Because every particle in the trap interacts with every other particle, ion
trapping simulation falls in the category of long-range interaction
problems.
The long-range interaction problem is notorious for its
computational intensity: it is generally on a sequential
machine [6]. If a
``tree-based force calculation" is implemented, computational time can
be reduced to
on a sequential machine; an adjustable error
term controls the tradeoff between
speed and accuracy [6][2]. Utilizing parallel
machines should allow for
significant improvements in speed without compromising accuracy.
Another computationally intensive algorithm which should
show significant speed-up on a parallel machine is that of the
Fast Fourier Transform. The Fourier transform, which projects
a function onto a set of periodic functions, is
useful for indicating whether a function is periodic and for analyzing the
frequency components of a periodic signal.
The Fourier series, ,
corresponding to a discrete set of data points,
, is
defined as [6]:
The Fast Fourier Transform is a algorithm for computing
the Fourier series of a set of
data points. One goal of
the proposed project is to implement the Fast Fourier transform
in HPF on a parallel machine.
At least two finite-difference methods will be explored as a means of modeling the time evolution of the ions' positions and velocities. The first method is the Verlet algorithm, which, in its simplest form, uses the particles' positions at the two previous time steps and the forces on the particles to generate a new set of position vectors [1]:
where represents a particle's position vector at time
and
represents a the force acting on a
particle at time
.
The second method is the Gear predictor-corrector algorithm,
which uses a Taylor series approximation to `predict' the
position vector at time
, then re-evaluates
higher-order derivatives using the newly generated position
vectors, and finally `corrects' the position vectors accordingly
[7].