Algebraic Geometry Over Semi-Structures and Hyper-Structures of Characteristic One
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Finite Generation of Symmetric Ideals
FINITE GENERATION OF SYMMETRIC IDEALS MATTHIAS ASCHENBRENNER AND CHRISTOPHER J. HILLAR In memoriam Karin Gatermann (1965–2005 ). Abstract. Let A be a commutative Noetherian ring, and let R = A[X] be the polynomial ring in an infinite collection X of indeterminates over A. Let SX be the group of permutations of X. The group SX acts on R in a natural way, and this in turn gives R the structure of a left module over the left group ring R[SX ]. We prove that all ideals of R invariant under the action of SX are finitely generated as R[SX ]-modules. The proof involves introducing a certain well-quasi-ordering on monomials and developing a theory of Gr¨obner bases and reduction in this setting. We also consider the concept of an invariant chain of ideals for finite-dimensional polynomial rings and relate it to the finite generation result mentioned above. Finally, a motivating question from chemistry is presented, with the above framework providing a suitable context in which to study it. 1. Introduction A pervasive theme in invariant theory is that of finite generation. A fundamen- tal example is a theorem of Hilbert stating that the invariant subrings of finite- dimensional polynomial algebras over finite groups are finitely generated [6, Corol- lary 1.5]. In this article, we study invariant ideals of infinite-dimensional polynomial rings. Of course, when the number of indeterminates is finite, Hilbert’s basis theo- rem tells us that any ideal (invariant or not) is finitely generated. Our setup is as follows. Let X be an infinite collection of indeterminates, and let SX be the group of permutations of X. -
Interval Notation and Linear Inequalities
CHAPTER 1 Introductory Information and Review Section 1.7: Interval Notation and Linear Inequalities Linear Inequalities Linear Inequalities Rules for Solving Inequalities: 86 University of Houston Department of Mathematics SECTION 1.7 Interval Notation and Linear Inequalities Interval Notation: Example: Solution: MATH 1300 Fundamentals of Mathematics 87 CHAPTER 1 Introductory Information and Review Example: Solution: Example: 88 University of Houston Department of Mathematics SECTION 1.7 Interval Notation and Linear Inequalities Solution: Additional Example 1: Solution: MATH 1300 Fundamentals of Mathematics 89 CHAPTER 1 Introductory Information and Review Additional Example 2: Solution: 90 University of Houston Department of Mathematics SECTION 1.7 Interval Notation and Linear Inequalities Additional Example 3: Solution: Additional Example 4: Solution: MATH 1300 Fundamentals of Mathematics 91 CHAPTER 1 Introductory Information and Review Additional Example 5: Solution: Additional Example 6: Solution: 92 University of Houston Department of Mathematics SECTION 1.7 Interval Notation and Linear Inequalities Additional Example 7: Solution: MATH 1300 Fundamentals of Mathematics 93 Exercise Set 1.7: Interval Notation and Linear Inequalities For each of the following inequalities: Write each of the following inequalities in interval (a) Write the inequality algebraically. notation. (b) Graph the inequality on the real number line. (c) Write the inequality in interval notation. 23. 1. x is greater than 5. 2. x is less than 4. 24. 3. x is less than or equal to 3. 4. x is greater than or equal to 7. 25. 5. x is not equal to 2. 6. x is not equal to 5 . 26. 7. x is less than 1. 8. -
An Introduction to Operad Theory
AN INTRODUCTION TO OPERAD THEORY SAIMA SAMCHUCK-SCHNARCH Abstract. We give an introduction to category theory and operad theory aimed at the undergraduate level. We first explore operads in the category of sets, and then generalize to other familiar categories. Finally, we develop tools to construct operads via generators and relations, and provide several examples of operads in various categories. Throughout, we highlight the ways in which operads can be seen to encode the properties of algebraic structures across different categories. Contents 1. Introduction1 2. Preliminary Definitions2 2.1. Algebraic Structures2 2.2. Category Theory4 3. Operads in the Category of Sets 12 3.1. Basic Definitions 13 3.2. Tree Diagram Visualizations 14 3.3. Morphisms and Algebras over Operads of Sets 17 4. General Operads 22 4.1. Basic Definitions 22 4.2. Morphisms and Algebras over General Operads 27 5. Operads via Generators and Relations 33 5.1. Quotient Operads and Free Operads 33 5.2. More Examples of Operads 38 5.3. Coloured Operads 43 References 44 1. Introduction Sets equipped with operations are ubiquitous in mathematics, and many familiar operati- ons share key properties. For instance, the addition of real numbers, composition of functions, and concatenation of strings are all associative operations with an identity element. In other words, all three are examples of monoids. Rather than working with particular examples of sets and operations directly, it is often more convenient to abstract out their common pro- perties and work with algebraic structures instead. For instance, one can prove that in any monoid, arbitrarily long products x1x2 ··· xn have an unambiguous value, and thus brackets 2010 Mathematics Subject Classification. -
An Elementary Approach to Boolean Algebra
Eastern Illinois University The Keep Plan B Papers Student Theses & Publications 6-1-1961 An Elementary Approach to Boolean Algebra Ruth Queary Follow this and additional works at: https://thekeep.eiu.edu/plan_b Recommended Citation Queary, Ruth, "An Elementary Approach to Boolean Algebra" (1961). Plan B Papers. 142. https://thekeep.eiu.edu/plan_b/142 This Dissertation/Thesis is brought to you for free and open access by the Student Theses & Publications at The Keep. It has been accepted for inclusion in Plan B Papers by an authorized administrator of The Keep. For more information, please contact [email protected]. r AN ELEr.:ENTARY APPRCACH TC BCCLF.AN ALGEBRA RUTH QUEAHY L _J AN ELE1~1ENTARY APPRCACH TC BC CLEAN ALGEBRA Submitted to the I<:athematics Department of EASTERN ILLINCIS UNIVERSITY as partial fulfillment for the degree of !•:ASTER CF SCIENCE IN EJUCATION. Date :---"'f~~-----/_,_ffo--..i.-/ _ RUTH QUEARY JUNE 1961 PURPOSE AND PLAN The purpose of this paper is to provide an elementary approach to Boolean algebra. It is designed to give an idea of what is meant by a Boclean algebra and to supply the necessary background material. The only prerequisite for this unit is one year of high school algebra and an open mind so that new concepts will be considered reason able even though they nay conflict with preconceived ideas. A mathematical science when put in final form consists of a set of undefined terms and unproved propositions called postulates, in terrrs of which all other concepts are defined, and from which all other propositions are proved. -
Interval Computations: Introduction, Uses, and Resources
Interval Computations: Introduction, Uses, and Resources R. B. Kearfott Department of Mathematics University of Southwestern Louisiana U.S.L. Box 4-1010, Lafayette, LA 70504-1010 USA email: [email protected] Abstract Interval analysis is a broad field in which rigorous mathematics is as- sociated with with scientific computing. A number of researchers world- wide have produced a voluminous literature on the subject. This article introduces interval arithmetic and its interaction with established math- ematical theory. The article provides pointers to traditional literature collections, as well as electronic resources. Some successful scientific and engineering applications are listed. 1 What is Interval Arithmetic, and Why is it Considered? Interval arithmetic is an arithmetic defined on sets of intervals, rather than sets of real numbers. A form of interval arithmetic perhaps first appeared in 1924 and 1931 in [8, 104], then later in [98]. Modern development of interval arithmetic began with R. E. Moore’s dissertation [64]. Since then, thousands of research articles and numerous books have appeared on the subject. Periodic conferences, as well as special meetings, are held on the subject. There is an increasing amount of software support for interval computations, and more resources concerning interval computations are becoming available through the Internet. In this paper, boldface will denote intervals, lower case will denote scalar quantities, and upper case will denote vectors and matrices. Brackets “[ ]” will delimit intervals while parentheses “( )” will delimit vectors and matrices.· Un- derscores will denote lower bounds of· intervals and overscores will denote upper bounds of intervals. Corresponding lower case letters will denote components of vectors. -
Math 210B. Finite-Dimensional Commutative Algebras Over a Field Let a Be a Nonzero finite-Dimensional Commutative Algebra Over a field K
Math 210B. Finite-dimensional commutative algebras over a field Let A be a nonzero finite-dimensional commutative algebra over a field k. Here is a general structure theorem for such A: Theorem 0.1. The set Max(A) of maximal ideals of A is finite, all primes of A are maximal and minimal, and the natural map Y A ! Am m is an isomorphism, with each Am having nilpotent maximal ideal. Qn In particular, if A is reduced then A ' i=1 ki for fields ki, with the maximal ideals given by the kernels of the projections A ! ki. The assertion in the reduced case follows from the rest since if A is reduced then so is each Am (and hence its nilpotent unique maximal ideal vanishes, implying Am must be a field). Note also that the nilpotence of the maximal ideal mAm implies that for some large n we have n n n Am = Am=m Am = (A=m )m = A=m (final equality since m is maximal in A), so the isomorphism in the Theorem can also be expressed Q n as saying A ' m A=m for large n. Most of the proof of this result is worked out in HW1 Exercise 7, and here we just address one point: the nilpotence of the maximal ideal of the local ring Am at each maximal ideal m of A. That is, we claim that the maximal ideal M := mAm is nilpotent. To establish such nilpotence, note that M is finitely generated as an Am-module since Am is noetherian (as A is obviously noetherian!). -
Irreducible Representations of Finite Monoids
U.U.D.M. Project Report 2019:11 Irreducible representations of finite monoids Christoffer Hindlycke Examensarbete i matematik, 30 hp Handledare: Volodymyr Mazorchuk Examinator: Denis Gaidashev Mars 2019 Department of Mathematics Uppsala University Irreducible representations of finite monoids Christoffer Hindlycke Contents Introduction 2 Theory 3 Finite monoids and their structure . .3 Introductory notions . .3 Cyclic semigroups . .6 Green’s relations . .7 von Neumann regularity . 10 The theory of an idempotent . 11 The five functors Inde, Coinde, Rese,Te and Ne ..................... 11 Idempotents and simple modules . 14 Irreducible representations of a finite monoid . 17 Monoid algebras . 17 Clifford-Munn-Ponizovski˘ıtheory . 20 Application 24 The symmetric inverse monoid . 24 Calculating the irreducible representations of I3 ........................ 25 Appendix: Prerequisite theory 37 Basic definitions . 37 Finite dimensional algebras . 41 Semisimple modules and algebras . 41 Indecomposable modules . 42 An introduction to idempotents . 42 1 Irreducible representations of finite monoids Christoffer Hindlycke Introduction This paper is a literature study of the 2016 book Representation Theory of Finite Monoids by Benjamin Steinberg [3]. As this book contains too much interesting material for a simple master thesis, we have narrowed our attention to chapters 1, 4 and 5. This thesis is divided into three main parts: Theory, Application and Appendix. Within the Theory chapter, we (as the name might suggest) develop the necessary theory to assist with finding irreducible representations of finite monoids. Finite monoids and their structure gives elementary definitions as regards to finite monoids, and expands on the basic theory of their structure. This part corresponds to chapter 1 in [3]. The theory of an idempotent develops just enough theory regarding idempotents to enable us to state a key result, from which the principal result later follows almost immediately. -
1 Affine Varieties
1 Affine Varieties We will begin following Kempf's Algebraic Varieties, and eventually will do things more like in Hartshorne. We will also use various sources for commutative algebra. What is algebraic geometry? Classically, it is the study of the zero sets of polynomials. We will now fix some notation. k will be some fixed algebraically closed field, any ring is commutative with identity, ring homomorphisms preserve identity, and a k-algebra is a ring R which contains k (i.e., we have a ring homomorphism ι : k ! R). P ⊆ R an ideal is prime iff R=P is an integral domain. Algebraic Sets n n We define affine n-space, A = k = f(a1; : : : ; an): ai 2 kg. n Any f = f(x1; : : : ; xn) 2 k[x1; : : : ; xn] defines a function f : A ! k : (a1; : : : ; an) 7! f(a1; : : : ; an). Exercise If f; g 2 k[x1; : : : ; xn] define the same function then f = g as polynomials. Definition 1.1 (Algebraic Sets). Let S ⊆ k[x1; : : : ; xn] be any subset. Then V (S) = fa 2 An : f(a) = 0 for all f 2 Sg. A subset of An is called algebraic if it is of this form. e.g., a point f(a1; : : : ; an)g = V (x1 − a1; : : : ; xn − an). Exercises 1. I = (S) is the ideal generated by S. Then V (S) = V (I). 2. I ⊆ J ) V (J) ⊆ V (I). P 3. V ([αIα) = V ( Iα) = \V (Iα). 4. V (I \ J) = V (I · J) = V (I) [ V (J). Definition 1.2 (Zariski Topology). We can define a topology on An by defining the closed subsets to be the algebraic subsets. -
On the Relation Between Hyperrings and Fuzzy Rings
ON THE RELATION BETWEEN HYPERRINGS AND FUZZY RINGS JEFFREY GIANSIRACUSA, JAIUNG JUN, AND OLIVER LORSCHEID ABSTRACT. We construct a full embedding of the category of hyperfields into Dress’s category of fuzzy rings and explicitly characterize the essential image — it fails to be essentially surjective in a very minor way. This embedding provides an identification of Baker’s theory of matroids over hyperfields with Dress’s theory of matroids over fuzzy rings (provided one restricts to those fuzzy rings in the essential image). The embedding functor extends from hyperfields to hyperrings, and we study this extension in detail. We also analyze the relation between hyperfields and Baker’s partial demifields. 1. Introduction The important and pervasive combinatorial notion of matroids has spawned a number of variants over the years. In [Dre86] and [DW91], Dress and Wenzel developed a unified framework for these variants by introducing a generalization of rings called fuzzy rings and defining matroids with coefficients in a fuzzy ring. Various flavors of matroids, including ordinary matroids, oriented matroids, and the valuated matroids introduced in [DW92], correspond to different choices of the coefficient fuzzy ring. Roughly speaking, a fuzzy ring is a set S with single-valued unital addition and multiplication operations that satisfy a list of conditions analogous to those of a ring, such as distributivity, but only up to a tolerance prescribed by a distinguished ideal-like subset S0. Beyond the work of Dress and Wenzel, fuzzy rings have not yet received significant attention in the literature. A somewhat different generalization of rings, known as hyperrings, has been around for many decades and has been studied very broadly in the literature. -
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). -
Math 263A Notes: Algebraic Combinatorics and Symmetric Functions
MATH 263A NOTES: ALGEBRAIC COMBINATORICS AND SYMMETRIC FUNCTIONS AARON LANDESMAN CONTENTS 1. Introduction 4 2. 10/26/16 5 2.1. Logistics 5 2.2. Overview 5 2.3. Down to Math 5 2.4. Partitions 6 2.5. Partial Orders 7 2.6. Monomial Symmetric Functions 7 2.7. Elementary symmetric functions 8 2.8. Course Outline 8 3. 9/28/16 9 3.1. Elementary symmetric functions eλ 9 3.2. Homogeneous symmetric functions, hλ 10 3.3. Power sums pλ 12 4. 9/30/16 14 5. 10/3/16 20 5.1. Expected Number of Fixed Points 20 5.2. Random Matrix Groups 22 5.3. Schur Functions 23 6. 10/5/16 24 6.1. Review 24 6.2. Schur Basis 24 6.3. Hall Inner product 27 7. 10/7/16 29 7.1. Basic properties of the Cauchy product 29 7.2. Discussion of the Cauchy product and related formulas 30 8. 10/10/16 32 8.1. Finishing up last class 32 8.2. Skew-Schur Functions 33 8.3. Jacobi-Trudi 36 9. 10/12/16 37 1 2 AARON LANDESMAN 9.1. Eigenvalues of unitary matrices 37 9.2. Application 39 9.3. Strong Szego limit theorem 40 10. 10/14/16 41 10.1. Background on Tableau 43 10.2. KOSKA Numbers 44 11. 10/17/16 45 11.1. Relations of skew-Schur functions to other fields 45 11.2. Characters of the symmetric group 46 12. 10/19/16 49 13. 10/21/16 55 13.1. -
Multidisciplinary Design Project Engineering Dictionary Version 0.0.2
Multidisciplinary Design Project Engineering Dictionary Version 0.0.2 February 15, 2006 . DRAFT Cambridge-MIT Institute Multidisciplinary Design Project This Dictionary/Glossary of Engineering terms has been compiled to compliment the work developed as part of the Multi-disciplinary Design Project (MDP), which is a programme to develop teaching material and kits to aid the running of mechtronics projects in Universities and Schools. The project is being carried out with support from the Cambridge-MIT Institute undergraduate teaching programe. For more information about the project please visit the MDP website at http://www-mdp.eng.cam.ac.uk or contact Dr. Peter Long Prof. Alex Slocum Cambridge University Engineering Department Massachusetts Institute of Technology Trumpington Street, 77 Massachusetts Ave. Cambridge. Cambridge MA 02139-4307 CB2 1PZ. USA e-mail: [email protected] e-mail: [email protected] tel: +44 (0) 1223 332779 tel: +1 617 253 0012 For information about the CMI initiative please see Cambridge-MIT Institute website :- http://www.cambridge-mit.org CMI CMI, University of Cambridge Massachusetts Institute of Technology 10 Miller’s Yard, 77 Massachusetts Ave. Mill Lane, Cambridge MA 02139-4307 Cambridge. CB2 1RQ. USA tel: +44 (0) 1223 327207 tel. +1 617 253 7732 fax: +44 (0) 1223 765891 fax. +1 617 258 8539 . DRAFT 2 CMI-MDP Programme 1 Introduction This dictionary/glossary has not been developed as a definative work but as a useful reference book for engi- neering students to search when looking for the meaning of a word/phrase. It has been compiled from a number of existing glossaries together with a number of local additions.