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Energy drift in molecular dynamics simulations

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Abstract

In molecular dynamics, Hamiltonian systems of differential equations are numerically integrated using the Störmer–Verlet method. One feature of these simulations is that there is an unphysical drift in the energy of the system over long integration periods. We study this energy drift, by considering a representative system in which it can be easily observed and studied. We show that if the system is started in a random initial configuration, the error in energy of the numerically computed solution is well modeled as a continuous-time stochastic process: geometric Brownian motion. We discuss what in our model is likely to remain the same or to change if our approach is applied to more realistic molecular dynamics simulations.

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References

  1. M. P. Allen and D. J. Tildesley, Computer Simulation of Liquids, Oxford University Press, Oxford, 1987.

    MATH  Google Scholar 

  2. G. Benettin and A. Giorgilli, On the Hamiltonian interpolation of near-to-the-identity symplectic mappings with application to symplectic integration algorithms, J. Stat. Phys., 74 (1993), pp. 1117–1142.

    Article  Google Scholar 

  3. P. Billingsley, Convergence of Probability Measures, John Wiley & Sons, Inc., New York, 1999.

    MATH  Google Scholar 

  4. G. Ciccotti, D. Frenkel, and I. R. McDonald, eds., Simulation of Liquids and Solids: Molecular Dynamics and Monte Carlo Methods in Statistical Mechanics, North-Holland, Amsterdam, 1987.

  5. D. Cottrell, Symplectic integration of simple collisions: A backward error analysis, Master’s thesis, McGill University, 2004. (www.math.mcgill.ca/∼cottrell/thesis.pdf)

  6. E. Faou, E. Hairer, and T.-L. Pham, Energy conservation with non-symplectic methods: examples and counter-examples, BIT, 44 (2004), pp. 699–709.

    Article  MATH  Google Scholar 

  7. E. Hairer, C. Lubich, and G. Wanner, Geometric Numerical Integration – Structure-Preserving Algorithms for Ordinary Differential Equations, Springer, New York, 2002.

    MATH  Google Scholar 

  8. E. Hairer, C. Lubich, and G. Wanner, Geometric numerical integration illustrated by the Störmer–Verlet method, Acta Numer., (2003), pp. 339–450.

  9. R. I. McLachlan and M. Perlmutter, Energy drift in reversible time integration, J. Phys. A, Math. Gen., 37 (2004), pp. L593–L598.

    Article  MATH  Google Scholar 

  10. C. S. O’Hern, L. E. Silbert, A. J. Liu, and S. R. Nagel, Jamming at zero temperature and zero applied stress: the epitome of disorder, Phys. Rev. E, 68 (2003), pp. 1–19.

    Article  Google Scholar 

  11. S. Reich, Backward error analysis for numerical integrators, SIAM J. Numer. Anal., 36 (1999), pp. 1549–1570.

    Article  MATH  Google Scholar 

  12. E. Shaw, H. Sigurgeirsson, and A. M. Stuart, A Markov model for billiards, preprint, Warwick Mathematics Institute, 2004.

  13. R. D. Skeel and D. J. Hardy, Practical construction of modified Hamiltonians, SIAM J. Sci. Comput., 23 (2001), pp. 1172–1188.

    Article  MATH  Google Scholar 

  14. R. D. Skeel and D. J. Hardy, Monitoring energy drift with shadow Hamiltonians, J. Comput. Phys., 206 (2005), pp. 432–452.

    Article  MATH  Google Scholar 

  15. L. Verlet, Computer “experiments” on classical fluids. I. Thermodynamical properties of Lennard–Jones molecules, Phys. Rev., 159 (1967), pp. 98–103.

    Google Scholar 

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Correspondence to P.F. Tupper.

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AMS subject classification (2000)

37M15, 37M05, 65G99

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Cottrell, D., Tupper, P. Energy drift in molecular dynamics simulations . Bit Numer Math 47, 507–523 (2007). https://doi.org/10.1007/s10543-007-0134-z

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  • DOI: https://doi.org/10.1007/s10543-007-0134-z

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