Algebraic Aspects in Tropical Mathematics
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ORDERED GROUPS VM Kopytov UDC 512.545
ORDERED GROUPS V. M. Kopytov UDC 512.545 In the paper "Ordered groups" there is given a survey of papers on ordered groups, reviewed in RZh Mathematika in 1975-1980. Starting in 1963 there occurred a qualitative jump in the theory of ordered groups, evoked by the inten- sive investigation of linerarly ordered (l. o. ) groups and the development of the theory of groups of automor- phisms of I.o. sets. As a result many sections of the theory of lattice ordered groups (l-groups) acquired an orderly and organized form, and profound classificationalresults were obtained in them. A natural con- sequence of this was the appearance in the recent past of several monographs on the theory of ordered groups, in particular, the books of Kokorin and Kopytov [26] (English translation [154]), Mura and Rhemtulla [182], Bigard, Keimel, and Wolfenstein [78]. The present survey is written on the materials of the Ref. Zh. "Matematika," mainly for the years 1975-1980, and reflects practicallyall directions of development of the theory of ordered groups with some accent on linearly and lattice ordered groups, which is explained by the intensivity and diversity of the inves- tigations in these domains. In the survey there are included some results reviewed in the years 1970-1974 and not reflected in previous surveys of the collection "Algebra. Topology. Geometry" of the annual 'Itogi Nauki i Tekhniki" [12, 13] or the book [26]. i. Linearly Ordered Groups Investigations on 1. o. groups were carried out mainly in the directions designated at the end of the six- ties and formulated in [26]. -
Exercises and Solutions in Groups Rings and Fields
EXERCISES AND SOLUTIONS IN GROUPS RINGS AND FIELDS Mahmut Kuzucuo˘glu Middle East Technical University [email protected] Ankara, TURKEY April 18, 2012 ii iii TABLE OF CONTENTS CHAPTERS 0. PREFACE . v 1. SETS, INTEGERS, FUNCTIONS . 1 2. GROUPS . 4 3. RINGS . .55 4. FIELDS . 77 5. INDEX . 100 iv v Preface These notes are prepared in 1991 when we gave the abstract al- gebra course. Our intention was to help the students by giving them some exercises and get them familiar with some solutions. Some of the solutions here are very short and in the form of a hint. I would like to thank B¨ulent B¨uy¨ukbozkırlı for his help during the preparation of these notes. I would like to thank also Prof. Ismail_ S¸. G¨ulo˘glufor checking some of the solutions. Of course the remaining errors belongs to me. If you find any errors, I should be grateful to hear from you. Finally I would like to thank Aynur Bora and G¨uldaneG¨um¨u¸sfor their typing the manuscript in LATEX. Mahmut Kuzucuo˘glu I would like to thank our graduate students Tu˘gbaAslan, B¨u¸sra C¸ınar, Fuat Erdem and Irfan_ Kadık¨oyl¨ufor reading the old version and pointing out some misprints. With their encouragement I have made the changes in the shape, namely I put the answers right after the questions. 20, December 2011 vi M. Kuzucuo˘glu 1. SETS, INTEGERS, FUNCTIONS 1.1. If A is a finite set having n elements, prove that A has exactly 2n distinct subsets. -
Formal Power Series - Wikipedia, the Free Encyclopedia
Formal power series - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Formal_power_series Formal power series From Wikipedia, the free encyclopedia In mathematics, formal power series are a generalization of polynomials as formal objects, where the number of terms is allowed to be infinite; this implies giving up the possibility to substitute arbitrary values for indeterminates. This perspective contrasts with that of power series, whose variables designate numerical values, and which series therefore only have a definite value if convergence can be established. Formal power series are often used merely to represent the whole collection of their coefficients. In combinatorics, they provide representations of numerical sequences and of multisets, and for instance allow giving concise expressions for recursively defined sequences regardless of whether the recursion can be explicitly solved; this is known as the method of generating functions. Contents 1 Introduction 2 The ring of formal power series 2.1 Definition of the formal power series ring 2.1.1 Ring structure 2.1.2 Topological structure 2.1.3 Alternative topologies 2.2 Universal property 3 Operations on formal power series 3.1 Multiplying series 3.2 Power series raised to powers 3.3 Inverting series 3.4 Dividing series 3.5 Extracting coefficients 3.6 Composition of series 3.6.1 Example 3.7 Composition inverse 3.8 Formal differentiation of series 4 Properties 4.1 Algebraic properties of the formal power series ring 4.2 Topological properties of the formal power series -
1. Rings of Fractions
1. Rings of Fractions 1.0. Rings and algebras (1.0.1) All the rings considered in this work possess a unit element; all the modules over such a ring are assumed unital; homomorphisms of rings are assumed to take unit element to unit element; and unless explicitly mentioned otherwise, all subrings of a ring A are assumed to contain the unit element of A. We generally consider commutative rings, and when we say ring without specifying, we understand this to mean a commutative ring. If A is a not necessarily commutative ring, we consider every A module to be a left A- module, unless we expressly say otherwise. (1.0.2) Let A and B be not necessarily commutative rings, φ : A ! B a homomorphism. Every left (respectively right) B-module M inherits the structure of a left (resp. right) A-module by the formula a:m = φ(a):m (resp m:a = m.φ(a)). When it is necessary to distinguish the A-module structure from the B-module structure on M, we use M[φ] to denote the left (resp. right) A-module so defined. If L is an A module, a homomorphism u : L ! M[φ] is therefore a homomorphism of commutative groups such that u(a:x) = φ(a):u(x) for a 2 A, x 2 L; one also calls this a φ-homomorphism L ! M, and the pair (u,φ) (or, by abuse of language, u) is a di-homomorphism from (A, L) to (B, M). The pair (A,L) made up of a ring A and an A module L therefore form the objects of a category where the morphisms are di-homomorphisms. -
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′. -
Kernel Methods for Knowledge Structures
Kernel Methods for Knowledge Structures Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften der Universität Karlsruhe (TH) genehmigte DISSERTATION von Dipl.-Inform.-Wirt. Stephan Bloehdorn Tag der mündlichen Prüfung: 10. Juli 2008 Referent: Prof. Dr. Rudi Studer Koreferent: Prof. Dr. Dr. Lars Schmidt-Thieme 2008 Karlsruhe Abstract Kernel methods constitute a new and popular field of research in the area of machine learning. Kernel-based machine learning algorithms abandon the explicit represen- tation of data items in the vector space in which the sought-after patterns are to be detected. Instead, they implicitly mimic the geometry of the feature space by means of the kernel function, a similarity function which maintains a geometric interpreta- tion as the inner product of two vectors. Knowledge structures and ontologies allow to formally model domain knowledge which can constitute valuable complementary information for pattern discovery. For kernel-based machine learning algorithms, a good way to make such prior knowledge about the problem domain available to a machine learning technique is to incorporate it into the kernel function. This thesis studies the design of such kernel functions. First, this thesis provides a theoretical analysis of popular similarity functions for entities in taxonomic knowledge structures in terms of their suitability as kernel func- tions. It shows that, in a general setting, many taxonomic similarity functions can not be guaranteed to yield valid kernel functions and discusses the alternatives. Secondly, the thesis addresses the design of expressive kernel functions for text mining applications. A first group of kernel functions, Semantic Smoothing Kernels (SSKs) retain the Vector Space Models (VSMs) representation of textual data as vec- tors of term weights but employ linguistic background knowledge resources to bias the original inner product in such a way that cross-term similarities adequately con- tribute to the kernel result. -
36 Rings of Fractions
36 Rings of fractions Recall. If R is a PID then R is a UFD. In particular • Z is a UFD • if F is a field then F[x] is a UFD. Goal. If R is a UFD then so is R[x]. Idea of proof. 1) Find an embedding R,! F where F is a field. 2) If p(x) 2 R[x] then p(x) 2 F[x] and since F[x] is a UFD thus p(x) has a unique factorization into irreducibles in F[x]. 3) Use the factorization in F[x] and the fact that R is a UFD to obtain a factorization of p(x) in R[x]. 36.1 Definition. If R is a ring then a subset S ⊆ R is a multiplicative subset if 1) 1 2 S 2) if a; b 2 S then ab 2 S 36.2 Example. Multiplicative subsets of Z: 1) S = Z 137 2) S0 = Z − f0g 3) Sp = fn 2 Z j p - ng where p is a prime number. Note: Sp = Z − hpi. 36.3 Proposition. If R is a ring, and I is a prime ideal of R then S = R − I is a multiplicative subset of R. Proof. Exercise. 36.4. Construction of a ring of fractions. Goal. For a ring R and a multiplicative subset S ⊆ R construct a ring S−1R such that every element of S becomes a unit in S−1R. Consider a relation on the set R × S: 0 0 0 0 (a; s) ∼ (a ; s ) if s0(as − a s) = 0 for some s0 2 S Check: ∼ is an equivalence relation. -
2.2 Kernel and Range of a Linear Transformation
2.2 Kernel and Range of a Linear Transformation Performance Criteria: 2. (c) Determine whether a given vector is in the kernel or range of a linear trans- formation. Describe the kernel and range of a linear transformation. (d) Determine whether a transformation is one-to-one; determine whether a transformation is onto. When working with transformations T : Rm → Rn in Math 341, you found that any linear transformation can be represented by multiplication by a matrix. At some point after that you were introduced to the concepts of the null space and column space of a matrix. In this section we present the analogous ideas for general vector spaces. Definition 2.4: Let V and W be vector spaces, and let T : V → W be a transformation. We will call V the domain of T , and W is the codomain of T . Definition 2.5: Let V and W be vector spaces, and let T : V → W be a linear transformation. • The set of all vectors v ∈ V for which T v = 0 is a subspace of V . It is called the kernel of T , And we will denote it by ker(T ). • The set of all vectors w ∈ W such that w = T v for some v ∈ V is called the range of T . It is a subspace of W , and is denoted ran(T ). It is worth making a few comments about the above: • The kernel and range “belong to” the transformation, not the vector spaces V and W . If we had another linear transformation S : V → W , it would most likely have a different kernel and range. -
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. -
Weakly Abelian Lattice-Ordered Groups 1
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 129, Number 3, Pages 677{684 S 0002-9939(00)05706-3 Article electronically published on September 20, 2000 WEAKLY ABELIAN LATTICE-ORDERED GROUPS A. M. W. GLASS (Communicated by Stephen D. Smith) Respectfully dedicated (with gratitude) to W. Charles Holland on his 65th Birthday Abstract. Every nilpotent lattice-ordered group is weakly Abelian; i.e., sat- isfies the identity x−1(y _ 1)x _ (y _ 1)2 =(y _ 1)2. In 1984, V. M. Kopytov asked if every weakly Abelian lattice-ordered group belongs to the variety generated by all nilpotent lattice-ordered groups [The Black Swamp Prob- lem Book, Question 40]. In the past 15 years, all attempts have centred on finding counterexamples. We show that two constructions of weakly Abelian lattice-ordered groups fail to be counterexamples. They include all preiously considered potential counterexamples and also many weakly Abelian ordered free groups on finitely many generators. If every weakly Abelian ordered free group on finitely many generators belongs to the variety generated by all nilpo- tent lattice-ordered groups, then every weakly Abelian lattice-ordered group belongs to this variety. This paper therefore redresses the balance and suggests that Kopytov's problem is even more intriguing. 1. Basic definitions and facts A group equipped with a partial order ≤ is called a p.o.group if axb ≤ ayb whenever x ≤ y. If, further, the partial order is a lattice (any pair of elements x & y have a least upper bound (denoted by x_y) and a greatest lower bound (denoted by x ^ y)), then the p.o. -
On Semifields of Type
I I G ◭◭ ◮◮ ◭ ◮ On semifields of type (q2n,qn,q2,q2,q), n odd page 1 / 19 ∗ go back Giuseppe Marino Olga Polverino Rocco Tromebtti full screen Abstract 2n n 2 2 close A semifield of type (q , q , q , q , q) (with n > 1) is a finite semi- field of order q2n (q a prime power) with left nucleus of order qn, right 2 quit and middle nuclei both of order q and center of order q. Semifields of type (q6, q3, q2, q2, q) have been completely classified by the authors and N. L. Johnson in [10]. In this paper we determine, up to isotopy, the form n n of any semifield of type (q2 , q , q2, q2, q) when n is an odd integer, proving n−1 that there exist 2 non isotopic potential families of semifields of this type. Also, we provide, with the aid of the computer, new examples of semifields of type (q14, q7, q2, q2, q), when q = 2. Keywords: semifield, isotopy, linear set MSC 2000: 51A40, 51E20, 12K10 1. Introduction A finite semifield S is a finite algebraic structure satisfying all the axioms for a skew field except (possibly) associativity. The subsets Nl = {a ∈ S | (ab)c = a(bc), ∀b, c ∈ S} , Nm = {b ∈ S | (ab)c = a(bc), ∀a, c ∈ S} , Nr = {c ∈ S | (ab)c = a(bc), ∀a, b ∈ S} and K = {a ∈ Nl ∩ Nm ∩ Nr | ab = ba, ∀b ∈ S} are fields and are known, respectively, as the left nucleus, the middle nucleus, the right nucleus and the center of the semifield. -
The Theory of Lattice-Ordered Groups
The Theory ofLattice-Ordered Groups Mathematics and Its Applications Managing Editor: M. HAZEWINKEL Centre for Mathematics and Computer Science, Amsterdam, The Netherlands Volume 307 The Theory of Lattice-Ordered Groups by V. M. Kopytov Institute ofMathematics, RussianAcademyof Sciences, Siberian Branch, Novosibirsk, Russia and N. Ya. Medvedev Altai State University, Bamaul, Russia Springer-Science+Business Media, B.Y A C.I.P. Catalogue record for this book is available from the Library ofCongress. ISBN 978-90-481-4474-7 ISBN 978-94-015-8304-6 (eBook) DOI 10.1007/978-94-015-8304-6 Printed on acid-free paper All Rights Reserved © 1994 Springer Science+Business Media Dordrecht Originally published by Kluwer Academic Publishers in 1994. Softcover reprint ofthe hardcover Ist edition 1994 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrie val system, without written permission from the copyright owner. Contents Preface IX Symbol Index Xlll 1 Lattices 1 1.1 Partially ordered sets 1 1.2 Lattices .. ..... 3 1.3 Properties of lattices 5 1.4 Distributive and modular lattices. Boolean algebras 6 2 Lattice-ordered groups 11 2.1 Definition of the l-group 11 2.2 Calculations in I-groups 15 2.3 Basic facts . 22 3 Convex I-subgroups 31 3.1 The lattice of convex l-subgroups .......... .. 31 3.2 Archimedean o-groups. Convex subgroups in o-groups. 34 3.3 Prime subgroups 39 3.4 Polars ... ..................... 43 3.5 Lattice-ordered groups with finite Boolean algebra of polars ......................