm. Math. Sci., 7:595–610, 2009.

    MathSciNet  MATH  Google Scholar 

  4. V.I. Arnol’d. Mathematical methods of classical mechanics. Springer-Verlag, New York, 1989.

    Google Scholar 

  5. Z. Artstein, I. G. Kevrekidis, M. Slemrod, and E. S. Titi. Slow observables of singularly perturbed differential equations. Nonlinearity, 20(11):2463–2481, 2007.

    Article  MathSciNet  MATH  Google Scholar 

  6. Z Artstein, J. Linshiz, and E. S. Titi. Young measure approach to computing slowly advancing fast oscillations. Multiscale Model. Simul., 6(4):1085–1097, 2007.

    Google Scholar 

  7. C. Beck. Brownian motion from deterministic dynamics. Phys. A, 169:324–336, 1990.

    Article  MathSciNet  Google Scholar 

  8. M. P. Calvo and J. M. Sanz-Serna. Instabilities and inaccuracies in the integration of highly oscillatory problems. SIAM J. Sci. Comput., 31(3):1653–1677, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  9. W. E. Analysis of the heterogeneous multiscale method for ordinary differential equations. Commun. Math. Sci., 1(3):423–436, 2003.

    MathSciNet  Google Scholar 

  10. W. E and B. Engquist. The heterogeneous multiscale methods. Commun. Math. Sci., 1(1):87–132, 2003.

    Google Scholar 

  11. W. E, B. Engquist, X. Li, W. Ren, and E. Vanden-Eijnden. Heterogeneous multiscale methods: A review. Comm. Comput. Phys., 2:367–450, 2007.

    Google Scholar 

  12. W. E, D. Liu, and E. Vanden-Eijnden. Analysis of multiscale methods for stochastic differential equations. Commun. on Pure and Applied Math., 58:1544–1585, 2005.

    Google Scholar 

  13. B. Engquist and Y.-H. Tsai. Heterogeneous multiscale methods for stiff ordinary differential equations. Math. Comp., 74(252):1707–1742, 2005.

    Article  MathSciNet  MATH  Google Scholar 

  14. I. Fatkullin and E. Vanden-Eijnden. A computational strategy for multiscale chaotic systems with applications to Lorenz 96 model. J. Comp. Phys., 200:605–638, 2004.

    Article  MathSciNet  MATH  Google Scholar 

  15. E. Fermi, J. Pasta, and S. Ulam. Studies of the nonlinear problems, i. Los Alamos Report LA-1940, 1955. Later published in Collected Papers of Enrico Fermi, ed. E. Segre, Vol. II (University of Chicago Press, 1965) p.978.

    Google Scholar 

  16. B. García-Archilla, J. M. Sanz-Serna, and R. D. Skeel. Long-time-step methods for oscillatory differential equations. SIAM J. Sci. Comput., 20(3):930–963, 1999.

    Article  MathSciNet  MATH  Google Scholar 

  17. C. W. Gear and I. G. Kevrekidis. Projective methods for stiff differential equations: problems with gaps in their eigenvalue spectrum. SIAM J. Sci. Comput., 24(4):1091–1106 (electronic), 2003.

    Google Scholar 

  18. C. W. Gear and I. G. Kevrekidis. Constraint-defined manifolds: a legacy code approach to low-dimensional computation. J. Sci. Comput., 25(1-2):17–28, 2005.

    MathSciNet  MATH  Google Scholar 

  19. C.W. Gear and K.A. Gallivan. Automatic methods for highly oscillatory ordinary differential equations. In Numerical analysis (Dundee, 1981), volume 912 of Lecture Notes in Math., pages 115–124. Springer, 1982.

    Google Scholar 

  20. D. Givon and R. Kupferman. White noise limits for discrete dynamical systems driven by fast deterministic dynamics. Phys. A, 335(3-4):385–412, 2004.

    Article  MathSciNet  Google Scholar 

  21. D. Givon, R. Kupferman, and A.M. Stuart. Extracting macroscopic dynamics: model problems and algorithms. Nonlinearity, 17:R55–R127, 2004.

    Article  MathSciNet  MATH  Google Scholar 

  22. M. Holland and I. Melbourne. Central limit theorems and invariance principles for Lorenz attractors. J. Lond. Math. Soc. (2), 76(2):345–364, 2007.

    Google Scholar 

  23. H.-O. Kreiss. Problems with different time scales for ordinary differential equations. SIAM J. Numer. Anal., 16(6):980–998, 1979.

    Article  MathSciNet  MATH  Google Scholar 

  24. H.-O. Kreiss. Problems with different time scales. In Acta numerica, 1992, pages 101–139. Cambridge Univ. Press, 1992.

    Google Scholar 

  25. H.-O. Kreiss and J. Lorenz. Manifolds of slow solutions for highly oscillatory problems. Indiana Univ. Math. J., 42(4):1169–1191, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  26. A.M. Majda, I. Timofeyev, and E. Vanden-Eijnden. Stochastic models for selected slow variables in large deterministic systems. Nonlinearity, 19:769–794, 2006.

    Article  MathSciNet  MATH  Google Scholar 

  27. I. Melbourne and A. M. Stuart. A note on diffusion limits of chaotic skew product flows. Nonlinearity, 24:1361–1367, 2011.

    Article  MathSciNet  MATH  Google Scholar 

  28. G. Papanicolaou. Introduction to the asymptotic analysis of stochastic equations. In Modern modeling of continuum phenomena, volume 16 of Lectures in Applied Mathematics, pages 47–109. Amer. Math. Soc., Providence, RI, 1977.

    Google Scholar 

  29. G. A. Pavliotis and A. M. Stuart. Multiscale Methods: Averaging and Homogenization. Number 53 in Texts in Applied Mathematics. Springer-Verlag, New York, 2008.

    Google Scholar 

  30. R.L. Petzold, O.J. Laurent, and Y. Jeng. Numerical solution of highly oscillatory ordinary differential equations. Acta Numerica, 6:437–483, 1997.

    Article  Google Scholar 

  31. J. M. Sanz-Serna. Modulated Fourier expansions and heterogeneous multiscale methods. IMA J. Numer. Anal., 29(3):595–605, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  32. R.E. Scheid. The accurate numerical solution of highly oscillatory ordinary differential equations. Mathematics of Computation, 41(164):487–509, 1983.

    Article  MathSciNet  MATH  Google Scholar 

  33. M. Tao, H. Owhadi, and J. Marsden. Non-intrusive and structure preserving multiscale integration of stiff odes, sdes and hamiltonian systems with hidden slow dynamics via flow averaging. Multiscale Model. Simul., 8:1269-1324, 2010.

    Article  MathSciNet  MATH  Google Scholar 

  34. E. Vanden-Eijnden. Numerical techniques for multi-scale dynamical systems with stochastic effects. Comm. Math. Sci., 1:385–391, 2003.

    MathSciNet  MATH  Google Scholar 

  35. E. Vanden-Eijnden. On HMM-like integrators and projective integration methods for systems with multiple time scales. Commun. Math. Sci., 5:495–505, 2007.

    MathSciNet  MATH  Google Scholar 

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Acknowledgements

Research are performed under the support of NSF DMS-0714612. Tsai is 499 partially supported by a Sloan Fellowship. We thank Seong Jun Kim for comments, corrections 500 and a careful reading of the manuscript.

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Correspondence to Gil Ariel .

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Ariel, G., Engquist, B., Tsai, YH.R. (2012). Oscillatory Systems with Three Separated Time Scales: Analysis and Computation. In: Engquist, B., Runborg, O., Tsai, YH. (eds) Numerical Analysis of Multiscale Computations. Lecture Notes in Computational Science and Engineering, vol 82. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21943-6_2

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