Informal Complete Metric Space and Fixed Point Theorems
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The Universal Property of Inverse Semigroup Equivariant KK-Theory
KYUNGPOOK Math. J. 61(2021), 111-137 https://doi.org/10.5666/KMJ.2021.61.1.111 pISSN 1225-6951 eISSN 0454-8124 c Kyungpook Mathematical Journal The Universal Property of Inverse Semigroup Equivariant KK-theory Bernhard Burgstaller Departamento de Matematica, Universidade Federal de Santa Catarina, CEP 88.040-900 Florian´opolis-SC, Brasil e-mail : [email protected] Abstract. Higson proved that every homotopy invariant, stable and split exact func- tor from the category of C∗-algebras to an additive category factors through Kasparov's KK-theory. By adapting a group equivariant generalization of this result by Thomsen, we generalize Higson's result to the inverse semigroup and locally compact, not necessarily Hausdorff groupoid equivariant setting. 1. Introduction In [3], Cuntz noted that if F is a homotopy invariant, stable and split exact func- tor from the category of separable C∗-algebras to the category of abelian groups then Kasparov's KK-theory acts on F , that is, every element of KK(A; B) induces a natural map F (A) ! F (B). Higson [4], on the other hand, developed Cuntz' find- ings further and proved that every such functor F factorizes through the category K consisting of separable C∗-algebras as the object class and KK-theory together with the Kasparov product as the morphism class, that is, F is the composition F^ ◦ κ of a universal functor κ from the class of C∗-algebras to K and a functor F^ from K to abelian groups. In [12], Thomsen generalized Higson's findings to the group equivariant setting by replacing everywhere in the above statement algebras by equivariant algebras, ∗- homomorphisms by equivariant ∗-homomorphisms and KK-theory by equivariant KK-theory (the proof is however far from such a straightforward replacement). -
FUNCTIONAL ANALYSIS 1. Metric and Topological Spaces A
FUNCTIONAL ANALYSIS CHRISTIAN REMLING 1. Metric and topological spaces A metric space is a set on which we can measure distances. More precisely, we proceed as follows: let X 6= ; be a set, and let d : X×X ! [0; 1) be a map. Definition 1.1. (X; d) is called a metric space if d has the following properties, for arbitrary x; y; z 2 X: (1) d(x; y) = 0 () x = y (2) d(x; y) = d(y; x) (3) d(x; y) ≤ d(x; z) + d(z; y) Property 3 is called the triangle inequality. It says that a detour via z will not give a shortcut when going from x to y. The notion of a metric space is very flexible and general, and there are many different examples. We now compile a preliminary list of metric spaces. Example 1.1. If X 6= ; is an arbitrary set, then ( 0 x = y d(x; y) = 1 x 6= y defines a metric on X. Exercise 1.1. Check this. This example does not look particularly interesting, but it does sat- isfy the requirements from Definition 1.1. Example 1.2. X = C with the metric d(x; y) = jx−yj is a metric space. X can also be an arbitrary non-empty subset of C, for example X = R. In fact, this works in complete generality: If (X; d) is a metric space and Y ⊆ X, then Y with the same metric is a metric space also. Example 1.3. Let X = Cn or X = Rn. For each p ≥ 1, n !1=p X p dp(x; y) = jxj − yjj j=1 1 2 CHRISTIAN REMLING defines a metric on X. -
An Introduction to Inverse Semigroups and Their Connections to C*-Algebras
CARLETON UNIVERSITY SCHOOL OF MATHEMATICS AND STATISTICS HONOURS PROJECT TITLE: An Introduction to Inverse Semigroups and Their Connections To C*-Algebras AUTHOR: Kyle Cheaney SUPERVISOR: Dr. Charles Starling DATE: August 24, 2020 AN INTRODUCTION TO INVERSE SEMIGROUPS AND THEIR CONNECTIONS TO C∗-ALGEBRAS KYLE CHEANEY: 101012022 Abstract. This paper sets out to provide the reader with a basic introduction to inverse semigroups, as well as a proof of the Wagner-Preston Representation Theorem. It then focuses on finite directed graphs, specifically the graph inverse semigroup and how properties of the semigroup correspond to properties of C∗ algebras associated to such graphs. 1. Introduction The study of inverse semigroups was founded in the 1950's by three mathematicians: Ehresmann, Preston, and Wagner, as a way to algebraically describe pseudogroups of trans- formations. The purpose of this paper is to introduce the topic of inverse semigroups and some of the basic properties and theorems. We use these basics to relate the inverse semi- group formed by a directed graph to the corresponding graph C∗ algebra. The study of such C∗ algebras is still an active topic of research in analysis, thus providing a connection between abstract algebraic objects and complex analysis. In section 2, we outline some preliminary definitions and results which will be our basic tools for working with inverse semigroups. Section 3 provides a more detailed introduction to inverse semigroups and contains a proof of the Wagner-Preston representation theorem, a cornerstone in the study of inverse semigroups. In section 4, we present some detailed examples of inverse semigroups, including proving said sets are in fact inverse semigroups and discussing what their idempotents look like. -
SOME ALGEBRAIC DEFINITIONS and CONSTRUCTIONS Definition
SOME ALGEBRAIC DEFINITIONS AND CONSTRUCTIONS Definition 1. A monoid is a set M with an element e and an associative multipli- cation M M M for which e is a two-sided identity element: em = m = me for all m M×. A−→group is a monoid in which each element m has an inverse element m−1, so∈ that mm−1 = e = m−1m. A homomorphism f : M N of monoids is a function f such that f(mn) = −→ f(m)f(n) and f(eM )= eN . A “homomorphism” of any kind of algebraic structure is a function that preserves all of the structure that goes into the definition. When M is commutative, mn = nm for all m,n M, we often write the product as +, the identity element as 0, and the inverse of∈m as m. As a convention, it is convenient to say that a commutative monoid is “Abelian”− when we choose to think of its product as “addition”, but to use the word “commutative” when we choose to think of its product as “multiplication”; in the latter case, we write the identity element as 1. Definition 2. The Grothendieck construction on an Abelian monoid is an Abelian group G(M) together with a homomorphism of Abelian monoids i : M G(M) such that, for any Abelian group A and homomorphism of Abelian monoids−→ f : M A, there exists a unique homomorphism of Abelian groups f˜ : G(M) A −→ −→ such that f˜ i = f. ◦ We construct G(M) explicitly by taking equivalence classes of ordered pairs (m,n) of elements of M, thought of as “m n”, under the equivalence relation generated by (m,n) (m′,n′) if m + n′ = −n + m′. -
Course 221: Michaelmas Term 2006 Section 3: Complete Metric Spaces, Normed Vector Spaces and Banach Spaces
Course 221: Michaelmas Term 2006 Section 3: Complete Metric Spaces, Normed Vector Spaces and Banach Spaces David R. Wilkins Copyright c David R. Wilkins 1997–2006 Contents 3 Complete Metric Spaces, Normed Vector Spaces and Banach Spaces 2 3.1 The Least Upper Bound Principle . 2 3.2 Monotonic Sequences of Real Numbers . 2 3.3 Upper and Lower Limits of Bounded Sequences of Real Numbers 3 3.4 Convergence of Sequences in Euclidean Space . 5 3.5 Cauchy’s Criterion for Convergence . 5 3.6 The Bolzano-Weierstrass Theorem . 7 3.7 Complete Metric Spaces . 9 3.8 Normed Vector Spaces . 11 3.9 Bounded Linear Transformations . 15 3.10 Spaces of Bounded Continuous Functions on a Metric Space . 19 3.11 The Contraction Mapping Theorem and Picard’s Theorem . 20 3.12 The Completion of a Metric Space . 23 1 3 Complete Metric Spaces, Normed Vector Spaces and Banach Spaces 3.1 The Least Upper Bound Principle A set S of real numbers is said to be bounded above if there exists some real number B such x ≤ B for all x ∈ S. Similarly a set S of real numbers is said to be bounded below if there exists some real number A such that x ≥ A for all x ∈ S. A set S of real numbers is said to be bounded if it is bounded above and below. Thus a set S of real numbers is bounded if and only if there exist real numbers A and B such that A ≤ x ≤ B for all x ∈ S. -
MAS4107 Linear Algebra 2 Linear Maps And
Introduction Groups and Fields Vector Spaces Subspaces, Linear . Bases and Coordinates MAS4107 Linear Algebra 2 Linear Maps and . Change of Basis Peter Sin More on Linear Maps University of Florida Linear Endomorphisms email: [email protected]fl.edu Quotient Spaces Spaces of Linear . General Prerequisites Direct Sums Minimal polynomial Familiarity with the notion of mathematical proof and some experience in read- Bilinear Forms ing and writing proofs. Familiarity with standard mathematical notation such as Hermitian Forms summations and notations of set theory. Euclidean and . Self-Adjoint Linear . Linear Algebra Prerequisites Notation Familiarity with the notion of linear independence. Gaussian elimination (reduction by row operations) to solve systems of equations. This is the most important algorithm and it will be assumed and used freely in the classes, for example to find JJ J I II coordinate vectors with respect to basis and to compute the matrix of a linear map, to test for linear dependence, etc. The determinant of a square matrix by cofactors Back and also by row operations. Full Screen Close Quit Introduction 0. Introduction Groups and Fields Vector Spaces These notes include some topics from MAS4105, which you should have seen in one Subspaces, Linear . form or another, but probably presented in a totally different way. They have been Bases and Coordinates written in a terse style, so you should read very slowly and with patience. Please Linear Maps and . feel free to email me with any questions or comments. The notes are in electronic Change of Basis form so sections can be changed very easily to incorporate improvements. -
General Topology
General Topology Tom Leinster 2014{15 Contents A Topological spaces2 A1 Review of metric spaces.......................2 A2 The definition of topological space.................8 A3 Metrics versus topologies....................... 13 A4 Continuous maps........................... 17 A5 When are two spaces homeomorphic?................ 22 A6 Topological properties........................ 26 A7 Bases................................. 28 A8 Closure and interior......................... 31 A9 Subspaces (new spaces from old, 1)................. 35 A10 Products (new spaces from old, 2)................. 39 A11 Quotients (new spaces from old, 3)................. 43 A12 Review of ChapterA......................... 48 B Compactness 51 B1 The definition of compactness.................... 51 B2 Closed bounded intervals are compact............... 55 B3 Compactness and subspaces..................... 56 B4 Compactness and products..................... 58 B5 The compact subsets of Rn ..................... 59 B6 Compactness and quotients (and images)............. 61 B7 Compact metric spaces........................ 64 C Connectedness 68 C1 The definition of connectedness................... 68 C2 Connected subsets of the real line.................. 72 C3 Path-connectedness.......................... 76 C4 Connected-components and path-components........... 80 1 Chapter A Topological spaces A1 Review of metric spaces For the lecture of Thursday, 18 September 2014 Almost everything in this section should have been covered in Honours Analysis, with the possible exception of some of the examples. For that reason, this lecture is longer than usual. Definition A1.1 Let X be a set. A metric on X is a function d: X × X ! [0; 1) with the following three properties: • d(x; y) = 0 () x = y, for x; y 2 X; • d(x; y) + d(y; z) ≥ d(x; z) for all x; y; z 2 X (triangle inequality); • d(x; y) = d(y; x) for all x; y 2 X (symmetry). -
Be a Metric Space
2 The University of Sydney show that Z is closed in R. The complement of Z in R is the union of all the Pure Mathematics 3901 open intervals (n, n + 1), where n runs through all of Z, and this is open since every union of open sets is open. So Z is closed. Metric Spaces 2000 Alternatively, let (an) be a Cauchy sequence in Z. Choose an integer N such that d(xn, xm) < 1 for all n ≥ N. Put x = xN . Then for all n ≥ N we have Tutorial 5 |xn − x| = d(xn, xN ) < 1. But xn, x ∈ Z, and since two distinct integers always differ by at least 1 it follows that xn = x. This holds for all n > N. 1. Let X = (X, d) be a metric space. Let (xn) and (yn) be two sequences in X So xn → x as n → ∞ (since for all ε > 0 we have 0 = d(xn, x) < ε for all such that (yn) is a Cauchy sequence and d(xn, yn) → 0 as n → ∞. Prove that n > N). (i)(xn) is a Cauchy sequence in X, and 4. (i) Show that if D is a metric on the set X and f: Y → X is an injective (ii)(xn) converges to a limit x if and only if (yn) also converges to x. function then the formula d(a, b) = D(f(a), f(b)) defines a metric d on Y , and use this to show that d(m, n) = |m−1 − n−1| defines a metric Solution. -
Semigroups and Monoids
S Luis Alonso-Ovalle // Contents Subgroups Semigroups and monoids Subgroups Groups. A group G is an algebra consisting of a set G and a single binary operation ◦ satisfying the following axioms: . ◦ is completely defined and G is closed under ◦. ◦ is associative. G contains an identity element. Each element in G has an inverse element. Subgroups. We define a subgroup G0 as a subalgebra of G which is itself a group. Examples: . The group of even integers with addition is a proper subgroup of the group of all integers with addition. The group of all rotations of the square h{I, R, R0, R00}, ◦i, where ◦ is the composition of the operations is a subgroup of the group of all symmetries of the square. Some non-subgroups: SEMIGROUPS AND MONOIDS . The system h{I, R, R0}, ◦i is not a subgroup (and not even a subalgebra) of the original group. Why? (Hint: ◦ closure). The set of all non-negative integers with addition is a subalgebra of the group of all integers with addition, because the non-negative integers are closed under addition. But it is not a subgroup because it is not itself a group: it is associative and has a zero, but . does any member (except for ) have an inverse? Order. The order of any group G is the number of members in the set G. The order of any subgroup exactly divides the order of the parental group. E.g.: only subgroups of order , , and are possible for a -member group. (The theorem does not guarantee that every subset having the proper number of members will give rise to a subgroup. -
DEFINITIONS and THEOREMS in GENERAL TOPOLOGY 1. Basic
DEFINITIONS AND THEOREMS IN GENERAL TOPOLOGY 1. Basic definitions. A topology on a set X is defined by a family O of subsets of X, the open sets of the topology, satisfying the axioms: (i) ; and X are in O; (ii) the intersection of finitely many sets in O is in O; (iii) arbitrary unions of sets in O are in O. Alternatively, a topology may be defined by the neighborhoods U(p) of an arbitrary point p 2 X, where p 2 U(p) and, in addition: (i) If U1;U2 are neighborhoods of p, there exists U3 neighborhood of p, such that U3 ⊂ U1 \ U2; (ii) If U is a neighborhood of p and q 2 U, there exists a neighborhood V of q so that V ⊂ U. A topology is Hausdorff if any distinct points p 6= q admit disjoint neigh- borhoods. This is almost always assumed. A set C ⊂ X is closed if its complement is open. The closure A¯ of a set A ⊂ X is the intersection of all closed sets containing X. A subset A ⊂ X is dense in X if A¯ = X. A point x 2 X is a cluster point of a subset A ⊂ X if any neighborhood of x contains a point of A distinct from x. If A0 denotes the set of cluster points, then A¯ = A [ A0: A map f : X ! Y of topological spaces is continuous at p 2 X if for any open neighborhood V ⊂ Y of f(p), there exists an open neighborhood U ⊂ X of p so that f(U) ⊂ V . -
5 Definition and Examples of Groups
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan 5 Definition and Examples of Groups In Section 3, properties of binary operations were emphasized-closure, iden- tity, inverses, associativity. Now these properties will be studied from a slightly different viewpoint by considering systems (S, ∗) that satisfy all four of the properties. Such mathematical systems are called groups. A group may be defined as follows. Definition 5.1 A set G is a group with respect to a binary operation ∗ if the following properties are satisfied: (i) (x ∗ y) ∗ z = x ∗ (y ∗ z) for all elements x, y, and z of G (the Asso- ciative Law); (ii) there exists an element e of G (the identity element of G) such that e ∗ x = x = x ∗ e, for all elements x of G; (iii) for each element x of G there exists an element x0 of G (the inverse of x) such that x ∗ x0 = e = x0 ∗ x (where e is the identity element of G). A group G is Abelian (or commutative) if x ∗ y = y ∗ x for all elements x and y of G. Remark 5.1 The phrase ”with respect” should be noted. For example, the set Z is a group with respect to addition but not with respect to multiplication (it has no inverses for elements other than ±1.) Example 5.1 We can obtain some simple examples of groups by considering appropriate subsets of the familiar number systems. (a) The set of even integers is an Abelian group with respect to addition. 1 (b) The set N of positive integers is not a group with respect to addition since it has no identity element. -
MATH 4140/MATH 5140: Abstract Algebra II
MATH 4140/MATH 5140: Abstract Algebra II Farid Aliniaeifard April 30, 2018 Contents 1 Rings and Isomorphism (See Chapter 3 of the textbook) 2 1.1 Definitions and examples . .2 1.2 Units and Zero-divisors . .6 1.3 Useful facts about fields and integral domains . .6 1.4 Homomorphism and isomorphism . .7 2 Polynomials Arithmetic and the Division algorithm 9 3 Ideals and Quotient Rings 11 3.1 Finitely Generated Ideals . 12 3.2 Congruence . 13 3.3 Quotient Ring . 13 4 The Structure of R=I When I Is Prime or Maximal 16 5 EPU 17 p 6 Z[ d], an integral domain which is not a UFD 22 7 The field of quotients of an integral domain 24 8 If R is a UDF, so is R[x] 26 9 Vector Spaces 28 10 Simple Extensions 30 11 Algebraic Extensions 33 12 Splitting Fields 35 13 Separability 38 14 Finite Fields 40 15 The Galois Group 43 1 16 The Fundamental Theorem of Galois Theory 45 16.1 Galois Extensions . 47 17 Solvability by Radicals 51 17.1 Solvable groups . 51 18 Roots of Unity 52 19 Representation Theory 53 19.1 G-modules and Group algebras . 54 19.2 Action of a group on a set yields a G-module . 54 20 Reducibility 57 21 Inner product space 58 22 Maschke's Theorem 59 1 Rings and Isomorphism (See Chapter 3 of the text- book) 1.1 Definitions and examples Definition. A ring is a nonempty set R equipped with two operations (usually written as addition (+) and multiplication(.) and we denote the ring with its operations by (R,+,.)) that satisfy the following axioms.