Cantor's Diagonal Argument: a New Aspect

Total Page:16

File Type:pdf, Size:1020Kb

Cantor's Diagonal Argument: a New Aspect CANTOR’S DIAGONAL ARGUMENT: A NEW ASPECT. Alexander.A.Zenkin ( [email protected] ) Dorodnitsyn Computing Center of the Russian Academy of Sciences. Abstract. – In the paper, Cantor’s diagonal proof of the theorem about the cardinality of power-set, |X| < |P(X)|, is analyzed. It is shown first that a key point of the proof is an explicit usage of the counter-example method. It means that an only counter-example (Cantor’s new element of P(X) not belonging to a mapping of X onto P(X)) is sufficient in order to formally disprove a common statement (the assumption of Cantor’s proof that there is a mapping of X onto P(X) including all elements from P(X)), but a total number of all possible counter-examples (a cardinality of P(X)) plays no role in such disproof. In addition Cantor’s conclusion in the form |X| < |P(X)| is deduced from the fact that the difference between infinite sets, P(X) and X, amounts to one element, that is such conclusion contradicts fatally the main property of infinite sets. So, it takes place the following unique situation: the formal logic of Cantor’s proof is unobjectionable, but the proof itself has no relation to and does not use quantitative properties, i.e., a number of elements or a cardinality, of the set, P(X). It is proved as well that if to suppose that a set of all possible Cantor’s counter-examples is infinite, then the Cantor argument leads to an infinite “reasoning” which does not allow to disprove the assumption, |X| = |P(X)|, i.e., makes Cantor’s statement, |X| < |P(X)|, unprovable within the framework of just traditional Cantor’s proof and from the point of view of classical mathematics. Consider the Cantor theorem about the cardinality of a power-set [1,2] and its traditional diagonal proof [3]. Here and further P(X) is a power-set and |X| is a cardinality of an arbitrary set X, and, for short, RAA = Reductio and Absurdum, CDM = Cantor’s Diagonal Method, AD-element = Anti- Diagonal element generated by the CDM-application. CANTOR’S THEOREM-1 (1890). |X| < |P(X)|. PROOF-1 (by RAA-method). It’s obvious that |X| £ |P(X)|. Assume that j maps X onto P(X). Define a new subset of X as follows: X*={x Î X | x Ï j(x)}. Then X* Í X, and if X* = j(y) for some y Î X, then yÎ X* ® y Ï j(y) ® y Ï X* and y Ï X* ® y Î j(y) ® y Î X*. The last is impossible. Q.E.D. As Esenin-Volpin notes rightly (see his commentary in [3], p.172]), the main stage of Cantor’s proof is a proof of the statement that “for any X there is not a bijection of X onto P(X)”. Unfortunately, this very important remark of Esenin-Volpin was not appreciated at its true value and did not have a continuation. However this short comment leads to very important consequences concerning a true understanding of a logical nature of Cantor’s diagonal argument. To begin an analysis of the Cantor proof, remind of some fundamental statements of modern set theory [1-4]. DEFINITION-1. A set, Z, is infinite iff it’s equivalent to its own subset. LEMMA-1. If a difference between numbers of elements of two infinite sets, say Z1 and Z2 , is finite, then the sets, Z1 and Z2 , are equivalent, i.e., |Z1| = |Z2|. DEFINITION-2. Two infinite sets, say Z1 and Z2, are equivalent, i.e., |Z1| = |Z2|, iff there is a 1-1-correspondence between Z1 and Z2 . LEMMA-2. If there is not a 1-1-correspondence between elements of sets, Z1 and Z2, then - 1 - the sets Z1 and Z2 are not equivalent, i.e., |Z1| ¹ |Z2|. Now, taking into account the Esenin-Volpin comment, rewrite Cantor’s Theorem-1 and its traditional proof in the following equivalent form. Remark that we shall speak “an element YÎP(X) belongs to the mapping j (and write YÎj) if there is xÎX such that Y=j(x)”. CANTOR’S THEOREM-2 (1873, 1890). There is not a bijection between X and P(X) for any X. PROOF-2 (by RAA-method). Assume that there is a bijection j that maps X onto P(X). Following Cantor, define a new subset of X: X*={x Î X | x Ï j(x)}. Then X*ÎP(X), but "YÎj[X* ¹ Y], i.e., X*Ïj. Indeed, if X* = j(y) for some y Î X, then y Î X* ® y Ï j(y) ® y Ï X* and y Ï X* ® y Î j(y) ® y Î X*. The last is impossible. From the proven fact X*Ïj, it follows that the given mapping j is not a 1-1-correspondence between X and P(X). Consequently, by virtue of the arbitrariness of j, there is not a bijection between X and P(X) for any X. Q.E.D. CANTOR’S THEOREM-3. |X| < |P(X)|. PROOF-3. From Theorem-2, Lemma-2, and the obvious inequality |X| £ |P(X)|, it follows that |X| < |P(X)|. So, the idea, prompted by the Esenin-Volpin comment, consists in an explicit separation of a logical (Cantor’s Theorem-2) and set-theoretical (Cantor’s Theorem-3) aspects of the traditional Cantor diagonal argument. A comparison of the logic of Cantor’s Proof-2 with the logical scheme of the classical method of counter-example allows to reveal a unique meta-mathematical fact that a key point of Cantor’s diagonal argument is an explicit usage just of the counter- example method. Indeed, consider a logical scheme of classical counter-example method. 1. There is a common hypothetical statement, "x P(x), xÎD, where D is a set of all possible values of x for which the predicate, P(x), is defined. 2. By means of a searching in D (e.g., by Monte Carlo method), the fact is established (if any) that $x*ÎD ØP(x*). 3. From this only fact it follows that Ø["xÎD P(x)]. CONSEQUENCE-1. In order to disprove a common statement, "x P(x), an only counter- example x*, for which ØP(x*), is sufficient. CONSEQUENCE-2. The cardinality of a set of all possible counter-examples, x, for which ØP(x), is not taken into account and is not used within the framework of the counter-example method. Consider one of the most bright examples of a real application of counter-example method in mathematics. EXAMPLE-1. In the XVIII century great Euler formulated the following quite plausible common statement. EULER’S CONJECTURE. For any exponent r ³ 3 the Diophantine equation, r r r r r n = n1 + n2 + n3 + … + ns , has no solutions in natural numbers if s < r. By s=2, Euler’s Hypothesis entails Last Fermat Theorem. During about 200 years nobody was able either to prove or disprove the Hypothesis. And only in 1967 a group of American mathematicians with a power computer revealed ... only one counter-example [5], 1445 = 275 + 845 + 1105 + 1335 , - 2 - where r = 5, s = 4, i.e. s < r. This only counter-example disproved Euler’s Hypothesis forever. So, repeat once again, in order to disprove a common statement an only counter-example is sufficient (Consequence-1, above). And the fact that a set of such counter-examples may be (in reality) infinite plays no role in such disproof (Consequence-2, above). In other words, the disproof of a common statement by means of a given counter-example and the question about a factual number of such counter-examples, i.e., about the cardinality of the set of all possible counter-examples, are absolutely different, independent problems. Now consider another example of a usage of the counter-example method. EXAMPLE-2. Within the framework of traditional Cantor’s diagonal proof of the Theorem- 1, there is the following fragment. According to the assumption of Cantor’s proof, there is a bijection j: X ® P(X), i.e., {B:} all elements of P(X) belong to the given j. Then Cantor defines a new object X*={x Î X | x Ï j(x)} such that X*ÎP(X), but X*Ïj. It means that $X*ÎP(X)[X*Ïj], i.e., {ØB:} not all elements of P(X) belong to the given j. So, from the point of view of classical logic, Cantor’s AD-element, X*, is a counter-example disproving the common statement B. These two examples show that there are two different versions of the counter-example method: in the first version (call it a classical one) a counter-example is searched for in a set of all possible realizations of a common hypothesis; in the second version (call it a CDM-version) a counter-example is algorithmically deduced from the hypothesis which this counter-example must disprove. Remark, that the CDM-version is a distinctive feature just of Cantor’s diagonal argument and can be formulated in the following common form [10]. STATEMENT-1. The famous Cantor Diagonal Method (in its any meta-mathematical realizations) is a special case of the Counter-Example Method where a counter-example itself is not searched for in a set of all possible realizations of a given common statement, but is algorithmically deduced from the given common statement, which this counter-example must disprove. Now we shall prove some theorems elucidating some “hidden” logical peculiarities of the Cantor’s diagonal argument just from the set-theoretical point of view.
Recommended publications
  • Is Uncountable the Open Interval (0, 1)
    Section 2.4:R is uncountable (0, 1) is uncountable This assertion and its proof date back to the 1890’s and to Georg Cantor. The proof is often referred to as “Cantor’s diagonal argument” and applies in more general contexts than we will see in these notes. Our goal in this section is to show that the setR of real numbers is uncountable or non-denumerable; this means that its elements cannot be listed, or cannot be put in bijective correspondence with the natural numbers. We saw at the end of Section 2.3 that R has the same cardinality as the interval ( π , π ), or the interval ( 1, 1), or the interval (0, 1). We will − 2 2 − show that the open interval (0, 1) is uncountable. Georg Cantor : born in St Petersburg (1845), died in Halle (1918) Theorem 42 The open interval (0, 1) is not a countable set. Dr Rachel Quinlan MA180/MA186/MA190 Calculus R is uncountable 143 / 222 Dr Rachel Quinlan MA180/MA186/MA190 Calculus R is uncountable 144 / 222 The open interval (0, 1) is not a countable set A hypothetical bijective correspondence Our goal is to show that the interval (0, 1) cannot be put in bijective correspondence with the setN of natural numbers. Our strategy is to We recall precisely what this set is. show that no attempt at constructing a bijective correspondence between It consists of all real numbers that are greater than zero and less these two sets can ever be complete; it can never involve all the real than 1, or equivalently of all the points on the number line that are numbers in the interval (0, 1) no matter how it is devised.
    [Show full text]
  • Cardinality of Sets
    Cardinality of Sets MAT231 Transition to Higher Mathematics Fall 2014 MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 1 / 15 Outline 1 Sets with Equal Cardinality 2 Countable and Uncountable Sets MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 2 / 15 Sets with Equal Cardinality Definition Two sets A and B have the same cardinality, written jAj = jBj, if there exists a bijective function f : A ! B. If no such bijective function exists, then the sets have unequal cardinalities, that is, jAj 6= jBj. Another way to say this is that jAj = jBj if there is a one-to-one correspondence between the elements of A and the elements of B. For example, to show that the set A = f1; 2; 3; 4g and the set B = {♠; ~; }; |g have the same cardinality it is sufficient to construct a bijective function between them. 1 2 3 4 ♠ ~ } | MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 3 / 15 Sets with Equal Cardinality Consider the following: This definition does not involve the number of elements in the sets. It works equally well for finite and infinite sets. Any bijection between the sets is sufficient. MAT231 (Transition to Higher Math) Cardinality of Sets Fall 2014 4 / 15 The set Z contains all the numbers in N as well as numbers not in N. So maybe Z is larger than N... On the other hand, both sets are infinite, so maybe Z is the same size as N... This is just the sort of ambiguity we want to avoid, so we appeal to the definition of \same cardinality." The answer to our question boils down to \Can we find a bijection between N and Z?" Does jNj = jZj? True or false: Z is larger than N.
    [Show full text]
  • 17 Axiom of Choice
    Math 361 Axiom of Choice 17 Axiom of Choice De¯nition 17.1. Let be a nonempty set of nonempty sets. Then a choice function for is a function f sucFh that f(S) S for all S . F 2 2 F Example 17.2. Let = (N)r . Then we can de¯ne a choice function f by F P f;g f(S) = the least element of S: Example 17.3. Let = (Z)r . Then we can de¯ne a choice function f by F P f;g f(S) = ²n where n = min z z S and, if n = 0, ² = min z= z z = n; z S . fj j j 2 g 6 f j j j j j 2 g Example 17.4. Let = (Q)r . Then we can de¯ne a choice function f as follows. F P f;g Let g : Q N be an injection. Then ! f(S) = q where g(q) = min g(r) r S . f j 2 g Example 17.5. Let = (R)r . Then it is impossible to explicitly de¯ne a choice function for . F P f;g F Axiom 17.6 (Axiom of Choice (AC)). For every set of nonempty sets, there exists a function f such that f(S) S for all S . F 2 2 F We say that f is a choice function for . F Theorem 17.7 (AC). If A; B are non-empty sets, then the following are equivalent: (a) A B ¹ (b) There exists a surjection g : B A. ! Proof. (a) (b) Suppose that A B.
    [Show full text]
  • Georg Cantor English Version
    GEORG CANTOR (March 3, 1845 – January 6, 1918) by HEINZ KLAUS STRICK, Germany There is hardly another mathematician whose reputation among his contemporary colleagues reflected such a wide disparity of opinion: for some, GEORG FERDINAND LUDWIG PHILIPP CANTOR was a corruptor of youth (KRONECKER), while for others, he was an exceptionally gifted mathematical researcher (DAVID HILBERT 1925: Let no one be allowed to drive us from the paradise that CANTOR created for us.) GEORG CANTOR’s father was a successful merchant and stockbroker in St. Petersburg, where he lived with his family, which included six children, in the large German colony until he was forced by ill health to move to the milder climate of Germany. In Russia, GEORG was instructed by private tutors. He then attended secondary schools in Wiesbaden and Darmstadt. After he had completed his schooling with excellent grades, particularly in mathematics, his father acceded to his son’s request to pursue mathematical studies in Zurich. GEORG CANTOR could equally well have chosen a career as a violinist, in which case he would have continued the tradition of his two grandmothers, both of whom were active as respected professional musicians in St. Petersburg. When in 1863 his father died, CANTOR transferred to Berlin, where he attended lectures by KARL WEIERSTRASS, ERNST EDUARD KUMMER, and LEOPOLD KRONECKER. On completing his doctorate in 1867 with a dissertation on a topic in number theory, CANTOR did not obtain a permanent academic position. He taught for a while at a girls’ school and at an institution for training teachers, all the while working on his habilitation thesis, which led to a teaching position at the university in Halle.
    [Show full text]
  • Equivalents to the Axiom of Choice and Their Uses A
    EQUIVALENTS TO THE AXIOM OF CHOICE AND THEIR USES A Thesis Presented to The Faculty of the Department of Mathematics California State University, Los Angeles In Partial Fulfillment of the Requirements for the Degree Master of Science in Mathematics By James Szufu Yang c 2015 James Szufu Yang ALL RIGHTS RESERVED ii The thesis of James Szufu Yang is approved. Mike Krebs, Ph.D. Kristin Webster, Ph.D. Michael Hoffman, Ph.D., Committee Chair Grant Fraser, Ph.D., Department Chair California State University, Los Angeles June 2015 iii ABSTRACT Equivalents to the Axiom of Choice and Their Uses By James Szufu Yang In set theory, the Axiom of Choice (AC) was formulated in 1904 by Ernst Zermelo. It is an addition to the older Zermelo-Fraenkel (ZF) set theory. We call it Zermelo-Fraenkel set theory with the Axiom of Choice and abbreviate it as ZFC. This paper starts with an introduction to the foundations of ZFC set the- ory, which includes the Zermelo-Fraenkel axioms, partially ordered sets (posets), the Cartesian product, the Axiom of Choice, and their related proofs. It then intro- duces several equivalent forms of the Axiom of Choice and proves that they are all equivalent. In the end, equivalents to the Axiom of Choice are used to prove a few fundamental theorems in set theory, linear analysis, and abstract algebra. This paper is concluded by a brief review of the work in it, followed by a few points of interest for further study in mathematics and/or set theory. iv ACKNOWLEDGMENTS Between the two department requirements to complete a master's degree in mathematics − the comprehensive exams and a thesis, I really wanted to experience doing a research and writing a serious academic paper.
    [Show full text]
  • Bijections and Infinities 1 Key Ideas
    INTRODUCTION TO MATHEMATICAL REASONING Worksheet 6 Bijections and Infinities 1 Key Ideas This week we are going to focus on the notion of bijection. This is a way we have to compare two different sets, and say that they have \the same number of elements". Of course, when sets are finite everything goes smoothly, but when they are not... things get spiced up! But let us start, as usual, with some definitions. Definition 1. A bijection between a set X and a set Y consists of matching elements of X with elements of Y in such a way that every element of X has a unique match, and every element of Y has a unique match. Example 1. Let X = f1; 2; 3g and Y = fa; b; cg. An example of a bijection between X and Y consists of matching 1 with a, 2 with b and 3 with c. A NOT example would match 1 and 2 with a and 3 with c. In this case, two things fail: a has two partners, and b has no partner. Note: if you are familiar with these concepts, you may have recognized a bijection as a function between X and Y which is both injective (1:1) and surjective (onto). We will revisit the notion of bijection in this language in a few weeks. For now, we content ourselves of a slightly lower level approach. However, you may be a little unhappy with the use of the word \matching" in a mathematical definition. Here is a more formal definition for the same concept.
    [Show full text]
  • CSC 443 – Database Management Systems Data and Its Structure
    CSC 443 – Database Management Systems Lecture 3 –The Relational Data Model Data and Its Structure • Data is actually stored as bits, but it is difficult to work with data at this level. • It is convenient to view data at different levels of abstraction . • Schema : Description of data at some abstraction level. Each level has its own schema. • We will be concerned with three schemas: physical , conceptual , and external . 1 Physical Data Level • Physical schema describes details of how data is stored: tracks, cylinders, indices etc. • Early applications worked at this level – explicitly dealt with details. • Problem: Routines were hard-coded to deal with physical representation. – Changes to data structure difficult to make. – Application code becomes complex since it must deal with details. – Rapid implementation of new features impossible. Conceptual Data Level • Hides details. – In the relational model, the conceptual schema presents data as a set of tables. • DBMS maps from conceptual to physical schema automatically. • Physical schema can be changed without changing application: – DBMS would change mapping from conceptual to physical transparently – This property is referred to as physical data independence 2 Conceptual Data Level (con’t) External Data Level • In the relational model, the external schema also presents data as a set of relations. • An external schema specifies a view of the data in terms of the conceptual level. It is tailored to the needs of a particular category of users. – Portions of stored data should not be seen by some users. • Students should not see their files in full. • Faculty should not see billing data. – Information that can be derived from stored data might be viewed as if it were stored.
    [Show full text]
  • Some Set Theory We Should Know Cardinality and Cardinal Numbers
    SOME SET THEORY WE SHOULD KNOW CARDINALITY AND CARDINAL NUMBERS De¯nition. Two sets A and B are said to have the same cardinality, and we write jAj = jBj, if there exists a one-to-one onto function f : A ! B. We also say jAj · jBj if there exists a one-to-one (but not necessarily onto) function f : A ! B. Then the SchrÄoder-BernsteinTheorem says: jAj · jBj and jBj · jAj implies jAj = jBj: SchrÄoder-BernsteinTheorem. If there are one-to-one maps f : A ! B and g : B ! A, then jAj = jBj. A set is called countable if it is either ¯nite or has the same cardinality as the set N of positive integers. Theorem ST1. (a) A countable union of countable sets is countable; (b) If A1;A2; :::; An are countable, so is ¦i·nAi; (c) If A is countable, so is the set of all ¯nite subsets of A, as well as the set of all ¯nite sequences of elements of A; (d) The set Q of all rational numbers is countable. Theorem ST2. The following sets have the same cardinality as the set R of real numbers: (a) The set P(N) of all subsets of the natural numbers N; (b) The set of all functions f : N ! f0; 1g; (c) The set of all in¯nite sequences of 0's and 1's; (d) The set of all in¯nite sequences of real numbers. The cardinality of N (and any countable in¯nite set) is denoted by @0. @1 denotes the next in¯nite cardinal, @2 the next, etc.
    [Show full text]
  • Axioms of Set Theory and Equivalents of Axiom of Choice Farighon Abdul Rahim Boise State University, [email protected]
    Boise State University ScholarWorks Mathematics Undergraduate Theses Department of Mathematics 5-2014 Axioms of Set Theory and Equivalents of Axiom of Choice Farighon Abdul Rahim Boise State University, [email protected] Follow this and additional works at: http://scholarworks.boisestate.edu/ math_undergraduate_theses Part of the Set Theory Commons Recommended Citation Rahim, Farighon Abdul, "Axioms of Set Theory and Equivalents of Axiom of Choice" (2014). Mathematics Undergraduate Theses. Paper 1. Axioms of Set Theory and Equivalents of Axiom of Choice Farighon Abdul Rahim Advisor: Samuel Coskey Boise State University May 2014 1 Introduction Sets are all around us. A bag of potato chips, for instance, is a set containing certain number of individual chip’s that are its elements. University is another example of a set with students as its elements. By elements, we mean members. But sets should not be confused as to what they really are. A daughter of a blacksmith is an element of a set that contains her mother, father, and her siblings. Then this set is an element of a set that contains all the other families that live in the nearby town. So a set itself can be an element of a bigger set. In mathematics, axiom is defined to be a rule or a statement that is accepted to be true regardless of having to prove it. In a sense, axioms are self evident. In set theory, we deal with sets. Each time we state an axiom, we will do so by considering sets. Example of the set containing the blacksmith family might make it seem as if sets are finite.
    [Show full text]
  • DISCONTINUITY SETS of SOME INTERVAL BIJECTIONS E. De
    International Journal of Pure and Applied Mathematics Volume 79 No. 1 2012, 47-55 AP ISSN: 1311-8080 (printed version) url: http://www.ijpam.eu ijpam.eu DISCONTINUITY SETS OF SOME INTERVAL BIJECTIONS E. de Amo1 §, M. D´ıaz Carrillo2, J. Fern´andez S´anchez3 1,3Departamento de Algebra´ y An´alisis Matem´atico Universidad de Almer´ıa 04120, Almer´ıa, SPAIN 2Departamento de An´alisis Matem´atico Universidad de Granada 18071, Granada, SPAIN Abstract: In this paper we prove that the discontinuity set of any bijective function from [a, b[ to [c, d] is infinite. We then proceed to give a gallery of examples which shows that this is the best we can expect, and that it is possible that any intermediate case exists. We conclude with an example of a (nowhere continuous) bijective function which exhibits a dense graph in the rectangle [a, b[ × [c, d] . AMS Subject Classification: 26A06, 26A09 Key Words: discontinuity set, fixed point 1. Introduction During our investigations [1] concerning on the application of Ergodic Theory of Numbers to generate singular functions (i.e., their derivatives vanish almost everywhere), we came across a bijection from a closed interval to another that it is not closed: c : [0, 1] −→ [0, 1[, given by (segments on some intervals): (n − 1)! n! − 1 1 c (x) := x − + n n2 n + 1 1 1 1 1 which maps 1 − n! , 1 − (n+1)! onto n+1 , n and c(1) = 0. h h h h c 2012 Academic Publications, Ltd. Received: April 19, 2012 url: www.acadpubl.eu §Correspondence author 48 E.
    [Show full text]
  • Set (Mathematics) from Wikipedia, the Free Encyclopedia
    Set (mathematics) From Wikipedia, the free encyclopedia A set in mathematics is a collection of well defined and distinct objects, considered as an object in its own right. Sets are one of the most fundamental concepts in mathematics. Developed at the end of the 19th century, set theory is now a ubiquitous part of mathematics, and can be used as a foundation from which nearly all of mathematics can be derived. In mathematics education, elementary topics such as Venn diagrams are taught at a young age, while more advanced concepts are taught as part of a university degree. Contents The intersection of two sets is made up of the objects contained in 1 Definition both sets, shown in a Venn 2 Describing sets diagram. 3 Membership 3.1 Subsets 3.2 Power sets 4 Cardinality 5 Special sets 6 Basic operations 6.1 Unions 6.2 Intersections 6.3 Complements 6.4 Cartesian product 7 Applications 8 Axiomatic set theory 9 Principle of inclusion and exclusion 10 See also 11 Notes 12 References 13 External links Definition A set is a well defined collection of objects. Georg Cantor, the founder of set theory, gave the following definition of a set at the beginning of his Beiträge zur Begründung der transfiniten Mengenlehre:[1] A set is a gathering together into a whole of definite, distinct objects of our perception [Anschauung] and of our thought – which are called elements of the set. The elements or members of a set can be anything: numbers, people, letters of the alphabet, other sets, and so on.
    [Show full text]
  • Chapter 7 Cardinality of Sets
    Chapter 7 Cardinality of sets 7.1 1-1 Correspondences A 1-1 correspondence between sets A and B is another name for a function f : A ! B that is 1-1 and onto. If f is a 1-1 correspondence between A and B, then f associates every element of B with a unique element of A (at most one element of A because it is 1-1, and at least one element of A because it is onto). That is, for each element b 2 B there is exactly one a 2 A so that the ordered pair (a; b) 2 f. Since f is a function, for every a 2 A there is exactly one b 2 B such that (a; b) 2 f. Thus, f \pairs up" the elements of A and the elements of B. When such a function f exists, we say A and B can be put into 1-1 correspondence. When we count the number of objects in a collection (that is, set), say 1; 2; 3; : : : ; n, we are forming a 1-1 correspondence between the objects in the collection and the numbers in f1; 2; : : : ; ng. The same is true when we arrange the objects in a collection in a line or sequence. The first object in the sequence corresponds to 1, the second to 2, and so on. Because they will arise in what follows, we reiterate two facts. • If f is a 1-1 correspondence between A and B then it has an inverse, and f −1 isa 1-1 correspondence between B and A.
    [Show full text]