Domain and Range Operations in Semigroups and Rings
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Computing Finite Semigroups
Computing finite semigroups J. East, A. Egri-Nagy, J. D. Mitchell, and Y. P´eresse August 24, 2018 Abstract Using a variant of Schreier's Theorem, and the theory of Green's relations, we show how to reduce the computation of an arbitrary subsemigroup of a finite regular semigroup to that of certain associated subgroups. Examples of semigroups to which these results apply include many important classes: transformation semigroups, partial permutation semigroups and inverse semigroups, partition monoids, matrix semigroups, and subsemigroups of finite regular Rees matrix and 0-matrix semigroups over groups. For any subsemigroup of such a semigroup, it is possible to, among other things, efficiently compute its size and Green's relations, test membership, factorize elements over the generators, find the semigroup generated by the given subsemigroup and any collection of additional elements, calculate the partial order of the D-classes, test regularity, and determine the idempotents. This is achieved by representing the given subsemigroup without exhaustively enumerating its elements. It is also possible to compute the Green's classes of an element of such a subsemigroup without determining the global structure of the semigroup. Contents 1 Introduction 2 2 Mathematical prerequisites4 3 From transformation semigroups to arbitrary regular semigroups6 3.1 Actions on Green's classes . .6 3.2 Faithful representations of stabilisers . .7 3.3 A decomposition for Green's classes . .8 3.4 Membership testing . 11 3.5 Classes within classes . 13 4 Specific classes of semigroups 14 4.1 Transformation semigroups . 15 4.2 Partial permutation semigroups and inverse semigroups . 16 4.3 Matrix semigroups . -
Free Idempotent Generated Semigroups and Endomorphism Monoids of Independence Algebras
Free idempotent generated semigroups and endomorphism monoids of independence algebras Yang Dandan & Victoria Gould Semigroup Forum ISSN 0037-1912 Semigroup Forum DOI 10.1007/s00233-016-9802-0 1 23 Your article is published under the Creative Commons Attribution license which allows users to read, copy, distribute and make derivative works, as long as the author of the original work is cited. You may self- archive this article on your own website, an institutional repository or funder’s repository and make it publicly available immediately. 1 23 Semigroup Forum DOI 10.1007/s00233-016-9802-0 RESEARCH ARTICLE Free idempotent generated semigroups and endomorphism monoids of independence algebras Yang Dandan1 · Victoria Gould2 Received: 18 January 2016 / Accepted: 3 May 2016 © The Author(s) 2016. This article is published with open access at Springerlink.com Abstract We study maximal subgroups of the free idempotent generated semigroup IG(E), where E is the biordered set of idempotents of the endomorphism monoid End A of an independence algebra A, in the case where A has no constants and has finite rank n. It is shown that when n ≥ 3 the maximal subgroup of IG(E) containing a rank 1 idempotent ε is isomorphic to the corresponding maximal subgroup of End A containing ε. The latter is the group of all unary term operations of A. Note that the class of independence algebras with no constants includes sets, free group acts and affine algebras. Keywords Independence algebra · Idempotent · Biordered set 1 Introduction Let S be a semigroup with set E = E(S) of idempotents, and let E denote the subsemigroup of S generated by E. -
Arxiv:1905.10901V1 [Cs.LG] 26 May 2019
Seeing Convolution Through the Eyes of Finite Transformation Semigroup Theory: An Abstract Algebraic Interpretation of Convolutional Neural Networks Andrew Hryniowski1;2;3, Alexander Wong1;2;3 1 Video and Image Processing Research Group, Systems Design Engineering, University of Waterloo 2 Waterloo Artificial Intelligence Institute, Waterloo, ON 3 DarwinAI Corp., Waterloo, ON fapphryni, [email protected] Abstract of applications, particularly for prediction using structured data. Despite such successes, a major challenge with lever- Researchers are actively trying to gain better insights aging convolutional neural networks is the sheer number of into the representational properties of convolutional neural learnable parameters within such networks, making under- networks for guiding better network designs and for inter- standing and gaining insights about them a daunting task. As preting a network’s computational nature. Gaining such such, researchers are actively trying to gain better insights insights can be an arduous task due to the number of pa- and understanding into the representational properties of rameters in a network and the complexity of a network’s convolutional neural networks, especially since it can lead architecture. Current approaches of neural network inter- to better design and interpretability of such networks. pretation include Bayesian probabilistic interpretations and One direction that holds a lot of promise in improving information theoretic interpretations. In this study, we take a understanding of convolutional neural networks, but is much different approach to studying convolutional neural networks less explored than other approaches, is the construction of by proposing an abstract algebraic interpretation using finite theoretical models and interpretations of such networks. Cur- transformation semigroup theory. -
Transformation Semigroups and Their Automorphisms
Transformation Semigroups and their Automorphisms Wolfram Bentz University of Hull Joint work with Jo~aoAra´ujo(CEMAT, Universidade Nova de Lisboa) Peter J. Cameron (University of St Andrews) York Semigroup York, October 9, 2019 X Let X be a set and TX = X be full transformation monoid on X , under composition. Note that TX contains the symmetric group over X (as its group of units) We will only consider finite X , and more specifically Tn = TXn , Sn = SXn , where Xn = f1;:::; ng for n 2 N For S ≤ Tn, we are looking at the interaction of S \ Sn and S Transformation Monoids and Permutation Groups Wolfram Bentz (Hull) Transformation Semigroups October 9, 2019 2 / 23 Note that TX contains the symmetric group over X (as its group of units) We will only consider finite X , and more specifically Tn = TXn , Sn = SXn , where Xn = f1;:::; ng for n 2 N For S ≤ Tn, we are looking at the interaction of S \ Sn and S Transformation Monoids and Permutation Groups X Let X be a set and TX = X be full transformation monoid on X , under composition. Wolfram Bentz (Hull) Transformation Semigroups October 9, 2019 2 / 23 We will only consider finite X , and more specifically Tn = TXn , Sn = SXn , where Xn = f1;:::; ng for n 2 N For S ≤ Tn, we are looking at the interaction of S \ Sn and S Transformation Monoids and Permutation Groups X Let X be a set and TX = X be full transformation monoid on X , under composition. Note that TX contains the symmetric group over X (as its group of units) Wolfram Bentz (Hull) Transformation Semigroups October 9, 2019 2 / 23 Transformation Monoids and Permutation Groups X Let X be a set and TX = X be full transformation monoid on X , under composition. -
Green's Relations in Finite Transformation Semigroups
Green’s Relations in Finite Transformation Semigroups Lukas Fleischer Manfred Kufleitner FMI, University of Stuttgart∗ Universitätsstraße 38, 70569 Stuttgart, Germany {fleischer,kufleitner}@fmi.uni-stuttgart.de Abstract. We consider the complexity of Green’s relations when the semigroup is given by transformations on a finite set. Green’s relations can be defined by reachability in the (right/left/two-sided) Cayley graph. The equivalence classes then correspond to the strongly connected com- ponents. It is not difficult to show that, in the worst case, the number of equivalence classes is in the same order of magnitude as the number of el- ements. Another important parameter is the maximal length of a chain of components. Our main contribution is an exponential lower bound for this parameter. There is a simple construction for an arbitrary set of generators. However, the proof for constant alphabet is rather involved. Our results also apply to automata and their syntactic semigroups. 1 Introduction Let Q be a finite set with n elements. There are nn mappings from Q to Q. Such mappings are called transformations and the elements of Q are called states. The composition of transformations defines an associative operation. If Σ is some arbi- trary subset of transformations, we can consider the transformation semigroup S generated by Σ; this is the closure of Σ under composition.1 The set of all trans- arXiv:1703.04941v1 [cs.FL] 15 Mar 2017 formations on Q is called the full transformation semigroup on Q. One can view (Q, Σ) as a description of S. Since every element s of a semigroup S defines a trans- formation x 7→ x · s on S1 = S ∪ {1}, every semigroup S admits such a description ∗ This work was supported by the DFG grants DI 435/5-2 and KU 2716/1-1. -
Math 311 - Introduction to Proof and Abstract Mathematics Group Assignment # 15 Name: Due: at the End of Class on Tuesday, March 26Th
Math 311 - Introduction to Proof and Abstract Mathematics Group Assignment # 15 Name: Due: At the end of class on Tuesday, March 26th More on Functions: Definition 5.1.7: Let A, B, C, and D be sets. Let f : A B and g : C D be functions. Then f = g if: → → A = C and B = D • For all x A, f(x)= g(x). • ∈ Intuitively speaking, this definition tells us that a function is determined by its underlying correspondence, not its specific formula or rule. Another way to think of this is that a function is determined by the set of points that occur on its graph. 1. Give a specific example of two functions that are defined by different rules (or formulas) but that are equal as functions. 2. Consider the functions f(x)= x and g(x)= √x2. Find: (a) A domain for which these functions are equal. (b) A domain for which these functions are not equal. Definition 5.1.9 Let X be a set. The identity function on X is the function IX : X X defined by, for all x X, → ∈ IX (x)= x. 3. Let f(x)= x cos(2πx). Prove that f(x) is the identity function when X = Z but not when X = R. Definition 5.1.10 Let n Z with n 0, and let a0,a1, ,an R such that an = 0. The function p : R R is a ∈ ≥ ··· ∈ 6 n n−1 → polynomial of degree n with real coefficients a0,a1, ,an if for all x R, p(x)= anx +an−1x + +a1x+a0. -
1 Monoids and Groups
1 Monoids and groups 1.1 Definition. A monoid is a set M together with a map M × M ! M; (x; y) 7! x · y such that (i) (x · y) · z = x · (y · z) 8x; y; z 2 M (associativity); (ii) 9e 2 M such that x · e = e · x = x for all x 2 M (e = the identity element of M). 1.2 Examples. 1) Z with addition of integers (e = 0) 2) Z with multiplication of integers (e = 1) 3) Mn(R) = fthe set of all n × n matrices with coefficients in Rg with ma- trix multiplication (e = I = the identity matrix) 4) U = any set P (U) := fthe set of all subsets of Ug P (U) is a monoid with A · B := A [ B and e = ?. 5) Let U = any set F (U) := fthe set of all functions f : U ! Ug F (U) is a monoid with multiplication given by composition of functions (e = idU = the identity function). 1.3 Definition. A monoid is commutative if x · y = y · x for all x; y 2 M. 1.4 Example. Monoids 1), 2), 4) in 1.2 are commutative; 3), 5) are not. 1 1.5 Note. Associativity implies that for x1; : : : ; xk 2 M the expression x1 · x2 ····· xk has the same value regardless how we place parentheses within it; e.g.: (x1 · x2) · (x3 · x4) = ((x1 · x2) · x3) · x4 = x1 · ((x2 · x3) · x4) etc. 1.6 Note. A monoid has only one identity element: if e; e0 2 M are identity elements then e = e · e0 = e0 1.7 Definition. -
Lecture 3 Partially Ordered Sets
Lecture 3 Partially ordered sets Now for something totally different. In life, useful sets are rarely “just” sets. They often come with additional structure. For example, R isn’t useful just because it’s some set. It’s useful because we can add its elements, multiply its elements, and even compare its elements. If A is, for example, the set of all bananas and apples on earth, it’s not as natural to do any of these things with elements of A. Today, we’ll talk about a structure called a partial order. 3.1 Preliminaries First, let me remind you of something called the Cartesian product, or direct product of sets. Definition 3.1.1. Let A and B be sets. Then the Cartesian product of A and B is defined to be the set consisting of all pairs (a, b) where a A and œ b B. We denote the Cartesian product by œ A B. ◊ Example 3.1.2. R2 is the Cartesian product R R. ◊ Example 3.1.3. Let T be the set of all t-shirts in Hiro’s closet, and S the set of all shorts in Hiro’s closet. Then S T represents the collection of all ◊ possible outfits Hiro is willing to consider in August. (I.e., Hiro is willing to consider putting on any of his shorts together with any of his t-shirts.) 23 24 LECTURE 3. PARTIALLY ORDERED SETS Note that we can “repeat” the Cartesian product operation, or apply it many times at once. Example 3.1.4. -
Lecture 19: Alternating Group
MATH 433 Applied Algebra Lecture 19: Alternating group. Abstract groups. Sign of a permutation Theorem 1 For any n ≥ 2 there exists a unique function sgn : S(n) → {−1, 1} such that • sgn(πσ)= sgn(π) sgn(σ) for all π, σ ∈ S(n), • sgn(τ)= −1 for any transposition τ in S(n). A permutation π is called even if it is a product of an even number of transpositions, and odd if it is a product of an odd number of transpositions. It turns out that π is even if sgn(π)=1 and odd if sgn(π)= −1. Theorem 2 (i) sgn(πσ)= sgn(π) sgn(σ) for any π, σ ∈ S(n). (ii) sgn(π−1)= sgn(π) for any π ∈ S(n). (iii) sgn(id) = 1. (iv) sgn(τ)= −1 for any transposition τ. (v) sgn(σ)=(−1)r−1 for any cycle σ of length r. Alternating group Given an integer n ≥ 2, the alternating group on n symbols, denoted An or A(n), is the set of all even permutations in the symmetric group S(n). Theorem (i) For any two permutations π, σ ∈ A(n), the product πσ is also in A(n). (ii) The identity function id is in A(n). (iii) For any permutation π ∈ A(n), the inverse π−1 is in A(n). In other words, the product of even permutations is even, the identity function is an even permutation, and the inverse of an even permutation is even. Theorem The alternating group A(n) has n!/2 elements. -
Theoretical Probability and Statistics
Theoretical Probability and Statistics Charles J. Geyer Copyright 1998, 1999, 2000, 2001, 2008 by Charles J. Geyer September 5, 2008 Contents 1 Finite Probability Models 1 1.1 Probability Mass Functions . 1 1.2 Events and Measures . 5 1.3 Random Variables and Expectation . 6 A Greek Letters 9 B Sets and Functions 11 B.1 Sets . 11 B.2 Intervals . 12 B.3 Functions . 12 C Summary of Brand-Name Distributions 14 C.1 The Discrete Uniform Distribution . 14 C.2 The Bernoulli Distribution . 14 i Chapter 1 Finite Probability Models The fundamental idea in probability theory is a probability model, also called a probability distribution. Probability models can be specified in several differ- ent ways • probability mass function (PMF), • probability density function (PDF), • distribution function (DF), • probability measure, and • function mapping from one probability model to another. We will meet probability mass functions and probability measures in this chap- ter, and will meet others later. The terms “probability model” and “probability distribution” don’t indicate how the model is specified, just that it is specified somehow. 1.1 Probability Mass Functions A probability mass function (PMF) is a function pr Ω −−−−→ R which satisfies the following conditions: its values are nonnegative pr(ω) ≥ 0, ω ∈ Ω (1.1a) and sum to one X pr(ω) = 1. (1.1b) ω∈Ω The domain Ω of the PMF is called the sample space of the probability model. The sample space is required to be nonempty in order that (1.1b) make sense. 1 CHAPTER 1. FINITE PROBABILITY MODELS 2 In this chapter we require all sample spaces to be finite sets. -
Inverse Monoids Associated with the Complexity Class NP
Inverse monoids associated with the complexity class NP J.C. Birget 6 March 2017 Abstract We study the P versus NP problem through properties of functions and monoids, continuing the work of [3]. Here we consider inverse monoids whose properties and relationships determine whether P is different from NP, or whether injective one-way functions (with respect to worst-case complexity) exist. 1 Introduction We give a few definitions before motivating the monoid approach to the P versus NP problem. Some of these notions appeared already in [3]. By function we mean a partial function A∗ → A∗, where A is a finite alphabet (usually, A = {0, 1}), and A∗ denotes the set of all finite strings over A. Let Dom(f) (⊆ A∗) denote the domain of f, i.e., {x ∈ A∗ : f(x) is defined}; and let Im(f) (⊆ A∗) denote the image (or range) of f, i.e., {f(x) : x ∈ ∗ ∗ Dom(f)}. The length of x ∈ A is denoted by |x|. The restriction of f to X ⊆ A is denoted by f|X , and the identity function on X is denoted by idX or id|X . Definition 1.1 (inverse, co-inverse, mutual inverse) A function f ′ is an inverse of a function f iff f ◦ f ′ ◦ f = f. In that case we also say that f is a co-inverse of f ′. If f ′ is both an inverse and a co-inverse of f, we say that f ′ is a mutual inverse of f, or that f ′ and f are mutual inverses (of each other).1 It is easy to see that f ′ is an inverse of f iff for every y ∈ Im(f): f ′(y) is defined and f ′(y) ∈ f −1(y). -
Math 131: Introduction to Topology 1
Math 131: Introduction to Topology 1 Professor Denis Auroux Fall, 2019 Contents 9/4/2019 - Introduction, Metric Spaces, Basic Notions3 9/9/2019 - Topological Spaces, Bases9 9/11/2019 - Subspaces, Products, Continuity 15 9/16/2019 - Continuity, Homeomorphisms, Limit Points 21 9/18/2019 - Sequences, Limits, Products 26 9/23/2019 - More Product Topologies, Connectedness 32 9/25/2019 - Connectedness, Path Connectedness 37 9/30/2019 - Compactness 42 10/2/2019 - Compactness, Uncountability, Metric Spaces 45 10/7/2019 - Compactness, Limit Points, Sequences 49 10/9/2019 - Compactifications and Local Compactness 53 10/16/2019 - Countability, Separability, and Normal Spaces 57 10/21/2019 - Urysohn's Lemma and the Metrization Theorem 61 1 Please email Beckham Myers at [email protected] with any corrections, questions, or comments. Any mistakes or errors are mine. 10/23/2019 - Category Theory, Paths, Homotopy 64 10/28/2019 - The Fundamental Group(oid) 70 10/30/2019 - Covering Spaces, Path Lifting 75 11/4/2019 - Fundamental Group of the Circle, Quotients and Gluing 80 11/6/2019 - The Brouwer Fixed Point Theorem 85 11/11/2019 - Antipodes and the Borsuk-Ulam Theorem 88 11/13/2019 - Deformation Retracts and Homotopy Equivalence 91 11/18/2019 - Computing the Fundamental Group 95 11/20/2019 - Equivalence of Covering Spaces and the Universal Cover 99 11/25/2019 - Universal Covering Spaces, Free Groups 104 12/2/2019 - Seifert-Van Kampen Theorem, Final Examples 109 2 9/4/2019 - Introduction, Metric Spaces, Basic Notions The instructor for this course is Professor Denis Auroux. His email is [email protected] and his office is SC539.