Mathematical Objects and Mathematical Structure
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The Mathematical Structure of the Aesthetic
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 12 June 2017 doi:10.20944/preprints201706.0055.v1 Peer-reviewed version available at Philosophies 2017, 2, 14; doi:10.3390/philosophies2030014 Article A New Kind of Aesthetics – The Mathematical Structure of the Aesthetic Akihiro Kubota 1,*, Hirokazu Hori 2, Makoto Naruse 3 and Fuminori Akiba 4 1 Art and Media Course, Department of Information Design, Tama Art University, 2-1723 Yarimizu, Hachioji, Tokyo 192-0394, Japan; [email protected] 2 Interdisciplinary Graduate School, University of Yamanashi, 4-3-11 Takeda, Kofu,Yamanashi 400-8511, Japan; [email protected] 3 Network System Research Institute, National Institute of Information and Communications Technology, 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan; [email protected] 4 Philosophy of Information Group, Department of Systems and Social Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan; [email protected] * Correspondence: [email protected]; Tel.: +81-42-679-5634 Abstract: This paper proposes a new approach to investigation into the aesthetics. Specifically, it argues that it is possible to explain the aesthetic and its underlying dynamic relations with axiomatic structure (the octahedral axiom derived category) based on contemporary mathematics – namely, category theory – and through this argument suggests the possibility for discussion about the mathematical structure of the aesthetic. If there was a way to describe the structure of aesthetics with the language of mathematical structures and mathematical axioms – a language completely devoid of arbitrariness – then we would make possible a synthetical argument about the essential human activity of “the aesthetics”, and we would also gain a new method and viewpoint on the philosophy and meaning of the act of creating a work of art and artistic activities. -
Structure” of Physics: a Case Study∗ (Journal of Philosophy 106 (2009): 57–88)
The “Structure” of Physics: A Case Study∗ (Journal of Philosophy 106 (2009): 57–88) Jill North We are used to talking about the “structure” posited by a given theory of physics. We say that relativity is a theory about spacetime structure. Special relativity posits one spacetime structure; different models of general relativity posit different spacetime structures. We also talk of the “existence” of these structures. Special relativity says that the world’s spacetime structure is Minkowskian: it posits that this spacetime structure exists. Understanding structure in this sense seems important for understand- ing what physics is telling us about the world. But it is not immediately obvious just what this structure is, or what we mean by the existence of one structure, rather than another. The idea of mathematical structure is relatively straightforward. There is geometric structure, topological structure, algebraic structure, and so forth. Mathematical structure tells us how abstract mathematical objects t together to form different types of mathematical spaces. Insofar as we understand mathematical objects, we can understand mathematical structure. Of course, what to say about the nature of mathematical objects is not easy. But there seems to be no further problem for understanding mathematical structure. ∗For comments and discussion, I am extremely grateful to David Albert, Frank Arntzenius, Gordon Belot, Josh Brown, Adam Elga, Branden Fitelson, Peter Forrest, Hans Halvorson, Oliver Davis Johns, James Ladyman, David Malament, Oliver Pooley, Brad Skow, TedSider, Rich Thomason, Jason Turner, Dmitri Tymoczko, the philosophy faculty at Yale, audience members at The University of Michigan in fall 2006, and in 2007 at the Paci c APA, the Joint Session of the Aristotelian Society and Mind Association, and the Bellingham Summer Philosophy Conference. -
Group Theory
Appendix A Group Theory This appendix is a survey of only those topics in group theory that are needed to understand the composition of symmetry transformations and its consequences for fundamental physics. It is intended to be self-contained and covers those topics that are needed to follow the main text. Although in the end this appendix became quite long, a thorough understanding of group theory is possible only by consulting the appropriate literature in addition to this appendix. In order that this book not become too lengthy, proofs of theorems were largely omitted; again I refer to other monographs. From its very title, the book by H. Georgi [211] is the most appropriate if particle physics is the primary focus of interest. The book by G. Costa and G. Fogli [102] is written in the same spirit. Both books also cover the necessary group theory for grand unification ideas. A very comprehensive but also rather dense treatment is given by [428]. Still a classic is [254]; it contains more about the treatment of dynamical symmetries in quantum mechanics. A.1 Basics A.1.1 Definitions: Algebraic Structures From the structureless notion of a set, one can successively generate more and more algebraic structures. Those that play a prominent role in physics are defined in the following. Group A group G is a set with elements gi and an operation ◦ (called group multiplication) with the properties that (i) the operation is closed: gi ◦ g j ∈ G, (ii) a neutral element g0 ∈ G exists such that gi ◦ g0 = g0 ◦ gi = gi , (iii) for every gi exists an −1 ∈ ◦ −1 = = −1 ◦ inverse element gi G such that gi gi g0 gi gi , (iv) the operation is associative: gi ◦ (g j ◦ gk) = (gi ◦ g j ) ◦ gk. -
What's in a Name? the Matrix As an Introduction to Mathematics
St. John Fisher College Fisher Digital Publications Mathematical and Computing Sciences Faculty/Staff Publications Mathematical and Computing Sciences 9-2008 What's in a Name? The Matrix as an Introduction to Mathematics Kris H. Green St. John Fisher College, [email protected] Follow this and additional works at: https://fisherpub.sjfc.edu/math_facpub Part of the Mathematics Commons How has open access to Fisher Digital Publications benefited ou?y Publication Information Green, Kris H. (2008). "What's in a Name? The Matrix as an Introduction to Mathematics." Math Horizons 16.1, 18-21. Please note that the Publication Information provides general citation information and may not be appropriate for your discipline. To receive help in creating a citation based on your discipline, please visit http://libguides.sjfc.edu/citations. This document is posted at https://fisherpub.sjfc.edu/math_facpub/12 and is brought to you for free and open access by Fisher Digital Publications at St. John Fisher College. For more information, please contact [email protected]. What's in a Name? The Matrix as an Introduction to Mathematics Abstract In lieu of an abstract, here is the article's first paragraph: In my classes on the nature of scientific thought, I have often used the movie The Matrix to illustrate the nature of evidence and how it shapes the reality we perceive (or think we perceive). As a mathematician, I usually field questions elatedr to the movie whenever the subject of linear algebra arises, since this field is the study of matrices and their properties. So it is natural to ask, why does the movie title reference a mathematical object? Disciplines Mathematics Comments Article copyright 2008 by Math Horizons. -
The Matrix As an Introduction to Mathematics
St. John Fisher College Fisher Digital Publications Mathematical and Computing Sciences Faculty/Staff Publications Mathematical and Computing Sciences 2012 What's in a Name? The Matrix as an Introduction to Mathematics Kris H. Green St. John Fisher College, [email protected] Follow this and additional works at: https://fisherpub.sjfc.edu/math_facpub Part of the Mathematics Commons How has open access to Fisher Digital Publications benefited ou?y Publication Information Green, Kris H. (2012). "What's in a Name? The Matrix as an Introduction to Mathematics." Mathematics in Popular Culture: Essays on Appearances in Film, Fiction, Games, Television and Other Media , 44-54. Please note that the Publication Information provides general citation information and may not be appropriate for your discipline. To receive help in creating a citation based on your discipline, please visit http://libguides.sjfc.edu/citations. This document is posted at https://fisherpub.sjfc.edu/math_facpub/18 and is brought to you for free and open access by Fisher Digital Publications at St. John Fisher College. For more information, please contact [email protected]. What's in a Name? The Matrix as an Introduction to Mathematics Abstract In my classes on the nature of scientific thought, I have often used the movie The Matrix (1999) to illustrate how evidence shapes the reality we perceive (or think we perceive). As a mathematician and self-confessed science fiction fan, I usually field questionselated r to the movie whenever the subject of linear algebra arises, since this field is the study of matrices and their properties. So it is natural to ask, why does the movie title reference a mathematical object? Of course, there are many possible explanations for this, each of which probably contributed a little to the naming decision. -
Math Object Identifiers – Towards Research Data in Mathematics
Math Object Identifiers – Towards Research Data in Mathematics Michael Kohlhase Computer Science, FAU Erlangen-N¨urnberg Abstract. We propose to develop a system of “Math Object Identi- fiers” (MOIs: digital object identifiers for mathematical concepts, ob- jects, and models) and a process of registering them. These envisioned MOIs constitute a very lightweight form of semantic annotation that can support many knowledge-based workflows in mathematics, e.g. clas- sification of articles via the objects mentioned or object-based search. In essence MOIs are an enabling technology for Linked Open Data for mathematics and thus makes (parts of) the mathematical literature into mathematical research data. 1 Introduction The last years have seen a surge in interest in scaling computer support in scientific research by preserving, making accessible, and managing research data. For most subjects, research data consist in measurement or simulation data about the objects of study, ranging from subatomic particles via weather systems to galaxy clusters. Mathematics has largely been left untouched by this trend, since the objects of study – mathematical concepts, objects, and models – are by and large ab- stract and their properties and relations apply whole classes of objects. There are some exceptions to this, concrete integer sequences, finite groups, or ℓ-functions and modular form are collected and catalogued in mathematical data bases like the OEIS (Online Encyclopedia of Integer Sequences) [Inc; Slo12], the GAP Group libraries [GAP, Chap. 50], or the LMFDB (ℓ-Functions and Modular Forms Data Base) [LMFDB; Cre16]. Abstract mathematical structures like groups, manifolds, or probability dis- tributions can formalized – usually by definitions – in logical systems, and their relations expressed in form of theorems which can be proved in the logical sys- tems as well. -
1.3 Matrices and Matrix Operations 1.3.1 De…Nitions and Notation Matrices Are Yet Another Mathematical Object
20 CHAPTER 1. SYSTEMS OF LINEAR EQUATIONS AND MATRICES 1.3 Matrices and Matrix Operations 1.3.1 De…nitions and Notation Matrices are yet another mathematical object. Learning about matrices means learning what they are, how they are represented, the types of operations which can be performed on them, their properties and …nally their applications. De…nition 50 (matrix) 1. A matrix is a rectangular array of numbers. in which not only the value of the number is important but also its position in the array. 2. The numbers in the array are called the entries of the matrix. 3. The size of the matrix is described by the number of its rows and columns (always in this order). An m n matrix is a matrix which has m rows and n columns. 4. The elements (or the entries) of a matrix are generally enclosed in brack- ets, double-subscripting is used to index the elements. The …rst subscript always denote the row position, the second denotes the column position. For example a11 a12 ::: a1n a21 a22 ::: a2n A = 2 ::: ::: ::: ::: 3 (1.5) 6 ::: ::: ::: ::: 7 6 7 6 am1 am2 ::: amn 7 6 7 =4 [aij] , i = 1; 2; :::; m, j =5 1; 2; :::; n (1.6) Enclosing the general element aij in square brackets is another way of representing a matrix A . 5. When m = n , the matrix is said to be a square matrix. 6. The main diagonal in a square matrix contains the elements a11; a22; a33; ::: 7. A matrix is said to be upper triangular if all its entries below the main diagonal are 0. -
1 Sets and Set Notation. Definition 1 (Naive Definition of a Set)
LINEAR ALGEBRA MATH 2700.006 SPRING 2013 (COHEN) LECTURE NOTES 1 Sets and Set Notation. Definition 1 (Naive Definition of a Set). A set is any collection of objects, called the elements of that set. We will most often name sets using capital letters, like A, B, X, Y , etc., while the elements of a set will usually be given lower-case letters, like x, y, z, v, etc. Two sets X and Y are called equal if X and Y consist of exactly the same elements. In this case we write X = Y . Example 1 (Examples of Sets). (1) Let X be the collection of all integers greater than or equal to 5 and strictly less than 10. Then X is a set, and we may write: X = f5; 6; 7; 8; 9g The above notation is an example of a set being described explicitly, i.e. just by listing out all of its elements. The set brackets {· · ·} indicate that we are talking about a set and not a number, sequence, or other mathematical object. (2) Let E be the set of all even natural numbers. We may write: E = f0; 2; 4; 6; 8; :::g This is an example of an explicity described set with infinitely many elements. The ellipsis (:::) in the above notation is used somewhat informally, but in this case its meaning, that we should \continue counting forever," is clear from the context. (3) Let Y be the collection of all real numbers greater than or equal to 5 and strictly less than 10. Recalling notation from previous math courses, we may write: Y = [5; 10) This is an example of using interval notation to describe a set. -
The (Homo)Morphism Concept: Didactic Transposition, Meta-Discourse and Thematisation Thomas Hausberger
The (homo)morphism concept: didactic transposition, meta-discourse and thematisation Thomas Hausberger To cite this version: Thomas Hausberger. The (homo)morphism concept: didactic transposition, meta-discourse and the- matisation. International Journal of Research in Undergraduate Mathematics Education, Springer, 2017, 3 (3), pp.417-443. 10.1007/s40753-017-0052-7. hal-01408419 HAL Id: hal-01408419 https://hal.archives-ouvertes.fr/hal-01408419 Submitted on 20 Feb 2021 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. Noname manuscript No. (will be inserted by the editor) The (homo)morphism concept: didactic transposition, meta-discourse and thematisation Thomas Hausberger Received: date / Accepted: date Abstract This article focuses on the didactic transposition of the homomor- phism concept and on the elaboration and evaluation of an activity dedicated to the teaching of this fundamental concept in Abstract Algebra. It does not restrict to Group Theory but on the contrary raises the issue of the teaching and learning of algebraic structuralism, thus bridging Group and Ring Theo- ries and highlighting the phenomenon of thematisation. Emphasis is made on epistemological analysis and its interaction with didactics. The rationale of the isomorphism and homomorphism concepts is discussed, in particular through a textbook analysis focusing on the meta-discourse that mathematicians offer to illuminate the concepts. -
The Design and Validation of a Group Theory Concept Inventory
Portland State University PDXScholar Dissertations and Theses Dissertations and Theses Summer 8-10-2015 The Design and Validation of a Group Theory Concept Inventory Kathleen Mary Melhuish Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Part of the Algebra Commons, Higher Education Commons, and the Science and Mathematics Education Commons Let us know how access to this document benefits ou.y Recommended Citation Melhuish, Kathleen Mary, "The Design and Validation of a Group Theory Concept Inventory" (2015). Dissertations and Theses. Paper 2490. https://doi.org/10.15760/etd.2487 This Dissertation is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. The Design and Validation of a Group Theory Concept Inventory by Kathleen Mary Melhuish A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematics Education Dissertation Committee: Sean Larsen, Chair John Caughman Samuel Cook Andrea Goforth Portland State University 2015 © 2015 Kathleen Mary Melhuish Abstract Within undergraduate mathematics education, there are few validated instruments designed for large-scale usage. The Group Concept Inventory (GCI) was created as an instrument to evaluate student conceptions related to introductory group theory topics. The inventory was created in three phases: domain analysis, question creation, and field-testing. The domain analysis phase included using an expert protocol to arrive at the topics to be assessed, analyzing curriculum, and reviewing literature. -
Vector Spaces
Vector spaces The vector spaces Rn, properties of vectors, and generalizing - introduction Now that you have a grounding in working with vectors in concrete form, we go abstract again. Here’s the plan: (1) The set of all vectors of a given length n has operations of addition and scalar multiplication on it. (2) Vector addition and scalar multiplication have certain properties (which we’ve proven already) (3) We say that the set of vectors of length n with these operations form a vector space Rn (3) So let’s take any mathematical object (m × n matrix, continuous function, discontinuous function, integrable function) and define operations that we’ll call “addition” and “scalar multiplication” on that object. If the set of those objects satisfies all the same properties that vectors do ... we’ll call them ... I know ... we’ll call them vectors, and say that they form a vector space. Functions can be vectors! Matrices can be vectors! (4) Why stop there? You know the dot product? Of two vectors? That had some properties, which were proven for vectors of length n? If we can define a function on our other “vectors” (matrices! continuous functions!) that has the same properties ... we’ll call it a dot product too. Actually, the more general term is inner product. (5) Finally, vector norms (magnitudes). Have properties. Which were proven for vectors of length n.So,ifwecan define functions on our other “vectors” that have the same properties ... those are norms, too. In fact, we can even define other norms on regular vectors in Rn - there is more than one way to measure the length of an vector. -
Structure, Isomorphism and Symmetry We Want to Give a General Definition
Structure, Isomorphism and Symmetry We want to give a general definition of what is meant by a (mathematical) structure that will cover most of the structures that you will meet. It is in this setting that we will define what is meant by isomorphism and symmetry. We begin with the simplest type of structure, that of an internal structure on a set. Definition 1 (Internal Structure). An internal structure on a set A is any element of A or of any set that can be obtained from A by means of Cartesian products and the power set operation, e.g., A £ A, }(A), A £ }(A), }((A £ A) £ A),... Example 1 (An Element of A). a 2 A Example 2 (A Relation on A). R ⊆ A £ A =) R 2 }(A £ A). Example 3 (A Binary Operation on A). p : A £ A ! A =) p 2 }((A £ A) £ A). To define an external structure on a set A (e.g. a vector space structure) we introduce a second set K. The elements of K or of those sets which can be obtained from K and A by means of Cartesian products and the power set operation and which is not an internal structure on A are called K-structures on A. Definition 2 (K-Structure). A K-structure on a set A is any element of K or of those sets which can be obtained from K and A by means of Cartesian products and the power set operation and which is not an internal structure on A. Example 4 (External Operation on A).