DOCSLIB.ORG

Concepts of Mathematics for Students of Physics and Engineering: a Dictionary

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Concepts of Mathematics for Students of Physics and Engineering: a Dictionary NASA/TP—2003-212088 Concepts of Mathematics for Students of Physics and Engineering: A Dictionary Joseph C. Kolecki Glenn Research Center, Cleveland, Ohio August 2003 The NASA STI Program Office . in Profile Since its founding, NASA has been dedicated to • CONFERENCE PUBLICATION. Collected the advancement of aeronautics and space papers from scientific and technical science. The NASA Scientific and Technical conferences, symposia, seminars, or other Information (STI) Program Office plays a key part meetings sponsored or cosponsored by in helping NASA maintain this important role. NASA. The NASA STI Program Office is operated by • SPECIAL PUBLICATION. Scientific, Langley Research Center, the Lead Center for technical, or historical information from NASA’s scientific and technical information. The NASA programs, projects, and missions, NASA STI Program Office provides access to the often concerned with subjects having NASA STI Database, the largest collection of substantial public interest. aeronautical and space science STI in the world. The Program Office is also NASA’s institutional • TECHNICAL TRANSLATION. English- mechanism for disseminating the results of its language translations of foreign scientific research and development activities. These results and technical material pertinent to NASA’s are published by NASA in the NASA STI Report mission. Series, which includes the following report types: Specialized services that complement the STI • TECHNICAL PUBLICATION. Reports of Program Office’s diverse offerings include completed research or a major significant creating custom thesauri, building customized phase of research that present the results of databases, organizing and publishing research NASA programs and include extensive data results . even providing videos. or theoretical analysis. Includes compilations of significant scientific and technical data and For more information about the NASA STI information deemed to be of continuing Program Office, see the following: reference value. NASA’s counterpart of peer- reviewed formal professional papers but • Access the NASA STI Program Home Page has less stringent limitations on manuscript at http://www.sti.nasa.gov length and extent of graphic presentations. • E-mail your question via the Internet to • TECHNICAL MEMORANDUM. Scientific [email protected] and technical findings that are preliminary or of specialized interest, e.g., quick release • Fax your question to the NASA Access reports, working papers, and bibliographies Help Desk at 301–621–0134 that contain minimal annotation. Does not contain extensive analysis. • Telephone the NASA Access Help Desk at 301–621–0390 • CONTRACTOR REPORT. Scientific and technical findings by NASA-sponsored • Write to: contractors and grantees. NASA Access Help Desk NASA Center for AeroSpace Information 7121 Standard Drive Hanover, MD 21076 NASA/TP—2003-212088 Concepts of Mathematics for Students of Physics and Engineering: A Dictionary Joseph C. Kolecki Glenn Research Center, Cleveland, Ohio National Aeronautics and Space Administration Glenn Research Center August 2003 Available from NASA Center for Aerospace Information National Technical Information Service 7121 Standard Drive 5285 Port Royal Road Hanover, MD 21076 Springfield, VA 22100 Available electronically at http://gltrs.grc.nasa.gov Table of Contents Summary ............................................................................................................................................... 1 Introduction ........................................................................................................................................... 1 Logic and Reasoning ............................................................................................................................. 1 Sets ........................................................................................................................................................ 2 Logical Sentences and Truth Sets ......................................................................................................... 4 Numbers ................................................................................................................................................ 5 Primes and Factors ................................................................................................................................ 6 Intervals of the Real Line ...................................................................................................................... 7 Relations ................................................................................................................................................ 8 Equivalence .......................................................................................................................................... 9 Ordering ............................................................................................................................................... 9 Mapping .............................................................................................................................................. 11 Transformations .................................................................................................................................. 11 Functions.............................................................................................................................................. 12 Sequences............................................................................................................................................. 13 Curves, Surfaces, and Regions............................................................................................................. 15 Mathematical Spaces............................................................................................................................ 16 Abstract Algebra .................................................................................................................................. 17 Appendixes AIdeas From Various Mathematical Disciplines ........................................................................ 21 BDivisibility of Integers in Base 10 (Integer10)........................................................................... 25 CImplications and Equivalences ................................................................................................. 27 DConjunctions and Disjunctions................................................................................................. 29 ELaws and Theorems of Logic ................................................................................................... 31 FLaws and Theorems of Set Algebra.......................................................................................... 33 GProperties of Continuous Functions ......................................................................................... 35 HDefinitions and Theorems From Calculus................................................................................ 37 I Real-Valued Functions as a Vector Space ................................................................................ 43 JLogical Puzzles and Paradoxes.................................................................................................. 45 KBasics of Aristotelian Logic ..................................................................................................... 49 Bibliography......................................................................................................................................... 53 NASA/TP—2003-212088 iii Concepts of Mathematics for Students of Physics and Engineering: A Dictionary Joseph C. Kolecki National Aeronautics and Space Administration Glenn Research Center Cleveland, Ohio 44135 Summary The appendixes are a compendium of additional A physicist with an engineering background, the au- topics, the contents of which are too large to be thor presents a mathematical dictionary containing included as individual citations. I have compiled material encountered over many years of study and compendia such as these ever since high school to professional work at NASA. This work is a compi- enable me to rationally organize material from a lation of the author’s experience and progress in the variety of areas and to supplement missing field of study represented and consists of personal information in published material. For example, the notes and observations that can be used by students in material in appendix H, Definitions and Theorems physics and engineering. From Calculus, enabled me to see the actual lay of the land without worrying about the complex supporting arguments and proofs. The beauty in mathematical Introduction theorems can be seen most clearly when they are treated in this manner. This mathematics dictionary is one of three that I Mathematics is an endless field of study, and no one compiled over the years and is the most complete, my publication can encompass it or even begin to. intentions having been to publish it for two reasons: Although the present book makes no such claims, the the first is that the material contained herein represents reader may ask, Why write such a mathematics areas of knowledge I had to assimilate and apply when dictionary at all when there are numerous ones on the called upon. As a physicist with an engineering market? The answer is that dictionaries differ: formal background, my work encompassed both fields. dictionaries function as
Load more

Recommended publications
  • A Theory of Well-Connected Relations 99
    INFORMA TION SCIENCES 19, 97- 134 (1979) 97 A Theory of Well-conwcted Relations SUDHIR K. ARORA and K. C. SMITH Lkpartment of Conputer Science, Uniwrsity of Toronto, Toronto, Cuna& MSS IA7 Communicated by John M. Richardson ABSTRACT The simple concept of a well-connected relation (WCR) is defined and then developed into a theory for studying the structure of binary relations. Several interesting partitions of a binary relation are identified. It is shown that binary relations can be separated into families which form a hierarchy. Finally, concepts of universal algebra are extended to the family of “prime” relations. One application for the theory is in the logical design of data bases. INTRODUCTION Data in an information system have been studied from several points of view [2, 4, 9, 10, Ill. With the growing interest in data base systems, the possibility for structuring the data in various ways has been explored by several authors. For example, Delobel [9] defines “elementary functional relations” and proposes a theory based on this building block; Zaniolo [lo] defines “atomic relations” as a basic building block for data; Furtado and Kerschberg [ 1 l] have “quotient relations.” Further, many authors have noted and studied specific data structures, such as “functional dependencies” [4], “multivalued dependencies” [5], “contextual dependencies” [6], “mutual de- pendencies” [12] (which happen to be same as contextual dependencies), and “hierarchical dependencies” [ 131. In this paper we define a new building block, “well-connected relations,” and propose a theory to study binary relations. Elsewhere [6] we have applied this theory to the study of dependency structures of data.
    [Show full text]
  • Math Preliminaries
    Preliminaries We establish here a few notational conventions used throughout the text. Arithmetic with ∞ We shall sometimes use the symbols “∞” and “−∞” in simple arithmetic expressions involving real numbers. The interpretation given to such ex- pressions is the usual, natural one; for example, for all real numbers x, we have −∞ < x < ∞, x + ∞ = ∞, x − ∞ = −∞, ∞ + ∞ = ∞, and (−∞) + (−∞) = −∞. Some such expressions have no sensible interpreta- tion (e.g., ∞ − ∞). Logarithms and exponentials We denote by log x the natural logarithm of x. The logarithm of x to the base b is denoted logb x. We denote by ex the usual exponential function, where e ≈ 2.71828 is the base of the natural logarithm. We may also write exp[x] instead of ex. Sets and relations We use the symbol ∅ to denote the empty set. For two sets A, B, we use the notation A ⊆ B to mean that A is a subset of B (with A possibly equal to B), and the notation A ( B to mean that A is a proper subset of B (i.e., A ⊆ B but A 6= B); further, A ∪ B denotes the union of A and B, A ∩ B the intersection of A and B, and A \ B the set of all elements of A that are not in B. For sets S1,...,Sn, we denote by S1 × · · · × Sn the Cartesian product xiv Preliminaries xv of S1,...,Sn, that is, the set of all n-tuples (a1, . , an), where ai ∈ Si for i = 1, . , n. We use the notation S×n to denote the Cartesian product of n copies of a set S, and for x ∈ S, we denote by x×n the element of S×n consisting of n copies of x.
    [Show full text]
  • Sets, Relations, Pos and Lattices
    Contents 1 Discrete structures F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 1 / 23 Discrete structures Section outline Lattices (contd.) Boolean lattice 1 Discrete structures Boolean lattice structure Sets Boolean algebra Relations Additional Boolean algebra Lattices properties F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 2 / 23 S = fXjX 62 Xg S 2 S? [Russell’s paradox] Set union: A [ B A B Set intersection: A \ B A B U Complement: S A Set difference: A − B = A \ B A B + Natural numbers: N = f0; 1; 2; 3;:::g or f1; 2; 3;:::g = Z Integers: Z = f:::; −3; −2; −1; 0; 1; 2; 3;:::g Universal set: U Empty set: ? = fg Discrete structures Sets Sets A set A of elements: A = fa; b; cg F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 3 / 23 S = fXjX 62 Xg S 2 S? [Russell’s paradox] Set union: A [ B A B Set intersection: A \ B A B U Complement: S A Set difference: A − B = A \ B A B Integers: Z = f:::; −3; −2; −1; 0; 1; 2; 3;:::g Universal set: U Empty set: ? = fg Discrete structures Sets Sets A set A of elements: A = fa; b; cg + Natural numbers: N = f0; 1; 2; 3;:::g or f1; 2; 3;:::g = Z F TECHN O OL E O T G U Y IT K T H S A N R I A N G A P I U D R N I 19 51 yog, km s kOflm^ Chittaranjan Mandal (IIT Kharagpur) SCLD January 21, 2020 3 / 23 S = fXjX
    [Show full text]
  • Sets, Functions
    Sets 1 Sets Informally: A set is a collection of (mathematical) objects, with the collection treated as a single mathematical object. Examples: • real numbers, • complex numbers, C • integers, • All students in our class Defining Sets Sets can be defined directly: e.g. {1,2,4,8,16,32,…}, {CSC1130,CSC2110,…} Order, number of occurence are not important. e.g. {A,B,C} = {C,B,A} = {A,A,B,C,B} A set can be an element of another set. {1,{2},{3,{4}}} Defining Sets by Predicates The set of elements, x, in A such that P(x) is true. {}x APx| ( ) The set of prime numbers: Commonly Used Sets • N = {0, 1, 2, 3, …}, the set of natural numbers • Z = {…, -2, -1, 0, 1, 2, …}, the set of integers • Z+ = {1, 2, 3, …}, the set of positive integers • Q = {p/q | p Z, q Z, and q ≠ 0}, the set of rational numbers • R, the set of real numbers Special Sets • Empty Set (null set): a set that has no elements, denoted by ф or {}. • Example: The set of all positive integers that are greater than their squares is an empty set. • Singleton set: a set with one element • Compare: ф and {ф} – Ф: an empty set. Think of this as an empty folder – {ф}: a set with one element. The element is an empty set. Think of this as an folder with an empty folder in it. Venn Diagrams • Represent sets graphically • The universal set U, which contains all the objects under consideration, is represented by a rectangle.
    [Show full text]
  • Cantor on Infinity in Nature, Number, and the Divine Mind
    Cantor on Infinity in Nature, Number, and the Divine Mind Anne Newstead Abstract. The mathematician Georg Cantor strongly believed in the existence of actually infinite numbers and sets. Cantor’s “actualism” went against the Aristote- lian tradition in metaphysics and mathematics. Under the pressures to defend his theory, his metaphysics changed from Spinozistic monism to Leibnizian volunta- rist dualism. The factor motivating this change was two-fold: the desire to avoid antinomies associated with the notion of a universal collection and the desire to avoid the heresy of necessitarian pantheism. We document the changes in Can- tor’s thought with reference to his main philosophical-mathematical treatise, the Grundlagen (1883) as well as with reference to his article, “Über die verschiedenen Standpunkte in bezug auf das aktuelle Unendliche” (“Concerning Various Perspec- tives on the Actual Infinite”) (1885). I. he Philosophical Reception of Cantor’s Ideas. Georg Cantor’s dis- covery of transfinite numbers was revolutionary. Bertrand Russell Tdescribed it thus: The mathematical theory of infinity may almost be said to begin with Cantor. The infinitesimal Calculus, though it cannot wholly dispense with infinity, has as few dealings with it as possible, and contrives to hide it away before facing the world Cantor has abandoned this cowardly policy, and has brought the skeleton out of its cupboard. He has been emboldened on this course by denying that it is a skeleton. Indeed, like many other skeletons, it was wholly dependent on its cupboard, and vanished in the light of day.1 1Bertrand Russell, The Principles of Mathematics (London: Routledge, 1992 [1903]), 304.
    [Show full text]
  • The Structure of the 3-Separations of 3-Connected Matroids
    THE STRUCTURE OF THE 3{SEPARATIONS OF 3{CONNECTED MATROIDS JAMES OXLEY, CHARLES SEMPLE, AND GEOFF WHITTLE Abstract. Tutte defined a k{separation of a matroid M to be a partition (A; B) of the ground set of M such that |A|; |B|≥k and r(A)+r(B) − r(M) <k. If, for all m<n, the matroid M has no m{separations, then M is n{connected. Earlier, Whitney showed that (A; B) is a 1{separation of M if and only if A is a union of 2{connected components of M.WhenM is 2{connected, Cunningham and Edmonds gave a tree decomposition of M that displays all of its 2{separations. When M is 3{connected, this paper describes a tree decomposition of M that displays, up to a certain natural equivalence, all non-trivial 3{ separations of M. 1. Introduction One of Tutte’s many important contributions to matroid theory was the introduction of the general theory of separations and connectivity [10] de- fined in the abstract. The structure of the 1–separations in a matroid is elementary. They induce a partition of the ground set which in turn induces a decomposition of the matroid into 2–connected components [11]. Cun- ningham and Edmonds [1] considered the structure of 2–separations in a matroid. They showed that a 2–connected matroid M can be decomposed into a set of 3–connected matroids with the property that M can be built from these 3–connected matroids via a canonical operation known as 2–sum. Moreover, there is a labelled tree that gives a precise description of the way that M is built from the 3–connected pieces.
    [Show full text]
  • Matroids with Nine Elements
    Matroids with nine elements Dillon Mayhew School of Mathematics, Statistics & Computer Science Victoria University Wellington, New Zealand [email protected] Gordon F. Royle School of Computer Science & Software Engineering University of Western Australia Perth, Australia [email protected] February 2, 2008 Abstract We describe the computation of a catalogue containing all matroids with up to nine elements, and present some fundamental data arising from this cataogue. Our computation confirms and extends the results obtained in the 1960s by Blackburn, Crapo & Higgs. The matroids and associated data are stored in an online database, arXiv:math/0702316v1 [math.CO] 12 Feb 2007 and we give three short examples of the use of this database. 1 Introduction In the late 1960s, Blackburn, Crapo & Higgs published a technical report describing the results of a computer search for all simple matroids on up to eight elements (although the resulting paper [2] did not appear until 1973). In both the report and the paper they said 1 “It is unlikely that a complete tabulation of 9-point geometries will be either feasible or desirable, as there will be many thousands of them. The recursion g(9) = g(8)3/2 predicts 29260.” Perhaps this comment dissuaded later researchers in matroid theory, because their cata- logue remained unextended for more than 30 years, which surely makes it one of the longest standing computational results in combinatorics. However, in this paper we demonstrate that they were in fact unduly pessimistic, and describe an orderly algorithm (see McKay [7] and Royle [11]) that confirms their computations and extends them by determining the 383172 pairwise non-isomorphic matroids on nine elements (see Table 1).
    [Show full text]
  • Section 3: Equivalence Relations
    10.3.1 Section 3: Equivalence Relations • Definition: Let R be a binary relation on A. R is an equivalence relation on A if R is reflexive, symmetric, and transitive. • From the last section, we demonstrated that Equality on the Real Numbers and Congruence Modulo p on the Integers were reflexive, symmetric, and transitive, so we can describe them as equivalence relations. 10.3.2 Examples • What is the “smallest” equivalence relation on a set A? R = {(a,a) | a Î A}, so that n(R) = n(A). • What is the “largest” equivalence relation on a set A? R = A ´ A, so that n(R) = [n(A)]2. Equivalence Classes 10.3.3 • Definition: If R is an equivalence relation on a set A, and a Î A, then the equivalence class of a is defined to be: [a] = {b Î A | (a,b) Î R}. • In other words, [a] is the set of all elements which relate to a by R. • For example: If R is congruence mod 5, then [3] = {..., -12, -7, -2, 3, 8, 13, 18, ...}. • Another example: If R is equality on Q, then [2/3] = {2/3, 4/6, 6/9, 8/12, 10/15, ...}. • Observation: If b Î [a], then [b] = [a]. 10.3.4 A String Example • Let S = {0,1} and denote L(s) = length of s, for any string s Î S*. Consider the relation: R = {(s,t) | s,t Î S* and L(s) = L(t)} • R is an equivalence relation. Why? • REF: For all s Î S*, L(s) = L(s); SYM: If L(s) = L(t), then L(t) = L(s); TRAN: If L(s) = L(t) and L(t) = L(u), L(s) = L(u).
    [Show full text]
  • Parity Systems and the Delta-Matroid Intersection Problem
    Parity Systems and the Delta-Matroid Intersection Problem Andr´eBouchet ∗ and Bill Jackson † Submitted: February 16, 1998; Accepted: September 3, 1999. Abstract We consider the problem of determining when two delta-matroids on the same ground-set have a common base. Our approach is to adapt the theory of matchings in 2-polymatroids developed by Lov´asz to a new abstract system, which we call a parity system. Examples of parity systems may be obtained by combining either, two delta- matroids, or two orthogonal 2-polymatroids, on the same ground-sets. We show that many of the results of Lov´aszconcerning ‘double flowers’ and ‘projections’ carry over to parity systems. 1 Introduction: the delta-matroid intersec- tion problem A delta-matroid is a pair (V, ) with a finite set V and a nonempty collection of subsets of V , called theBfeasible sets or bases, satisfying the following axiom:B ∗D´epartement d’informatique, Universit´edu Maine, 72017 Le Mans Cedex, France. [email protected] †Department of Mathematical and Computing Sciences, Goldsmiths’ College, London SE14 6NW, England. [email protected] 1 the electronic journal of combinatorics 7 (2000), #R14 2 1.1 For B1 and B2 in and v1 in B1∆B2, there is v2 in B1∆B2 such that B B1∆ v1, v2 belongs to . { } B Here P ∆Q = (P Q) (Q P ) is the symmetric difference of two subsets P and Q of V . If X\ is a∪ subset\ of V and if we set ∆X = B∆X : B , then we note that (V, ∆X) is a new delta-matroid.B The{ transformation∈ B} (V, ) (V, ∆X) is calledB a twisting.
    [Show full text]
  • Computing Partitions Within SQL Queries: a Dead End? Frédéric Dumonceaux, Guillaume Raschia, Marc Gelgon
    Computing Partitions within SQL Queries: A Dead End? Frédéric Dumonceaux, Guillaume Raschia, Marc Gelgon To cite this version: Frédéric Dumonceaux, Guillaume Raschia, Marc Gelgon. Computing Partitions within SQL Queries: A Dead End?. 2013. hal-00768156 HAL Id: hal-00768156 https://hal.archives-ouvertes.fr/hal-00768156 Submitted on 20 Dec 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. Computing Partitions within SQL Queries: A Dead End? Fr´ed´eric Dumonceaux – Guillaume Raschia – Marc Gelgon December 20, 2012 Abstract The primary goal of relational databases is to provide efficient query processing on sets of tuples and thereafter, query evaluation and optimization strategies are a key issue in database implementation. Producing universally fast execu- tion plans remains a challenging task since the underlying relational model has a significant impact on algebraic definition of the operators, thereby on their implementation in terms of space and time complexity. At least, it should pre- vent a quadratic behavior in order to consider scaling-up towards the processing of large datasets. The main purpose of this paper is to show that there is no trivial relational modeling for managing collections of partitions (i.e.
    [Show full text]
  • Cantor's Discovery of Transfinite Numbers
    HISTORIA MATHEMATICA 22 (1995), 33-42 "What Fermented in Me for Years": Cantor's Discovery of Transfinite Numbers Jos~ FERREIROS History of Science and Technology, 543 Stephens Hall, Unioersity of California at Berkeley, Berkeley, California 94720 Transfinite (ordinal) numbers were a crucial step in the development of Cantor's set theory. The new concept depended in various ways on previous problems and results, and especially on two questions that were at the center of Cantor's attention in September 1882, when he was about to make his discovery. First, the proof of the Cantor-Bendixson theorem motivated the introduction of transfinite numbers, and at the same time suggested the "principle of limitation," which is the key to the connection between transfinite numbers and infinite powers. Second, Dedekind's ideas, which Cantor discussed in September 1882, seem to have played an important heuristic role in his decision to consider the "symbols of infinity" that he had been using as true numbers, i.e., as autonomous objects; to this end Cantor introduced in his work, for the first time, ideas on (well) ordered sets. © 1995 Academic Press, Inc. Los ntimeros (ordinales) transfinitos constituyeron un paso clave en el desarrollo de la teorfa de conjuntos de Cantor. La nueva idea dependi6 en varias formas de resultados y problemas previos, pero especialmente de dos cuestiones que ocuparon a Cantor en septiem- bre de 1882, estando a punto de realizar su descubrimiento. En primer lugar, el teorema de Cantor-Bendixson, cuya demostraci6n motiv6 la introducci6n de los ntimeros transfinitos, y a la vez sugiri6 el "principio de limitaci6n" que constituye la clave de la conexi6n entre ntimeros transfinitos y potencias infinitas.
    [Show full text]
  • Applications of Ultrafilters in Ergodic Theory and Combinatorial Number
    Vrije Universiteit Amsterdam Jagiellonian University Master Thesis Applications of Ultrafilters in Ergodic Theory and Combinatorial Number Theory Supervisors: Author: Dr. Tanja Eisner Jakub Konieczny Prof. Dr. Ale Jan Homburg Dr Piotr Niemiec A thesis submitted in fulfilment of the requirements for the degree of Master of Mathematics in the Department of Mathematics, Vrije Universiteit Amsterdam Instytut Matematyki, Jagiellonian University arXiv:1310.1056v2 [math.DS] 16 Oct 2013 October 2013 Declaration of Authorship I, Jakub Konieczny, declare that this thesis titled “Applications of Ultrafilters in Ergodic Theory and Combinatorial Number Theory” is my own. I confirm that: This work was done wholly or mainly while in candidature for a research degree at these Universities. Where I have consulted the published work of others, this is always clearly at- tributed. Where I have quoted from the work of others, the source is always given. With the exception of such quotations, this thesis is entirely my own work. I have acknowledged all main sources of help. Signed: Date: i “Thanks to my solid academic training, today I can write hundreds of words on virtually any topic without possessing a shred of information, which is how I got a good job in journalism." Dave Barry VRIJE UNIVERSITEIT AMSTERDAM JAGIELLONIAN UNIVERSITY Abstract Faculty of Sciences, Department of Mathematics Wydział Matematyki i Informatyki, Instytut Matematyki Master of Mathematics Applications of Ultrafilters in Ergodic Theory and Combinatorial Number Theory by Jakub Konieczny Ultrafilters are very useful and versatile objects with applications throughout mathemat- ics: in topology, analysis, combinarotics, model theory, and even theory of social choice. Proofs based on ultrafilters tend to be shorter and more elegant than their classical coun- terparts.
    [Show full text]