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Nonlinear Instability in Multiple Time Stepping Molecular Dynamics

Nonlinear Instability in Multiple Time Stepping Molecular Dynamics. Jesús Izaguirre , Qun Ma, Department of Computer Science and Engineering University of Notre Dame and Robert Skeel Department of Computer Science and Beckman Institute University of Illinois, Urbana-Champaign SAC’03

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Nonlinear Instability in Multiple Time Stepping Molecular Dynamics

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  1. Nonlinear Instability in Multiple Time Stepping Molecular Dynamics Jesús Izaguirre, Qun Ma, Department of Computer Science and EngineeringUniversity of Notre Dame and Robert Skeel Department of Computer Science and Beckman Institute University of Illinois, Urbana-Champaign SAC’03 March 10, 2003 Supported by NSF CAREER and BIOCOMPLEXITY grants

  2. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  3. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  4. Classical molecular dynamics • Newton’s equations of motion: • Atoms • Molecules • CHARMM potential(Chemistry at Harvard MolecularMechanics) Bonds, angles and torsions

  5. The CHARMM potential terms Bond Angle Improper Dihedral

  6. Energy functions

  7. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  8. Multiple time stepping • Fast/slow force splitting • Bonded: “fast” (small periods) • Long range nonbonded: “slow” (large char. time) • Evaluate slow forces less frequently • Fast forces cheap • Slow force evaluation expensive Fast forces, t Slow forces, t

  9. Verlet-I/r-RESPA/Impulse Grubmüller,Heller, Windemuth and Schulten, 1991 Tuckerman, Berne and Martyna, 1992 • The state-of-the-art MTS integrator • Fast/slow splitting of nonbonded terms via switching functions • 2nd order accurate, time reversible Algorithm 1. Half step discretization of Impulse integrator

  10. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  11. Linear instability of Impulse Linear instability: energy growth occurs unless longest t < 1/2 shortest period. Total energy(Kcal/mol) vs. time (fs) Impulse MOLLY - ShortAvg MOLLY - LongAvg

  12. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear “instabilities” (overheating) • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  13. Nonlinear instability of Impulse • Approach • Analytical: Stability conditions for a nonlinear model problem • Numerical: Long simulations differing only in outer time steps; correlation between step size and overheating • Results: energy growth occurs unless longest t < 1/3 shortest period. • Unconditionally unstable 3rd order nonlinear resonance • Flexible waters: outer time step less than 3~3.3fs • Constrained-bond proteins w/ SHAKE: time step less than 4~5fs Ma, Izaguirre and Skeel (SISC, 2003)

  14. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  15. Nonlinear instability: analytical • Approach: • 1-D nonlinear model problem, in the neighborhood of stable equilibrium • MTS splitting of potential: • Analyze the reversible symplectic map • Express stability condition in terms of problem parameters • Result: • 3rd order resonance stable only if “equality” met • 4th order resonance stable only if “inequality” met • Impulse unstable at 3rd order resonance in practice

  16. Nonlinear: analytical (cont.) • Main result. Let 1. (3rd order) Map stable at equilibrium if and unstable if • Impulseis unstable in practice. 2. (4th order) Map stable if and unstable if • May be stable at the 4th order resonance.

  17. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  18. Nonlinear resonance: numerical Fig. 1: Left: Flexible water system. Right: Energy drift from 500ps MD simulation of flexible water at room temperature revealing 3:1 and 4:1 nonlinear resonance (3.3363 and 2.4 fs)

  19. Nonlinear resonance: numerical Fig. 2. Energy drift from 500ps MD simulation of flexible water at room temperature revealing 3:1 (3.3363)

  20. Nonlinear: numerical (cont.) Fig. 3. Left: Flexible melittin protein (PDB entry 2mlt). Right: energy drift from 10ns MD simulation at 300K revealing 3:1 nonlinear resonance (at 3, 3.27 and 3.78 fs).

  21. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  22. Concluding remarks • MTS restricted by a 3:1 nonlinear resonance that causes overheating • Longest time step < 1/3 fastest normal mode • Important for long MD simulations due to: • Faster computers enabling longer simulations • Long time kinetics and sampling, e.g., protein folding • Use stochasticity for long time kinetics • For large system size, NVE  NVT

  23. Overview • Background • Classical molecular dynamics (MD) • Multiple time stepping integrator • Linear instability • Nonlinear instabilities • Analytical approach • Numerical approach • Concluding remarks • Acknowledgements • Key references

  24. Acknowledgements • People • Dr. Thierry Matthey • Dr. Ruhong Zhou, Dr. Pierro Procacci • Dr. Andrew McCammon hosted JI in May 2001 at UCSD • Dept. of Mathematics, UCSD, hosted RS Aug. 2000 – Aug. 2001 • Resources • Hydra and BOB clusters at ND • Norwegian Supercomputing Center, Bergen, Norway • Funding • NSF CAREER Award ACI-0135195 • NSF BIOCOMPLEXITY-IBN-0083653

  25. Key references [1] Overcoming instabilities in Verlet-I/r-RESPA with the mollified impulse method. J. A. Izaguirre, Q. Ma, T. Matthey, et al.. In T. Schlick and H. H. Gan, editors, Proceedings of the 3rd International Workshop on Algorithms for Macromolecular Modeling, Vol. 24 of Lecture Notes in Computational Science and Engineering, pages 146-174, Springer-Verlag, Berlin, New York, 2002 [2] Verlet-I/r-RESPA/Impulse is limited by nonlinear instability. Q. Ma, J. A. Izaguirre, and R. D. Skeel. Accepted by the SIAM Journal on Scientific Computing, 2002. Available at http://www.nd.edu/~qma1/publication_h.html. [3] Targeted mollified impulse – a multiscale stochastic integrator for molecular dynamics. Q. Ma and J. A. Izaguirre. Submitted to the SIAM Journal on Multiscale Modeling and Simulation, 2003. [4] Nonlinear instability in multiple time stepping molecular dynamics. Q. Ma, J. A. Izaguirre, and R. D. Skeel. In Proceedings of the 2003 ACM Symposium on Applied Computing (SAC’03), pages 167-171, Melborne, Florida. March 9-12, 2003

  26. Key references [5] Long time step molecular dynamics using targeted Langevin Stabilization. Q. Ma and J. A. Izaguirre. In Proceedings of the 2003 ACM Symposium on Applied Computing (SAC’03), pages 178-182, Melborne, Florida. March 9-12, 2003 [6] Dangers of multiple-time-step methods. J. J. Biesiadecki and R. D. Skeel. J. Comp. Phys., 109(2):318–328, Dec. 1993. [7] Difficulties with multiple time stepping and the fast multipole algorithm in molecular dynamics. T. Bishop, R. D. Skeel, and K. Schulten. J. Comp. Chem., 18(14):1785–1791, Nov. 15, 1997. [8] Masking resonance artifacts in force-splitting methods for biomolecular simulations by extrapolative Langevin dynamics. A. Sandu and T. Schlick. J. Comut. Phys, 151(1):74-113, May 1, 1999

  27. THE END. THANKS!

  28. Nonlinear: numerical (cont.) Fig. 4. Left: Melittin protein and water. Right: Energy drift from 500ps SHAKE- constrained MD simulation at 300K revealing combined 4:1 and 3:1 nonlinear resonance.

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