History of numbers. Numbers were probably first used many thousands of
years ago in commerce, and initially only whole numbers and perhaps rational
numbers were needed. But already in Babylonian times, practical problems of
geometry began to require square roots. Nevertheless, for a very long time, and
despite some development of algebra, only numbers that could somehow in
principle be constructed mechanically were ever considered. The invention of flux ions by Isaac
Newton in the late 1600s, however, introduced the idea of continuous
variables - numbers with a continuous range of possible sizes. But while this
was a convenient and powerful notion, it also involved a new level of
abstraction, and it brought with it considerable confusion about fundamental
issues. In fact, it was really only through the development of rigorous
mathematical analysis in the late 1800s that this confusion finally began to
clear up. And already by the 1880s Georg
Cantor and others had constructed completely discontinuous functions, in
which the idea of treating numbers as continuous variables where only the size
matters was called into question. But until almost the 1970s, and the emergence
of fractal geometry and chaos theory, these functions were largely considered
as mathematical curiosities, of no practical relevance.
Independent of pure mathematics, however, practical applications of numbers
have always had to go beyond the abstract idealization of continuous variables.
For whether one does calculations by hand, by mechanical calculator or by electronic
computer, one always needs an explicit representation for numbers, typically in
terms of a sequence of digits of a certain length. (From the 1930s to 1960s,
some work was done on so-called analog computers which used electrical voltages
to represent continuous variables, but such machines turned out not to be
reliable enough for most practical purposes.) From the earliest days of
electronic computing, however, great efforts were made to try to approximate a
continuum of numbers as closely as possible. And indeed for studying systems
with fairly simple behavior, such approximations can typically be made to work.
But as we shall see later in this chapter, with more complex behavior, it is
almost inevitable that the approximation breaks down, and there is no choice
but to look at the explicit representations of numbers.