Weak convergence is a basic tool of modern nonlinear analysis because it
enjoys the same compactness properties that finite dimensional spaces
do: basically, bounded sequences are weak relatively compact sets.
Nonetheless, weak conver- gence does not behave as one would desire with
respect to nonlinear functionals and operations. This difficulty is what
makes nonlinear analysis much harder than would normally be expected.
Parametrized measures is a device to under- stand weak convergence and
its behavior with respect to nonlinear functionals. Under suitable
hypotheses, it yields a way of representing through integrals weak
limits of compositions with nonlinear functions. It is particularly
helpful in comprehending oscillatory phenomena and in keeping track of
how oscilla- tions change when a nonlinear functional is applied. Weak
convergence also plays a fundamental role in the modern treatment of the
calculus of variations, again because uniform bounds in norm for se-
quences allow to have weak convergent subsequences. In order to achieve
the existence of minimizers for a particular functional, the property of
weak lower semicontinuity should be established first. This is the
crucial and most delicate step in the so-called direct method of the
calculus of variations. A fairly large amount of work has been devoted
to determine under what assumptions we can have this lower
semicontinuity with respect to weak topologies for nonlin- ear
functionals in the form of integrals. The conclusion of all this work is
that some type of convexity, understood in a broader sense, is usually
involved.