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Beeman's algorithm

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Beeman's algorithm is a method for numerically integrating ordinary differential equations of order 2. Beeman in his paper introduced several predictor-corrector methods adapted to the equation of motion , where x is the position and the velocity. Most popular and known under the name Beeman's method became a reduced explicit variant of the order 3 method, which is closely related to Verlet integration. It produces identical positions to the Verlet iteration, but is more accurate in velocities.[citation needed] It is most commonly used in molecular dynamics simulations.

Equation

The formula used to compute the positions at time is:

.

With this prediction of the position vector, the (in the evaluation of ) implicit system

is iterated one or two times. The values on the right are the old values of the last iterations, resulting in the new values on the left. Beeman also proposed to alternatively replace the velocity update in the last equation by the second order Adams–Moulton method:

where

  • is present time (i.e.: independent variable)
  • is the time step size
  • is the position at time t
  • is the velocity at time t
  • is the acceleration at time t, computed as a function of
  • the last term is the error term, using the big O notation

Predictor-Corrector Modifications

In systems where the forces are a function of velocity in addition to position, the above equations need to be modified into a predictor-corrector form whereby the velocities at time are predicted and the forces calculated, before producing a corrected form of the velocities.

An example is:

The velocities at time t = are then calculated from the positions.

The accelerations at time t = are then calculated from the positions and predicted velocities.

Error term

As shown above, the error term is for position and velocity. In comparison, Verlet is for position and for velocity. In exchange for greater accuracy, Beeman's algorithm is moderately computationally more expensive.

Memory Requirements

The simulation must keep track of position, velocity, acceleration and previous acceleration vectors per particle (though some clever work-arounds for storing the previous acceleration vector are possible), keeping its memory requirements on par with velocity Verlet and slightly more expensive than the original Verlet method.

References

  • Sadus, Richard J. (2002), Molecular Theory of Fluids: Theory, Algorithms and Object-Orientation, Elsevier, p. 231, ISBN 0444510826