1 CE 530 Molecular Simulation Lecture 23 Symmetric MD Integrators David A. Kofke Department of Chemical Engineering SUNY Buffalo

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Presentation transcript:

1 CE 530 Molecular Simulation Lecture 23 Symmetric MD Integrators David A. Kofke Department of Chemical Engineering SUNY Buffalo

2 Molecular Dynamics Integration  Equations of motion in cartesian coordinates  Previously, we examined basic MD integrators Verlet family Verlet; Leap-frog; Velocity Verlet Popular because of their simplicity and effectiveness  Today we will consider Symmetry features that make the Verlet methods work so well Multiple-timestep extensions of the Verlet algorithms pairwise additive forces 2-dimensional space (for example) F

3 Integration Algorithms  Features of a good integrator minimal need to compute forces (a very expensive calculation) good stability for large time steps good accuracy conserves energy and momentum noise less important than drift  The true (continuum) equations of motions display certain symmetries time-reversible area-preserving (symplectic)  Good integrators can be constructed by paying attention to these features

4 Symmetry  An object displays symmetry if some transformation leaves it (or something about it) unaltered Original shape 90º rotation Horizontal reflection

5 Time Symmetry  Path traced by a mechanical system is unchanged upon reversal of momenta or time e.g., motion in a constant gravitational field  Another view Substitution leaves equations of motion unchanged

6 An Irreversible Integrator  Forward Euler well known to be quite bad  Examine time reversibility Assume we have progressed forward in time an increment  t; positions and momenta are now unit mass

7 An Irreversible Integrator  Forward Euler well known to be quite bad  Examine time reversibility Assume we have progressed forward in time an increment  t; positions and momenta are now Reverse time, and step back to original condition unit mass

8 An Irreversible Integrator  Forward Euler well known to be quite bad  Examine time reversibility Assume we have progressed forward in time an increment  t; positions and momenta are now Reverse time, and step back to original condition Insert from above for unit mass

9 An Irreversible Integrator  Forward Euler well known to be quite bad  Examine time reversibility Assume we have progressed forward in time an increment  t; positions and momenta are now Reverse time, and step back to original condition Insert from above for ; Cancel unit mass

10 An Irreversible Integrator  Forward Euler well known to be quite bad  Examine time reversibility Assume we have progressed forward in time an increment  t; positions and momenta are now Reverse time, and step back to original condition Insert from above for ; Simplify Equal only in limit of zero time step Inequality indicates lack of time reversibility Verlet integrators are time reversible unit mass

11 Symplectic Symmetry 1.  Consider motion of a single particle in 1D Described using a 2D phase space (x,p) Hamiltonian Equations of motion Phase space Forthcoming result are easily generalized to higher dimensional phase space, but hard to visualize unit mass {p(t),x(t)} trajectory

12 Symplectic Symmetry 2.  Consider motion of a differential element through phase space Shape of element is distorted by motion Area of the element is preserved  This is a manifestation of the symplectic symmetry of the equations of motion

13 Classical Harmonic Oscillator  Exactly solvable example  Solution

14 Liouville Formulation 1.  Operator-based view of mechanics  Very useful for deriving symplectic, time-reversible integration schemes  Consider an arbitrary function of phase-space coordinates and thereby a function of time time derivative is  Define the Liouville operator  So

15 Liouville Formulation 2.  Operator form  This has the solution in principle this gives f at any time t in practice it is not directly useful  Let f be the phase-space vector then the solution gives the trajectory through phase space  Harmonic oscillator

16 Separation of Liouville Operator 1.  Position and momentum parts  Propagator of either part can be solved analytically by itself

17 Separation of Liouville Operator 2.  Liouville components do not commute result differs depending on order in which they are applied  Otherwise we could write  We could then apply each propagator in sequence to move the system ahead in time Advance momentum Advance position This is incorrect

18 Trotter Expansion  The following relation does hold for example, if P = 2  We cannot work with infinite P but for large P …plus a correction

19 Formulating an Integrator  Using the large-P approximation  To advance the system over the time interval T break Liouville operator into displacement parts iL x + iL p write apply the Trotter expansion, and interpret T/P as a discretized time  t application of P times advances the system (approximately) through T  An integrator formulated this way will be both time- reversible and symplectic

20 Examination of Integrator 1.  Consider effect of one time step on positions and momenta  First apply exp(iL p  t/2)  Then apply exp(iL x  t)  Finally apply exp(iL p  t/2) again

21 Examination of Integrator 2.  One time step  Examine effect on coordinate and momentum  It’s the Velocity Verlet integrator!  Higher-order algorithms can be derived systematically by including higher orders in the Trotter factorization Not appealing because introduces derivatives of forces

22 A Deep Truth  Verlet integrator replaces the true Liouville propagator by an approximate one  We can make these equal by saying the approximate propagator is obtained as the propagator of an approximate Liouville operator  or  This corresponds to some unknown Hamiltonian and this Hamiltonian is conserved by the Verlet propagator the Verlet algorithm will not likely give rise to drift in the true Hamiltonian, since this “shadow” Hamiltonian is conserved

23 Other Decompositions  Other choices for the decomposition of the Liouville operator can be worthwhile  Some choices: Separation of short- and long-ranged forces Separation of fast and slow time-scale motions  Approach involves defining a reference system that is solved more precisely (more frequently)  Difference between real and reference is updated over a longer time scale  RESPA (Reversible) REference System Propagator Algorithm Uses numerical solution of reference  NAPA Numerical Analytical Propagator Algorithm Uses a reference that can be solved analytically Martyna, Tuckerman, Berne

24 RESPA: Force Decomposition 1.  Decompose force into short (F s ) and long (F l ) range contributions S(x) is a switching function that turns off the force at some distance  Liouville operator

25 RESPA: Force Decomposition 2.  Liouville operator  Trotter factorization of propagator  Decompose term treating short-range forces  Long-range forces are computed n times less frequently than short-range ones Long-range forces vary more slowly They are more expensive to calculate, because more pairs

26 RESPA: Force Decomposition 3.  Full RESPA propagator  Procedure Repeat for n steps update short-range force, evaluate new momenta evaluate new positions Evaluate long-range forces, update momenta Repeat

27 RESPA: Time-Scale Decomposition  Many systems display disparate time scales of motion Massive particles interacting with light ones helium in argon Stiff and loose potentials intramolecular and intermolecular forces  Approach works as before Integrate fast motions (degrees of freedom) using short time step Integrate slow motions using long time step