The Reverse Mathematics of Elementary Recursive Nonstandard Analysis: a Robust Contribution to the Foundations of Mathematics

Total Page:16

File Type:pdf, Size:1020Kb

The Reverse Mathematics of Elementary Recursive Nonstandard Analysis: a Robust Contribution to the Foundations of Mathematics Faculteit Wetenschappen Vakgroep Zuivere Wiskunde en Computeralgebra The Reverse Mathematics of Elementary Recursive Nonstandard Analysis: A Robust Contribution to the Foundations of Mathematics Sam Sanders Promotoren: Christian Impens Andreas Weiermann Proefschrift voorgelegd aan de Faculteit Wetenschap- pen tot het behalen van de graad van Doctor in de Wetenschappen richting Wiskunde. 1 I dedicate this dissertation to the founding fathers of Reverse Mathematics and Nonstandard Analysis. 3 Contents Preface 5 Chapter I. ERNA and Reverse Mathematics 7 1. Introduction 7 1.1. Introducing ERNA 7 1.2. Introducing Reverse Mathematics 8 2. ERNA, the system 10 2.1. Language and axioms 10 2.2. ERNA and Transfer 17 2.3. ERNA and the Chuaqui and Suppes system 27 3. Mathematics in ERNA 29 3.1. Mathematics without Transfer 29 3.2. Mathematics with Transfer 37 4. Reverse Mathematics in ERNA 42 4.1. A copy of Reverse Mathematics for WKL0 42 4.2. ERNA and Constructive Reverse Mathematics 50 4.3. Reverse Mathematics beyond WKL0 51 Chapter II. Beyond "-δ: Relative infinitesimals and ERNA 63 1. Introduction 63 2. ERNAA, the system 65 2.1. Language and axioms 65 2.2. Consistency 66 3. ERNAA and Transfer 70 3.1. ERNAA and Stratified Transfer 70 3.2. ERNAA and Classical Transfer 72 3.3. Classical vs. Stratified Transfer 74 4. Mathematics in ERNAA 77 5. ERNAA versus ERNA 84 5.1. More Reverse Mathematics in ERNA 85 5.2. Conservation and expansion for ERNA 89 5.3. Intensionality 93 6. Concluding remarks 96 Chapter III. Relative arithmetic 99 Introduction: internal beauty 99 1. Internal relativity 100 2. The reduction theorem 101 3. Approaching Peano Arithmetic 103 4. Reducing Transfer to the reduction theorem 105 4 . Contents 5. Arithmetical truth 106 6. Philosophical considerations 107 Appendix A. Technical Appendix 109 1. Fundamental functions of ERNA 109 2. Applications of fundamental functions 111 Appendix B. Dutch Summary 117 1. Samenvatting 117 Appendix C. Acknowledgments 119 1. Thanks 119 Appendix. Bibliography 121 Bibliography 121 . Contents 5 Preface Reverse Mathematics (RM) is a program in the Foundations of Mathematics founded by Harvey Friedman in the Seventies ([17, 18]). The aim of RM is to determine the minimal axioms required to prove a certain theorem of `ordinary' mathematics. In many cases one observes that these minimal axioms are also equivalent to this theorem. This phenomenon is called the `Main Theme' of RM and theorem 1.2 is a good example thereof. In practice, most theorems of everyday mathematics are 1 equivalent to one of the four systems WKL0, ACA0, ATR0 and Π1-CA0 or provable in the base theory RCA0. An excellent introduction to RM is Stephen Simpson's monograph [46]. Nonstandard Analysis has always played an important role in RM. ([32,52, 53]). One of the open problems in the literature is the RM of theories of first-order strength I∆0 + exp ([46, p. 406]). In Chapter I, we formulate a solution to this problem in theorem 1.3. This theorem shows that many of the equivalences from theorem 1.2 remain correct when we replace equality by infinitesimal proximity `≈' from Nonstandard Analysis. The base theory now is ERNA, a nonstandard extension of I∆0 + exp. The principle that corresponds to `Weak K¨onig'slemma' is the Universal Transfer Principle (see axiom schema 1.57). In particular, one can say that the RM of ERNA+Π1-TRANS is a `copy up to infinitesimals’ of the RM of WKL0. This implies that RM is `robust' in the sense this term is used in Statistics and Computer Science ([25,35]). Furthermore, we obtain applications of our results in Theoretical Physics in the form of the `Isomorphism Theorem' (see theorem 1.106). This philosophical excursion is the first application of RM outside of Mathematics and implies that `whether reality is continuous or discrete is undecidable because of the way mathematics is used in Physics' (see paragraph 3.2.4, p. 53). We briefly explore a connection with the program `Constructive Reverse Mathematics' ([30, 31]) and in the rest of Chapter I, we consider the RM of ACA0 and related systems. In particular, we prove theorem 1.161, which is a first step towards a `copy up to infinitesimals’ of the RM of ACA0. However, one major aesthetic problem with these results is the introduction of extra quantifiers in many of the theorems listed in theorem 1.3 (see e.g. theorem 1.94). To overcome this hurdle, we explore Relative Nonstandard Analysis in Chapters II and III. This new framework involves many degrees of infinity instead of the classical `binary' picture where only two degrees ‘finite' and ‘infinite’ are available. We extend ERNA to a theory of Relative Nonstandard Analysis called ERNAA and show how this theory and its extensions allow for a completely quantifier- free development of analysis. We also study the metamathematics of ERNAA, motivated by RM. Several ERNA-theorems would not have been discovered without considering ERNAA first. I. Preface 7 CHAPTER I ERNA and Reverse Mathematics That through which all things come into being, is not a thing in itself. Tao Te Ching Lao Tse 1. Introduction 1.1. Introducing ERNA. Hilbert's Program, proposed in 1921, called for an axiomatic formalization of mathematics, together with a proof that this axiomati- zation is consistent. The consistency proof itself was to be carried out using only what Hilbert called finitary methods. In due time, many characterized Hilbert's informal notion of ‘finitary’ as that which can be formalized in Primitive Recursive Arithmetic (PRA), proposed in 1923 by Skolem (see e.g. [51]). By G¨odel'ssecond incompleteness theorem (1931) it became evident that only par- tial realizations of Hilbert's program are possible. The system proposed by Chuaqui and Suppes, recently adapted by R¨osslerand Jeˇr´abek, is such a partial realization, in that it provides an axiomatic foundation for basic analysis, with a PRA consis- tency proof ([11], [42]). Sommer and Suppes's improved system allows definition by recursion, which does away with a lot of explicit axioms, and still has a PRA proof of consistency ([49, p. 21]). This system is called Elementary Recursive Nonstandard Analysis, in short ERNA. Its consistency is proved via Herbrand's Theorem (1930), which is restricted to quantifier-free formulas Q(x1; : : : ; xn), usually containing free variables. Alternatively, one might say it is restricted to universal sentences (8x1) ::: (8xn)Q(x1; : : : ; xn): We will use Herbrand's theorem in the following form (see [11] and [49]); for more details, see [8] and [21]. 1.1. Theorem. A quantifier-free theory T is consistent if and only if every finite set of instantiated axioms of T is consistent. Since Herbrand's theorem requires that ERNA's axioms be written in a quantifier- free form, some axioms definitely look artificial. Fortunately, theorems do not suffer from the quantifier-free restriction. As it turns out, ERNA is not strong enough to develop basic analysis (see theorem 1.3) and hence an extension of ERNA is required. In section 2.2, we extend ERNA with a Transfer principle for universal sentences, called Π1-TRANS. In nonstan- dard mathematics, Transfer expresses Leibniz's principle that the `same' laws hold for standard and nonstandard objects alike. The consistency of the extended theory 8 I. ERNA and Reverse Mathematics − ERNA + Π1-TRANS is provable in PRA via a finite iteration of ERNA's consis- tency proof (see theorem 1.58). The theory ERNA + Π1-TRANS has important applications in `Reverse Mathematics', introduced next. 1.2. Introducing Reverse Mathematics. Reverse Mathematics is a pro- gram in Foundations of Mathematics founded around 1975 by Harvey Friedman ([17] and [18]) and developed intensely by Stephen Simpson, Kazuyuki Tanaka and others; for an overview of the subject, see [46] and [47]. The goal of Reverse Mathematics is to determine what (minimal) axiom system is necessary to prove a particular theorem of ordinary mathematics. By now, it is well known that large portions of mathematics (especially so in analysis) can be carried out in systems far weaker than ZFC, the `usual' background theory for mathematics. Classifying theorems according to their logical strength reveals the following striking phenom- enon: `It turns out that, in many particular cases, if a mathematical theorem is proved from appropriately weak set existence axioms, then the axioms will be logi- cally equivalent to the theorem' ([46, Preface]). This recurring phenomenon is called the `Main theme' of Reverse Mathematics (see e.g. [45]) and a good instance is the following theorem from [46, p. 36]. 1.2. Theorem (Reverse Mathematics for WKL0). Within RCA0, one can prove that Weak K¨onig'sLemma (WKL) is equivalent to each of the following mathemat- ical statements: (1) The Heine-Borel lemma: every covering of [0; 1] by a sequence of open intervals has a finite subcovering. (2) Every covering of a compact metric space by a sequence of open sets has a finite subcovering. (3) Every continuous real-valued function on [0; 1], or on any compact metric space, is bounded. (4) Every continuous real-valued function on [0; 1], or on any compact metric space, is uniformly continuous. (5) Every continuous real-valued function on [0; 1] is Riemann integrable. (6) The maximum principle: every continuous real-valued function on [0; 1], or on any compact metric space, is bounded, or (equivalently) has a supre- mum or (equivalently) attains its maximum. (7) The Peano existence theorem: if f(x; y) is continuous in the neighbourhood of (0; 0), then the initial value problem y0 = f(x; y), y(0) = 0 has a continuously differentiable solution in the neighbourhood of (0; 0).
Recommended publications
  • Large but Finite
    Department of Mathematics MathClub@WMU Michigan Epsilon Chapter of Pi Mu Epsilon Large but Finite Drake Olejniczak Department of Mathematics, WMU What is the biggest number you can imagine? Did you think of a million? a billion? a septillion? Perhaps you remembered back to the time you heard the term googol or its show-off of an older brother googolplex. Or maybe you thought of infinity. No. Surely, `infinity' is cheating. Large, finite numbers, truly monstrous numbers, arise in several areas of mathematics as well as in astronomy and computer science. For instance, Euclid defined perfect numbers as positive integers that are equal to the sum of their proper divisors. He is also credited with the discovery of the first four perfect numbers: 6, 28, 496, 8128. It may be surprising to hear that the ninth perfect number already has 37 digits, or that the thirteenth perfect number vastly exceeds the number of particles in the observable universe. However, the sequence of perfect numbers pales in comparison to some other sequences in terms of growth rate. In this talk, we will explore examples of large numbers such as Graham's number, Rayo's number, and the limits of the universe. As well, we will encounter some fast-growing sequences and functions such as the TREE sequence, the busy beaver function, and the Ackermann function. Through this, we will uncover a structure on which to compare these concepts and, hopefully, gain a sense of what it means for a number to be truly large. 4 p.m. Friday October 12 6625 Everett Tower, WMU Main Campus All are welcome! http://www.wmich.edu/mathclub/ Questions? Contact Patrick Bennett ([email protected]) .
    [Show full text]
  • A List of Arithmetical Structures Complete with Respect to the First
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Theoretical Computer Science 257 (2001) 115–151 www.elsevier.com/locate/tcs A list of arithmetical structures complete with respect to the ÿrst-order deÿnability Ivan Korec∗;X Slovak Academy of Sciences, Mathematical Institute, Stefanikovaà 49, 814 73 Bratislava, Slovak Republic Abstract A structure with base set N is complete with respect to the ÿrst-order deÿnability in the class of arithmetical structures if and only if the operations +; × are deÿnable in it. A list of such structures is presented. Although structures with Pascal’s triangles modulo n are preferred a little, an e,ort was made to collect as many simply formulated results as possible. c 2001 Elsevier Science B.V. All rights reserved. MSC: primary 03B10; 03C07; secondary 11B65; 11U07 Keywords: Elementary deÿnability; Pascal’s triangle modulo n; Arithmetical structures; Undecid- able theories 1. Introduction A list of (arithmetical) structures complete with respect of the ÿrst-order deÿnability power (shortly: def-complete structures) will be presented. (The term “def-strongest” was used in the previous versions.) Most of them have the base set N but also structures with some other universes are considered. (Formal deÿnitions are given below.) The class of arithmetical structures can be quasi-ordered by ÿrst-order deÿnability power. After the usual factorization we obtain a partially ordered set, and def-complete struc- tures will form its greatest element. Of course, there are stronger structures (with respect to the ÿrst-order deÿnability) outside of the class of arithmetical structures.
    [Show full text]
  • Parameter Free Induction and Provably Total Computable Functions
    Parameter free induction and provably total computable functions Lev D. Beklemishev∗ Steklov Mathematical Institute Gubkina 8, 117966 Moscow, Russia e-mail: [email protected] November 20, 1997 Abstract We give a precise characterization of parameter free Σn and Πn in- − − duction schemata, IΣn and IΠn , in terms of reflection principles. This I − I − allows us to show that Πn+1 is conservative over Σn w.r.t. boolean com- binations of Σn+1 sentences, for n ≥ 1. In particular, we give a positive I − answer to a question, whether the provably recursive functions of Π2 are exactly the primitive recursive ones. We also characterize the provably − recursive functions of theories of the form IΣn + IΠn+1 in terms of the fast growing hierarchy. For n = 1 the corresponding class coincides with the doubly-recursive functions of Peter. We also obtain sharp results on the strength of bounded number of instances of parameter free induction in terms of iterated reflection. Keywords: parameter free induction, provably recursive functions, re- flection principles, fast growing hierarchy Mathematics Subject Classification: 03F30, 03D20 1 Introduction In this paper we shall deal with the first order theories containing Kalmar ele- mentary arithmetic EA or, equivalently, I∆0 + Exp (cf. [11]). We are interested in the general question how various ways of formal reasoning correspond to models of computation. This kind of analysis is traditionally based on the con- cept of provably total recursive function (p.t.r.f.) of a theory. Given a theory T containing EA, a function f(~x) is called provably total recursive in T , iff there is a Σ1 formula φ(~x, y), sometimes called specification, that defines the graph of f in the standard model of arithmetic and such that T ⊢ ∀~x∃!y φ(~x, y).
    [Show full text]
  • The Infinite and Contradiction: a History of Mathematical Physics By
    The infinite and contradiction: A history of mathematical physics by dialectical approach Ichiro Ueki January 18, 2021 Abstract The following hypothesis is proposed: \In mathematics, the contradiction involved in the de- velopment of human knowledge is included in the form of the infinite.” To prove this hypothesis, the author tries to find what sorts of the infinite in mathematics were used to represent the con- tradictions involved in some revolutions in mathematical physics, and concludes \the contradiction involved in mathematical description of motion was represented with the infinite within recursive (computable) set level by early Newtonian mechanics; and then the contradiction to describe discon- tinuous phenomena with continuous functions and contradictions about \ether" were represented with the infinite higher than the recursive set level, namely of arithmetical set level in second or- der arithmetic (ordinary mathematics), by mechanics of continuous bodies and field theory; and subsequently the contradiction appeared in macroscopic physics applied to microscopic phenomena were represented with the further higher infinite in third or higher order arithmetic (set-theoretic mathematics), by quantum mechanics". 1 Introduction Contradictions found in set theory from the end of the 19th century to the beginning of the 20th, gave a shock called \a crisis of mathematics" to the world of mathematicians. One of the contradictions was reported by B. Russel: \Let w be the class [set]1 of all classes which are not members of themselves. Then whatever class x may be, 'x is a w' is equivalent to 'x is not an x'. Hence, giving to x the value w, 'w is a w' is equivalent to 'w is not a w'."[52] Russel described the crisis in 1959: I was led to this contradiction by Cantor's proof that there is no greatest cardinal number.
    [Show full text]
  • Primality Testing for Beginners
    STUDENT MATHEMATICAL LIBRARY Volume 70 Primality Testing for Beginners Lasse Rempe-Gillen Rebecca Waldecker http://dx.doi.org/10.1090/stml/070 Primality Testing for Beginners STUDENT MATHEMATICAL LIBRARY Volume 70 Primality Testing for Beginners Lasse Rempe-Gillen Rebecca Waldecker American Mathematical Society Providence, Rhode Island Editorial Board Satyan L. Devadoss John Stillwell Gerald B. Folland (Chair) Serge Tabachnikov The cover illustration is a variant of the Sieve of Eratosthenes (Sec- tion 1.5), showing the integers from 1 to 2704 colored by the number of their prime factors, including repeats. The illustration was created us- ing MATLAB. The back cover shows a phase plot of the Riemann zeta function (see Appendix A), which appears courtesy of Elias Wegert (www.visual.wegert.com). 2010 Mathematics Subject Classification. Primary 11-01, 11-02, 11Axx, 11Y11, 11Y16. For additional information and updates on this book, visit www.ams.org/bookpages/stml-70 Library of Congress Cataloging-in-Publication Data Rempe-Gillen, Lasse, 1978– author. [Primzahltests f¨ur Einsteiger. English] Primality testing for beginners / Lasse Rempe-Gillen, Rebecca Waldecker. pages cm. — (Student mathematical library ; volume 70) Translation of: Primzahltests f¨ur Einsteiger : Zahlentheorie - Algorithmik - Kryptographie. Includes bibliographical references and index. ISBN 978-0-8218-9883-3 (alk. paper) 1. Number theory. I. Waldecker, Rebecca, 1979– author. II. Title. QA241.R45813 2014 512.72—dc23 2013032423 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy a chapter for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given.
    [Show full text]
  • The Notion Of" Unimaginable Numbers" in Computational Number Theory
    Beyond Knuth’s notation for “Unimaginable Numbers” within computational number theory Antonino Leonardis1 - Gianfranco d’Atri2 - Fabio Caldarola3 1 Department of Mathematics and Computer Science, University of Calabria Arcavacata di Rende, Italy e-mail: [email protected] 2 Department of Mathematics and Computer Science, University of Calabria Arcavacata di Rende, Italy 3 Department of Mathematics and Computer Science, University of Calabria Arcavacata di Rende, Italy e-mail: [email protected] Abstract Literature considers under the name unimaginable numbers any positive in- teger going beyond any physical application, with this being more of a vague description of what we are talking about rather than an actual mathemati- cal definition (it is indeed used in many sources without a proper definition). This simply means that research in this topic must always consider shortened representations, usually involving recursion, to even being able to describe such numbers. One of the most known methodologies to conceive such numbers is using hyper-operations, that is a sequence of binary functions defined recursively starting from the usual chain: addition - multiplication - exponentiation. arXiv:1901.05372v2 [cs.LO] 12 Mar 2019 The most important notations to represent such hyper-operations have been considered by Knuth, Goodstein, Ackermann and Conway as described in this work’s introduction. Within this work we will give an axiomatic setup for this topic, and then try to find on one hand other ways to represent unimaginable numbers, as well as on the other hand applications to computer science, where the algorith- mic nature of representations and the increased computation capabilities of 1 computers give the perfect field to develop further the topic, exploring some possibilities to effectively operate with such big numbers.
    [Show full text]
  • The Reverse Mathematics of Cousin's Lemma
    VICTORIAUNIVERSITYOFWELLINGTON Te Herenga Waka School of Mathematics and Statistics Te Kura Matai Tatauranga PO Box 600 Tel: +64 4 463 5341 Wellington 6140 Fax: +64 4 463 5045 New Zealand Email: sms-offi[email protected] The reverse mathematics of Cousin’s lemma Jordan Mitchell Barrett Supervisors: Rod Downey, Noam Greenberg Friday 30th October 2020 Submitted in partial fulfilment of the requirements for the Bachelor of Science with Honours in Mathematics. Abstract Cousin’s lemma is a compactness principle that naturally arises when study- ing the gauge integral, a generalisation of the Lebesgue integral. We study the ax- iomatic strength of Cousin’s lemma for various classes of functions, using Fried- arXiv:2011.13060v1 [math.LO] 25 Nov 2020 man and Simpson’s reverse mathematics in second-order arithmetic. We prove that, over RCA0: (i) Cousin’s lemma for continuous functions is equivalent to the system WKL0; (ii) Cousin’s lemma for Baire 1 functions is at least as strong as ACA0; (iii) Cousin’s lemma for Baire 2 functions is at least as strong as ATR0. Contents 1 Introduction 1 2 Integration and Cousin’s lemma 5 2.1 Riemann integration . .5 2.2 Gauge integration . .6 2.3 Cousin’s lemma . .7 3 Logical prerequisites 9 3.1 Computability . .9 3.2 Second-order arithmetic . 12 3.3 The arithmetical and analytical hierarchies . 13 4 Subsystems of second-order arithmetic 17 4.1 Formal systems . 17 4.2 RCA0 .......................................... 18 4.3 WKL0 .......................................... 19 4.4 ACA0 .......................................... 21 4.5 ATR0 .......................................... 22 1 4.6 P1-CA0 ......................................... 23 5 Analysis in second-order arithmetic 25 5.1 Number systems .
    [Show full text]
  • Ackermann and the Superpowers
    Ackermann and the superpowers Ant´onioPorto and Armando B. Matos Original version 1980, published in \ACM SIGACT News" Modified in October 20, 2012 Modified in January 23, 2016 (working paper) Abstract The Ackermann function a(m; n) is a classical example of a total re- cursive function which is not primitive recursive. It grows faster than any primitive recursive function. It is usually defined by a general recurrence together with two \boundary" conditions. In this paper we obtain a closed form of a(m; n), which involves the Knuth superpower notation, namely m−2 a(m; n) = 2 " (n + 3) − 3. Generalized Ackermann functions, that is functions satisfying only the general recurrence and one of the bound- ary conditions are also studied. In particular, we show that the function m−2 2 " (n + 2) − 2 also belongs to the \Ackermann class". 1 Introduction and definitions The \arrow" or \superpower" notation has been introduced by Knuth [1] as a convenient way of expressing very large numbers. It is based on the infinite sequence of operators: +, ∗, ",... We shall see that the arrow notation is closely related to the Ackermann function (see, for instance, [2]). 1.1 The Superpowers Let us begin with the following sequence of integer operators, where all the operators are right associative. a × n = a + a + ··· + a (n a's) a " n = a × a × · · · × a (n a's) 2 a " n = a " a "···" a (n a's) m In general we define a " n as 1 Definition 1 m m−1 m−1 m−1 a " n = a " a "··· " a | {z } n a's m The operator " is not associative for m ≥ 1.
    [Show full text]
  • 53 More Algorithms
    Eric Roberts Handout #53 CS 106B March 9, 2015 More Algorithms Outline for Today • The plan for today is to walk through some of my favorite tree More Algorithms and graph algorithms, partly to demystify the many real-world applications that make use of those algorithms and partly to for Trees and Graphs emphasize the elegance and power of algorithmic thinking. • These algorithms include: – Google’s Page Rank algorithm for searching the web – The Directed Acyclic Word Graph format – The union-find algorithm for efficient spanning-tree calculation Eric Roberts CS 106B March 9, 2015 Page Rank Page Rank Algorithm The heart of the Google search engine is the page rank algorithm, The page rank algorithm gives each page a rating of its importance, which was described in a 1999 by Larry Page, Sergey Brin, Rajeev which is a recursively defined measure whereby a page becomes Motwani, and Terry Winograd. important if other important pages link to it. The PageRank Citation Ranking: One way to think about page rank is to imagine a random surfer on Bringing Order to the Web the web, following links from page to page. The page rank of any page is roughly the probability that the random surfer will land on a January 29, 1998 particular page. Since more links go to the important pages, the Abstract surfer is more likely to end up there. The importance of a Webpage is an inherently subjective matter, which depends on the reader’s interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages.
    [Show full text]
  • Infinitesimals
    Infinitesimals: History & Application Joel A. Tropp Plan II Honors Program, WCH 4.104, The University of Texas at Austin, Austin, TX 78712 Abstract. An infinitesimal is a number whose magnitude ex- ceeds zero but somehow fails to exceed any finite, positive num- ber. Although logically problematic, infinitesimals are extremely appealing for investigating continuous phenomena. They were used extensively by mathematicians until the late 19th century, at which point they were purged because they lacked a rigorous founda- tion. In 1960, the logician Abraham Robinson revived them by constructing a number system, the hyperreals, which contains in- finitesimals and infinitely large quantities. This thesis introduces Nonstandard Analysis (NSA), the set of techniques which Robinson invented. It contains a rigorous de- velopment of the hyperreals and shows how they can be used to prove the fundamental theorems of real analysis in a direct, natural way. (Incredibly, a great deal of the presentation echoes the work of Leibniz, which was performed in the 17th century.) NSA has also extended mathematics in directions which exceed the scope of this thesis. These investigations may eventually result in fruitful discoveries. Contents Introduction: Why Infinitesimals? vi Chapter 1. Historical Background 1 1.1. Overview 1 1.2. Origins 1 1.3. Continuity 3 1.4. Eudoxus and Archimedes 5 1.5. Apply when Necessary 7 1.6. Banished 10 1.7. Regained 12 1.8. The Future 13 Chapter 2. Rigorous Infinitesimals 15 2.1. Developing Nonstandard Analysis 15 2.2. Direct Ultrapower Construction of ∗R 17 2.3. Principles of NSA 28 2.4. Working with Hyperreals 32 Chapter 3.
    [Show full text]
  • The Hyperreals
    THE HYPERREALS LARRY SUSANKA Abstract. In this article we define the hyperreal numbers, an ordered field containing the real numbers as well as infinitesimal numbers. These infinites- imals have magnitude smaller than that of any nonzero real number and have intuitively appealing properties, harkening back to the thoughts of the inven- tors of analysis. We use the ultrafilter construction of the hyperreal numbers which employs common properties of sets, rather than the original approach (see A. Robinson Non-Standard Analysis [5]) which used model theory. A few of the properties of the hyperreals are explored and proofs of some results from real topology and calculus are created using hyperreal arithmetic in place of the standard limit techniques. Contents The Hyperreal Numbers 1. Historical Remarks and Overview 2 2. The Construction 3 3. Vocabulary 6 4. A Collection of Exercises 7 5. Transfer 10 6. The Rearrangement and Hypertail Lemmas 14 Applications 7. Open, Closed and Boundary For Subsets of R 15 8. The Hyperreal Approach to Real Convergent Sequences 16 9. Series 18 10. More on Limits 20 11. Continuity and Uniform Continuity 22 12. Derivatives 26 13. Results Related to the Mean Value Theorem 28 14. Riemann Integral Preliminaries 32 15. The Infinitesimal Approach to Integration 36 16. An Example of Euler, Revisited 37 References 40 Index 41 Date: June 27, 2018. 1 2 LARRY SUSANKA 1. Historical Remarks and Overview The historical Euclid-derived conception of a line was as an object possessing \the quality of length without breadth" and which satisfies the various axioms of Euclid's geometric structure.
    [Show full text]
  • A Topological Regularizer for Classifiers Via Persistent Homology
    A Topological Regularizer for Classifiers via Persistent Homology Chao Chen Xiuyan Ni Qinxun Bai Yusu Wang Stony Brook University City University of New York Hikvision Research America Ohio State University Abstract 2002). Such norms produce a model with relatively less flexibility and thus is less likely to overfit. Regularization plays a crucial role in super- A particularly interesting category of methods is in- vised learning. Most existing methods enforce spired by the geometry. These methods design new a global regularization in a structure agnos- penalty terms to enforce a geometric simplicity of the tic manner. In this paper, we initiate a new classifier. Some methods stipulate that similar data direction and propose to enforce the struc- should have similar score according to the classifier, tural simplicity of the classification boundary and enforce the smoothness of the classifier function by regularizing over its topological complexity. (Belkin et al., 2006; Zhou and Schölkopf, 2005; Bai In particular, our measurement of topologi- et al., 2016). Others directly pursue a simple geom- cal complexity incorporates the importance etry of the classifier boundary, i.e., the submanifold of topological features (e.g., connected com- separating different classes (Cai and Sowmya, 2007; ponents, handles, and so on) in a meaningful Varshney and Willsky, 2010; Lin et al., 2012, 2015). manner, and provides a direct control over These geometry-based regularizers are intuitive and spurious topological structures. We incorpo- have been shown to be useful in many supervised and rate the new measurement as a topological semi-supervised learning settings. However, regulariz- penalty in training classifiers. We also pro- ing total smoothness of the classifier (or that of the pose an efficient algorithm to compute the classification boundary) is not always flexible enough to gradient of such penalty.
    [Show full text]