Cantor’S Paradise and the Parable of Frozen Time
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Does the Category of Multisets Require a Larger Universe Than
Pure Mathematical Sciences, Vol. 2, 2013, no. 3, 133 - 146 HIKARI Ltd, www.m-hikari.com Does the Category of Multisets Require a Larger Universe than that of the Category of Sets? Dasharath Singh (Former affiliation: Indian Institute of Technology Bombay) Department of Mathematics, Ahmadu Bello University, Zaria, Nigeria [email protected] Ahmed Ibrahim Isah Department of Mathematics Ahmadu Bello University, Zaria, Nigeria [email protected] Alhaji Jibril Alkali Department of Mathematics Ahmadu Bello University, Zaria, Nigeria [email protected] Copyright © 2013 Dasharath Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract In section 1, the concept of a category is briefly described. In section 2, it is elaborated how the concept of category is naturally intertwined with the existence of a universe of discourse much larger than what is otherwise sufficient for a large part of mathematics. It is also remarked that the extended universe for the category of sets is adequate for the category of multisets as well. In section 3, fundamentals required for adequately describing a category are extended to defining a multiset category, and some of its distinctive features are outlined. Mathematics Subject Classification: 18A05, 18A20, 18B99 134 Dasharath Singh et al. Keywords: Category, Universe, Multiset Category, objects. 1. Introduction to categories The history of science and that of mathematics, in particular, records that at times, a by- product may turn out to be of greater significance than the main objective of a research. -
6.5 the Recursion Theorem
6.5. THE RECURSION THEOREM 417 6.5 The Recursion Theorem The recursion Theorem, due to Kleene, is a fundamental result in recursion theory. Theorem 6.5.1 (Recursion Theorem, Version 1 )Letϕ0,ϕ1,... be any ac- ceptable indexing of the partial recursive functions. For every total recursive function f, there is some n such that ϕn = ϕf(n). The recursion Theorem can be strengthened as follows. Theorem 6.5.2 (Recursion Theorem, Version 2 )Letϕ0,ϕ1,... be any ac- ceptable indexing of the partial recursive functions. There is a total recursive function h such that for all x ∈ N,ifϕx is total, then ϕϕx(h(x)) = ϕh(x). 418 CHAPTER 6. ELEMENTARY RECURSIVE FUNCTION THEORY A third version of the recursion Theorem is given below. Theorem 6.5.3 (Recursion Theorem, Version 3 ) For all n ≥ 1, there is a total recursive function h of n +1 arguments, such that for all x ∈ N,ifϕx is a total recursive function of n +1arguments, then ϕϕx(h(x,x1,...,xn),x1,...,xn) = ϕh(x,x1,...,xn), for all x1,...,xn ∈ N. As a first application of the recursion theorem, we can show that there is an index n such that ϕn is the constant function with output n. Loosely speaking, ϕn prints its own name. Let f be the recursive function such that f(x, y)=x for all x, y ∈ N. 6.5. THE RECURSION THEOREM 419 By the s-m-n Theorem, there is a recursive function g such that ϕg(x)(y)=f(x, y)=x for all x, y ∈ N. -
Cantor, God, and Inconsistent Multiplicities*
STUDIES IN LOGIC, GRAMMAR AND RHETORIC 44 (57) 2016 DOI: 10.1515/slgr-2016-0008 Aaron R. Thomas-Bolduc University of Calgary CANTOR, GOD, AND INCONSISTENT MULTIPLICITIES* Abstract. The importance of Georg Cantor’s religious convictions is often ne- glected in discussions of his mathematics and metaphysics. Herein I argue, pace Jan´e(1995), that due to the importance of Christianity to Cantor, he would have never thought of absolutely infinite collections/inconsistent multiplicities, as being merely potential, or as being purely mathematical entities. I begin by considering and rejecting two arguments due to Ignacio Jan´e based on letters to Hilbert and the generating principles for ordinals, respectively, showing that my reading of Cantor is consistent with that evidence. I then argue that evidence from Cantor’s later writings shows that he was still very religious later in his career, and thus would not have given up on the reality of the absolute, as that would imply an imperfection on the part of God. The theological acceptance of his set theory was very important to Can- tor. Despite this, the influence of theology on his conception of absolutely infinite collections, or inconsistent multiplicities, is often ignored in contem- porary literature.1 I will be arguing that due in part to his religious convic- tions, and despite an apparent tension between his earlier and later writings, Cantor would never have considered inconsistent multiplicities (similar to what we now call proper classes) as completed in a mathematical sense, though they are completed in Intellectus Divino. Before delving into the issue of the actuality or otherwise of certain infinite collections, it will be informative to give an explanation of Cantor’s terminology, as well a sketch of Cantor’s relationship with religion and reli- gious figures. -
April 22 7.1 Recursion Theorem
CSE 431 Theory of Computation Spring 2014 Lecture 7: April 22 Lecturer: James R. Lee Scribe: Eric Lei Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the permission of the Instructor. An interesting question about Turing machines is whether they can reproduce themselves. A Turing machine cannot be be defined in terms of itself, but can it still somehow print its own source code? The answer to this question is yes, as we will see in the recursion theorem. Afterward we will see some applications of this result. 7.1 Recursion Theorem Our end goal is to have a Turing machine that prints its own source code and operates on it. Last lecture we proved the existence of a Turing machine called SELF that ignores its input and prints its source code. We construct a similar proof for the recursion theorem. We will also need the following lemma proved last lecture. ∗ ∗ Lemma 7.1 There exists a computable function q :Σ ! Σ such that q(w) = hPwi, where Pw is a Turing machine that prints w and hats. Theorem 7.2 (Recursion theorem) Let T be a Turing machine that computes a function t :Σ∗ × Σ∗ ! Σ∗. There exists a Turing machine R that computes a function r :Σ∗ ! Σ∗, where for every w, r(w) = t(hRi; w): The theorem says that for an arbitrary computable function t, there is a Turing machine R that computes t on hRi and some input. Proof: We construct a Turing Machine R in three parts, A, B, and T , where T is given by the statement of the theorem. -
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. -
The Logic of Recursive Equations Author(S): A
The Logic of Recursive Equations Author(s): A. J. C. Hurkens, Monica McArthur, Yiannis N. Moschovakis, Lawrence S. Moss, Glen T. Whitney Source: The Journal of Symbolic Logic, Vol. 63, No. 2 (Jun., 1998), pp. 451-478 Published by: Association for Symbolic Logic Stable URL: http://www.jstor.org/stable/2586843 . Accessed: 19/09/2011 22:53 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Association for Symbolic Logic is collaborating with JSTOR to digitize, preserve and extend access to The Journal of Symbolic Logic. http://www.jstor.org THE JOURNAL OF SYMBOLIC LOGIC Volume 63, Number 2, June 1998 THE LOGIC OF RECURSIVE EQUATIONS A. J. C. HURKENS, MONICA McARTHUR, YIANNIS N. MOSCHOVAKIS, LAWRENCE S. MOSS, AND GLEN T. WHITNEY Abstract. We study logical systems for reasoning about equations involving recursive definitions. In particular, we are interested in "propositional" fragments of the functional language of recursion FLR [18, 17], i.e., without the value passing or abstraction allowed in FLR. The 'pure," propositional fragment FLRo turns out to coincide with the iteration theories of [1]. Our main focus here concerns the sharp contrast between the simple class of valid identities and the very complex consequence relation over several natural classes of models. -
Sets - June 24 Chapter 1 - Sets and Functions
Math 300 - Introduction to Mathematical reasoning Summer 2013 Lecture 1: Sets - June 24 Chapter 1 - Sets and Functions Definition and Examples Sets are a \well-defined” collection of objects. We shall not say what we mean by \well-defined” in this course. At an introductory level, it suffices to think of a Set as a collection of objects. Some examples of sets are - • Collection of students taking Math 300, • Collection of all possible speeds that your car can attain, • Collection of all matrices with real entries (Math 308). Examples We mention some mathematical examples which we shall use throughout the course. Keep these examples in mind. • N - the set of natural numbers. Here, N = f1; 2; 3;:::; g • Z - the set of integers. Here, Z = f;:::; −3; −2; −1; 0; 1; 2; 3;:::; g • Q - the set of rational numbers. The set of rational numbers can described as fractions, where the numerator and denominator of the fraction are both integers and the denominator is not equal to zero. • R - the set of real numbers. • R+ - the set of positive real numbers. The objects of the set are called elements, members or points of the set. Usually a set is denoted by a capital letter. The elements of the set are denoted by lowercase letters. The symbol 2 denotes the phrase \belongs to". Let A be a set and let x be an element of the set A. The statement x 2 A should be read as x belongs to the set A. For example, the statement \1 2 N" should be read as \1 belongs to the set of natural numbers". -
Fractal Curves and Complexity
Perception & Psychophysics 1987, 42 (4), 365-370 Fractal curves and complexity JAMES E. CUTI'ING and JEFFREY J. GARVIN Cornell University, Ithaca, New York Fractal curves were generated on square initiators and rated in terms of complexity by eight viewers. The stimuli differed in fractional dimension, recursion, and number of segments in their generators. Across six stimulus sets, recursion accounted for most of the variance in complexity judgments, but among stimuli with the most recursive depth, fractal dimension was a respect able predictor. Six variables from previous psychophysical literature known to effect complexity judgments were compared with these fractal variables: symmetry, moments of spatial distribu tion, angular variance, number of sides, P2/A, and Leeuwenberg codes. The latter three provided reliable predictive value and were highly correlated with recursive depth, fractal dimension, and number of segments in the generator, respectively. Thus, the measures from the previous litera ture and those of fractal parameters provide equal predictive value in judgments of these stimuli. Fractals are mathematicalobjectsthat have recently cap determine the fractional dimension by dividing the loga tured the imaginations of artists, computer graphics en rithm of the number of unit lengths in the generator by gineers, and psychologists. Synthesized and popularized the logarithm of the number of unit lengths across the ini by Mandelbrot (1977, 1983), with ever-widening appeal tiator. Since there are five segments in this generator and (e.g., Peitgen & Richter, 1986), fractals have many curi three unit lengths across the initiator, the fractionaldimen ous and fascinating properties. Consider four. sion is log(5)/log(3), or about 1.47. -
I Want to Start My Story in Germany, in 1877, with a Mathematician Named Georg Cantor
LISTENING - Ron Eglash is talking about his project http://www.ted.com/talks/ 1) Do you understand these words? iteration mission scale altar mound recursion crinkle 2) Listen and answer the questions. 1. What did Georg Cantor discover? What were the consequences for him? 2. What did von Koch do? 3. What did Benoit Mandelbrot realize? 4. Why should we look at our hand? 5. What did Ron get a scholarship for? 6. In what situation did Ron use the phrase “I am a mathematician and I would like to stand on your roof.” ? 7. What is special about the royal palace? 8. What do the rings in a village in southern Zambia represent? 3)Listen for the second time and decide whether the statements are true or false. 1. Cantor realized that he had a set whose number of elements was equal to infinity. 2. When he was released from a hospital, he lost his faith in God. 3. We can use whatever seed shape we like to start with. 4. Mathematicians of the 19th century did not understand the concept of iteration and infinity. 5. Ron mentions lungs, kidney, ferns, and acacia trees to demonstrate fractals in nature. 6. The chief was very surprised when Ron wanted to see his village. 7. Termites do not create conscious fractals when building their mounds. 8. The tiny village inside the larger village is for very old people. I want to start my story in Germany, in 1877, with a mathematician named Georg Cantor. And Cantor decided he was going to take a line and erase the middle third of the line, and take those two resulting lines and bring them back into the same process, a recursive process. -
Review of Set-Theoretic Notations and Terminology A.J
Math 347 Review of Set-theoretic Notations and Terminology A.J. Hildebrand Review of Set-theoretic Notations and Terminology • Sets: A set is an unordered collection of objects, called the elements of the set. The standard notation for a set is the brace notation f::: g, with the elements of the set listed inside the pair of braces. • Set builder notation: Notation of the form f::: : ::: g, where the colon (:) has the meaning of \such that", the dots to the left of the colon indicate the generic form of the element in the set and the dots to 2 the right of the colon denote any constraints on the element. E.g., fx 2 R : x < 4g stands for \the set of 2 all x 2 R such that x < 4"; this is the same as the interval (−2; 2). Other examples of this notation are f2k : k 2 Zg (set of all even integers), fx : x 2 A and x 2 Bg (intersection of A and B, A \ B). 2 Note: Instead of a colon (:), one can also use a vertical bar (j) as a separator; e.g., fx 2 R j x < 4g. Both notations are equally acceptable. • Equality of sets: Two sets are equal if they contain the same elements. E.g., the sets f3; 4; 7g, f4; 3; 7g, f3; 3; 4; 7g are all equal since they contain the same three elements, namely 3, 4, 7. • Some special sets: • Empty set: ; (or fg) • \Double bar" sets: 1 ∗ Natural numbers: N = f1; 2;::: g (note that 0 is not an element of N) ∗ Integers: Z = f:::; −2; −1; 0; 1; 2;::: g ∗ Rational numbers: Q = fp=q : p; q 2 Z; q 6= 0g ∗ Real numbers: R • Intervals: ∗ Open interval: (a; b) = fx 2 R : a < x < bg ∗ Closed interval: [a; b] = fx 2 R : a ≤ x ≤ bg ∗ Half-open interval: [a; b) = fx 2 R : a ≤ x < bg • Universe: U (\universe", a \superset" of which all sets under consideration are assumed to be a subset). -
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. -
Lab 8: Recursion and Fractals
Lab 8: Recursion and Fractals In this lab you’ll get practice creating fractals with recursion. You will create a class that has will draw (at least) two types of fractals. Once completed, submit your .java file via Moodle. To make grading easier, please set up your class so that both fractals are drawn automatically when the constructor is executed. Create a Sierpinski triangle Step 1: In your class’s constructor, ask the user how large a canvas s/he wants. Step 2: Write a method drawTriangle that draws a triangle on the screen. This method will take the x,y coordinates of three points as well as the color of the triangle. For now, start with Step 3: In a method createSierpinski, determine the largest triangle that can fit on the canvas (given the canvas’s dimensions supplied by the user). Step 4: Create a method findMiddlePoints. This is the recursive method. It will take three sets of x,y coordinates for the outer triangle. (The first time the method is called, it will be called with the coordinates determined by the createSierpinski method.) The base case of the method will be determined by the minimum size triangle that can be displayed. The recursive case will be to calculate the three midpoints, defined by the three inputs. Then, by using the six coordinates (3 passed in and 3 calculated), the method will recur on the three interior triangles. Once these recursive calls have finished, use drawTriangle to draw the triangle defined by the three original inputs to the method.