Metrizable topological vector space#Additive sequences

{{Short description|A topological vector space whose topology can be defined by a metric}}

In functional analysis and related areas of mathematics, a metrizable (resp. pseudometrizable) topological vector space (TVS) is a TVS whose topology is induced by a metric (resp. pseudometric). An LM-space is an inductive limit of a sequence of locally convex metrizable TVS.

Pseudometrics and metrics

A pseudometric on a set X is a map d : X \times X \rarr \R satisfying the following properties:

  1. d(x, x) = 0 \text{ for all } x \in X;
  2. Symmetry: d(x, y) = d(y, x) \text{ for all } x, y \in X;
  3. Subadditivity: d(x, z) \leq d(x, y) + d(y, z) \text{ for all } x, y, z \in X.

A pseudometric is called a metric if it satisfies:

  1. Identity of indiscernibles: for all x, y \in X, if d(x, y) = 0 then x = y.

Ultrapseudometric

A pseudometric d on X is called a ultrapseudometric or a strong pseudometric if it satisfies:

  1. Strong/Ultrametric triangle inequality: d(x, z) \leq \max \{ d(x, y), d(y, z) \} \text{ for all } x, y, z \in X.

Pseudometric space

A pseudometric space is a pair (X, d) consisting of a set X and a pseudometric d on X such that X's topology is identical to the topology on X induced by d. We call a pseudometric space (X, d) a metric space (resp. ultrapseudometric space) when d is a metric (resp. ultrapseudometric).

=Topology induced by a pseudometric=

If d is a pseudometric on a set X then collection of open balls:

B_r(z) := \{ x \in X : d(x, z) < r \} as z ranges over X and r > 0 ranges over the positive real numbers,

forms a basis for a topology on X that is called the d-topology or the pseudometric topology on X induced by d.

:{{em|Convention}}: If (X, d) is a pseudometric space and X is treated as a topological space, then unless indicated otherwise, it should be assumed that X is endowed with the topology induced by d.

Pseudometrizable space

A topological space (X, \tau) is called pseudometrizable (resp. metrizable, ultrapseudometrizable) if there exists a pseudometric (resp. metric, ultrapseudometric) d on X such that \tau is equal to the topology induced by d.{{sfn|Narici|Beckenstein|2011|pp=1-18}}

Pseudometrics and values on topological groups

An additive topological group is an additive group endowed with a topology, called a group topology, under which addition and negation become continuous operators.

A topology \tau on a real or complex vector space X is called a vector topology or a TVS topology if it makes the operations of vector addition and scalar multiplication continuous (that is, if it makes X into a topological vector space).

Every topological vector space (TVS) X is an additive commutative topological group but not all group topologies on X are vector topologies.

This is because despite it making addition and negation continuous, a group topology on a vector space X may fail to make scalar multiplication continuous.

For instance, the discrete topology on any non-trivial vector space makes addition and negation continuous but do not make scalar multiplication continuous.

=Translation invariant pseudometrics=

If X is an additive group then we say that a pseudometric d on X is translation invariant or just invariant if it satisfies any of the following equivalent conditions:

  1. Translation invariance: d(x + z, y + z) = d(x, y) \text{ for all } x, y, z \in X;
  2. d(x, y) = d(x - y, 0) \text{ for all } x, y \in X.

=Value/G-seminorm=

If X is a topological group the a value or G-seminorm on X (the G stands for Group) is a real-valued map p : X \rarr \R with the following properties:{{sfn|Narici|Beckenstein|2011|pp=37-40}}

  1. Non-negative: p \geq 0.
  2. Subadditive: p(x + y) \leq p(x) + p(y) \text{ for all } x, y \in X;
  3. p(0) = 0..
  4. Symmetric: p(-x) = p(x) \text{ for all } x \in X.

where we call a G-seminorm a G-norm if it satisfies the additional condition:

  1. Total/Positive definite: If p(x) = 0 then x = 0.

==Properties of values==

If p is a value on a vector space X then:

  • |p(x) - p(y)| \leq p(x - y) \text{ for all } x, y \in X.{{sfn|Swartz|1992|p=15}}
  • p(n x) \leq n p(x) and \frac{1}{n} p(x) \leq p(x / n) for all x \in X and positive integers n.{{sfn|Wilansky|2013|p=17}}
  • The set \{ x \in X : p(x) = 0 \} is an additive subgroup of X.{{sfn|Swartz|1992|p=15}}

=Equivalence on topological groups=

{{Math theorem|name=Theorem{{sfn|Narici|Beckenstein|2011|pp=37-40}}|math_statement=

Suppose that X is an additive commutative group.

If d is a translation invariant pseudometric on X then the map p(x) := d(x, 0) is a value on X called the value associated with d, and moreover, d generates a group topology on X (i.e. the d-topology on X makes X into a topological group).

Conversely, if p is a value on X then the map d(x, y) := p(x - y) is a translation-invariant pseudometric on X and the value associated with d is just p.

}}

=Pseudometrizable topological groups=

{{Math theorem|name=Theorem{{sfn|Narici|Beckenstein|2011|pp=37-40}}|math_statement=

If (X, \tau) is an additive commutative topological group then the following are equivalent:

  1. \tau is induced by a pseudometric; (i.e. (X, \tau) is pseudometrizable);
  2. \tau is induced by a translation-invariant pseudometric;
  3. the identity element in (X, \tau) has a countable neighborhood basis.

If (X, \tau) is Hausdorff then the word "pseudometric" in the above statement may be replaced by the word "metric."

A commutative topological group is metrizable if and only if it is Hausdorff and pseudometrizable.

}}

=An invariant pseudometric that doesn't induce a vector topology=

Let X be a non-trivial (i.e. X \neq \{ 0 \}) real or complex vector space and let d be the translation-invariant trivial metric on X defined by d(x, x) = 0 and d(x, y) = 1 \text{ for all } x, y \in X such that x \neq y.

The topology \tau that d induces on X is the discrete topology, which makes (X, \tau) into a commutative topological group under addition but does {{em|not}} form a vector topology on X because (X, \tau) is disconnected but every vector topology is connected.

What fails is that scalar multiplication isn't continuous on (X, \tau).

This example shows that a translation-invariant (pseudo)metric is {{em|not}} enough to guarantee a vector topology, which leads us to define paranorms and F-seminorms.

Additive sequences

A collection \mathcal{N} of subsets of a vector space is called additive{{sfn|Wilansky|2013|pp=40-47}} if for every N \in \mathcal{N}, there exists some U \in \mathcal{N} such that U + U \subseteq N.

{{Math theorem|name=Continuity of addition at 0|math_statement=

If (X, +) is a group (as all vector spaces are), \tau is a topology on X, and X \times X is endowed with the product topology, then the addition map X \times X \to X (i.e. the map (x, y) \mapsto x + y) is continuous at the origin of X \times X if and only if the set of neighborhoods of the origin in (X, \tau) is additive. This statement remains true if the word "neighborhood" is replaced by "open neighborhood."{{sfn|Wilansky|2013|pp=40-47}}

}}

All of the above conditions are consequently a necessary for a topology to form a vector topology.

Additive sequences of sets have the particularly nice property that they define non-negative continuous real-valued subadditive functions.

These functions can then be used to prove many of the basic properties of topological vector spaces and also show that a Hausdorff TVS with a countable basis of neighborhoods is metrizable. The following theorem is true more generally for commutative additive topological groups.

{{Math theorem|name=Theorem|math_statement=

Let U_{\bull} = \left(U_i\right)_{i=0}^{\infty} be a collection of subsets of a vector space such that 0 \in U_i and U_{i+1} + U_{i+1} \subseteq U_i for all i \geq 0.

For all u \in U_0, let

\mathbb{S}(u) := \left\{ n_{\bull} = \left(n_1, \ldots, n_k\right) ~:~ k \geq 1, n_i \geq 0 \text{ for all } i, \text{ and } u \in U_{n_1} + \cdots + U_{n_k}\right\}.

Define f : X \to [0, 1] by f(x) = 1 if x \not\in U_0 and otherwise let

f(x) := \inf_{} \left\{ 2^{- n_1} + \cdots 2^{- n_k} ~:~ n_{\bull} = \left(n_1, \ldots, n_k\right) \in \mathbb{S}(x)\right\}.

Then f is subadditive (meaning f(x + y) \leq f(x) + f(y) \text{ for all } x, y \in X) and f = 0 on \bigcap_{i \geq 0} U_i, so in particular f(0) = 0.

If all U_i are symmetric sets then f(-x) = f(x) and if all U_i are balanced then f(s x) \leq f(x) for all scalars s such that |s| \leq 1 and all x \in X.

If X is a topological vector space and if all U_i are neighborhoods of the origin then f is continuous, where if in addition X is Hausdorff and U_{\bull} forms a basis of balanced neighborhoods of the origin in X then d(x, y) := f(x - y) is a metric defining the vector topology on X.

}}

{{collapse top|title=Proof|left=true}}

Assume that n_{\bull} = \left(n_1, \ldots, n_k\right) always denotes a finite sequence of non-negative integers and use the notation:

\sum 2^{- n_{\bull}} := 2^{- n_1} + \cdots + 2^{- n_k} \quad \text{ and } \quad \sum U_{n_{\bull}} := U_{n_1} + \cdots + U_{n_k}.

For any integers n \geq 0 and d > 2,

U_n \supseteq U_{n+1} + U_{n+1} \supseteq U_{n+1} + U_{n+2} + U_{n+2} \supseteq U_{n+1} + U_{n+2} + \cdots + U_{n+d} + U_{n+d+1} + U_{n+d+1}.

From this it follows that if n_{\bull} = \left(n_1, \ldots, n_k\right) consists of distinct positive integers then \sum U_{n_{\bull}} \subseteq U_{-1 + \min \left(n_{\bull}\right)}.

It will now be shown by induction on k that if n_{\bull} = \left(n_1, \ldots, n_k\right) consists of non-negative integers such that \sum 2^{- n_{\bull}} \leq 2^{- M} for some integer M \geq 0 then \sum U_{n_{\bull}} \subseteq U_M.

This is clearly true for k = 1 and k = 2 so assume that k > 2, which implies that all n_i are positive.

If all n_i are distinct then this step is done, and otherwise pick distinct indices i < j such that n_i = n_j and construct m_{\bull} = \left(m_1, \ldots, m_{k-1}\right) from n_{\bull} by replacing each n_i with n_i - 1 and deleting the j^{\text{th}} element of n_{\bull} (all other elements of n_{\bull} are transferred to m_{\bull} unchanged).

Observe that \sum 2^{- n_{\bull}} = \sum 2^{- m_{\bull}} and \sum U_{n_{\bull}} \subseteq \sum U_{m_{\bull}} (because U_{n_i} + U_{n_j} \subseteq U_{n_i - 1}) so by appealing to the inductive hypothesis we conclude that \sum U_{n_{\bull}} \subseteq \sum U_{m_{\bull}} \subseteq U_M, as desired.

It is clear that f(0) = 0 and that 0 \leq f \leq 1 so to prove that f is subadditive, it suffices to prove that f(x + y) \leq f(x) + f(y) when x, y \in X are such that f(x) + f(y) < 1, which implies that x, y \in U_0.

This is an exercise.

If all U_i are symmetric then x \in \sum U_{n_{\bull}} if and only if - x \in \sum U_{n_{\bull}} from which it follows that f(-x) \leq f(x) and f(-x) \geq f(x).

If all U_i are balanced then the inequality f(s x) \leq f(x) for all unit scalars s such that |s| \leq 1 is proved similarly.

Because f is a nonnegative subadditive function satisfying f(0) = 0, as described in the article on sublinear functionals, f is uniformly continuous on X if and only if f is continuous at the origin.

If all U_i are neighborhoods of the origin then for any real r > 0, pick an integer M > 1 such that 2^{-M} < r so that x \in U_M implies f(x) \leq 2^{-M} < r.

If the set of all U_i form basis of balanced neighborhoods of the origin then it may be shown that for any n > 1, there exists some 0 < r \leq 2^{-n} such that f(x) < r implies x \in U_n. \blacksquare

{{collapse bottom}}

Paranorms

If X is a vector space over the real or complex numbers then a paranorm on X is a G-seminorm (defined above) p : X \rarr \R on X that satisfies any of the following additional conditions, each of which begins with "for all sequences x_{\bull} = \left(x_i\right)_{i=1}^{\infty} in X and all convergent sequences of scalars s_{\bull} = \left(s_i\right)_{i=1}^{\infty}":{{sfn|Wilansky|2013|p=15}}

  1. Continuity of multiplication: if s is a scalar and x \in X are such that p\left(x_i - x\right) \to 0 and s_{\bull} \to s, then p\left(s_i x_i - s x\right) \to 0.
  2. Both of the conditions:

    • if s_{\bull} \to 0 and if x \in X is such that p\left(x_i - x\right) \to 0 then p\left(s_i x_i\right) \to 0;
    • if p\left(x_{\bull}\right) \to 0 then p\left(s x_i\right) \to 0 for every scalar s.

  3. Both of the conditions:

    • if p\left(x_{\bull}\right) \to 0 and s_{\bull} \to s for some scalar s then p\left(s_i x_i\right) \to 0;
    • if s_{\bull} \to 0 then p\left(s_i x\right) \to 0 \text{ for all } x \in X.

  4. Separate continuity:{{sfn|Schechter|1996|pp=689-691}}

    • if s_{\bull} \to s for some scalar s then p\left(s x_i - s x\right) \to 0 for every x \in X;
    • if s is a scalar, x \in X, and p\left(x_i - x\right) \to 0 then p\left(s x_i - s x\right) \to 0 .

A paranorm is called total if in addition it satisfies:

  • Total/Positive definite: p(x) = 0 implies x = 0.

=Properties of paranorms=

If p is a paranorm on a vector space X then the map d : X \times X \rarr \R defined by d(x, y) := p(x - y) is a translation-invariant pseudometric on X that defines a {{em|vector topology}} on X.{{sfn|Wilansky|2013|pp=15-18}}

If p is a paranorm on a vector space X then:

  • the set \{ x \in X : p(x) = 0 \} is a vector subspace of X.{{sfn|Wilansky|2013|pp=15-18}}
  • p(x + n) = p(x) \text{ for all } x, n \in X with p(n) = 0.{{sfn|Wilansky|2013|pp=15-18}}
  • If a paranorm p satisfies p(s x) \leq |s| p(x) \text{ for all } x \in X and scalars s, then p is absolutely homogeneity (i.e. equality holds){{sfn|Wilansky|2013|pp=15-18}} and thus p is a seminorm.

=Examples of paranorms=

  • If d is a translation-invariant pseudometric on a vector space X that induces a vector topology \tau on X (i.e. (X, \tau) is a TVS) then the map p(x) := d(x - y, 0) defines a continuous paranorm on (X, \tau); moreover, the topology that this paranorm p defines in X is \tau.{{sfn|Wilansky|2013|pp=15-18}}
  • If p is a paranorm on X then so is the map q(x) := p(x) / [1 + p(x)].{{sfn|Wilansky|2013|pp=15-18}}
  • Every positive scalar multiple of a paranorm (resp. total paranorm) is again such a paranorm (resp. total paranorm).
  • Every seminorm is a paranorm.{{sfn|Wilansky|2013|pp=15-18}}
  • The restriction of an paranorm (resp. total paranorm) to a vector subspace is an paranorm (resp. total paranorm).{{sfn|Schechter|1996|p=692}}
  • The sum of two paranorms is a paranorm.{{sfn|Wilansky|2013|pp=15-18}}
  • If p and q are paranorms on X then so is (p \wedge q)(x) := \inf_{} \{ p(y) + q(z) : x = y + z \text{ with } y, z \in X \}. Moreover, (p \wedge q) \leq p and (p \wedge q) \leq q. This makes the set of paranorms on X into a conditionally complete lattice.{{sfn|Wilansky|2013|pp=15-18}}
  • Each of the following real-valued maps are paranorms on X := \R^2:

    • (x, y) \mapsto |x|
    • (x, y) \mapsto |x| + |y|

  • The real-valued maps (x, y) \mapsto \sqrt{\left|x^2 - y^2\right|} and (x, y) \mapsto \left|x^2 - y^2\right|^{3/2} are {{em|not}} paranorms on X := \R^2.{{sfn|Wilansky|2013|pp=15-18}}
  • If x_{\bull} = \left(x_i\right)_{i \in I} is a Hamel basis on a vector space X then the real-valued map that sends x = \sum_{i \in I} s_i x_i \in X (where all but finitely many of the scalars s_i are 0) to \sum_{i \in I} \sqrt{\left|s_i\right|} is a paranorm on X, which satisfies p(sx) = \sqrt
    s
    p(x) for all x \in X and scalars s.{{sfn|Wilansky|2013|pp=15-18}}
  • The function p(x) := |\sin (\pi x)| + \min \{ 2, |x| \} is a paranorm on \R that is {{em|not}} balanced but nevertheless equivalent to the usual norm on R. Note that the function x \mapsto |\sin (\pi x)| is subadditive.{{sfn|Schechter|1996|p=691}}
  • Let X_{\Complex} be a complex vector space and let X_{\R} denote X_{\Complex} considered as a vector space over \R. Any paranorm on X_{\Complex} is also a paranorm on X_{\R}.{{sfn|Schechter|1996|p=692}}

''F''-seminorms

If X is a vector space over the real or complex numbers then an F-seminorm on X (the F stands for Fréchet) is a real-valued map p : X \to \Reals with the following four properties: {{sfn|Narici|Beckenstein|2011|pp=91-95}}

  1. Non-negative: p \geq 0.
  2. Subadditive: p(x + y) \leq p(x) + p(y) for all x, y \in X
  3. Balanced: p(a x) \leq p(x) for x \in X all scalars a satisfying |a| \leq 1;

    • This condition guarantees that each set of the form \{z \in X : p(z) \leq r\} or \{z \in X : p(z) < r\} for some r \geq 0 is a balanced set.

  4. For every x \in X, p\left(\tfrac{1}{n} x\right) \to 0 as n \to \infty

    • The sequence \left(\tfrac{1}{n}\right)_{n=1}^\infty can be replaced by any positive sequence converging to the zero.{{sfn|Jarchow|1981|pp=38-42}}

An F-seminorm is called an F-norm if in addition it satisfies:

  1. Total/Positive definite: p(x) = 0 implies x = 0.

An F-seminorm is called monotone if it satisfies:

  1. Monotone: p(r x) < p(s x) for all non-zero x \in X and all real s and t such that s < t.{{sfn|Jarchow|1981|pp=38-42}}

=''F''-seminormed spaces=

An F-seminormed space (resp. F-normed space){{sfn|Jarchow|1981|pp=38-42}} is a pair (X, p) consisting of a vector space X and an F-seminorm (resp. F-norm) p on X.

If (X, p) and (Z, q) are F-seminormed spaces then a map f : X \to Z is called an isometric embedding{{sfn|Jarchow|1981|pp=38-42}} if q(f(x) - f(y)) = p(x, y) \text{ for all } x, y \in X.

Every isometric embedding of one F-seminormed space into another is a topological embedding, but the converse is not true in general.{{sfn|Jarchow|1981|pp=38-42}}

=Examples of ''F''-seminorms=

  • Every positive scalar multiple of an F-seminorm (resp. F-norm, seminorm) is again an F-seminorm (resp. F-norm, seminorm).
  • The sum of finitely many F-seminorms (resp. F-norms) is an F-seminorm (resp. F-norm).
  • If p and q are F-seminorms on X then so is their pointwise supremum x \mapsto \sup \{p(x), q(x)\}. The same is true of the supremum of any non-empty finite family of F-seminorms on X.{{sfn|Jarchow|1981|pp=38-42}}
  • The restriction of an F-seminorm (resp. F-norm) to a vector subspace is an F-seminorm (resp. F-norm).{{sfn|Schechter|1996|p=692}}
  • A non-negative real-valued function on X is a seminorm if and only if it is a convex F-seminorm, or equivalently, if and only if it is a convex balanced G-seminorm.{{sfn|Schechter|1996|p=691}} In particular, every seminorm is an F-seminorm.
  • For any 0 < p < 1, the map f on \Reals^n defined by

    [f\left(x_1, \ldots, x_n\right)]^p = \left|x_1\right|^p + \cdots \left|x_n\right|^p

    is an F-norm that is not a norm.

  • If L : X \to Y is a linear map and if q is an F-seminorm on Y, then q \circ L is an F-seminorm on X.{{sfn|Jarchow|1981|pp=38-42}}
  • Let X_\Complex be a complex vector space and let X_\Reals denote X_\Complex considered as a vector space over \Reals. Any F-seminorm on X_\Complex is also an F-seminorm on X_\Reals.{{sfn|Schechter|1996|p=692}}

=Properties of ''F''-seminorms=

Every F-seminorm is a paranorm and every paranorm is equivalent to some F-seminorm.{{sfn|Schechter|1996|pp=689-691}}

Every F-seminorm on a vector space X is a value on X. In particular, p(x) = 0, and p(x) = p(-x) for all x \in X.

=Topology induced by a single ''F''-seminorm=

{{Math theorem|name=Theorem{{sfn|Narici|Beckenstein|2011|pp=91-95}}|math_statement=

Let p be an F-seminorm on a vector space X.

Then the map d : X \times X \to \Reals defined by

d(x, y) := p(x - y)

is a translation invariant pseudometric on X that defines a vector topology \tau on X.

If p is an F-norm then d is a metric.

When X is endowed with this topology then p is a continuous map on X.

The balanced sets \{x \in X ~:~ p(x) \leq r\}, as r ranges over the positive reals, form a neighborhood basis at the origin for this topology consisting of closed set.

Similarly, the balanced sets \{x \in X ~:~ p(x) < r\}, as r ranges over the positive reals, form a neighborhood basis at the origin for this topology consisting of open sets.

}}

=Topology induced by a family of ''F''-seminorms=

Suppose that \mathcal{L} is a non-empty collection of F-seminorms on a vector space X and for any finite subset \mathcal{F} \subseteq \mathcal{L} and any r > 0, let

U_{\mathcal{F}, r} := \bigcap_{p \in \mathcal{F}} \{x \in X : p(x) < r\}.

The set \left\{U_{\mathcal{F}, r} ~:~ r > 0, \mathcal{F} \subseteq \mathcal{L}, \mathcal{F} \text{ finite }\right\} forms a filter base on X that also forms a neighborhood basis at the origin for a vector topology on X denoted by \tau_{\mathcal{L}}.{{sfn|Jarchow|1981|pp=38-42}} Each U_{\mathcal{F}, r} is a balanced and absorbing subset of X.{{sfn|Jarchow|1981|pp=38-42}} These sets satisfy{{sfn|Jarchow|1981|pp=38-42}}

U_{\mathcal{F}, r/2} + U_{\mathcal{F}, r/2} \subseteq U_{\mathcal{F}, r}.

  • \tau_{\mathcal{L}} is the coarsest vector topology on X making each p \in \mathcal{L} continuous.{{sfn|Jarchow|1981|pp=38-42}}
  • \tau_{\mathcal{L}} is Hausdorff if and only if for every non-zero x \in X, there exists some p \in \mathcal{L} such that p(x) > 0.{{sfn|Jarchow|1981|pp=38-42}}
  • If \mathcal{F} is the set of all continuous F-seminorms on \left(X, \tau_{\mathcal{L}}\right) then \tau_{\mathcal{L}} = \tau_{\mathcal{F}}.{{sfn|Jarchow|1981|pp=38-42}}
  • If \mathcal{F} is the set of all pointwise suprema of non-empty finite subsets of \mathcal{F} of \mathcal{L} then \mathcal{F} is a directed family of F-seminorms and \tau_{\mathcal{L}} = \tau_{\mathcal{F}}.{{sfn|Jarchow|1981|pp=38-42}}

{{anchor|Fréchet combination}}

Fréchet combination

Suppose that p_{\bull} = \left(p_i\right)_{i=1}^{\infty} is a family of non-negative subadditive functions on a vector space X.

The Fréchet combination{{sfn|Wilansky|2013|pp=15-18}} of p_{\bull} is defined to be the real-valued map

p(x) := \sum_{i=1}^{\infty} \frac{p_i(x)}{2^{i} \left[ 1 + p_i(x)\right]}.

=As an ''F''-seminorm=

Assume that p_{\bull} = \left(p_i\right)_{i=1}^{\infty} is an increasing sequence of seminorms on X and let p be the Fréchet combination of p_{\bull}.

Then p is an F-seminorm on X that induces the same locally convex topology as the family p_{\bull} of seminorms.{{sfn|Narici|Beckenstein|2011|p=123}}

Since p_{\bull} = \left(p_i\right)_{i=1}^{\infty} is increasing, a basis of open neighborhoods of the origin consists of all sets of the form \left\{ x \in X ~:~ p_i(x) < r\right\} as i ranges over all positive integers and r > 0 ranges over all positive real numbers.

The translation invariant pseudometric on X induced by this F-seminorm p is

d(x, y) = \sum^{\infty}_{i=1} \frac{1}{2^i} \frac{p_i( x - y )}{1 + p_i( x - y )}.

This metric was discovered by Fréchet in his 1906 thesis for the spaces of real and complex sequences with pointwise operations.{{sfn|Narici|Beckenstein|2011|pp=156-175}}

=As a paranorm=

If each p_i is a paranorm then so is p and moreover, p induces the same topology on X as the family p_{\bull} of paranorms.{{sfn|Wilansky|2013|pp=15-18}}

This is also true of the following paranorms on X:

  • q(x) := \inf_{} \left\{ \sum_{i=1}^n p_i(x) + \frac{1}{n} ~:~ n > 0 \text{ is an integer }\right\}.{{sfn|Wilansky|2013|pp=15-18}}
  • r(x) := \sum_{n=1}^{\infty} \min \left\{ \frac{1}{2^n}, p_n(x)\right\}.{{sfn|Wilansky|2013|pp=15-18}}

=Generalization=

The Fréchet combination can be generalized by use of a bounded remetrization function.

A {{em|{{visible anchor|bounded remetrization function}}}}{{sfn|Schechter|1996|p=487}} is a continuous non-negative non-decreasing map R : [0, \infty) \to [0, \infty) that has a bounded range, is subadditive (meaning that R(s + t) \leq R(s) + R(t) for all s, t \geq 0), and satisfies R(s) = 0 if and only if s = 0.

Examples of bounded remetrization functions include \arctan t, \tanh t, t \mapsto \min \{t, 1\}, and t \mapsto \frac{t}{1 + t}.{{sfn|Schechter|1996|p=487}}

If d is a pseudometric (respectively, metric) on X and R is a bounded remetrization function then R \circ d is a bounded pseudometric (respectively, bounded metric) on X that is uniformly equivalent to d.{{sfn|Schechter|1996|p=487}}

Suppose that p_\bull = \left(p_i\right)_{i=1}^\infty is a family of non-negative F-seminorm on a vector space X, R is a bounded remetrization function, and r_\bull = \left(r_i\right)_{i=1}^\infty is a sequence of positive real numbers whose sum is finite.

Then

p(x) := \sum_{i=1}^\infty r_i R\left(p_i(x)\right)

defines a bounded F-seminorm that is uniformly equivalent to the p_\bull.{{sfn|Schechter|1996|pp=692-693}}

It has the property that for any net x_\bull = \left(x_a\right)_{a \in A} in X, p\left(x_\bull\right) \to 0 if and only if p_i\left(x_\bull\right) \to 0 for all i.{{sfn|Schechter|1996|pp=692-693}}

p is an F-norm if and only if the p_\bull separate points on X.{{sfn|Schechter|1996|pp=692-693}}

Characterizations

=Of (pseudo)metrics induced by (semi)norms=

A pseudometric (resp. metric) d is induced by a seminorm (resp. norm) on a vector space X if and only if d is translation invariant and absolutely homogeneous, which means that for all scalars s and all x, y \in X, in which case the function defined by p(x) := d(x, 0) is a seminorm (resp. norm) and the pseudometric (resp. metric) induced by p is equal to d.

=Of pseudometrizable TVS=

If (X, \tau) is a topological vector space (TVS) (where note in particular that \tau is assumed to be a vector topology) then the following are equivalent:{{sfn|Narici|Beckenstein|2011|pp=91-95}}

  1. X is pseudometrizable (i.e. the vector topology \tau is induced by a pseudometric on X).
  2. X has a countable neighborhood base at the origin.
  3. The topology on X is induced by a translation-invariant pseudometric on X.
  4. The topology on X is induced by an F-seminorm.
  5. The topology on X is induced by a paranorm.

=Of metrizable TVS=

If (X, \tau) is a TVS then the following are equivalent:

  1. X is metrizable.
  2. X is Hausdorff and pseudometrizable.
  3. X is Hausdorff and has a countable neighborhood base at the origin.{{sfn|Narici|Beckenstein|2011|pp=91-95}}{{sfn|Jarchow|1981|pp=38-42}}
  4. The topology on X is induced by a translation-invariant metric on X.{{sfn|Narici|Beckenstein|2011|pp=91-95}}
  5. The topology on X is induced by an F-norm.{{sfn|Narici|Beckenstein|2011|pp=91-95}}{{sfn|Jarchow|1981|pp=38-42}}
  6. The topology on X is induced by a monotone F-norm.{{sfn|Jarchow|1981|pp=38-42}}
  7. The topology on X is induced by a total paranorm.

{{Math theorem|name=Birkhoff–Kakutani theorem|math_statement=

If (X, \tau) is a topological vector space then the following three conditions are equivalent:{{harvnb|Köthe|1983|loc=section 15.11}}In fact, this is true for topological group, for the proof doesn't use the scalar multiplications.

  1. The origin \{ 0 \} is closed in X, and there is a countable basis of neighborhoods for 0 in X.
  2. (X, \tau) is metrizable (as a topological space).
  3. There is a translation-invariant metric on X that induces on X the topology \tau, which is the given topology on X.

By the Birkhoff–Kakutani theorem, it follows that there is an equivalent metric that is translation-invariant.

}}

=Of locally convex pseudometrizable TVS=

If (X, \tau) is TVS then the following are equivalent:{{sfn|Narici|Beckenstein|2011|p=123}}

  1. X is locally convex and pseudometrizable.
  2. X has a countable neighborhood base at the origin consisting of convex sets.
  3. The topology of X is induced by a countable family of (continuous) seminorms.
  4. The topology of X is induced by a countable increasing sequence of (continuous) seminorms \left(p_i\right)_{i=1}^{\infty} (increasing means that for all i, p_i \geq p_{i+1}.
  5. The topology of X is induced by an F-seminorm of the form:

    p(x) = \sum_{n=1}^{\infty} 2^{-n} \operatorname{arctan} p_n(x)

    where \left(p_i\right)_{i=1}^{\infty} are (continuous) seminorms on X.{{sfn|Schechter|1996|p=706}}

Quotients

Let M be a vector subspace of a topological vector space (X, \tau).

  • If X is a pseudometrizable TVS then so is X / M.{{sfn|Narici|Beckenstein|2011|pp=91-95}}
  • If X is a complete pseudometrizable TVS and M is a closed vector subspace of X then X / M is complete.{{sfn|Narici|Beckenstein|2011|pp=91-95}}
  • If X is metrizable TVS and M is a closed vector subspace of X then X / M is metrizable.{{sfn|Narici|Beckenstein|2011|pp=91-95}}
  • If p is an F-seminorm on X, then the map P : X / M \to \R defined by

    P(x + M) := \inf_{} \{ p(x + m) : m \in M \}

    is an F-seminorm on X / M that induces the usual quotient topology on X / M.{{sfn|Narici|Beckenstein|2011|pp=91-95}} If in addition p is an F-norm on X and if M is a closed vector subspace of X then P is an F-norm on X.{{sfn|Narici|Beckenstein|2011|pp=91-95}}

Examples and sufficient conditions

  • Every seminormed space (X, p) is pseudometrizable with a canonical pseudometric given by d(x, y) := p(x - y) for all x, y \in X.{{sfn|Narici|Beckenstein|2011|pp=115-154}}.
  • If (X, d) is pseudometric TVS with a translation invariant pseudometric d, then p(x) := d(x, 0) defines a paranorm.{{sfn|Wilansky|2013|pp=15-16}} However, if d is a translation invariant pseudometric on the vector space X (without the addition condition that (X, d) is {{em|pseudometric TVS}}), then d need not be either an F-seminorm{{sfn|Schaefer|Wolff|1999|pp=91-92}} nor a paranorm.
  • If a TVS has a bounded neighborhood of the origin then it is pseudometrizable; the converse is in general false.{{sfn|Narici|Beckenstein|2011|pp=156-175}}
  • If a Hausdorff TVS has a bounded neighborhood of the origin then it is metrizable.{{sfn|Narici|Beckenstein|2011|pp=156-175}}
  • Suppose X is either a DF-space or an LM-space. If X is a sequential space then it is either metrizable or else a Montel DF-space.

If X is Hausdorff locally convex TVS then X with the strong topology, \left(X, b\left(X, X^{\prime}\right)\right), is metrizable if and only if there exists a countable set \mathcal{B} of bounded subsets of X such that every bounded subset of X is contained in some element of \mathcal{B}.{{sfn|Narici|Beckenstein|2011|pp=225-273}}

The strong dual space X_b^{\prime} of a metrizable locally convex space (such as a Fréchet spaceGabriyelyan, S.S. [https://arxiv.org/pdf/1412.1497.pdf "On topological spaces and topological groups with certain local countable networks] (2014)) X is a DF-space.{{sfn|Schaefer|Wolff|1999|p=154}}

The strong dual of a DF-space is a Fréchet space.{{sfn|Schaefer|Wolff|1999|p=196}}

The strong dual of a reflexive Fréchet space is a bornological space.{{sfn|Schaefer|Wolff|1999|p=154}}

The strong bidual (that is, the strong dual space of the strong dual space) of a metrizable locally convex space is a Fréchet space.{{sfn|Schaefer|Wolff|1999|p=153}}

If X is a metrizable locally convex space then its strong dual X_b^{\prime} has one of the following properties, if and only if it has all of these properties: (1) bornological, (2) infrabarreled, (3) barreled.{{sfn|Schaefer|Wolff|1999|p=153}}

=Normability=

A topological vector space is seminormable if and only if it has a convex bounded neighborhood of the origin.

Moreover, a TVS is normable if and only if it is Hausdorff and seminormable.{{sfn|Narici|Beckenstein|2011|pp=156-175}}

Every metrizable TVS on a finite-dimensional vector space is a normable locally convex complete TVS, being TVS-isomorphic to Euclidean space. Consequently, any metrizable TVS that is {{em|not}} normable must be infinite dimensional.

If M is a metrizable locally convex TVS that possess a countable fundamental system of bounded sets, then M is normable.{{sfn|Schaefer|Wolff|1999|pp=68-72}}

If X is a Hausdorff locally convex space then the following are equivalent:

  1. X is normable.
  2. X has a (von Neumann) bounded neighborhood of the origin.
  3. the strong dual space X^{\prime}_b of X is normable.{{sfn|Trèves|2006|p=201}}

and if this locally convex space X is also metrizable, then the following may be appended to this list:

  1. the strong dual space of X is metrizable.{{sfn|Trèves|2006|p=201}}
  2. the strong dual space of X is a Fréchet–Urysohn locally convex space.

In particular, if a metrizable locally convex space X (such as a Fréchet space) is {{em|not}} normable then its strong dual space X^{\prime}_b is not a Fréchet–Urysohn space and consequently, this complete Hausdorff locally convex space X^{\prime}_b is also neither metrizable nor normable.

Another consequence of this is that if X is a reflexive locally convex TVS whose strong dual X^{\prime}_b is metrizable then X^{\prime}_b is necessarily a reflexive Fréchet space, X is a DF-space, both X and X^{\prime}_b are necessarily complete Hausdorff ultrabornological distinguished webbed spaces, and moreover, X^{\prime}_b is normable if and only if X is normable if and only if X is Fréchet–Urysohn if and only if X is metrizable. In particular, such a space X is either a Banach space or else it is not even a Fréchet–Urysohn space.

Metrically bounded sets and bounded sets

Suppose that (X, d) is a pseudometric space and B \subseteq X.

The set B is metrically bounded or d-bounded if there exists a real number R > 0 such that d(x, y) \leq R for all x, y \in B;

the smallest such R is then called the diameter or d-diameter of B.{{sfn|Narici|Beckenstein|2011|pp=156-175}}

If B is bounded in a pseudometrizable TVS X then it is metrically bounded;

the converse is in general false but it is true for locally convex metrizable TVSs.{{sfn|Narici|Beckenstein|2011|pp=156-175}}

Properties of pseudometrizable TVS

{{Math theorem|name=Theorem{{sfn|Wilansky|2013|p=57}}|math_statement=

All infinite-dimensional separable complete metrizable TVS are homeomorphic.

}}

  • Every metrizable locally convex TVS is a quasibarrelled space,{{sfn|Jarchow|1981|p=222}} bornological space, and a Mackey space.
  • Every complete {{em|pseudo}}metrizable TVS is a barrelled space and a Baire space (and hence non-meager).{{sfn|Narici|Beckenstein|2011|pp=371-423}} However, there exist metrizable Baire spaces that are not complete.{{sfn|Narici|Beckenstein|2011|pp=371-423}}
  • If X is a metrizable locally convex space, then the strong dual of X is bornological if and only if it is barreled, if and only if it is infrabarreled.{{sfn|Schaefer|Wolff|1999|p=153}}
  • If X is a complete pseudometrizable TVS and M is a closed vector subspace of X, then X / M is complete.{{sfn|Narici|Beckenstein|2011|pp=91-95}}
  • The strong dual of a locally convex metrizable TVS is a webbed space.{{sfn|Narici|Beckenstein|2011|pp=459-483}}
  • If (X, \tau) and (X, \nu) are complete metrizable TVSs (i.e. F-spaces) and if \nu is coarser than \tau then \tau = \nu;{{sfn|Köthe|1969|p=168}} this is no longer guaranteed to be true if any one of these metrizable TVSs is not complete.{{sfn|Wilansky|2013|p=59}} Said differently, if (X, \tau) and (X, \nu) are both F-spaces but with different topologies, then neither one of \tau and \nu contains the other as a subset. One particular consequence of this is, for example, that if (X, p) is a Banach space and (X, q) is some other normed space whose norm-induced topology is finer than (or alternatively, is coarser than) that of (X, p) (i.e. if p \leq C q or if q \leq C p for some constant C > 0), then the only way that (X, q) can be a Banach space (i.e. also be complete) is if these two norms p and q are equivalent; if they are not equivalent, then (X, q) can not be a Banach space.

    As another consequence, if (X, p) is a Banach space and (X, \nu) is a Fréchet space, then the map p : (X, \nu) \to \R is continuous if and only if the Fréchet space (X, \nu) {{em|is}} the TVS (X, p) (here, the Banach space (X, p) is being considered as a TVS, which means that its norm is "forgetten" but its topology is remembered).

  • A metrizable locally convex space is normable if and only if its strong dual space is a Fréchet–Urysohn locally convex space.
  • Any product of complete metrizable TVSs is a Baire space.{{sfn|Narici|Beckenstein|2011|pp=371-423}}
  • A product of metrizable TVSs is metrizable if and only if it all but at most countably many of these TVSs have dimension 0.{{sfn|Schaefer|Wolff|1999|pp=12-35}}
  • A product of pseudometrizable TVSs is pseudometrizable if and only if it all but at most countably many of these TVSs have the trivial topology.
  • Every complete {{em|pseudo}}metrizable TVS is a barrelled space and a Baire space (and thus non-meager).{{sfn|Narici|Beckenstein|2011|pp=371-423}}
  • The dimension of a complete metrizable TVS is either finite or uncountable.{{sfn|Schaefer|Wolff|1999|pp=12-35}}

=Completeness=

{{Main|Complete topological vector space}}

Every topological vector space (and more generally, a topological group) has a canonical uniform structure, induced by its topology, which allows the notions of completeness and uniform continuity to be applied to it.

If X is a metrizable TVS and d is a metric that defines X's topology, then its possible that X is complete as a TVS (i.e. relative to its uniformity) but the metric d is {{em|not}} a complete metric (such metrics exist even for X = \R).

Thus, if X is a TVS whose topology is induced by a pseudometric d, then the notion of completeness of X (as a TVS) and the notion of completeness of the pseudometric space (X, d) are not always equivalent.

The next theorem gives a condition for when they are equivalent:

{{Math theorem|name=Theorem|math_statement=

If X is a pseudometrizable TVS whose topology is induced by a {{em|translation invariant}} pseudometric d, then d is a complete pseudometric on X if and only if X is complete as a TVS.{{sfn|Narici|Beckenstein|2011|pp=47-50}}

}}

{{Math theorem|name=Theorem{{sfn|Schaefer|Wolff|1999|p=35}}{{Cite journal|last1=Klee|first1=V. L.|title=Invariant metrics in groups (solution of a problem of Banach)|year=1952|journal=Proc. Amer. Math. Soc.|volume=3|issue=3|pages=484–487|url=https://www.ams.org/journals/proc/1952-003-03/S0002-9939-1952-0047250-4/S0002-9939-1952-0047250-4.pdf|doi = 10.1090/s0002-9939-1952-0047250-4 |doi-access=free}}|note=Klee|math_statement=

Let d be {{em|any}}Not assumed to be translation-invariant. metric on a vector space X such that the topology \tau induced by d on X makes (X, \tau) into a topological vector space. If (X, d) is a complete metric space then (X, \tau) is a complete-TVS.

}}

{{Math theorem|name=Theorem|math_statement=

If X is a TVS whose topology is induced by a paranorm p, then X is complete if and only if for every sequence \left(x_i\right)_{i=1}^{\infty} in X, if \sum_{i=1}^{\infty} p\left(x_i\right) < \infty then \sum_{i=1}^{\infty} x_i converges in X.{{sfn|Wilansky|2013|pp=56-57}}

}}

If M is a closed vector subspace of a complete pseudometrizable TVS X, then the quotient space X / M is complete.{{sfn|Narici|Beckenstein|2011|pp=47-66}}

If M is a {{em|complete}} vector subspace of a metrizable TVS X and if the quotient space X / M is complete then so is X.{{sfn|Narici|Beckenstein|2011|pp=47-66}} If X is not complete then M := X, but not complete, vector subspace of X.

A Baire separable topological group is metrizable if and only if it is cosmic.Gabriyelyan, S.S. [https://arxiv.org/pdf/1412.1497.pdf "On topological spaces and topological groups with certain local countable networks] (2014)

=Subsets and subsequences=

  • Let M be a separable locally convex metrizable topological vector space and let C be its completion. If S is a bounded subset of C then there exists a bounded subset R of X such that S \subseteq \operatorname{cl}_C R.{{sfn|Schaefer|Wolff|1999|pp=190-202}}
  • Every totally bounded subset of a locally convex metrizable TVS X is contained in the closed convex balanced hull of some sequence in X that converges to 0.
  • In a pseudometrizable TVS, every bornivore is a neighborhood of the origin.{{sfn|Narici|Beckenstein|2011|pp=172-173}}
  • If d is a translation invariant metric on a vector space X, then d(n x, 0) \leq n d(x, 0) for all x \in X and every positive integer n.{{sfn|Rudin|1991|p=22}}
  • If \left(x_i\right)_{i=1}^{\infty} is a null sequence (that is, it converges to the origin) in a metrizable TVS then there exists a sequence \left(r_i\right)_{i=1}^{\infty} of positive real numbers diverging to \infty such that \left(r_i x_i\right)_{i=1}^{\infty} \to 0.{{sfn|Rudin|1991|p=22}}
  • A subset of a complete metric space is closed if and only if it is complete. If a space X is not complete, then X is a closed subset of X that is not complete.
  • If X is a metrizable locally convex TVS then for every bounded subset B of X, there exists a bounded disk D in X such that B \subseteq X_D, and both X and the auxiliary normed space X_D induce the same subspace topology on B.{{sfn|Narici|Beckenstein|2011|pp=441-457}}

{{Math theorem|name=Banach-Saks theorem{{sfn|Rudin|1991|p=67}}|math_statement=

If \left(x_n\right)_{n=1}^{\infty} is a sequence in a locally convex metrizable TVS (X, \tau) that converges {{em|weakly}} to some x \in X, then there exists a sequence y_{\bull} = \left(y_i\right)_{i=1}^{\infty} in X such that y_{\bull} \to x in (X, \tau) and each y_i is a convex combination of finitely many x_n.

}}

{{Math theorem|name=Mackey's countability condition{{sfn|Narici|Beckenstein|2011|pp=156-175}}|math_statement=

Suppose that X is a locally convex metrizable TVS and that \left(B_i\right)_{i=1}^{\infty} is a countable sequence of bounded subsets of X.

Then there exists a bounded subset B of X and a sequence \left(r_i\right)_{i=1}^{\infty} of positive real numbers such that B_i \subseteq r_i B for all i.

}}

Generalized series

As described in this article's section on generalized series, for any I-indexed family family \left(r_i\right)_{i \in I} of vectors from a TVS X, it is possible to define their sum \textstyle\sum\limits_{i \in I} r_i as the limit of the net of finite partial sums F \in \operatorname{FiniteSubsets}(I) \mapsto \textstyle\sum\limits_{i \in F} r_i where the domain \operatorname{FiniteSubsets}(I) is directed by \,\subseteq.\,

If I = \N and X = \Reals, for instance, then the generalized series \textstyle\sum\limits_{i \in \N} r_i converges if and only if \textstyle\sum\limits_{i=1}^\infty r_i converges unconditionally in the usual sense (which for real numbers, is equivalent to absolute convergence).

If a generalized series \textstyle\sum\limits_{i \in I} r_i converges in a metrizable TVS, then the set \left\{i \in I : r_i \neq 0\right\} is necessarily countable (that is, either finite or countably infinite);

in other words, all but at most countably many r_i will be zero and so this generalized series \textstyle\sum\limits_{i \in I} r_i ~=~ \textstyle\sum\limits_{\stackrel{i \in I}{r_i \neq 0}} r_i is actually a sum of at most countably many non-zero terms.

=Linear maps=

If X is a pseudometrizable TVS and A maps bounded subsets of X to bounded subsets of Y, then A is continuous.{{sfn|Narici|Beckenstein|2011|pp=156-175}}

Discontinuous linear functionals exist on any infinite-dimensional pseudometrizable TVS.{{sfn|Narici|Beckenstein|2011|p=125}} Thus, a pseudometrizable TVS is finite-dimensional if and only if its continuous dual space is equal to its algebraic dual space.{{sfn|Narici|Beckenstein|2011|p=125}}

If F : X \to Y is a linear map between TVSs and X is metrizable then the following are equivalent:

  1. F is continuous;
  2. F is a (locally) bounded map (that is, F maps (von Neumann) bounded subsets of X to bounded subsets of Y);{{sfn|Jarchow|1981|pp=38-42}}
  3. F is sequentially continuous;{{sfn|Jarchow|1981|pp=38-42}}
  4. the image under F of every null sequence in X is a bounded set{{sfn|Jarchow|1981|pp=38-42}} where by definition, a {{em|null sequence}} is a sequence that converges to the origin.
  5. F maps null sequences to null sequences;

Open and almost open maps

:Theorem: If X is a complete pseudometrizable TVS, Y is a Hausdorff TVS, and T : X \to Y is a closed and almost open linear surjection, then T is an open map.{{sfn|Narici|Beckenstein|2011|pp=466-468}}

:Theorem: If T : X \to Y is a surjective linear operator from a locally convex space X onto a barrelled space Y (e.g. every complete pseudometrizable space is barrelled) then T is almost open.{{sfn|Narici|Beckenstein|2011|pp=466-468}}

:Theorem: If T : X \to Y is a surjective linear operator from a TVS X onto a Baire space Y then T is almost open.{{sfn|Narici|Beckenstein|2011|pp=466-468}}

:Theorem: Suppose T : X \to Y is a continuous linear operator from a complete pseudometrizable TVS X into a Hausdorff TVS Y. If the image of T is non-meager in Y then T : X \to Y is a surjective open map and Y is a complete metrizable space.{{sfn|Narici|Beckenstein|2011|pp=466-468}}

=Hahn-Banach extension property=

{{Main|Hahn-Banach theorem}}

A vector subspace M of a TVS X has the extension property if any continuous linear functional on M can be extended to a continuous linear functional on X.{{sfn|Narici|Beckenstein|2011|pp=225-273}}

Say that a TVS X has the Hahn-Banach extension property (HBEP) if every vector subspace of X has the extension property.{{sfn|Narici|Beckenstein|2011|pp=225-273}}

The Hahn-Banach theorem guarantees that every Hausdorff locally convex space has the HBEP.

For complete metrizable TVSs there is a converse:

{{Math theorem|name=Theorem|note=Kalton|math_statement=

Every complete metrizable TVS with the Hahn-Banach extension property is locally convex.{{sfn|Narici|Beckenstein|2011|pp=225-273}}

}}

If a vector space X has uncountable dimension and if we endow it with the finest vector topology then this is a TVS with the HBEP that is neither locally convex or metrizable.{{sfn|Narici|Beckenstein|2011|pp=225-273}}

See also

  • {{annotated link|Asymmetric norm}}
  • {{annotated link|Complete metric space}}
  • {{annotated link|Complete topological vector space}}
  • {{annotated link|Equivalence of metrics}}
  • {{annotated link|F-space}}
  • {{annotated link|Fréchet space}}
  • {{annotated link|Generalised metric}}
  • {{annotated link|K-space (functional analysis)}}
  • {{annotated link|Locally convex topological vector space}}
  • {{annotated link|Metric space}}
  • {{annotated link|Pseudometric space}}
  • {{annotated link|Relation of norms and metrics}}
  • {{annotated link|Seminorm}}
  • {{annotated link|Sublinear function}}
  • {{annotated link|Uniform space}}
  • {{annotated link|Ursescu theorem}}

Notes

{{reflist|group=note}}

Proofs

{{reflist|group=proof|refs=

Suppose the net \textstyle\sum\limits_{i \in I} r_i ~\stackrel{\scriptscriptstyle\text{def}}{=}~ {\textstyle\lim\limits_{A \in \operatorname{FiniteSubsets}(I)}} \ \textstyle\sum\limits_{i \in A} r_i = \lim \left\{\textstyle\sum\limits_{i\in A} r_i \,: A \subseteq I, A \text{ finite }\right\} converges to some point in a metrizable TVS X, where recall that this net's domain is the directed set (\operatorname{FiniteSubsets}(I), \subseteq).

Like every convergent net, this convergent net of partial sums A \mapsto \textstyle\sum\limits_{i \in A} r_i is a {{em|Cauchy net}}, which for this particular net means (by definition) that for every neighborhood W of the origin in X, there exists a finite subset A_0 of I such that

\textstyle\sum\limits_{i \in B} r_i - \textstyle\sum\limits_{i \in C} r_i \in W for all finite supersets B, C \supseteq A_0;

this implies that r_i \in W for every i \in I \setminus A_0 (by taking B := A_0 \cup \{i\} and C := A_0).

Since X is metrizable, it has a countable neighborhood basis U_1, U_2, \ldots at the origin, whose intersection is necessarily U_1 \cap U_2 \cap \cdots = \{0\} (since X is a Hausdorff TVS).

For every positive integer n \in \N, pick a finite subset A_n \subseteq I such that r_i \in U_n for every i \in I \setminus A_n.

If i belongs to (I \setminus A_1) \cap (I \setminus A_2) \cap \cdots = I \setminus \left(A_1 \cup A_2 \cup \cdots\right) then r_i belongs to U_1 \cap U_2 \cap \cdots = \{0\}.

Thus r_i = 0 for every index i \in I that does not belong to the countable set A_1 \cup A_2 \cup \cdots. \blacksquare

}}

References

{{reflist}}

Bibliography

  • {{Berberian Lectures in Functional Analysis and Operator Theory}}
  • {{Bourbaki Topological Vector Spaces}}
  • {{cite journal|last=Bourbaki|first=Nicolas|authorlink=Nicolas Bourbaki|journal=Annales de l'Institut Fourier|language=French|mr=0042609|pages=5–16 (1951)|title=Sur certains espaces vectoriels topologiques|url=|volume=2|year=1950| doi=10.5802/aif.16|doi-access=free}}
  • {{Edwards Functional Analysis Theory and Applications}}
  • {{Grothendieck Topological Vector Spaces}}
  • {{Jarchow Locally Convex Spaces}}
  • {{Khaleelulla Counterexamples in Topological Vector Spaces}}
  • {{Köthe Topological Vector Spaces I}}
  • {{Köthe Topological Vector Spaces II}}
  • {{Narici Beckenstein Topological Vector Spaces|edition=2}}
  • {{Rudin Walter Functional Analysis|edition=2}}
  • {{Robertson Topological Vector Spaces}}
  • {{Schaefer Wolff Topological Vector Spaces|edition=2}}
  • {{Schechter Handbook of Analysis and Its Foundations}}
  • {{Swartz An Introduction to Functional Analysis}}
  • {{Trèves François Topological vector spaces, distributions and kernels}}
  • {{Wilansky Modern Methods in Topological Vector Spaces}}
  • {{cite book|last=Husain|first=Taqdir|title=Barrelledness in topological and ordered vector spaces|publisher=Springer-Verlag|location=Berlin New York|year=1978|isbn=3-540-09096-7|oclc=4493665 }}

{{Functional analysis}}

{{Topological vector spaces}}

{{Metric spaces}}

Category:Metric spaces

Category:Topological vector spaces