The Universal Property of the Quotient
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Quotient Groups §7.8 (Ed.2), 8.4 (Ed.2): Quotient Groups and Homomorphisms, Part I
Math 371 Lecture #33 x7.7 (Ed.2), 8.3 (Ed.2): Quotient Groups x7.8 (Ed.2), 8.4 (Ed.2): Quotient Groups and Homomorphisms, Part I Recall that to make the set of right cosets of a subgroup K in a group G into a group under the binary operation (or product) (Ka)(Kb) = K(ab) requires that K be a normal subgroup of G. For a normal subgroup N of a group G, we denote the set of right cosets of N in G by G=N (read G mod N). Theorem 8.12. For a normal subgroup N of a group G, the product (Na)(Nb) = N(ab) on G=N is well-defined. We saw the proof of this before. Theorem 8.13. For a normal subgroup N of a group G, we have (1) G=N is a group under the product (Na)(Nb) = N(ab), (2) when jGj < 1 that jG=Nj = jGj=jNj, and (3) when G is abelian, so is G=N. Proof. (1) We know that the product is well-defined. The identity element of G=N is Ne because for all a 2 G we have (Ne)(Na) = N(ae) = Na; (Na)(Ne) = N(ae) = Na: The inverse of Na is Na−1 because (Na)(Na−1) = N(aa−1) = Ne; (Na−1)(Na) = N(a−1a) = Ne: Associativity of the product in G=N follows from the associativity in G: [(Na)(Nb)](Nc) = (N(ab))(Nc) = N((ab)c) = N(a(bc)) = (N(a))(N(bc)) = (N(a))[(N(b))(N(c))]: This establishes G=N as a group. -
Kernel and Image
Math 217 Worksheet 1 February: x3.1 Professor Karen E Smith (c)2015 UM Math Dept licensed under a Creative Commons By-NC-SA 4.0 International License. T Definitions: Given a linear transformation V ! W between vector spaces, we have 1. The source or domain of T is V ; 2. The target of T is W ; 3. The image of T is the subset of the target f~y 2 W j ~y = T (~x) for some x 2 Vg: 4. The kernel of T is the subset of the source f~v 2 V such that T (~v) = ~0g. Put differently, the kernel is the pre-image of ~0. Advice to the new mathematicians from an old one: In encountering new definitions and concepts, n m please keep in mind concrete examples you already know|in this case, think about V as R and W as R the first time through. How does the notion of a linear transformation become more concrete in this special case? Think about modeling your future understanding on this case, but be aware that there are other important examples and there are important differences (a linear map is not \a matrix" unless *source and target* are both \coordinate spaces" of column vectors). The goal is to become comfortable with the abstract idea of a vector space which embodies many n features of R but encompasses many other kinds of set-ups. A. For each linear transformation below, determine the source, target, image and kernel. 2 3 x1 3 (a) T : R ! R such that T (4x25) = x1 + x2 + x3. -
Lie Group Structures on Quotient Groups and Universal Complexifications for Infinite-Dimensional Lie Groups
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Functional Analysis 194, 347–409 (2002) doi:10.1006/jfan.2002.3942 Lie Group Structures on Quotient Groups and Universal Complexifications for Infinite-Dimensional Lie Groups Helge Glo¨ ckner1 Department of Mathematics, Louisiana State University, Baton Rouge, Louisiana 70803-4918 E-mail: [email protected] Communicated by L. Gross Received September 4, 2001; revised November 15, 2001; accepted December 16, 2001 We characterize the existence of Lie group structures on quotient groups and the existence of universal complexifications for the class of Baker–Campbell–Hausdorff (BCH–) Lie groups, which subsumes all Banach–Lie groups and ‘‘linear’’ direct limit r r Lie groups, as well as the mapping groups CK ðM; GÞ :¼fg 2 C ðM; GÞ : gjM=K ¼ 1g; for every BCH–Lie group G; second countable finite-dimensional smooth manifold M; compact subset SK of M; and 04r41: Also the corresponding test function r r # groups D ðM; GÞ¼ K CK ðM; GÞ are BCH–Lie groups. 2002 Elsevier Science (USA) 0. INTRODUCTION It is a well-known fact in the theory of Banach–Lie groups that the topological quotient group G=N of a real Banach–Lie group G by a closed normal Lie subgroup N is a Banach–Lie group provided LðNÞ is complemented in LðGÞ as a topological vector space [7, 30]. Only recently, it was observed that the hypothesis that LðNÞ be complemented can be omitted [17, Theorem II.2]. This strengthened result is then used in [17] to characterize those real Banach–Lie groups which possess a universal complexification in the category of complex Banach–Lie groups. -
The Category of Generalized Lie Groups 283
TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 199, 1974 THE CATEGORYOF GENERALIZEDLIE GROUPS BY SU-SHING CHEN AND RICHARD W. YOH ABSTRACT. We consider the category r of generalized Lie groups. A generalized Lie group is a topological group G such that the set LG = Hom(R, G) of continuous homomorphisms from the reals R into G has certain Lie algebra and locally convex topological vector space structures. The full subcategory rr of f-bounded (r positive real number) generalized Lie groups is shown to be left complete. The class of locally compact groups is contained in T. Various prop- erties of generalized Lie groups G and their locally convex topological Lie algebras LG = Horn (R, G) are investigated. 1. Introduction. The category FT of finite dimensional Lie groups does not admit arbitrary Cartesian products. Therefore we shall enlarge the category £r to the category T of generalized Lie groups introduced by K. Hofmann in [ll]^1) The category T contains well-known subcategories, such as the category of compact groups [11], the category of locally compact groups (see §5) and the category of finite dimensional De groups. The Lie algebra LG = Horn (R, G) of a generalized Lie group G is a vital and important device just as in the case of finite dimensional Lie groups. Thus we consider the category SI of locally convex topological Lie algebras (§2). The full subcategory Í2r of /--bounded locally convex topological Lie algebras of £2 is roughly speaking the family of all objects on whose open semiballs of radius r the Campbell-Hausdorff formula holds. -
Math 120 Homework 3 Solutions
Math 120 Homework 3 Solutions Xiaoyu He, with edits by Prof. Church April 21, 2018 [Note from Prof. Church: solutions to starred problems may not include all details or all portions of the question.] 1.3.1* Let σ be the permutation 1 7! 3; 2 7! 4; 3 7! 5; 4 7! 2; 5 7! 1 and let τ be the permutation 1 7! 5; 2 7! 3; 3 7! 2; 4 7! 4; 5 7! 1. Find the cycle decompositions of each of the following permutations: σ; τ; σ2; στ; τσ; τ 2σ. The cycle decompositions are: σ = (135)(24) τ = (15)(23)(4) σ2 = (153)(2)(4) στ = (1)(2534) τσ = (1243)(5) τ 2σ = (135)(24): 1.3.7* Write out the cycle decomposition of each element of order 2 in S4. Elements of order 2 are also called involutions. There are six formed from a single transposition, (12); (13); (14); (23); (24); (34), and three from pairs of transpositions: (12)(34); (13)(24); (14)(23). 3.1.6* Define ' : R× ! {±1g by letting '(x) be x divided by the absolute value of x. Describe the fibers of ' and prove that ' is a homomorphism. The fibers of ' are '−1(1) = (0; 1) = fall positive realsg and '−1(−1) = (−∞; 0) = fall negative realsg. 3.1.7* Define π : R2 ! R by π((x; y)) = x + y. Prove that π is a surjective homomorphism and describe the kernel and fibers of π geometrically. The map π is surjective because e.g. π((x; 0)) = x. The kernel of π is the line y = −x through the origin. -
Discrete Topological Transformations for Image Processing Michel Couprie, Gilles Bertrand
Discrete Topological Transformations for Image Processing Michel Couprie, Gilles Bertrand To cite this version: Michel Couprie, Gilles Bertrand. Discrete Topological Transformations for Image Processing. Brimkov, Valentin E. and Barneva, Reneta P. Digital Geometry Algorithms, 2, Springer, pp.73-107, 2012, Lecture Notes in Computational Vision and Biomechanics, 978-94-007-4174-4. 10.1007/978-94- 007-4174-4_3. hal-00727377 HAL Id: hal-00727377 https://hal-upec-upem.archives-ouvertes.fr/hal-00727377 Submitted on 3 Sep 2012 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Chapter 3 Discrete Topological Transformations for Image Processing Michel Couprie and Gilles Bertrand Abstract Topology-based image processing operators usually aim at trans- forming an image while preserving its topological characteristics. This chap- ter reviews some approaches which lead to efficient and exact algorithms for topological transformations in 2D, 3D and grayscale images. Some transfor- mations which modify topology in a controlled manner are also described. Finally, based on the framework of critical kernels, we show how to design a topologically sound parallel thinning algorithm guided by a priority function. 3.1 Introduction Topology-preserving operators, such as homotopic thinning and skeletoniza- tion, are used in many applications of image analysis to transform an object while leaving unchanged its topological characteristics. -
Kernel Methodsmethods Simple Idea of Data Fitting
KernelKernel MethodsMethods Simple Idea of Data Fitting Given ( xi,y i) i=1,…,n xi is of dimension d Find the best linear function w (hyperplane) that fits the data Two scenarios y: real, regression y: {-1,1}, classification Two cases n>d, regression, least square n<d, ridge regression New sample: x, < x,w> : best fit (regression), best decision (classification) 2 Primary and Dual There are two ways to formulate the problem: Primary Dual Both provide deep insight into the problem Primary is more traditional Dual leads to newer techniques in SVM and kernel methods 3 Regression 2 w = arg min ∑(yi − wo − ∑ xij w j ) W i j w = arg min (y − Xw )T (y − Xw ) W d(y − Xw )T (y − Xw ) = 0 dw ⇒ XT (y − Xw ) = 0 w = [w , w ,L, w ]T , ⇒ T T o 1 d X Xw = X y L T x = ,1[ x1, , xd ] , T −1 T ⇒ w = (X X) X y y = [y , y ,L, y ]T ) 1 2 n T −1 T xT y =< x (, X X) X y > 1 xT X = 2 M xT 4 n n×xd Graphical Interpretation ) y = Xw = Hy = X(XT X)−1 XT y = X(XT X)−1 XT y d X= n FICA Income X is a n (sample size) by d (dimension of data) matrix w combines the columns of X to best approximate y Combine features (FICA, income, etc.) to decisions (loan) H projects y onto the space spanned by columns of X Simplify the decisions to fit the features 5 Problem #1 n=d, exact solution n>d, least square, (most likely scenarios) When n < d, there are not enough constraints to determine coefficients w uniquely d X= n W 6 Problem #2 If different attributes are highly correlated (income and FICA) The columns become dependent Coefficients -
Quotient-Rings.Pdf
4-21-2018 Quotient Rings Let R be a ring, and let I be a (two-sided) ideal. Considering just the operation of addition, R is a group and I is a subgroup. In fact, since R is an abelian group under addition, I is a normal subgroup, and R the quotient group is defined. Addition of cosets is defined by adding coset representatives: I (a + I)+(b + I)=(a + b)+ I. The zero coset is 0+ I = I, and the additive inverse of a coset is given by −(a + I)=(−a)+ I. R However, R also comes with a multiplication, and it’s natural to ask whether you can turn into a I ring by multiplying coset representatives: (a + I) · (b + I)= ab + I. I need to check that that this operation is well-defined, and that the ring axioms are satisfied. In fact, everything works, and you’ll see in the proof that it depends on the fact that I is an ideal. Specifically, it depends on the fact that I is closed under multiplication by elements of R. R By the way, I’ll sometimes write “ ” and sometimes “R/I”; they mean the same thing. I Theorem. If I is a two-sided ideal in a ring R, then R/I has the structure of a ring under coset addition and multiplication. Proof. Suppose that I is a two-sided ideal in R. Let r, s ∈ I. Coset addition is well-defined, because R is an abelian group and I a normal subgroup under addition. I proved that coset addition was well-defined when I constructed quotient groups. -
Math 412. Adventure Sheet on Quotient Groups
Math 412. Adventure sheet on Quotient Groups Fix an arbitrary group (G; ◦). DEFINITION: A subgroup N of G is normal if for all g 2 G, the left and right N-cosets gN and Ng are the same subsets of G. NOTATION: If H ⊆ G is any subgroup, then G=H denotes the set of left cosets of H in G. Its elements are sets denoted gH where g 2 G. The cardinality of G=H is called the index of H in G. DEFINITION/THEOREM 8.13: Let N be a normal subgroup of G. Then there is a well-defined binary operation on the set G=N defined as follows: G=N × G=N ! G=N g1N ? g2N = (g1 ◦ g2)N making G=N into a group. We call this the quotient group “G modulo N”. A. WARMUP: Define the sign map: Sn ! {±1g σ 7! 1 if σ is even; σ 7! −1 if σ is odd. (1) Prove that sign map is a group homomorphism. (2) Use the sign map to give a different proof that An is a normal subgroup of Sn for all n. (3) Describe the An-cosets of Sn. Make a table to describe the quotient group structure Sn=An. What is the identity element? B. OPERATIONS ON COSETS: Let (G; ◦) be a group and let N ⊆ G be a normal subgroup. (1) Take arbitrary ng 2 Ng. Prove that there exists n0 2 N such that ng = gn0. (2) Take any x 2 g1N and any y 2 g2N. Prove that xy 2 g1g2N. -
Abelian Categories
Abelian Categories Lemma. In an Ab-enriched category with zero object every finite product is coproduct and conversely. π1 Proof. Suppose A × B //A; B is a product. Define ι1 : A ! A × B and π2 ι2 : B ! A × B by π1ι1 = id; π2ι1 = 0; π1ι2 = 0; π2ι2 = id: It follows that ι1π1+ι2π2 = id (both sides are equal upon applying π1 and π2). To show that ι1; ι2 are a coproduct suppose given ' : A ! C; : B ! C. It φ : A × B ! C has the properties φι1 = ' and φι2 = then we must have φ = φid = φ(ι1π1 + ι2π2) = ϕπ1 + π2: Conversely, the formula ϕπ1 + π2 yields the desired map on A × B. An additive category is an Ab-enriched category with a zero object and finite products (or coproducts). In such a category, a kernel of a morphism f : A ! B is an equalizer k in the diagram k f ker(f) / A / B: 0 Dually, a cokernel of f is a coequalizer c in the diagram f c A / B / coker(f): 0 An Abelian category is an additive category such that 1. every map has a kernel and a cokernel, 2. every mono is a kernel, and every epi is a cokernel. In fact, it then follows immediatly that a mono is the kernel of its cokernel, while an epi is the cokernel of its kernel. 1 Proof of last statement. Suppose f : B ! C is epi and the cokernel of some g : A ! B. Write k : ker(f) ! B for the kernel of f. Since f ◦ g = 0 the map g¯ indicated in the diagram exists. -
23. Kernel, Rank, Range
23. Kernel, Rank, Range We now study linear transformations in more detail. First, we establish some important vocabulary. The range of a linear transformation f : V ! W is the set of vectors the linear transformation maps to. This set is also often called the image of f, written ran(f) = Im(f) = L(V ) = fL(v)jv 2 V g ⊂ W: The domain of a linear transformation is often called the pre-image of f. We can also talk about the pre-image of any subset of vectors U 2 W : L−1(U) = fv 2 V jL(v) 2 Ug ⊂ V: A linear transformation f is one-to-one if for any x 6= y 2 V , f(x) 6= f(y). In other words, different vector in V always map to different vectors in W . One-to-one transformations are also known as injective transformations. Notice that injectivity is a condition on the pre-image of f. A linear transformation f is onto if for every w 2 W , there exists an x 2 V such that f(x) = w. In other words, every vector in W is the image of some vector in V . An onto transformation is also known as an surjective transformation. Notice that surjectivity is a condition on the image of f. 1 Suppose L : V ! W is not injective. Then we can find v1 6= v2 such that Lv1 = Lv2. Then v1 − v2 6= 0, but L(v1 − v2) = 0: Definition Let L : V ! W be a linear transformation. The set of all vectors v such that Lv = 0W is called the kernel of L: ker L = fv 2 V jLv = 0g: 1 The notions of one-to-one and onto can be generalized to arbitrary functions on sets. -
Positive Semigroups of Kernel Operators
Positivity 12 (2008), 25–44 c 2007 Birkh¨auser Verlag Basel/Switzerland ! 1385-1292/010025-20, published online October 29, 2007 DOI 10.1007/s11117-007-2137-z Positivity Positive Semigroups of Kernel Operators Wolfgang Arendt Dedicated to the memory of H.H. Schaefer Abstract. Extending results of Davies and of Keicher on !p we show that the peripheral point spectrum of the generator of a positive bounded C0-semigroup of kernel operators on Lp is reduced to 0. It is shown that this implies con- vergence to an equilibrium if the semigroup is also irreducible and the fixed space non-trivial. The results are applied to elliptic operators. Mathematics Subject Classification (2000). 47D06, 47B33, 35K05. Keywords. Positive semigroups, Kernel operators, asymptotic behaviour, trivial peripheral spectrum. 0. Introduction Irreducibility is a fundamental notion in Perron-Frobenius Theory. It had been introduced in a direct way by Perron and Frobenius for matrices, but it was H. H. Schaefer who gave the definition via closed ideals. This turned out to be most fruit- ful and led to a wealth of deep and important results. For applications Ouhabaz’ very simple criterion for irreduciblity of semigroups defined by forms (see [Ouh05, Sec. 4.2] or [Are06]) is most useful. It shows that for practically all boundary con- ditions, a second order differential operator in divergence form generates a positive 2 N irreducible C0-semigroup on L (Ω) where Ωis an open, connected subset of R . The main question in Perron-Frobenius Theory, is to determine the asymp- totic behaviour of the semigroup. If the semigroup is bounded (in fact Abel bounded suffices), and if the fixed space is non-zero, then irreducibility is equiv- alent to convergence of the Ces`aro means to a strictly positive rank-one opera- tor, i.e.