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mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, a dual system, dual pair, or duality over a
field Field may refer to: Expanses of open ground * Field (agriculture), an area of land used for agricultural purposes * Airfield, an aerodrome that lacks the infrastructure of an airport * Battlefield * Lawn, an area of mowed grass * Meadow, a grass ...
\mathbb is a triple (X, Y, b) consisting of two
vector space In mathematics and physics, a vector space (also called a linear space) is a set whose elements, often called ''vectors'', may be added together and multiplied ("scaled") by numbers called '' scalars''. Scalars are often real numbers, but can ...
s X and Y over \mathbb and a non-
degenerate Degeneracy, degenerate, or degeneration may refer to: Arts and entertainment * Degenerate (album), ''Degenerate'' (album), a 2010 album by the British band Trigger the Bloodshed * Degenerate art, a term adopted in the 1920s by the Nazi Party i ...
bilinear map In mathematics, a bilinear map is a function combining elements of two vector spaces to yield an element of a third vector space, and is linear in each of its arguments. Matrix multiplication is an example. Definition Vector spaces Let V, W ...
b : X \times Y \to \mathbb. Duality theory, the study of dual systems, is part of
functional analysis Functional analysis is a branch of mathematical analysis, the core of which is formed by the study of vector spaces endowed with some kind of limit-related structure (e.g. Inner product space#Definition, inner product, Norm (mathematics)#Defini ...
. According to
Helmut H. Schaefer Helmut Heinrich Schaefer (February 14, 1925 in Großenhain, Weimar Republic – December 16, 2005 in Tübingen, Germany) was a German mathematician, who worked primarily in functional analysis. His two best known scientific monographs are titl ...
, "the study of a locally convex space in terms of its dual is the central part of the modern theory of
topological vector space In mathematics, a topological vector space (also called a linear topological space and commonly abbreviated TVS or t.v.s.) is one of the basic structures investigated in functional analysis. A topological vector space is a vector space that is als ...
s, for it provides the deepest and most beautiful results of the subject."


Definition, notation, and conventions

;Pairings A or pair over a field \mathbb is a triple (X, Y, b), which may also be denoted by b(X, Y), consisting of two vector spaces X and Y over \mathbb (which this article assumes is either the
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every real ...
s or the
complex number In mathematics, a complex number is an element of a number system that extends the real numbers with a specific element denoted , called the imaginary unit and satisfying the equation i^= -1; every complex number can be expressed in the form ...
s \Complex) and a bilinear map b : X \times Y \to \mathbb, which is called the bilinear map associated with the pairing or simply the pairing's map/bilinear form. For every x \in X, define \begin b(x, \,\cdot\,) : \,& Y && \to &&\, \mathbb \\ & y && \mapsto &&\, b(x, y) \end and for every y \in Y, define \begin b(\,\cdot\,, y) : \,& X && \to &&\, \mathbb \\ & x && \mapsto &&\, b(x, y). \end Every b(x, \,\cdot\,) is a linear functional on Y and every b(\,\cdot\,, y) is a linear functional on X. Let b(X, \,\cdot\,) := \ \qquad \text \qquad b(\,\cdot\,, Y) := \ where each of these sets forms a vector space of linear functionals. It is common practice to write \langle x, y \rangle instead of b(x, y), in which case the pair is often denoted by \left\langle X, Y \right\rangle rather than (X, Y, \langle \cdot, \cdot \rangle).
However, this article will reserve use of \langle \cdot, \cdot \rangle for the canonical evaluation map (defined below) so as to avoid confusion for readers not familiar with this subject. ;Dual pairings A pairing (X, Y, b) is called a , a , or a over \mathbb if the bilinear form b is non-degenerate, which means that it satisfies the following two separation axioms: # Y separates/distinguishes points of X: if x \in X is such that b(x, \,\cdot\,) = 0 then x = 0; or equivalently, for all non-zero x \in X, the map b(x, \,\cdot\,) : Y \to \mathbb is not identically 0 (i.e. there exists a y \in Y such that b(x, y) \neq 0); # X separates/distinguishes points of Y: if y \in Y is such that b(\,\cdot\,, y) = 0 then y = 0; or equivalently, for all non-zero y \in Y, the map b(\,\cdot\,, y) : X \to \mathbb is not identically 0 (i.e. there exists an x \in X such that b(x, y) \neq 0). In this case say that b is non-degenerate, say that b places X and Y in duality (or in separated duality), and b is called the duality pairing of the (X, Y, b). ;Total subsets A subset S of Y is called if for every x \in X, b(x, s) = 0 \quad \text s \in S implies x = 0. A total subset of X is defined analogously (see footnote).A subset S of X is total if for all y \in Y, b(s, y) = 0 \quad \text s \in S implies y = 0. ;Orthogonality The vectors x and y are called , written x \perp y, if b(x, y) = 0. Two subsets R \subseteq X and S \subseteq Y are orthogonal, written R \perp S, if b(R, S) = \; that is, if b(r, s) = 0 for all r \in R and s \in S. The definition of a subset being orthogonal to a vector is defined analogously. The
orthogonal complement In the mathematical fields of linear algebra and functional analysis, the orthogonal complement of a subspace ''W'' of a vector space ''V'' equipped with a bilinear form ''B'' is the set ''W''⊥ of all vectors in ''V'' that are orthogonal to every ...
or annihilator of a subset R \subseteq X is R^ := \ := \.


Polar sets

Throughout, (X, Y, b) will be a pairing over \mathbb. The absolute polar or polar of a subset A of X is the set: A^ := \left\. Dually, the absolute polar or polar of a subset B of Y is denoted by B^ and defined by B^ := \left\ In this case, the absolute polar of a subset B of Y is also called the absolute prepolar or prepolar of B and may be denoted by ^ B. The polar B^ is necessarily a convex set containing 0 \in Y where if B is balanced then so is B^ and if B is a vector subspace of X then so too is B^ a vector subspace of Y. If A \subseteq X then the bipolar of A, denoted by A^, is the set ^\left(A^\right). Similarly, if B \subseteq Y then the bipolar of B is B^ := \left(^B\right)^. If A is a vector subspace of X, then A^ = A^ and this is also equal to the real polar of A.


Dual definitions and results

Given a pairing (X, Y, b), define a new pairing (Y, X, d) where d(y, x) := b(x, y) for all x \in X \quad \text y \in Y. There is a repeating theme in duality theory, which is that any definition for a pairing (X, Y, b) has a corresponding dual definition for the pairing (Y, X, d). :: Given any definition for a pairing (X, Y, b), one obtains a by applying it to the pairing (Y, X, d). This conventions also apply to theorems. :: Adhering to common practice, unless clarity is needed, whenever a definition (or result) for a pairing (X, Y, b) is given then this article will omit mention of the corresponding dual definition (or result) but nevertheless use it. For instance, if "X distinguishes points of Y" (resp, "S is a total subset of Y") is defined as above, then this convention immediately produces the dual definition of "Y distinguishes points of X" (resp, "S is a total subset of X"). This following notation is almost ubiquitous and it allows us to avoid having to assign a symbol to d. :: If a definition and its notation for a pairing (X, Y, b) depends on the order of X and Y (e.g. the definition of the Mackey topology \tau(X, Y, b) on X) then by switching the order of X and Y, then it is meant that definition applied to (Y, X, d) (e.g. \tau(Y, X, b) actually denotes the topology \tau(Y, X, d)). For instance, once the weak topology on X is defined, which is denoted by \sigma(X, Y, b), then this definition will automatically be applied to the pairing (Y, X, d) so as to obtain the definition of the weak topology on Y, where this topology will be denoted by \sigma(Y, X, b) rather than \sigma(Y, X, d). ;Identification of (X, Y) with (Y, X) Although it is technically incorrect and an abuse of notation, this article will also adhere to the following nearly ubiquitous convention of treating a pairing (X, Y, b) interchangeably with (Y, X, d) and also of denoting (Y, X, d) by (Y, X, b).


Examples


Restriction of a pairing

Suppose that (X, Y, b) is a pairing, M is a vector subspace of X, and N is a vector subspace of Y. Then the restriction of (X, Y, b) to M \times N is the pairing \left(M, N, b\big\vert_\right). If (X, Y, b) is a duality then it's possible for a restrictions to fail to be a duality (e.g. if Y \neq \ and N = \). This article will use the common practice of denoting the restriction \left(M, N, b\big\vert_\right) by (M, N, b).


Canonical duality on a vector space

Suppose that X is a vector space and let X^ denote the
algebraic dual space In mathematics, any vector space ''V'' has a corresponding dual vector space (or just dual space for short) consisting of all linear forms on ''V'', together with the vector space structure of pointwise addition and scalar multiplication by const ...
of X (that is, the space of all linear functionals on X). There is a canonical duality \left(X, X^, c\right) where c\left(x, x^\right) = \left\langle x, x^ \right\rangle = x^(x), which is called the evaluation map or the natural or canonical bilinear functional on X \times X^. Note in particular that for any x^ \in X^, c\left(\,\cdot\,, x^\right) is just another way of denoting x^; i.e. c\left(\,\cdot\,, x^\right) = x^(\,\cdot\,) = x^. If N is a vector subspace of X^ then the restriction of \left(X, X^, c\right) to X \times N is called the canonical pairing where if this pairing is a duality then it is instead called the canonical duality. Clearly, X always distinguishes points of N so the canonical pairing is a dual system if and only if N separates points of X. The following notation is now nearly ubiquitous in duality theory. The evaluation map will be denoted by \left\langle x, x^ \right\rangle = x^(x) (rather than by c) and \langle X, N \rangle will be written rather than (X, N, c). :Assumption: As is common practice, if X is a vector space and N is a vector space of linear functionals on X, then unless stated otherwise, it will be assumed that they are associated with the canonical pairing \langle X, N \rangle. If N is a vector subspace of X^ then X distinguishes points of N (or equivalently, (X, N, c) is a duality) if and only if N distinguishes points of X, or equivalently if N is total (that is, n(x) = 0 for all n \in N implies x = 0).


Canonical duality on a topological vector space

Suppose X is a
topological vector space In mathematics, a topological vector space (also called a linear topological space and commonly abbreviated TVS or t.v.s.) is one of the basic structures investigated in functional analysis. A topological vector space is a vector space that is als ...
(TVS) with
continuous dual space In mathematics, any vector space ''V'' has a corresponding dual vector space (or just dual space for short) consisting of all linear forms on ''V'', together with the vector space structure of pointwise addition and scalar multiplication by cons ...
X^. Then the restriction of the canonical duality \left(X, X^, c\right) to X × X^ defines a pairing \left(X, X^, c\big\vert_\right) for which X separates points of X^. If X^ separates points of X (which is true if, for instance, X is a Hausdorff locally convex space) then this pairing forms a duality. :Assumption: As is commonly done, whenever X is a TVS then, unless indicated otherwise, it will be assumed without comment that it's associated with the canonical pairing \left\langle X, X^ \right\rangle. ;Polars and duals of TVSs The following result shows that the
continuous linear functional In functional analysis and related areas of mathematics, a continuous linear operator or continuous linear mapping is a continuous linear transformation between topological vector spaces. An operator between two normed spaces is a bounded linear ...
s on a TVS are exactly those linear functionals that are bounded on a neighborhood of the origin.


Inner product spaces and complex conjugate spaces

A
pre-Hilbert space In mathematics, an inner product space (or, rarely, a Hausdorff pre-Hilbert space) is a real vector space or a complex vector space with an operation called an inner product. The inner product of two vectors in the space is a scalar, often d ...
(H, \langle \cdot, \cdot \rangle) is a dual pairing if and only if H is vector space over \R or H has dimension 0. Here it is assumed that the
sesquilinear form In mathematics, a sesquilinear form is a generalization of a bilinear form that, in turn, is a generalization of the concept of the dot product of Euclidean space. A bilinear form is linear in each of its arguments, but a sesquilinear form allows o ...
\langle \cdot, \cdot \rangle is
conjugate homogeneous In mathematics, a homogeneous function is a function of several variables such that, if all its arguments are multiplied by a scalar, then its value is multiplied by some power of this scalar, called the degree of homogeneity, or simply the '' ...
in its second coordinate and homogeneous in its first coordinate. Suppose that (H, \langle \cdot, \cdot \rangle) is a complex pre-Hilbert space with scalar multiplication denoted as usual by juxtaposition or by a dot \cdot. Define the map \,\cdot\, \perp \,\cdot\, : \Complex \times H \to H \quad \text \quad c \perp x := \overline x, where the right hand side uses the scalar multiplication of H. Let \overline denote the
complex conjugate vector space In mathematics, the complex conjugate of a complex vector space V\, is a complex vector space \overline V, which has the same elements and additive group structure as V, but whose scalar multiplication involves conjugation of the scalars. In other ...
of H, where \overline denotes the additive group of (H, +) (so vector addition in \overline is identical to vector addition in H) but with scalar multiplication in \overline being the map \,\cdot\, \perp \,\cdot\, (instead of the scalar multiplication that H is endowed with). The map b : H \times \overline \to \Complex defined by b(x, y) := \langle x, y \rangle is linear in both coordinatesThat b is linear in its first coordinate is obvious. Suppose c is a scalar. Then b(x, c \perp y) = b\left(x, \overline y\right) = \langle x, \overline y \rangle = c \langle x, y \rangle = c b(x, y), which shows that b is linear in its second coordinate. and so \left(H, \overline, \langle \cdot, \cdot \rangle\right) forms a dual pairing.


Other examples


Weak topology

Suppose that (X, Y, b) is a pairing of vector spaces over \mathbb. If S \subseteq Y then the weak topology on X induced by S (and b) is the weakest TVS topology on X, denoted by \sigma(X, S, b) or simply \sigma(X, S), making all maps b(\,\cdot\,, y) : X \to \mathbb continuous as y ranges over S. If S is not clear from context then it should be assumed to be all of Y, in which case it is called the weak topology on X (induced by Y). The notation X_, X_, or (if no confusion could arise) simply X_ is used to denote X endowed with the weak topology \sigma(X, S, b). Importantly, the weak topology depends on the function b, the usual topology on \Complex, and X's vector space structure but on the algebraic structures of Y. Similarly, if R \subseteq X then the dual definition of the weak topology on Y induced by R (and b), which is denoted by \sigma(Y, R, b) or simply \sigma(Y, R) (see footnote for details).The weak topology on Y is the weakest TVS topology on Y making all maps b(x, \,\cdot\,) : Y \to \mathbb continuous, as x ranges over R. The dual notation of (Y, \sigma(Y, R, b)), (Y, \sigma(Y, R)), or simply (Y, \sigma) may also be used to denote Y endowed with the weak topology \sigma(Y, R, b). If R is not clear from context then it should be assumed to be all of X, in which case it is simply called the weak topology on Y (induced by X). :: If "\sigma(X, Y, b)" is attached to a topological definition (e.g. \sigma(X, Y, b)-converges, \sigma(X, Y, b)-bounded, \operatorname_(S), etc.) then it means that definition when the first space (i.e. X) carries the \sigma(X, Y, b) topology. Mention of b or even X and Y may be omitted if no confusion will arise. So for instance, if a sequence \left(a_i\right)_^ in Y "\sigma-converges" or "weakly converges" then this means that it converges in (Y, \sigma(Y, X, b)) whereas if it were a sequence in X then this would mean that it converges in (X, \sigma(X, Y, b))). The topology \sigma(X, Y, b) is
locally convex In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological ve ...
since it is determined by the family of seminorms p_y : X \to \R defined by p_y(x) := , b(x, y), , as y ranges over Y. If x \in X and \left(x_i\right)_ is a
net Net or net may refer to: Mathematics and physics * Net (mathematics), a filter-like topological generalization of a sequence * Net, a linear system of divisors of dimension 2 * Net (polyhedron), an arrangement of polygons that can be folded up ...
in X, then \left(x_i\right)_ \sigma(X, Y, b)-converges to x if \left(x_i\right)_ converges to X in (X, \sigma(X, Y, b)). A net \left(x_i\right)_ \sigma(X, Y, b)-converges to x if and only if for all y \in Y, b\left(x_i, y\right) converges to b(x, y). If \left(x_i\right)_^ is a sequence of
orthonormal In linear algebra, two vectors in an inner product space are orthonormal if they are orthogonal (or perpendicular along a line) unit vectors. A set of vectors form an orthonormal set if all vectors in the set are mutually orthogonal and all of un ...
vectors in Hilbert space, then \left(x_i\right)_^ converges weakly to 0 but does not norm-converge to 0 (or any other vector). If (X, Y, b) is a pairing and N is a proper vector subspace of Y such that (X, N, b) is a dual pair, then \sigma(X, N, b) is strictly coarser than \sigma(X, Y, b). ;Bounded subsets A subset S of X is \sigma(X, Y, b)-bounded if and only if \sup_ , b(S, y), < \infty \quad \text y \in Y, where , b(S, y), := \. ;Hausdorffness If (X, Y, b) is a pairing then the following are equivalent: # X distinguishes points of Y; # The map y \mapsto b(\,\cdot\,, y) defines an
injection Injection or injected may refer to: Science and technology * Injective function, a mathematical function mapping distinct arguments to distinct values * Injection (medicine), insertion of liquid into the body with a syringe * Injection, in broadca ...
from Y into the algebraic dual space of X; # \sigma(Y, X, b) is Hausdorff.


Weak representation theorem

The following theorem is of fundamental importance to duality theory because it completely characterizes the continuous dual space of (X, \sigma(X, Y, b)). Consequently, the
continuous dual space In mathematics, any vector space ''V'' has a corresponding dual vector space (or just dual space for short) consisting of all linear forms on ''V'', together with the vector space structure of pointwise addition and scalar multiplication by cons ...
of (X, \sigma(X, Y, b)) is (X, \sigma(X, Y, b))^ = b(\,\cdot\,, Y) := \left\. With respect to the canonical pairing, if X is a TVS whose continuous dual space X^ separates points on X (i.e. such that \left(X, \sigma\left(X, X^\right)\right) is Hausdorff, which implies that X is also necessarily Hausdorff) then the continuous dual space of \left(X^, \sigma\left(X^, X\right)\right) is equal to the set of all "evaluation at a point x" maps as x ranges over X (i.e. the map that send x^ \in X^ to x^(x)). This is commonly written as \left(X^, \sigma\left(X^, X\right)\right)^ = X \qquad \text \qquad \left(X^_\right)^ = X. This very important fact is why results for polar topologies on continuous dual spaces, such as the
strong dual topology In functional analysis and related areas of mathematics, the strong dual space of a topological vector space (TVS) X is the continuous dual space X^ of X equipped with the strong (dual) topology or the topology of uniform convergence on bounded sub ...
\beta\left(X^, X\right) on X^ for example, can also often be applied to the original TVS X; for instance, X being identified with \left(X^_\right)^ means that the topology \beta\left(\left(X^_\right)^, X^_\right) on \left(X^_\right)^ can instead be thought of as a topology on X. Moreover, if X^ is endowed with a topology that is finer than \sigma\left(X^, X\right) then the continuous dual space of X^ will necessarily contain \left(X^_\right)^ as a subset. So for instance, when X^ is endowed with the strong dual topology (and so is denoted by X^_) then \left(X^_\right)^ ~\supseteq~ \left(X^_\right)^ ~=~ X which (among other things) allows for X to be endowed with the subspace topology induced on it by, say, the strong dual topology \beta\left(\left(X^_\right)^, X^_\right) (this topology is also called the strong
bidual In functional analysis and related areas of mathematics, the strong dual space of a topological vector space (TVS) X is the continuous dual space X^ of X equipped with the strong (dual) topology or the topology of uniform convergence on bounded sub ...
topology and it appears in the theory of
reflexive space In the area of mathematics known as functional analysis, a reflexive space is a locally convex topological vector space (TVS) for which the canonical evaluation map from X into its bidual (which is the strong dual of the strong dual of X) is an iso ...
s: the Hausdorff locally convex TVS X is said to be if \left(X^_\right)^ = X and it will be called if in addition the strong bidual topology \beta\left(\left(X^_\right)^, X^_\right) on X is equal to X's original/starting topology).


Orthogonals, quotients, and subspaces

If (X, Y, b) is a pairing then for any subset S of X: If X is a normed space then under the canonical duality, S^ is norm closed in X^ and S^ is norm closed in X. ;Subspaces Suppose that M is a vector subspace of X and let (M, Y, b) denote the restriction of (X, Y, b) to M \times Y. The weak topology \sigma(M, Y, b) on M is identical to the
subspace topology In topology and related areas of mathematics, a subspace of a topological space ''X'' is a subset ''S'' of ''X'' which is equipped with a topology induced from that of ''X'' called the subspace topology (or the relative topology, or the induced to ...
that M inherits from (X, \sigma(X, Y, b)). Also, \left(M, Y / M^, b\big\vert_M\right) is a paired space (where Y / M^ means Y / \left(M^\right)) where b\big\vert_M : M \times Y / M^ \to \mathbb is defined by \left(m, y + M^\right) \mapsto b(m, y). The topology \sigma\left(M, Y / M^, b\big\vert_M\right) is equal to the
subspace topology In topology and related areas of mathematics, a subspace of a topological space ''X'' is a subset ''S'' of ''X'' which is equipped with a topology induced from that of ''X'' called the subspace topology (or the relative topology, or the induced to ...
that M inherits from (X, \sigma(X, Y, b)). Furthermore, if (X, \sigma(X, Y, b)) is a dual system then so is \left(M, Y / M^, b\big\vert_M\right). ;Quotients Suppose that M is a vector subspace of X. Then \left(X / M, M^, b / M\right)is a paired space where b / M : X / M \times M^ \to \mathbb is defined by (x + M, y) \mapsto b(x, y). The topology \sigma\left(X / M, M^\right) is identical to the usual
quotient topology In topology and related areas of mathematics, the quotient space of a topological space under a given equivalence relation is a new topological space constructed by endowing the quotient set of the original topological space with the quotient t ...
induced by (X, \sigma(X, Y, b)) on X / M.


Polars and the weak topology

If X is a locally convex space and if H is a subset of the continuous dual space X^, then H is \sigma\left(X^, X\right)-bounded if and only if H \subseteq B^ for some
barrel A barrel or cask is a hollow cylindrical container with a bulging center, longer than it is wide. They are traditionally made of wooden staves and bound by wooden or metal hoops. The word vat is often used for large containers for liquids, ...
B in X. The following results are important for defining polar topologies. If (X, Y, b) is a pairing and A \subseteq X, then:
  1. The polar A^ of A is a closed subset of (Y, \sigma(Y, X, b)).
  2. The polars of the following sets are identical: (a) A; (b) the convex hull of A; (c) the
    balanced hull In linear algebra and related areas of mathematics a balanced set, circled set or disk in a vector space (over a field \mathbb with an absolute value function , \cdot , ) is a set S such that a S \subseteq S for all scalars a satisfying , a, ...
    of A; (d) the \sigma(X, Y, b)-closure of A; (e) the \sigma(X, Y, b)-closure of the
    convex balanced hull In mathematics, a subset ''C'' of a Real number, real or Complex number, complex vector space is said to be absolutely convex or disked if it is Convex set, convex and Balanced set, balanced (some people use the term "circled" instead of "balanced") ...
    of A.
  3. The
    bipolar theorem In mathematics, the bipolar theorem is a theorem in functional analysis that characterizes the bipolar (that is, the polar of the polar) of a set. In convex analysis, the bipolar theorem refers to a necessary and sufficient conditions for a cone t ...
    : The bipolar of A, denoted by A^, is equal to the \sigma(X, Y, b)-closure of the convex balanced hull of A. * The
    bipolar theorem In mathematics, the bipolar theorem is a theorem in functional analysis that characterizes the bipolar (that is, the polar of the polar) of a set. In convex analysis, the bipolar theorem refers to a necessary and sufficient conditions for a cone t ...
    in particular "is an indispensable tool in working with dualities."
  4. A is \sigma(X, Y, b)-bounded if and only if A^ is absorbing in Y.
  5. If in addition Y distinguishes points of X then A is \sigma(X, Y, b)-
    bounded Boundedness or bounded may refer to: Economics * Bounded rationality, the idea that human rationality in decision-making is bounded by the available information, the cognitive limitations, and the time available to make the decision * Bounded e ...
    if and only if it is \sigma(X, Y, b)-
    totally bounded In topology and related branches of mathematics, total-boundedness is a generalization of compactness for circumstances in which a set is not necessarily closed. A totally bounded set can be covered by finitely many subsets of every fixed “size ...
    .
If (X, Y, b) is a pairing and \tau is a locally convex topology on X that is consistent with duality, then a subset B of X is a
barrel A barrel or cask is a hollow cylindrical container with a bulging center, longer than it is wide. They are traditionally made of wooden staves and bound by wooden or metal hoops. The word vat is often used for large containers for liquids, ...
in (X, \tau) if and only if B is the
polar Polar may refer to: Geography Polar may refer to: * Geographical pole, either of two fixed points on the surface of a rotating body or planet, at 90 degrees from the equator, based on the axis around which a body rotates * Polar climate, the c ...
of some \sigma(Y, X, b)-bounded subset of Y.


Transposes


Transpose of a linear map with respect to pairings

Let (X, Y, b) and (W, Z, c) be pairings over \mathbb and let F : X \to W be a linear map. For all z \in Z, let c(F(\,\cdot\,), z) : X \to \mathbb be the map defined by x \mapsto c(F(\,\cdot\,), z). It is said that Fs transpose or adjoint is well-defined if the following conditions are satisfies: # X distinguishes points of Y (or equivalently, the map y \mapsto b(\,\cdot\,, y) from Y into the algebraic dual X^ is
injective In mathematics, an injective function (also known as injection, or one-to-one function) is a function that maps distinct elements of its domain to distinct elements; that is, implies . (Equivalently, implies in the equivalent contrapositiv ...
), and # c(F(\,\cdot\,), Z) \subseteq b(\,\cdot\,, Y), where c(F(\,\cdot\,), Z) := \. In this case, for any z \in Z there exists (by condition 2) a unique (by condition 1) y \in Y such that c(F(\,\cdot\,), z) = b(\,\cdot\,, y)), where this element of Y will be denoted by ^t F(z). This defines a linear map ^t F : Z \to Y called the transpose or adjoint of F with respect to (X, Y, b) and (W, Z, c) (this should not to be confused with the
Hermitian adjoint In mathematics, specifically in operator theory, each linear operator A on a Euclidean vector space defines a Hermitian adjoint (or adjoint) operator A^* on that space according to the rule :\langle Ax,y \rangle = \langle x,A^*y \rangle, where ...
). It is easy to see that the two conditions mentioned above (i.e. for "the transpose is well-defined") are also necessary for ^t F to be well-defined. For every z \in Z, the defining condition for ^t F(z) is c(F(\,\cdot\,), z) = b\left(\,\cdot\,, ^t F(z)\right), that is, c(F(x), z) = b\left(x, ^t F(z)\right) for all x \in X. By the conventions mentioned at the beginning of this article, this also defines the transpose of linear maps of the form Z \to Y,If G : Z \to Y is a linear map then G's transpose, ^t G : X \to W, is well-defined if and only if Z distinguishes points of W and b(X, G(\,\cdot\,)) \subseteq c(W, \,\cdot\,). In this case, for each x \in X, the defining condition for ^t G(x) is: c(x, G(\,\cdot\,)) = c\left(^t G(x), \,\cdot\,\right). X \to Z,If H : X \to Z is a linear map then H's transpose, ^t H : W \to Y, is well-defined if and only if X distinguishes points of Y and c(W, H(\,\cdot\,)) \subseteq b(\,\cdot\,, Y). In this case, for each w \in W, the defining condition for ^t H(w) is: c(w, H(\,\cdot\,)) = b\left(\,\cdot\,, ^t H(w)\right). W \to Y,If H : W \to Y is a linear map then H's transpose, ^t H : X \to Q, is well-defined if and only if W distinguishes points of Z and b(X, H(\,\cdot\,)) \subseteq c(\,\cdot\,, Z). In this case, for each x \in X, the defining condition for ^t H(x) is: c(x, H(\,\cdot\,)) = b\left(\,\cdot\,, ^t H(x)\right). Y \to W,If H : Y \to W is a linear map then H's transpose, ^t H : Z \to X, is well-defined if and only if Y distinguishes points of X and c(H(\,\cdot\,), Z) \subseteq b(X, \,\cdot\,). In this case, for each z \in Z, the defining condition for ^t H(z) is: c(H(\,\cdot\,), z) = b\left(^t H(z), \,\cdot\,\right). etc. (see footnote for details). ;Properties of the transpose Throughout, (X, Y, b) and (W, Z, c) be pairings over \mathbb and F : X \to W will be a linear map whose transpose ^t F : Z \to Y is well-defined. * ^t F : Z \to Y is
injective In mathematics, an injective function (also known as injection, or one-to-one function) is a function that maps distinct elements of its domain to distinct elements; that is, implies . (Equivalently, implies in the equivalent contrapositiv ...
(i.e. \operatorname ^t F = \) if and only if the range of F is dense in \left(W, \sigma\left(W, Z, c\right)\right). * If in addition to ^t F being well-defined, the transpose of ^t F is also well-defined then ^ F = F. * Suppose (U, V, a) is a pairing over \mathbb and E : U \to X is a linear map whose transpose ^t E : Y \to V is well-defined. Then the transpose of F \circ E : U \to W, which is ^t (F \circ E) : Z \to V, is well-defined and ^t (F \circ E) = ^t E \circ ^t F. * If F : X \to W is a vector space isomorphism then ^t F : Z \to Y is bijective, the transpose of F^ : W \to X, which is ^t \left(F^\right) : Y \to Z, is well-defined, and ^t \left(F^\right) = \left(^t F\right)^ * Let S \subseteq X and let S^ denotes the absolute polar of A, then: *# (S) = \left(^t F\right)^\left(S^\right); *# if F(S) \subseteq T for some T \subseteq W, then ^t F\left(T^\right) \subseteq S^; *# if T \subseteq W is such that ^t F\left(T^\right) \subseteq S^, then F(S) \subseteq T^; *# if T \subseteq W and S \subseteq X are weakly closed disks then ^t F\left(T^\right) \subseteq S^ if and only if F(S) \subseteq T; *# \operatorname ^t F =
F(X) F, or f, is the sixth letter in the Latin alphabet, used in the modern English alphabet, the alphabets of other western European languages and others worldwide. Its name in English is ''ef'' (pronounced ), and the plural is ''efs''. Hist ...
. : These results hold when the real polar is used in place of the absolute polar. If X and Y are normed spaces under their canonical dualities and if F : X \to Y is a continuous linear map, then \, F\, = \left\, ^t F\right\, .


Weak continuity

A linear map F : X \to W is weakly continuous (with respect to (X, Y, b) and (W, Z, c)) if F : (X, \sigma(X, Y, b)) \to (W, (W, Z, c)) is continuous. The following result shows that the existence of the transpose map is intimately tied to the weak topology.


Weak topology and the canonical duality

Suppose that X is a vector space and that X^ is its the algebraic dual. Then every \sigma\left(X, X^\right)-bounded subset of X is contained in a finite dimensional vector subspace and every vector subspace of X is \sigma\left(X, X^\right)-closed.


Weak completeness

If (X, \sigma(X, Y, b)) is a
complete topological vector space In functional analysis and related areas of mathematics, a complete topological vector space is a topological vector space (TVS) with the property that whenever points get progressively closer to each other, then there exists some point x towards ...
say that X is \sigma(X, Y, b)-complete or (if no ambiguity can arise) weakly-complete. There exist
Banach space In mathematics, more specifically in functional analysis, a Banach space (pronounced ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vector ...
s that are not weakly-complete (despite being complete in their norm topology). If X is a vector space then under the canonical duality, \left(X^, \sigma\left(X^, X\right)\right) is complete. Conversely, if Z is a Hausdorff
locally convex In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological ve ...
TVS with continuous dual space Z^, then \left(Z, \sigma\left(Z, Z^\right)\right) is complete if and only if Z = \left(Z^\right)^; that is, if and only if the map Z \to \left(Z^\right)^ defined by sending z \in Z to the evaluation map at z (i.e. z^ \mapsto z^(z)) is a bijection. In particular, with respect to the canonical duality, if Y is a vector subspace of X^ such that Y separates points of X, then (Y, \sigma(Y, X)) is complete if and only if Y = X^. Said differently, there does exist a proper vector subspace Y \neq X^ of X^ such that (X, \sigma(X, Y)) is Hausdorff and Y is complete in the
weak-* topology In mathematics, weak topology is an alternative term for certain initial topologies, often on topological vector spaces or spaces of linear operators, for instance on a Hilbert space. The term is most commonly used for the initial topology of a ...
(i.e. the topology of pointwise convergence). Consequently, when the
continuous dual space In mathematics, any vector space ''V'' has a corresponding dual vector space (or just dual space for short) consisting of all linear forms on ''V'', together with the vector space structure of pointwise addition and scalar multiplication by cons ...
X^ of a Hausdorff
locally convex In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological ve ...
TVS X is endowed with the
weak-* topology In mathematics, weak topology is an alternative term for certain initial topologies, often on topological vector spaces or spaces of linear operators, for instance on a Hilbert space. The term is most commonly used for the initial topology of a ...
, then X^_ is
complete Complete may refer to: Logic * Completeness (logic) * Completeness of a theory, the property of a theory that every formula in the theory's language or its negation is provable Mathematics * The completeness of the real numbers, which implies t ...
if and only if X^ = X^ (that is, if and only if linear functional on X is continuous).


Identification of ''Y'' with a subspace of the algebraic dual

If X distinguishes points of Y and if Z denotes the range of the injection y \mapsto b(\,\cdot\,, y) then Z is a vector subspace of the
algebraic dual space In mathematics, any vector space ''V'' has a corresponding dual vector space (or just dual space for short) consisting of all linear forms on ''V'', together with the vector space structure of pointwise addition and scalar multiplication by const ...
of X and the pairing (X, Y, b) becomes canonically identified with the canonical pairing \langle X, Z \rangle (where \left\langle x, x^ \right\rangle := x^(x) is the natural evaluation map). In particular, in this situation it will be assumed
without loss of generality ''Without loss of generality'' (often abbreviated to WOLOG, WLOG or w.l.o.g.; less commonly stated as ''without any loss of generality'' or ''with no loss of generality'') is a frequently used expression in mathematics. The term is used to indicate ...
that Y is a vector subspace of X's algebraic dual and b is the evaluation map. :: Often, whenever y \mapsto b(\,\cdot\,, y) is injective (especially when (X, Y, b) forms a dual pair) then it is common practice to assume
without loss of generality ''Without loss of generality'' (often abbreviated to WOLOG, WLOG or w.l.o.g.; less commonly stated as ''without any loss of generality'' or ''with no loss of generality'') is a frequently used expression in mathematics. The term is used to indicate ...
that Y is a vector subspace of the algebraic dual space of X, that b is the natural evaluation map, and also denote Y by X^. In a completely analogous manner, if Y distinguishes points of X then it is possible for X to be identified as a vector subspace of Y's algebraic dual space.


Algebraic adjoint

In the special case where the dualities are the canonical dualities \left\langle X, X^ \right\rangle and \left\langle W, W^ \right\rangle, the transpose of a linear map F : X \to W is always well-defined. This transpose is called the algebraic adjoint of F and it will be denoted by F^; that is, F^ = ^t F : W^ \to X^. In this case, for all w^ \in W^, F^\left(w^\right) = w^ \circ F where the defining condition for F^\left(w^\right) is: \left\langle x, F^\left(w^\right) \right\rangle = \left\langle F(x), w^ \right\rangle \quad \text >x \in X, or equivalently, F^\left(w^\right)(x) = w^(F(x)) \quad \text x \in X. ;Examples If X = Y = \mathbb^n for some integer n, \mathcal = \left\ is a basis for X with
dual basis In linear algebra, given a vector space ''V'' with a basis ''B'' of vectors indexed by an index set ''I'' (the cardinality of ''I'' is the dimension of ''V''), the dual set of ''B'' is a set ''B''∗ of vectors in the dual space ''V''∗ with th ...
\mathcal^ = \left\, F : \mathbb^n \to \mathbb^n is a linear operator, and the matrix representation of F with respect to \mathcal is M := \left(f_\right), then the transpose of M is the matrix representation with respect to \mathcal^ of F^.


Weak continuity and openness

Suppose that \left\langle X, Y \right\rangle and \langle W, Z \rangle are canonical pairings (so Y \subseteq X^and Z \subseteq W^) that are dual systems and let F : X \to W be a linear map. Then F : X \to W is weakly continuous if and only if it satisfies any of the following equivalent conditions: # F : (X, \sigma(X, Y)) \to (W, \sigma(W, Z)) is continuous; # F^(Z) \subseteq Y # the transpose of ''F'', ^t F : Z \to Y, with respect to \left\langle X, Y \right\rangle and \langle W, Z \rangle is well-defined. If F is weakly continuous then ^t F : : (Z, \sigma(Z, W)) \to (Y, \sigma(Y, X)) will be continuous and furthermore, ^ F = F A map g : A \to B between topological spaces is relatively open if g : A \to \operatorname g is an
open map In mathematics, more specifically in topology, an open map is a function between two topological spaces that maps open sets to open sets. That is, a function f : X \to Y is open if for any open set U in X, the image f(U) is open in Y. Likewise, a ...
ping, where \operatorname g is the range of g. Suppose that \langle X, Y \rangle and \langle W, Z \rangle are dual systems and F : X \to W is a weakly continuous linear map. Then the following are equivalent: # F : (X, \sigma(X, Y)) \to (W, \sigma(W, Z)) is relatively open; # The range of ^t F is \sigma(Y, X)-closed in Y; # \operatorname ^t F = (\operatorname F)^ Furthermore, * F : X \to W is injective (resp. bijective) if and only if ^t F is surjective (resp. bijective); * F : X \to W is surjective if and only if ^t F : : (Z, \sigma(Z, W)) \to (Y, \sigma(Y, X)) is relatively open and injective.


= Transpose of a map between TVSs

= The transpose of map between two TVSs is defined if and only if F is weakly continuous. If F : X \to Y is a linear map between two Hausdorff locally convex topological vector spaces then: * If F is continuous then it is weakly continuous and ^t F is both Mackey continuous and strongly continuous. * If F is weakly continuous then it is both Mackey continuous and strongly continuous (defined below). * If F is weakly continuous then it is continuous if and only if ^t F : ^ \to X^ maps
equicontinuous In mathematical analysis, a family of functions is equicontinuous if all the functions are continuous and they have equal variation over a given neighbourhood, in a precise sense described herein. In particular, the concept applies to countable fa ...
subsets of Y^ to equicontinuous subsets of X^. * If X and Y are normed spaces then F is continuous if and only if it is weakly continuous, in which case \, F\, = \left\, ^t F\right\, . * If F is continuous then F : X \to Y is relatively open if and only if F is weakly relatively open (i.e. F : \left(X, \sigma\left(X, X^\right)\right) \to \left(Y, \sigma\left(Y, Y^\right)\right) is relatively open) and every equicontinuous subsets of \operatorname ^t F = ^t F\left(Y^\right) is the image of some equicontinuous subsets of Y^. * If F is continuous injection then F : X \to Y is a TVS-embedding (or equivalently, a
topological embedding In mathematics, an embedding (or imbedding) is one instance of some mathematical structure contained within another instance, such as a group that is a subgroup. When some object X is said to be embedded in another object Y, the embedding is giv ...
) if and only if every equicontinuous subsets of X^ is the image of some equicontinuous subsets of Y^.


Metrizability and separability

Let X be a
locally convex In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological ve ...
space with continuous dual space X^ and let K \subseteq X^. # If K is
equicontinuous In mathematical analysis, a family of functions is equicontinuous if all the functions are continuous and they have equal variation over a given neighbourhood, in a precise sense described herein. In particular, the concept applies to countable fa ...
or \sigma\left(X^, X\right)-compact, and if D \subseteq X^ is such that \operatorname Dis dense in X, then the subspace topology that K inherits from \left(X^, \sigma\left(X^, D\right)\right) is identical to the subspace topology that K inherits from \left(X^, \sigma\left(X^, X\right)\right). # If X is separable and K is equicontinuous then K, when endowed with the subspace topology induced by \left(X^, \sigma\left(X^, X\right)\right), is
metrizable In topology and related areas of mathematics, a metrizable space is a topological space that is homeomorphic to a metric space. That is, a topological space (X, \mathcal) is said to be metrizable if there is a metric d : X \times X \to , \infty) ...
. # If X is separable and
metrizable In topology and related areas of mathematics, a metrizable space is a topological space that is homeomorphic to a metric space. That is, a topological space (X, \mathcal) is said to be metrizable if there is a metric d : X \times X \to , \infty) ...
, then \left(X^, \sigma\left(X^, X\right)\right) is separable. # If X is a normed space then X is separable if and only if the closed unit call the continuous dual space of X is metrizable when given the subspace topology induced by \left(X^, \sigma\left(X^, X\right)\right). # If X is a normed space whose continuous dual space is separable (when given the usual norm topology), then X is separable.


Polar topologies and topologies compatible with pairing

Starting with only the weak topology, the use of
polar set In functional and convex analysis, and related disciplines of mathematics, the polar set A^ is a special convex set associated to any subset A of a vector space X lying in the dual space X^. The bipolar of a subset is the polar of A^, but lies ...
s produces a range of locally convex topologies. Such topologies are called polar topologies. The weak topology is the weakest topology of this range. Throughout, (X, Y, b) will be a pairing over \mathbb and \mathcal will be a non-empty collection of \sigma(X, Y, b)-bounded subsets of X.


Polar topologies

Given a collection \mathcal of subsets of X, the
polar topology In functional analysis and related areas of mathematics a polar topology, topology of \mathcal-convergence or topology of uniform convergence on the sets of \mathcal is a method to define locally convex topologies on the vector spaces of a pairing ...
on Y determined by \mathcal (and b) or the \mathcal-topology on Y is the unique
topological vector space In mathematics, a topological vector space (also called a linear topological space and commonly abbreviated TVS or t.v.s.) is one of the basic structures investigated in functional analysis. A topological vector space is a vector space that is als ...
(TVS) topology on Y for which \left\ forms a
subbasis In topology, a subbase (or subbasis, prebase, prebasis) for a topological space X with topology T is a subcollection B of T that generates T, in the sense that T is the smallest topology containing B. A slightly different definition is used by so ...
of neighborhoods at the origin. When Y is endowed with this \mathcal-topology then it is denoted by ''Y''\mathcal. Every polar topology is necessarily
locally convex In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological ve ...
. When \mathcal is a
directed set In mathematics, a directed set (or a directed preorder or a filtered set) is a nonempty set A together with a reflexive and transitive binary relation \,\leq\, (that is, a preorder), with the additional property that every pair of elements has ...
with respect to subset inclusion (i.e. if for all G, K \in \mathcal there exists some K \in \mathcal such that G \cup H \subseteq K) then this neighborhood subbasis at 0 actually forms a
neighborhood basis In topology and related areas of mathematics, the neighbourhood system, complete system of neighbourhoods, or neighbourhood filter \mathcal(x) for a point x in a topological space is the collection of all neighbourhoods of x. Definitions Neighbour ...
at 0. The following table lists some of the more important polar topologies. :: If \Delta(X, Y, b) denotes a polar topology on Y then Y endowed with this topology will be denoted by Y_, Y_ or simply Y_ (e.g. for \sigma(Y, X, b) we'd have \Delta = \sigma so that Y_, Y_ and Y_ all denote Y endowed with \sigma(X, Y, b)).


Definitions involving polar topologies

;Continuity A linear map F : X \to W is Mackey continuous (with respect to (X, Y, b) and (W, Z, c)) if F : (X, \tau(X, Y, b)) \to (W, \tau(W, Z, c)) is continuous. A linear map F : X \to W is strongly continuous (with respect to (X, Y, b) and (W, Z, c)) if F : (X, \beta(X, Y, b)) \to (W, \beta(W, Z, c)) is continuous. ;Bounded subsets A subset of X is weakly bounded (resp. Mackey bounded, strongly bounded) if it is bounded in (X, \sigma(X, Y, b)) (resp. bounded in (X, \tau(X, Y, b)), bounded in (X, \beta(X, Y, b))).


Topologies compatible with a pair

If (X, Y, b) is a pairing over \mathbb and \mathcal is a vector topology on X then \mathcal is a topology of the pairing and that it is compatible (or consistent) with the pairing (X, Y, b) if it is
locally convex In functional analysis and related areas of mathematics, locally convex topological vector spaces (LCTVS) or locally convex spaces are examples of topological vector spaces (TVS) that generalize normed spaces. They can be defined as topological ve ...
and if the continuous dual space of \left(X, \mathcal\right) = b(\,\cdot\,, Y).Of course, there is an analogous definition for topologies on Y to be "compatible it a pairing" but this article will only deal with topologies on X. If X distinguishes points of Y then by identifying Y as a vector subspace of X's algebraic dual, the defining condition becomes: \left(X, \mathcal\right)^ = Y. Some authors (e.g. rèves 2006and chaefer 1999 require that a topology of a pair also be Hausdorff, which it would have to be if Y distinguishes the points of X (which these authors assume). The weak topology \sigma(X, Y, b) is compatible with the pairing (X, Y, b) (as was shown in the Weak representation theorem) and it is in fact the weakest such topology. There is a strongest topology compatible with this pairing and that is the
Mackey topology In functional analysis and related areas of mathematics, the Mackey topology, named after George Mackey, is the finest topology for a topological vector space which still preserves the continuous dual. In other words the Mackey topology does not mak ...
. If N is a normed space that is not reflexive then the usual norm topology on its continuous dual space is compatible with the duality \left(N^, N\right).


Mackey-Arens theorem

The following is one of the most important theorems in duality theory. It follows that the Mackey topology \tau(X, Y, b), which recall is the polar topology generated by all \sigma(X, Y, b)-compact disks in Y, is the strongest locally convex topology on X that is compatible with the pairing (X, Y, b). A locally convex space whose given topology is identical to the Mackey topology is called a
Mackey space In mathematics, particularly in functional analysis, a Mackey space is a locally convex topological vector space ''X'' such that the topology of ''X'' coincides with the Mackey topology τ(''X'',''X′''), the finest topology which still preser ...
. The following consequence of the above Mackey-Arens theorem is also called the Mackey-Arens theorem.


Mackey's theorem, barrels, and closed convex sets

If X is a TVS (over \Reals or \Complex) then a half-space is a set of the form \ for some real r and some continuous linear functional f on X. The above theorem implies that the closed and convex subsets of a locally convex space depend on the continuous dual space. Consequently, the closed and convex subsets are the same in any topology compatible with duality; that is, if \mathcal and \mathcal are any locally convex topologies on X with the same continuous dual spaces, then a convex subset of X is closed in the \mathcal topology if and only if it is closed in the \mathcal topology. This implies that the \mathcal-closure of any convex subset of X is equal to its \mathcal-closure and that for any \mathcal-closed
disk Disk or disc may refer to: * Disk (mathematics), a geometric shape * Disk storage Music * Disc (band), an American experimental music band * ''Disk'' (album), a 1995 EP by Moby Other uses * Disk (functional analysis), a subset of a vector sp ...
A in X, A = A^. In particular, if B is a subset of X then B is a
barrel A barrel or cask is a hollow cylindrical container with a bulging center, longer than it is wide. They are traditionally made of wooden staves and bound by wooden or metal hoops. The word vat is often used for large containers for liquids, ...
in (X, \mathcal) if and only if it is a barrel in (X, \mathcal). The following theorem shows that
barrels A barrel or cask is a hollow cylindrical container with a bulging center, longer than it is wide. They are traditionally made of wooden staves and bound by wooden or metal hoops. The word vat is often used for large containers for liquids, u ...
(i.e. closed absorbing disks) are exactly the polars of weakly bounded subsets. If X is a topological vector space then: # A closed absorbing and
balanced In telecommunications and professional audio, a balanced line or balanced signal pair is a circuit consisting of two conductors of the same type, both of which have equal impedances along their lengths and equal impedances to ground and to other ...
subset B of X absorbs each convex compact subset of X (i.e. there exists a real r > 0 such that r B contains that set). # If X is Hausdorff and locally convex then every barrel in X absorbs every convex bounded complete subset of X. All of this leads to Mackey's theorem, which is one of the central theorems in the theory of dual systems. In short, it states the bounded subsets are the same for any two Hausdorff locally convex topologies that are compatible with the same duality.


Examples

;Space of finite sequences Let X denote the space of all sequences of scalars r_ = \left(r_i\right)_^ such that r_i = 0 for all sufficiently large i. Let Y = X and define a bilinear map b : X \times X \to \mathbb by b\left(r_, s_\right) := \sum_^ r_i s_i. Then \sigma(X, X, b) = \tau(X, X, b). Moreover, a subset T \subseteq X is \sigma(X, X, b)-bounded (resp. \beta(X, X, b)-bounded) if and only if there exists a sequence m_ = \left(m_i\right)_^ of positive real numbers such that \left, t_i\ \leq m_i for all t_ = \left(t_i\right)_^ \in T and all indices i (resp. and m_ \in X). It follows that there are weakly bounded (that is, \sigma(X, X, b)-bounded) subsets of X that are not strongly bounded (that is, not \beta(X, X, b)-bounded).


See also

* * * * * * * * * * * * * *


Notes


References


Bibliography

* * Michael Reed and Barry Simon, ''Methods of Modern Mathematical Physics, Vol. 1, Functional Analysis,'' Section III.3. Academic Press, San Diego, 1980. . * * * *


External links


Duality Theory
{{DEFAULTSORT:Dual Pair Functional analysis
Pair Pair or PAIR or Pairing may refer to: Government and politics * Pair (parliamentary convention), matching of members unable to attend, so as not to change the voting margin * ''Pair'', a member of the Prussian House of Lords * ''Pair'', the Frenc ...
Topological vector spaces