Mar/Apr 2000

ARTICLE TOOLS

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Richard Feynman once remarked that unless one is able to make one's ideas understandable to college freshmen, one doesn't really understand them. On the other hand, when asked by a reporter to explain why he was awarded the Nobel Prize, Feynman remarked, "Listen buddy, if I could explain it in fifty words or less, it wouldn't be worth a Nobel Prize."

There are two truths here: (1) Important ideas can be made accessible without dumbing them down; (2) The details of a scientific theory are important and typically inaccessible except to individuals with the requisite training. The hallmark of good science writing—the Feynman Test, let's call it—is the ability to heed both of these truths at the same time.

Yair Guttmann's project centers on a question of fundamental interest, growing out of the increasing use of probabilistic reasoning in physics over the last 150 years: Why do statistical methods work so well at predicting the behavior of huge numbers of particles enclosed in containers even though the physics that describes the individual behaviors of those particles is purely deterministic? Hence, it is an ideal subject for a book that seeks to make important scientific and philosophical issues accessible without garbling essential technical details. Alas, Guttmann fails the Feynman Test, but his failure is instructive.

Guttmann observes that a "philosophical temperament" is needed for a book such as this "on the nature of probabilities in statistical mechanics. … For most physicists, the topic is too 'academic.'" Guttmann himself champions what he calls the "pragmatist" approach to statistical mechanics (statistical mechanics explains the macroscopic properties of a physical system by a probabilistic description ...