JAMES Gleick covers a new area of science in his bestseller, Chaos. Gleick, an editor and reporter for the New York Times, conveys the findings of different scientists in a mind-gripping book.
The science of Chaos is concerned with questions that core sciences are only just beginning to ask. Gleick asks a series of simple questions and then leads the reader through steps to show how complex these effortless questions really are.
How long is a coastline? A simple answer would approximate the length of the coastline by first assuming a straight line that cuts through its rough turns and then by measuring the length of that line. The science of Chaos, however, is more demanding. Approximations of the shoreline are not enough. The rough edges of the seashore have to be considered. Without measuring the rough edges, calculations are always going to be approximate, but never on the mark. Indeed, the rough edges of the coastline could be measured to infinite proximity. Once a reliable measurement is found, upon closer examination, another more contiguous is found. This process continues ad infinitum. A structure is found through the process. The study of the resulting structures is the core of Chaos.
While many might find such questions trivial, meteorologists who are still unable to predict the weather accurately due to randomness need help - every bit of it precise. The weather, unlike a simple dynamics problem, is not periodic and any attempt at forecasting it should not fall prey to approximations and possible errors.
Approximations are a cause of error, especially when compounded over and over. There is a need to curb these errors, but every attempt to restrain approximations gives the same result: Chaos. Beautiful pictures are created when random numbers are graphed, but no concrete solutions recognized as universal have yet been found.
Science students are taught that non-linear problems cannot be solved, but Chaos takes a different approach. The science of Chaos specializes in non-linearity and making sense of randomness without rounding-up approximations. Attempts are made by many scientists towards universality in order to find encompassing equations that fit the Chaos, but many have failed.
The author’s account of the lives of scientists that research Chaos adds flavor to the simplified technical details in the book. Gleick underlines the problems of specialty and the need for an interdisciplinary approach to manage the problems of Chaos. Each discipline has its own way to deal with numbers, but Chaos cuts through all these disciplines. From economists to psychiatrists to biologists to medical doctors, the problem of random occurrence remains unanswered.
The book sometimes diverts the reader’s attention from the central problem of Chaos, to unimportant facts about the process of scientific discovery. Where an idea of a certain model that deals with Chaos would have sufficed, the author expands into the procedures used by the scientists. These are easily forgiven considering the scope of the book, but they do take away from the book’s seamlessness.
The level of detail in the book is also inconsistent. It sometimes details the process of experimentation and at other times gives a birds-eye-view of the field of Chaos. The coverage of the scientific material in the book is, in my opinion, chaotic. Nevertheless, many insights are made into the making of science. These visions are educational and entertaining.
Gleick visits William Kuhn, author of the Structure of Scientific Revolutions. Kuhn argues that science does not develop in gradual steps, but takes leaps towards paradigm shifts. These leaps he calls “scientific revolutions.” Indeed, the advancements in the science of Chaos could be the genesis of a scientific revolution in progress.
The models that scientists made to describe Chaos created magnificent shapes and also gave us some exactness in tackling randomness. Edward Lorenz in 1963, a recognized physicist, created a way to cut through randomness. The Lorenz attractor created fluttering butterflies. To an artist some order is found, but to a mathematician, the artistic picture remains meaningless. Lorenz’s equations could only predict a few strands, but then lose focus. Helg Von Koch managed to redesign the quandary of random numbers to a fractal (used in computer modeling of natural structures that do not have simple geometric shapes for example, clouds, coastlines) and scaling problems when he described the Koch curve in 1904. The Koch curve manages the approximation problem through creating smaller and smaller triangles compounded over one another indefinitely. Scaling means that there are similarities between pieces big and small, every triangle in the Koch curve has similarities to every other, but the randomness still persists.
To add to the field of Chaos, scientific communities remain separate, internally closed to interdisciplinary reach. Chaos cuts across disciplines, but has not got recognition needed to become a favored science on its own. This is largely because graduate students do not believe it will boost their careers should they embark on Chaos experiments and departments worry about their reputations.
Problems that could result in a solution monopolize scientific inquiry. Non-linear randomness has not yet attained the required respect among academic circles. Examining graphs of Chaos, one sees a periodic flow and this aspect of Chaos remains unintelligible to science. Scientists familiar with advancements in the field of Chaos, however, use its methods as lenses capable of changing the way they see the world.