Ben Davenport & Bob Panoff

Written in Fortran and optimized for vector supercomputers with care to enure high performance on RISC-based workstations, GalaxSee performs a direct integration of Newton's law of motion for N bodies of arbitrary mass: the force on each mass is computed by summing its pair interaction with all other masses, and this force is used to compute the acceleration and hence updated velocities and positions of all bodies in the system. A simple Euler integration is used to make the integration routine simple to understand; a more refined integration can be swapped if desired. The student is encouraged to invesigate the effect of varying step size on both the qualitative and quantitative results. The output consists of real-time animation of the galaxy using NCSA DataScope (for Macintosh) or NCSA Collage (which runs on Mac's, PC's and X-window systems). Projection views are given for XY, XZ, and YZ planes.

A sample lesson involves starting with a spherical distribution of same-mass stars, given an initial rotation around one of the axes. By altering the rate of rotation or changing the stellar mass, the student is able to distinguish these two components to conclude that increased mass gives rise to greater in-fall, and rotational velocity gives rise to a flattened disk in the two directions normal to the axis of rotation. For each run, the user is prompted for the number of stars, the mass per star, the initial rate of rotation, the length of the run, and the frequency with which animation frames are generated.

GalaxSee is itself part of a larger effort instituted by Dr. Panoff to develop a variety of public domain codes using public domain visualization software to yield interactive simulations that encourage and enable project-oriented learning in an interdisciplinary, computational science course. These codes and materials have proven highly successful and adaptable for use in undergraduate courses in physics, mathematics, and computer science, along with our course in computational science. It is a striking example for many of the power of scientific visualization to achieve fundamental insight and understanding of complex phenomena, in understanding the role of supercomputers, and in exploring the nature of computational science itself.