Seminormed Rings Jan 23 2020.Pdf

Total Page:16

File Type:pdf, Size:1020Kb

Seminormed Rings Jan 23 2020.Pdf 1.2.SEMINORMEDRINGS 29 January 23, 2020, 3:12pm 1.2. Seminormed rings All rings will be commutative with identity, denoted by 1. All ring homomorphisms take the identity to the identity. If R is a ring, we write R⇥ := R 0 . \{ } 1.2.1. Seminormed rings. A seminorm on a ring A is a seminorm on the underlying abelian group that satisfies 1 1 and is submultiplicative in the sense thatk·kab a b for all a, b A.Thisimplies 1k k=1unless is the zero seminorm. A seminormedk kk ringkis·k ak pair (A, 2), where A is a ringk andk is a seminormk·k on A.Anormed ring is a seminormed ring for whichk·k the seminorm is a norm.k A·kBanach ring is a complete normed ring. A normed field (resp. Banach field) is a normed (resp. Banach) ring that is also a field. Lemma 1.2.1. If is a nonzero seminorm on a ring A, then a =0for all invertible elements a A. As a consequence,k·k a nonzero seminorm on a field is a norm.k k6 2 1 Proof. If a A is invertible, then 1 = 1 a a− ,so a = 0. 2 k kk k·k k k k6 ⇤ A morphism of seminormed rings is a bounded ring homomorphism. As in the case of semigroups, there are two natural categories of seminormed rings, using bounded homomorphisms and contractive homomorphisms as morphisms, respectively. Each category has several full subcategories in which the objects are normed or even Banach rings, and/or are non-Archimedean. Some properties of these categories are developed in the exercises. 1.2.2. Power-multiplicative norms and valuations. We often require seminorms to satisfy stronger conditions than being submultiplicative. For instance, we say that a seminorm on A is power-multiplicative if an = a n for n 1. For such norms, we have the following usefulk· criterion.k k k k k ≥ Lemma 1.2.2. A power-multiplicative seminorm on a ring A is non-Archimedean i↵ n 1 for all n Z. k·k k k 2 The inequality n 1 can be interpreted as the failure of Archimedes’ axiom. k k Proof. The direct implication is trivial. Now suppose n 1 for all n and pick a, b A. For any n 1wehave k k 2 ≥ 1/n n n 1/n n j n j a + b = (a + b) = a b − k k k k j j=0 ✓ ◆ X 1/n n n j n j 1/n a b − (n + 1) max a , b . 0 k j kk k k k 1 {k k k k} j=0 X ✓ ◆ 1/n @ A Since limn (n + 1) = 1, this proves that a + b max a , b . ⇤ !1 k k {k k k k} A seminorm on a ring A is multiplicative if 1 = 1 and ab = a b for a, b A. More generally, ank· elementk a A is multiplicative if abk k= a b kfork all bk kA·.k Ak multiplicative2 seminorm will be called a semivaluation2 .3 k k k k·k k 2 A multiplicative norm on a ring A is called a valuation; we then call (A, )avalued ring. In this case, A must be an integralk·k domain, and extends uniquely to a valuationk·k on the fraction field Frac(A), see Exercise 1.2.7, so (Frac(A), k·)k is therefore a valued field. Valued fields will be studied in 1.3. We shall often denote a valuationk·k on a field by instead of . § |·| k·k 3When is the zero seminorm, the terminology is a bit inconsistent: every element is multiplicative but the k·k seminorm is not multiplicative. should address this at some point! 30 1.SEMINORMEDCOMMUTATIVEALGEBRA Remark 1.2.3. In the literature, valuations are usually assumed non-Archimedean and are often written additively, so that a valuation on a ring A becomes a function v : A⇥ R satisfying v(1) = 0, ! v(a+b) min v(a),v(b) , and v(ab)=v(a)+v(b) for a, b A⇥. To such a function we can associate a valuation≥ (in the{ sense above)} by setting = "v,where"2 (0, 1) is an arbitrary constant. Following Berkovich we shall work multiplicatively,|·| even though, in2 some situations, the additive convention may seem more natural. Remark 1.2.4. It is also possible to consider more general norms and seminorms. Consider an ordered abelian group Γ, with group operation written multiplicatively. Equip Γ 0 with the ordering from Γtogether with 0 <γfor every γ Γ. A (non-Archimedean) Krull seminormt{ } on a ring A is now given by a function : A Γ 2 0 satisfying 0 = 0, 1 1, a = a for a A, a + b max a , b k,· andk ab! ta{ }b for a, b kAk. A Krullk k seminormk isk a Krullk k norm2if a k=0ik↵a = 0,{ andk k itk isk} a Krullk valuationkk kkif kab = a2 b for all a, b A. In the theory of adic spaces,k k general Krull valuations (there simply calledk k valuations)k kk k play a key2 role, whereas for Berkovich spaces the focus is on the case Γ= R+⇥. 1.2.3. Operations. Many of the operations on semigroups extend to semirings. The proofs of the following simple properties are relegated to the exercises. A subring of a seminormed ring becomes a seminormed ring in the subspace seminorm. The same is true for normed rings and Banach rings. If a A is an ideal, then the quotient ring A/a is a seminormed ring in the quotient seminorm. If A is a seminormed⇢ ring, then the separation (resp. completion, resp. separated completion) of A is a normed (resp. complete seminormed, resp. Banach) ring. The product of a family of seminormed rings is a seminormed ring. Similarly, the direct limit (resp. complete direct limit) of a direct system of seminormed rings is a seminormed (resp. Banach) ring. There is also a localization procedure for seminormed ring. This is discussed in the more general context of seminormed modules, see 1.4.3. § 1.2.4. Examples. Examples of seminormed rings abound. Here is a small sample. Other examples can be built from these using operations such as products and relative polydisc algebras, see 1.8. § Example 1.2.5. Any ring A equipped with the trivial norm,definedby 0 = 0 and a =1 for a = 0 is a non-Archimedean Banach ring. This example, which at first mayk appeark irrelevant,k k in fact has6 interesting applications. Example 1.2.6. The field C is a Banach field with respect to the usual valuation ,see Example 1.1.5. The valued subfield (R, ) is also a Banach field, whereas the further|·| subfield1 (Q, ) is not a Banach field: its completion|·|1 is of course (R, ). The valued subring (Z, ) is a|·| Banach1 ring. |·|1 |·|1 Example 1.2.7. The field C can be equipped with the hybrid norm,definedby := k·khyb max 0, ,where 0 and are the trivial and usual absolute value on C,respectively. The{| hybrid · | |·| norm1} is power-multiplicative,|·| |·|1 but not multiplicative. Example 1.2.8. Given a prime p and a real number " (0, 1), define a p-adic valuation p," on n b 2 n |·| Q as follows: for a Q⇥,writea = p ,whereb, c Z and p - bc;then a p," := " . The (separated) 2 c 2 | | completion Qp," of Q with respect to this valuation is a the field of p-adic numbers. Arithmetic considerations sometimes dictate a natural choice of ", such as " =1/p. Example 1.2.9. Let k be any field, and r R+⇥. As in Example 1.1.10, the polynomial ring k[T ] 2 i min i ai=0 can be equipped with the following norm: i aiT = r { | 6 }. This norm is non-Archimedean, multiplicative, and restricts to the trivialk norm onkk.Whenr 1, k[T ] is a Banach ring. When r<1, the completion of k[T ]istheringkP[[ T ]] of formal power≥ series, equipped with a valuation 1.2.SEMINORMEDRINGS 31 satisfying the same formula as above. In this case, the fraction field of k[[ T ]] i s t h e fi e l d k(( T )) of formal Laurent series. The valuation on k(( T )) again satisfies the same formula and is complete, so k(( T )) is a complete valued field. Example 1.2.10. As a variant of Example 1.2.9, let k be a field and r R+⇥.Providek[T ]with i i 2 the following norm: aiT = r . This restricts to the trivial norm on k,butisneither k i k i ai=0 non-Archimedean nor multiplicative,{ nor| 6 complete} for any r. See Exercise 1.2.26. P P Example 1.2.11. We can give a multi-variable generalization of Example 1.2.9 as follows. Given r ,...,r R⇥, we can define a monomial valuation on the polynomial ring k[T ,...,T ]by 1 n 2 + k·kr 1 n a T ⌫ := max r⌫ a =0 , k ⌫ kr { | ⌫ 6 } ⌫ Zn X2 + ⌫ n ⌫i ⌫ n ⌫i where we use the multi-index notation T = i=1 Ti and r = i=1 ri for ⌫ =(⌫1,...,⌫n). We will further generalize this construction, as well as the multivariable version of Example 1.2.10, in 1.8. Q Q § Example 1.2.12. If A is a ring and a A is an ideal, then we define an a-adic seminorm on A ⇢ n orda(a) as follows.
Recommended publications
  • Boundedness in Linear Topological Spaces
    BOUNDEDNESS IN LINEAR TOPOLOGICAL SPACES BY S. SIMONS Introduction. Throughout this paper we use the symbol X for a (real or complex) linear space, and the symbol F to represent the basic field in question. We write R+ for the set of positive (i.e., ^ 0) real numbers. We use the term linear topological space with its usual meaning (not necessarily Tx), but we exclude the case where the space has the indiscrete topology (see [1, 3.3, pp. 123-127]). A linear topological space is said to be a locally bounded space if there is a bounded neighbourhood of 0—which comes to the same thing as saying that there is a neighbourhood U of 0 such that the sets {(1/n) U} (n = 1,2,—) form a base at 0. In §1 we give a necessary and sufficient condition, in terms of invariant pseudo- metrics, for a linear topological space to be locally bounded. In §2 we discuss the relationship of our results with other results known on the subject. In §3 we introduce two ways of classifying the locally bounded spaces into types in such a way that each type contains exactly one of the F spaces (0 < p ^ 1), and show that these two methods of classification turn out to be identical. Also in §3 we prove a metrization theorem for locally bounded spaces, which is related to the normal metrization theorem for uniform spaces, but which uses a different induction procedure. In §4 we introduce a large class of linear topological spaces which includes the locally convex spaces and the locally bounded spaces, and for which one of the more important results on boundedness in locally convex spaces is valid.
    [Show full text]
  • Functional Analysis 1 Winter Semester 2013-14
    Functional analysis 1 Winter semester 2013-14 1. Topological vector spaces Basic notions. Notation. (a) The symbol F stands for the set of all reals or for the set of all complex numbers. (b) Let (X; τ) be a topological space and x 2 X. An open set G containing x is called neigh- borhood of x. We denote τ(x) = fG 2 τ; x 2 Gg. Definition. Suppose that τ is a topology on a vector space X over F such that • (X; τ) is T1, i.e., fxg is a closed set for every x 2 X, and • the vector space operations are continuous with respect to τ, i.e., +: X × X ! X and ·: F × X ! X are continuous. Under these conditions, τ is said to be a vector topology on X and (X; +; ·; τ) is a topological vector space (TVS). Remark. Let X be a TVS. (a) For every a 2 X the mapping x 7! x + a is a homeomorphism of X onto X. (b) For every λ 2 F n f0g the mapping x 7! λx is a homeomorphism of X onto X. Definition. Let X be a vector space over F. We say that A ⊂ X is • balanced if for every α 2 F, jαj ≤ 1, we have αA ⊂ A, • absorbing if for every x 2 X there exists t 2 R; t > 0; such that x 2 tA, • symmetric if A = −A. Definition. Let X be a TVS and A ⊂ X. We say that A is bounded if for every V 2 τ(0) there exists s > 0 such that for every t > s we have A ⊂ tV .
    [Show full text]
  • HYPERCYCLIC SUBSPACES in FRÉCHET SPACES 1. Introduction
    PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 134, Number 7, Pages 1955–1961 S 0002-9939(05)08242-0 Article electronically published on December 16, 2005 HYPERCYCLIC SUBSPACES IN FRECHET´ SPACES L. BERNAL-GONZALEZ´ (Communicated by N. Tomczak-Jaegermann) Dedicated to the memory of Professor Miguel de Guzm´an, who died in April 2004 Abstract. In this note, we show that every infinite-dimensional separable Fr´echet space admitting a continuous norm supports an operator for which there is an infinite-dimensional closed subspace consisting, except for zero, of hypercyclic vectors. The family of such operators is even dense in the space of bounded operators when endowed with the strong operator topology. This completes the earlier work of several authors. 1. Introduction and notation Throughout this paper, the following standard notation will be used: N is the set of positive integers, R is the real line, and C is the complex plane. The symbols (mk), (nk) will stand for strictly increasing sequences in N.IfX, Y are (Hausdorff) topological vector spaces (TVSs) over the same field K = R or C,thenL(X, Y ) will denote the space of continuous linear mappings from X into Y , while L(X)isthe class of operators on X,thatis,L(X)=L(X, X). The strong operator topology (SOT) in L(X) is the one where the convergence is defined as pointwise convergence at every x ∈ X. A sequence (Tn) ⊂ L(X, Y )issaidtobeuniversal or hypercyclic provided there exists some vector x0 ∈ X—called hypercyclic for the sequence (Tn)—such that its orbit {Tnx0 : n ∈ N} under (Tn)isdenseinY .
    [Show full text]
  • Uniqueness of Von Neumann Bornology in Locally C∗-Algebras
    Scientiae Mathematicae Japonicae Online, e-2009 91 UNIQUENESS OF VON NEUMANN BORNOLOGY IN LOCALLY C∗-ALGEBRAS. A BORNOLOGICAL ANALOGUE OF JOHNSON’S THEOREM M. Oudadess Received May 31, 2008; revised March 20, 2009 Abstract. All locally C∗- structures on a commutative complex algebra have the same bound structure. It is also shown that a Mackey complete C∗-convex algebra is semisimple. By the well-known Johnson’s theorem [4], there is on a given complex semi-simple algebra a unique (up to an isomorphism) Banach algebra norm. R. C. Carpenter extended this result to commutative Fr´echet locally m-convex algebras [3]. Without metrizability, it is not any more valid even in the rich context of locally C∗-convex algebras. Below there are given telling examples where even a C∗-algebra structure is involved. We follow the terminology of [5], pp. 101-102. Let E be an involutive algebra and p a vector space seminorm on E. We say that p is a C∗-seminorm if p(x∗x)=[p(x)]2, for every x. An involutive topological algebra whose topology is defined by a (saturated) family of C∗-seminorms is called a C∗-convex algebra. A complete C∗-convex algebra is called a locally C∗-algebra (by Inoue). A Fr´echet C∗-convex algebra is a metrizable C∗- convex algebra, that is equivalently a metrizable locally C∗-algebra, or also a Fr´echet locally C∗-algebra. All the bornological notions can be found in [6]. The references for m-convexity are [5], [8] and [9]. Let us recall for convenience that the bounded structure (bornology) of a locally convex algebra (l.c.a.)(E,τ) is the collection Bτ of all the subsets B of E which are bounded in the sense of Kolmogorov and von Neumann, that is B is absorbed by every neighborhood of the origin (see e.g.
    [Show full text]
  • L P and Sobolev Spaces
    NOTES ON Lp AND SOBOLEV SPACES STEVE SHKOLLER 1. Lp spaces 1.1. Definitions and basic properties. Definition 1.1. Let 0 < p < 1 and let (X; M; µ) denote a measure space. If f : X ! R is a measurable function, then we define 1 Z p p kfkLp(X) := jfj dx and kfkL1(X) := ess supx2X jf(x)j : X Note that kfkLp(X) may take the value 1. Definition 1.2. The space Lp(X) is the set p L (X) = ff : X ! R j kfkLp(X) < 1g : The space Lp(X) satisfies the following vector space properties: (1) For each α 2 R, if f 2 Lp(X) then αf 2 Lp(X); (2) If f; g 2 Lp(X), then jf + gjp ≤ 2p−1(jfjp + jgjp) ; so that f + g 2 Lp(X). (3) The triangle inequality is valid if p ≥ 1. The most interesting cases are p = 1; 2; 1, while all of the Lp arise often in nonlinear estimates. Definition 1.3. The space lp, called \little Lp", will be useful when we introduce Sobolev spaces on the torus and the Fourier series. For 1 ≤ p < 1, we set ( 1 ) p 1 X p l = fxngn=1 j jxnj < 1 : n=1 1.2. Basic inequalities. Lemma 1.4. For λ 2 (0; 1), xλ ≤ (1 − λ) + λx. Proof. Set f(x) = (1 − λ) + λx − xλ; hence, f 0(x) = λ − λxλ−1 = 0 if and only if λ(1 − xλ−1) = 0 so that x = 1 is the critical point of f. In particular, the minimum occurs at x = 1 with value f(1) = 0 ≤ (1 − λ) + λx − xλ : Lemma 1.5.
    [Show full text]
  • Fact Sheet Functional Analysis
    Fact Sheet Functional Analysis Literature: Hackbusch, W.: Theorie und Numerik elliptischer Differentialgleichungen. Teubner, 1986. Knabner, P., Angermann, L.: Numerik partieller Differentialgleichungen. Springer, 2000. Triebel, H.: H¨ohere Analysis. Harri Deutsch, 1980. Dobrowolski, M.: Angewandte Funktionalanalysis, Springer, 2010. 1. Banach- and Hilbert spaces Let V be a real vector space. Normed space: A norm is a mapping k · k : V ! [0; 1), such that: kuk = 0 , u = 0; (definiteness) kαuk = jαj · kuk; α 2 R; u 2 V; (positive scalability) ku + vk ≤ kuk + kvk; u; v 2 V: (triangle inequality) The pairing (V; k · k) is called a normed space. Seminorm: In contrast to a norm there may be elements u 6= 0 such that kuk = 0. It still holds kuk = 0 if u = 0. Comparison of two norms: Two norms k · k1, k · k2 are called equivalent if there is a constant C such that: −1 C kuk1 ≤ kuk2 ≤ Ckuk1; u 2 V: If only one of these inequalities can be fulfilled, e.g. kuk2 ≤ Ckuk1; u 2 V; the norm k · k1 is called stronger than the norm k · k2. k · k2 is called weaker than k · k1. Topology: In every normed space a canonical topology can be defined. A subset U ⊂ V is called open if for every u 2 U there exists a " > 0 such that B"(u) = fv 2 V : ku − vk < "g ⊂ U: Convergence: A sequence vn converges to v w.r.t. the norm k · k if lim kvn − vk = 0: n!1 1 A sequence vn ⊂ V is called Cauchy sequence, if supfkvn − vmk : n; m ≥ kg ! 0 for k ! 1.
    [Show full text]
  • Basic Differentiable Calculus Review
    Basic Differentiable Calculus Review Jimmie Lawson Department of Mathematics Louisiana State University Spring, 2003 1 Introduction Basic facts about the multivariable differentiable calculus are needed as back- ground for differentiable geometry and its applications. The purpose of these notes is to recall some of these facts. We state the results in the general context of Banach spaces, although we are specifically concerned with the finite-dimensional setting, specifically that of Rn. Let U be an open set of Rn. A function f : U ! R is said to be a Cr map for 0 ≤ r ≤ 1 if all partial derivatives up through order r exist for all points of U and are continuous. In the extreme cases C0 means that f is continuous and C1 means that all partials of all orders exists and are continuous on m r r U. A function f : U ! R is a C map if fi := πif is C for i = 1; : : : ; m, m th where πi : R ! R is the i projection map defined by πi(x1; : : : ; xm) = xi. It is a standard result that mixed partials of degree less than or equal to r and of the same type up to interchanges of order are equal for a C r-function (sometimes called Clairaut's Theorem). We can consider a category with objects nonempty open subsets of Rn for various n and morphisms Cr-maps. This is indeed a category, since the composition of Cr maps is again a Cr map. 1 2 Normed Spaces and Bounded Linear Oper- ators At the heart of the differential calculus is the notion of a differentiable func- tion.
    [Show full text]
  • Appropriate Locally Convex Domains for Differential
    PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 86, Number 2, October 1982 APPROPRIATE LOCALLYCONVEX DOMAINS FOR DIFFERENTIALCALCULUS RICHARD A. GRAFF AND WOLFGANG M. RUESS Abstract. We make use of Grothendieck's notion of quasinormability to produce a comprehensive class of locally convex spaces within which differential calculus may be developed along the same lines as those employed within the class of Banach spaces and which include the previously known examples of such classes. In addition, we show that there exist Fréchet spaces which do not belong to any possible such class. 0. Introduction. In [2], the first named author introduced a theory of differential calculus in locally convex spaces. This theory differs from previous approaches to the subject in that the theory was an attempt to isolate a class of locally convex spaces to which the usual techniques of Banach space differential calculus could be extended, rather than an attempt to develop a theory of differential calculus for all locally convex spaces. Indeed, the original purpose of the theory was to study the maps which smooth nonlinear partial differential operators induce between Sobolev spaces by investigating the differentiability of these mappings with respect to a weaker (nonnormable) topology on the Sobolev spaces. The class of locally convex spaces thus isolated (the class of Z)-spaces, see Definition 1 below) was shown to include Banach spaces and several types of Schwartz spaces. A natural question to ask is whether there exists an easily-char- acterized class of D-spaces to which both of these classes belong. We answer this question in the affirmative in Theorem 1 below, the proof of which presents a much clearer picture of the nature of the key property of Z)-spaces than the corresponding result [2, Theorem 3.46].
    [Show full text]
  • Normed Linear Spaces of Continuous Functions
    NORMED LINEAR SPACES OF CONTINUOUS FUNCTIONS S. B. MYERS 1. Introduction. In addition to its well known role in analysis, based on measure theory and integration, the study of the Banach space B(X) of real bounded continuous functions on a topological space X seems to be motivated by two major objectives. The first of these is the general question as to relations between the topological properties of X and the properties (algebraic, topological, metric) of B(X) and its linear subspaces. The impetus to the study of this question has been given by various results which show that, under certain natural restrictions on X, the topological structure of X is completely determined by the structure of B{X) [3; 16; 7],1 and even by the structure of a certain type of subspace of B(X) [14]. Beyond these foundational theorems, the results are as yet meager and exploratory. It would be exciting (but surprising) if some natural metric property of B(X) were to lead to the unearthing of a new topological concept or theorem about X. The second goal is to obtain information about the structure and classification of real Banach spaces. The hope in this direction is based on the fact that every Banach space is (equivalent to) a linear subspace of B(X) [l] for some compact (that is, bicompact Haus- dorff) X. Properties have been found which characterize the spaces B(X) among all Banach spaces [ô; 2; 14], and more generally, prop­ erties which characterize those Banach spaces which determine the topological structure of some compact or completely regular X [14; 15].
    [Show full text]
  • Locally Convex Spaces Manv 250067-1, 5 Ects, Summer Term 2017 Sr 10, Fr
    LOCALLY CONVEX SPACES MANV 250067-1, 5 ECTS, SUMMER TERM 2017 SR 10, FR. 13:15{15:30 EDUARD A. NIGSCH These lecture notes were developed for the topics course locally convex spaces held at the University of Vienna in summer term 2017. Prerequisites consist of general topology and linear algebra. Some background in functional analysis will be helpful but not strictly mandatory. This course aims at an early and thorough development of duality theory for locally convex spaces, which allows for the systematic treatment of the most important classes of locally convex spaces. Further topics will be treated according to available time as well as the interests of the students. Thanks for corrections of some typos go out to Benedict Schinnerl. 1 [git] • 14c91a2 (2017-10-30) LOCALLY CONVEX SPACES 2 Contents 1. Introduction3 2. Topological vector spaces4 3. Locally convex spaces7 4. Completeness 11 5. Bounded sets, normability, metrizability 16 6. Products, subspaces, direct sums and quotients 18 7. Projective and inductive limits 24 8. Finite-dimensional and locally compact TVS 28 9. The theorem of Hahn-Banach 29 10. Dual Pairings 34 11. Polarity 36 12. S-topologies 38 13. The Mackey Topology 41 14. Barrelled spaces 45 15. Bornological Spaces 47 16. Reflexivity 48 17. Montel spaces 50 18. The transpose of a linear map 52 19. Topological tensor products 53 References 66 [git] • 14c91a2 (2017-10-30) LOCALLY CONVEX SPACES 3 1. Introduction These lecture notes are roughly based on the following texts that contain the standard material on locally convex spaces as well as more advanced topics.
    [Show full text]
  • Bounded Operator - Wikipedia, the Free Encyclopedia
    Bounded operator - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Bounded_operator Bounded operator From Wikipedia, the free encyclopedia In functional analysis, a branch of mathematics, a bounded linear operator is a linear transformation L between normed vector spaces X and Y for which the ratio of the norm of L(v) to that of v is bounded by the same number, over all non-zero vectors v in X. In other words, there exists some M > 0 such that for all v in X The smallest such M is called the operator norm of L. A bounded linear operator is generally not a bounded function; the latter would require that the norm of L(v) be bounded for all v, which is not possible unless Y is the zero vector space. Rather, a bounded linear operator is a locally bounded function. A linear operator on a metrizable vector space is bounded if and only if it is continuous. Contents 1 Examples 2 Equivalence of boundedness and continuity 3 Linearity and boundedness 4 Further properties 5 Properties of the space of bounded linear operators 6 Topological vector spaces 7 See also 8 References Examples Any linear operator between two finite-dimensional normed spaces is bounded, and such an operator may be viewed as multiplication by some fixed matrix. Many integral transforms are bounded linear operators. For instance, if is a continuous function, then the operator defined on the space of continuous functions on endowed with the uniform norm and with values in the space with given by the formula is bounded.
    [Show full text]
  • Chapter 6 Linear Transformations and Operators
    Chapter 6 Linear Transformations and Operators 6.1 The Algebra of Linear Transformations Theorem 6.1.1. Let V and W be vector spaces over the field F . Let T and U be two linear transformations from V into W . The function (T + U) defined pointwise by (T + U)(v) = T v + Uv is a linear transformation from V into W . Furthermore, if s F , the function (sT ) ∈ defined by (sT )(v) = s (T v) is also a linear transformation from V into W . The set of all linear transformation from V into W , together with the addition and scalar multiplication defined above, is a vector space over the field F . Proof. Suppose that T and U are linear transformation from V into W . For (T +U) defined above, we have (T + U)(sv + w) = T (sv + w) + U (sv + w) = s (T v) + T w + s (Uv) + Uw = s (T v + Uv) + (T w + Uw) = s(T + U)v + (T + U)w, 127 128 CHAPTER 6. LINEAR TRANSFORMATIONS AND OPERATORS which shows that (T + U) is a linear transformation. Similarly, we have (rT )(sv + w) = r (T (sv + w)) = r (s (T v) + (T w)) = rs (T v) + r (T w) = s (r (T v)) + rT (w) = s ((rT ) v) + (rT ) w which shows that (rT ) is a linear transformation. To verify that the set of linear transformations from V into W together with the operations defined above is a vector space, one must directly check the conditions of Definition 3.3.1. These are straightforward to verify, and we leave this exercise to the reader.
    [Show full text]