Like new forms of life, new branches of mathematics and science don't appear from nowhere. The ideas of fractal geometry can be traced to the late nineteenth century, when mathematicians created shapes -- sets of points -- that seemed to have no counterpart in nature. By a wonderful irony, the "abstract" mathematics descended from that work has now turned out to be MORE appropriate than any other for describing many natural shapes and processes.

Perhaps we shouldn't be surprised. The Greek geometers worked out the mathematics of the conic sections for its formal beauty; it was two thousand years before Copernicus and Brahe, Kepler and Newton overcame the preconception that all heavenly motions must be circular, and found the ellipse, parabola, and hyperbola in the paths of planets, comets, and projectiles.

In the 17th century Newton and Leibniz created calculus, with its techniques for "differentiating" or finding the derivative of functions -- in geometric terms, finding the tangent of a curve at any given point. True, some functions were discontinuous, with no tangent at a gap or an isolated point. Some had singularities: abrupt changes in direction at which the idea of a tangent becomes meaningless. But these were seen as exceptional, and attention was focused on the "well- behaved" functions that worked well in modeling nature.

Beginning in the early 1870s, though, a 50-year crisis transformed mathematical thinking. Weierstrass described a function that was continuous but nondifferentiable -- no tangent could be described at any point. Cantor showed how a simple, repeated procedure could turn a line into a dust of scattered points, and Peano generated a convoluted curve that eventually touches every point on a plane. These shapes seemed to fall "between" the usual categories of one-dimensional lines, two- dimensional planes and three-dimensional volumes. Most still saw them as "pathological" cases, but here and there they began to find applications.

In other areas of mathematics, too, strange shapes began to crop up. Poincare attempted to analyze the stability of the solar system in the 1880s and found that the many-body dynamical problem resisted traditional methods. Instead, he developed a qualitative approach, a "state space" in which each point represented a different planetary orbit, and studied what we would now call the topology -- the "connectedness" -- of whole families of orbits. This approach revealed that while many initial motions quickly settled into the familiar curves, there were also strange, "chaotic" orbits that never became periodic and predictable.

Other investigators trying to understand fluctuating, "noisy" phenomena -- the flooding of the Nile, price series in economics, the jiggling of molecules in Brownian motion in fluids -- found that traditional models could not match the data. They had to introduce apparently arbitrary scaling features, with spikes in the data becoming rarer as they grew larger, but never disappearing entirely.

For many years these developments seemed unrelated, but there were tantalizing hints of a common thread. Like the pure mathematicians' curves and the chaotic orbital motions, the graphs of irregular time series often had the property of self-similarity: a magnified small section looked very similar to a large one over a wide range of scales.

While many pure and applied mathematicians advanced these trends, it is Benoit Mandelbrot above all who saw what they had in common and pulled the threads together into the new discipline.

He was born in Warsaw in 1924, and moved to France in 1935. In a time when French mathematical training was strongly analytic, he visualized problems whenever possible, so that he could attack them in geometric terms. He attended the Ecole Polytechnique, then Caltech, where he encountered the tangled motions of fluid turbulence.

In 1958 he joined IBM, where he began a mathematical analysis of electronic "noise" -- and began to perceive a structure in it, a hierarchy of fluctuations of all sizes, that could not be explained by existing statistical methods. Through the years that followed, one seemingly unrelated problem after another was drawn into the growing body of ideas he would come to call fractal geometry.

As computers gained more graphic capabilities, the skills of his mind's eye were reinforced by visualization on display screens and plotters. Again and again, fractal models produced results -- series of flood heights, or cotton prices -- that experts said looked like "the real thing."

Visualization was extended to the physical world as well. In a provocative essay titled "How Long Is the Coast of Britain?" Mandelbrot noted that the answer depends on the scale at which one measures: it grows longer and longer as one takes into account every bay and inlet, every stone, every grain of sand. And he codified the "self-similarity" characteristic of many fractal shapes -- the reappearance of geometrically similar features at all scales.

First in isolated papers and lectures, then in two editions of his seminal book, he argued that many of science's traditional mathematical models are ill-suited to natural forms and processes: in fact, that many of the "pathological" shapes mathematicians had discovered generations before are useful approximations of tree bark and lung tissue, clouds and galaxies.

Mandelbrot was named an IBM Fellow in 1974, and continues to work at the IBM Watson Research Center. He has also been a visiting professor and guest lecturer at many universities.

noel@triumf.ca