The part of modern mathematical analysis in
which the basic purpose is to study functions
for which at least one of the variables
or
varies over an infinite-dimensional space. In its most general form such
a study falls into three parts: 1) the introduction and study
of infinite-dimensional spaces as such; 2) the
study of the simplest functions, namely, when
takes values in an infinite-dimensional space and
in a one-dimensional space (these are called functionals (cf.
Functional),
whence the name
"functional analysis" ); and 3) the study of
general functions of the type indicated — operators (cf.
Operator).
Linear functions
,
i.e. linear operators, have been most completely studied.
Their theory is essentially a generalization of
linear algebra
to the infinite-dimensional case. A combination of
the approaches of classical analysis and algebra is characteristic
for the methods of functional analysis, and this leads to relations
between what are at first glance very distant branches of mathematics.
Functional analysis as an independent mathematical discipline started at the
turn of the
19th century
and was finally established in the
1920's
and
1930's, on the one hand under the influence of the
study of specific classes of linear operators — integral operators and integral
equations connected with them — and on the other hand under
the influence of the purely intrinsic development of modern mathematics with its
desire to generalize and thus to clarify the true nature of
some regular behaviour. Quantum mechanics also had a great influence on
the development of functional analysis, since its basic concepts,
for example energy, turned out to be linear
operators (which physicists at first rather loosely
interpreted as infinite-dimensional matrices) on infinite-dimensional spaces.
1. The concept of a space.
Topological vector spaces (cf.
Topological vector space)
are the most general spaces figuring in
functional analysis. These are vector (linear) spaces
over the field of complex numbers
(or any other field, for example that of the real numbers,
)
which are simultaneously topological spaces and where the linear structure and
the topology are compatible in the sense that the linear
operations are continuous in the topology under consideration. In particular, if
is a metric space, then one has a metric vector space.
A more particular, but very important, situation arises when the concept of the norm
(the length) of a vector
is introduced axiomatically in a vector space
.
A vector space with a norm is called a
normed space.
It is
metrizable.
A metric
is introduced by the formula:
.
A vector space with a norm is called a
Banach space
if it is complete with respect to the metric indicated.
In a large number of problems the situation arises where one can introduce an
inner product
for any two vectors in the vector space
,
such that this product generalizes the usual scalar product in
three-dimensional space. A space provided with an inner product is called a
pre-Hilbert space;
it is a particular case of a normed space. If this space is complete, then it is called a
Hilbert space.
Infinite-dimensional spaces
are studied in functional analysis, that is, spaces in which
there is an infinite set of linearly independent vectors.
From a geometric point of view the simplest spaces are the Hilbert spaces
,
which have properties that mostly resemble those of finite-dimensional
spaces, because it is possible to introduce a concept similar to
that of the angle between two vectors by means
of the inner product. In particular, two vectors
are said to be orthogonal
if
.
The following result is true in
:
Let
be a subspace of
,
then any vector
has a projection
onto
,
that is, a vector
such that
is orthogonal to any vector in
.
Due to this fact, a large number of geometric constructions which
hold for finite-dimensional spaces can be transferred to Hilbert
spaces, where they often acquire an analytic character.
Geometric questions become distinctly more complicated when going from Hilbert spaces
to Banach spaces, and all the more so in general
topological vector spaces, because orthogonal projection is not
meaningful in them. For example, in the space
(
)
the vectors
form a
basis
in the sense that for each vector
"coordinate-wise"
expansion is valid:
The construction of a basis for the space

is already a bit more complicated; at the same time a basis can
be constructed in each of the known examples of Banach spaces. The
problem
arose: Does there exist a basis in every Banach space? This
problem, in spite of the efforts of many mathematicians, did not yield
a solution for more than 40 years and was only solved negatively in
1972
(see
[23]).
In functional analysis an important place is occupied by
"geometric"
themes, devoted to clarifying the properties of various sets
in Banach and other spaces, for example convex sets, compact sets
(the latter means that every sequence of points of such a set

has a subsequence converging to a point in

),
etc. Here, simply formulated questions often have very non-trivial
solutions. These problems are closely connected with the study
of isomorphisms between spaces, and with finding
universal representatives in some classes of spaces.
Specific function spaces have been studied in detail, since the
properties of these spaces usually determine the character of the solution to
a problem when it is obtained by the methods of functional analysis. The so-called
imbedding theorems
for the Sobolev spaces
,
,
and various generalizations of these, can serve as an example.
In connection with the demands of modern mathematical physics a
great number of specific spaces have arisen in which problems are naturally posed and which
thus must be studied. These spaces are usually constructed from initial
spaces using certain constructions. Below the most commonly
used constructions are given in their simplest versions.
1)
The
formation of an orthogonal sum
of Hilbert spaces
,
is a construction of a space
in terms of spaces
,
similar to the formation of
in terms of one-dimensional spaces.
2)
Passing to a quotient space:
Given a degenerate inner product
in a vector space
(that is,
is possible when
);
the Hilbert space
is defined as the completion of
with respect to
after first identifying with 0 all those vectors for which
.
3)
The
formation of a tensor product
is analogous to passing from functions of one variable
to functions of several variables
;
a similar construction is also used for an infinite number of
factors; one also considers symmetric and anti-symmetric tensor products consisting, in
the case of functions, of functions of several variables having these properties.
4)
The
formation of the projective limit
of Banach spaces
,
where
runs over a certain set of indices
.
By definition,
;
the topology in
,
roughly speaking, is given by the convergence
which means that
with respect to the norm in every
.
5)
The
formation of the inductive limit
of the Banach spaces
.
By definition,
;
the topology in
,
roughly speaking, is given by the convergence
which means that all the
lie in a certain
and that
with respect to the norm of this space.
6)
Interpolation
is the formation of
"intermediate"
spaces
from two spaces
and
,
where
;
for example, the construction from
and
of the space
of functions with fractional derivative
.
Procedures 4) and 5) are commonly applied when constructing topological vector
spaces. One distinguishes among such spaces the very
important class of the so-called nuclear spaces (cf.
Nuclear space),
each of which is constructed as a projective limit of Hilbert spaces
with the property that, for each
,
one can find a
such that
and the imbedding operator
is a Hilbert–Schmidt operator (see below, Section
).
An extensive and important branch of functional analysis has been
developed in which one studies topological and normed vector spaces
with a partial order, introduced axiomatically,
having natural properties (partially ordered spaces).
2. Functionals.
In functional analysis the study of continuous functionals
and linear functionals plays an essential role (cf.
Continuous functional;
Linear functional);
their properties are closely connected with the properties of the original space
.
Let
be a Banach space and let
be the set of continuous linear functionals on it;
is a vector space with respect to the usual
operations of adding functions and multiplying them by a number,
it becomes a Banach space if one introduces the norm
The space
is called the
dual
of
(cf. also
Adjoint space).
If
is finite-dimensional, then every linear functional is of the form
where

are the coordinates of the vector

with respect to a certain basis and

are numbers determined by the functional. It turns out that the formula also holds when

is a Hilbert space
(Riesz' theorem). Namely, in this case

,
where

is a certain vector in

.
This formula shows that a Hilbert space essentially coincides with its dual.
For a Banach space the situation is far more complicated: One can construct
,
and these spaces may turn out to be all different. At
the same time, there always exists a canonical imbedding of
into
,
namely, to each
one can associate the functional
,
where
,
.
The spaces
for which
are called
reflexive.
Generally, in the case of a Banach space even the existence of non-trivial
(that is, non-zero) linear functionals is not a simple question. This
question is easily solved affirmatively with the help of the
Hahn–Banach theorem.
The dual space
is, in a certain sense,
"better"
than the original space
.
For example, along with the norm one can introduce another
(weak)
topology in
which, in terms of convergence, is such that
if
for all
.
In this topology the unit ball in
is compact (which is never the case for infinite-dimensional spaces in the topology
generated by a norm). This makes it possible to study in more detail
a number of geometric questions about sets in the dual
space (for example, establishing the structure of convex sets, etc.).
For a number of specific spaces
the dual space
can be found explicitly. However, for the majority of Banach spaces, and especially
for topological vector spaces, the functionals are elements of a new kind
which cannot be expressed simply in terms of classical
analysis. The elements of the dual space are called
generalized functions.
For many questions in functional analysis and its applications an
essential role is played by a triple of spaces
,
where
is the original Hilbert space,
is a topological vector space (in particular, a
Hilbert space with a different inner product) and
is its dual space, the elements of which can be taken as generalized functions. The space
itself is then called a
rigged Hilbert space.
The study of linear functionals on
in many respects promotes a deeper understanding of the nature of the original space
.
On the other hand, in many questions it is necessary to study general functions
,
that is, non-linear functionals in the case of an infinite-dimensional
(cf.
Non-linear functional).
Since the unit ball in such a space
is non-compact, its study often encounters essential difficulties, although,
for example, such concepts as the differentiability of
,
its analyticity, etc. are easily generalized. One can consider a set of functions
having definite properties as a new topological vector space of functions
of
"an infinite number of variables" .
Such functions
also appear in constructing infinite tensor products
of spaces of functions of one variable. The study of such spaces,
of the operators on them, etc., is connected
with the requirements of quantum field theory (see
[22]).
3. Operators.
The main objects of study in functional analysis are operators
,
where
and
are topological vector (for the most part, normed
or Hilbert) spaces and, above all, linear operators (cf.
Linear operator).
When
and
are finite-dimensional, the linearity of an operator implies that it is of the form
where

are the coordinates of the vector

in a certain basis, and

are, analogously, the coordinates of

.
Thus, in the finite-dimensional case to each linear operator

corresponds, in terms of fixed bases in

and

,
a matrix
which gives a simple expression for

.
The study of linear operators in this case is a topic of linear algebra.
The situation becomes much more complicated when
and
become infinite-dimensional (even Hilbert) spaces. First of all, two classes
of operators arise here: continuous operators, for which the function
is continuous (they are also called
bounded,
since the continuity of an operator between Banach
spaces is equivalent to its boundedness), and
unbounded operators,
where there is no such continuity. The operators of the first
type are simpler, but those of the second type are met
more often, e.g. differential operators are of the second type.
The important (especially for quantum mechanics) class
of self-adjoint operators on a Hilbert space
has been studied most of all (cf.
Self-adjoint operator).
Other classes of operators on
,
closely connected with the self-adjoint operators (the
so-called unitary and normal operators, cf.
Unitary operator;
Normal operator),
have also been well studied.
Among the general facts about bounded operators acting in a Banach space
,
one can select the construction of a functional
calculus of analytic functions. Namely, the operator
is called the
resolvent of the operator
,
where
is the identity operator and
.
The points
for which the inverse operator
exists are called the
regular points
of
,
the complement of the set of regular points is called the
spectrum
of
.
The spectrum is never empty and lies in the disc
;
the eigen values of
,
of course, belong to
,
but the spectrum, generally speaking, does not entirely consist of them. If
is an analytic function defined in a neighbourhood of
,
and if
is some closed contour enclosing
and lying in the domain of analyticity of
,
then one puts
and calls

an
operator function.
If

is a polynomial, then

is obtained by simply replacing

in this polynomial by

.
The correspondence

has the important homomorphism properties:
Thus, under definite conditions on

one can define, for example,

,

,

,
etc.
Among the special classes of operators acting on a Banach space
the most important role is played by
the so-called completely-continuous or compact operators (cf.
Completely-continuous operator;
Compact operator).
If
is compact, then the equation
(
is a given vector and
is the desired vector) has been well studied. The analogues of all
the facts which hold for linear equations in finite-dimensional
spaces are also valid for this equation (the so-called
Fredholm theory).
For compact operators
one studies conditions which ensure that the system of eigen vectors of
and their associated vectors are dense in
,
that is, any vector in
can be approximated by linear combinations of eigen vectors
and associated vectors; etc. At the same time there are, even
for compact operators, problems which naturally arise but which are very
difficult to solve (for example, the theorem that each such operator has an
invariant subspace
different from 0 and the whole of
,
that is, a subspace
such that
;
in the finite-dimensional case the existence of
follows trivially from the fact that the spectrum is non-empty).
The spectrum of a compact operator
is discrete and may accumulate at 0 only. One
distinguishes important subclasses of the class of compact operators according to the
rate at which the eigen values approach 0.
Thus, very often one encounters Hilbert–Schmidt operators. If
is an operator on
,
then it is a
Hilbert–Schmidt operator
if and only if it is an integral operator with kernel
that is square-summable in both variables. Compact Volterra operators have also
been studied in detail. A study has also been made of
spectral operators for which there is an analogue for the resolution of the identity
;
etc. (see
[8]).
4. Banach algebras and representation theory.
In the early stages of the development of functional analysis the problems studied
were those that could be stated and solved in terms
of linear operations on elements of the space alone.
One of the powerful methods in mathematics is to represent abstract mathematical
objects by simpler (or more concrete) objects. For example, the
spectral theorem can be interpretated as representing a self-adjoint operator
by the operator which multiplies the measurable functions of a
certain class by the independent variable. If one
considers multiplication by Borel functions, one obtains a representation of
a commutative normed algebra of operators on a Hilbert
space. A more general example of this representation gives one of
the main theorems in the theory of commutative Banach algebras.
Let
be a commutative Banach algebra, for simplicity with an identity, that
is, a Banach space in which there is a commutative and associative multiplication
of elements
,
and let the norm satisfy
.
Further, let
be the set of all maximal ideals. Then a compact topology can be introduced on
so that every element
represents a complex-valued continuous function
,
,
and, moreover, the sum
and the product
of functions correspond to the sum
and the product
,
respectively (see
[7]).
In the non-commutative case representation theory has been studied
especially for the so-called algebras with an involution (see
Banach algebra).
A considerably richer representation theory has
been developed for topological groups (cf.
Representation of a topological group).
5. Non-linear functional analysis.
At the same time as the concept of a space was being
developed and deepened, the concept of a function was being developed and
generalized. In the end it became necessary to consider mappings (not
necessarily linear) from one space into another. One of the central
problems in non-linear functional analysis is the study of
such mappings. As in the linear case, a
mapping
of a space into (the real or complex)
numbers is called a functional. For non-linear mappings (in
particular, non-linear functionals) there are various methods to define
the concepts of a differential, a directional derivative,
etc., analogous to the corresponding concepts in classical mathematical analysis (see
[11],
[13],
[15]
and
Differentiation of a mapping).
An important problem in non-linear functional analysis is the problem
of determining the fixed points of a mapping (see
[11],
[13],
[15]
and
Fixed point).
When studying the eigen vectors of a non-linear mapping containing a
parameter there arises a phenomenon that is crucial in non-linear analysis
— so-called
bifurcation
(see
[15]).
In the investigation of fixed points and bifurcation points,
topological methods are extensively used: the
generalization to infinite-dimensional spaces of the
Brouwer–Bohl theorem
on the existence of fixed points for mappings
of finite-dimensional spaces, the index of a mapping (cf.
Index formulas),
etc.
6. The application of functional analysis in mathematical and theoretical physics.
Below, those branches of mathematical physics are given in
which some part of functional analysis is applied.
1)
The
spectral theory of operators
is applied in all theories of quantum physics: in quantum
-body
theory, in
quantum field theory
and in quantum statistical mechanics. In addition, spectral theory is applied
in the study of models of dynamical systems in classical mechanics,
in the study of linearized equations in hydrodynamics, in the study of Gibbs fields, etc.
2)
Scattering theory
is applied in quantum physics. It should be noted that
the modern mathematical theory of scattering arose first of all
in physics. In recent years scattering theory (the inverse problem)
has often been applied in integrating non-linear model equations in mathematical physics.
3)
Banach algebras
are applied in quantum field theory, especially in
so-called axiomatic field theory, and in studying various integrable models of a quantum
field and statistical mechanics. Von Neumann algebras are also used in these questions.
4)
Perturbation theory,
mainly the
perturbation theory for linear operators,
is applied in almost-all domains of mathematical physics: in
quantum field theory and in statistical mechanics, both
equilibrium and non-equilibrium (especially in investigating the so-called
kinetic equations, the compound spectra of multi-particle systems, etc.).
5)
Functional integration and measures in function spaces
are applied in
constructive quantum field theory
and in quantum statistical mechanics.
6)
Various integral representations
(Riesz' theorem, the Krein–Mil'man theorem, Choquet's
theorem, and others) are applied in axiomatic
quantum field theory and in statistical mechanics.
7)
Vector spaces
(mainly Hilbert spaces) are applied in quantum theory and in statistical physics.
8)
Generalized functions
are applied everywhere in mathematical physics as an important analytic tool (see also
Generalized function).