Mathematical Recipes (Early Draft)

Total Page:16

File Type:pdf, Size:1020Kb

Mathematical Recipes (Early Draft) Mathematical recipes (early draft) Dennis Yurichev <[email protected]> June 29, 2021 Contents 1 Unsorted parts 1 1.1 Fencepost error / off-by-one error .......................................... 1 1.2 GCD and LCM ..................................................... 2 1.2.1 GCD ...................................................... 2 1.2.2 Oculus VR Flicks and GCD .......................................... 3 1.2.3 LCM ...................................................... 4 1.3 Signed numbers: two’s complement ........................................ 5 1.3.1 Couple of additions about two’s complement form ............................ 7 1.3.2 -1 ....................................................... 8 1.4 Mandelbrot set .................................................... 8 1.4.1 A word about complex numbers ...................................... 8 1.4.2 How to draw the Mandelbrot set ...................................... 8 2 Boolean algebra 14 2.1 XOR (exclusive OR) .................................................. 14 2.1.1 Logical difference .............................................. 14 2.1.2 Everyday speech ............................................... 14 2.1.3 Encryption .................................................. 14 2.1.4 RAID14 .................................................... 14 2.1.5 XOR swap algorithm ............................................. 15 2.1.6 XOR linked list ................................................ 15 2.1.7 Switching value trick ............................................. 16 2.1.8 Zobrist hashing / tabulation hashing .................................... 16 2.1.9 By the way .................................................. 17 2.2 AND operation .................................................... 17 2.2.1 Checking if a value is on 2n boundary .................................... 17 2.2.2 KOI-8R Cyrillic encoding ........................................... 17 2.3 AND and OR as subtraction and addition ...................................... 18 2.3.1 ZX Spectrum ROM text strings ........................................ 18 2.4 Hamming weight / population count ........................................ 21 3 Set theory 22 3.1 Set theory explanation via boolean operations ................................... 22 3.1.1 Collecting TV series ............................................. 22 3.1.2 Rock band .................................................. 22 3.1.3 Languages .................................................. 23 3.1.4 De Morgan’s laws ............................................... 24 3.1.5 Powerset ................................................... 24 3.1.6 Inclusion-exclusion principle ........................................ 24 4 IEEE 754 27 4.1 IEEE 754 round-off errors ............................................... 27 4.1.1 The example from Wikipedia ........................................ 27 4.1.2 Conversion from double-precision to single-precision and back ..................... 31 4.1.3 The moral of the story ............................................ 35 4.1.4 All the files .................................................. 36 1Redundant Array of Independent Disks 1 2 5 Calculus 37 5.1 What is derivative? .................................................. 37 5.1.1 Square .................................................... 37 5.1.2 Cube ..................................................... 37 5.1.3 Line ...................................................... 38 5.1.4 Circle ..................................................... 38 5.1.5 Cylinder .................................................... 39 5.1.6 Sphere .................................................... 39 5.1.7 Conclusion .................................................. 40 6 Prime numbers 41 6.1 Integer factorization ................................................. 41 6.1.1 Using composite number as a container .................................. 42 6.1.2 Using composite number as a container (another example) ........................ 43 6.2 Coprime numbers .................................................. 44 6.3 Semiprime numbers ................................................. 45 6.4 How RSA2 works ................................................... 45 6.4.1 Fermat little theorem ............................................ 45 6.4.2 Euler’s totient function ........................................... 46 6.4.3 Euler’s theorem ............................................... 46 6.4.4 RSA example ................................................. 46 6.4.5 So how it works? ............................................... 47 6.4.6 Breaking RSA ................................................. 48 6.4.7 The difference between my simplified example and a real RSA algorithm ................ 48 6.4.8 The RSA signature .............................................. 49 6.4.9 Hybrid cryptosystem ............................................. 49 7 Modulo arithmetics 50 7.1 Quick introduction into modular arithmetic .................................... 50 7.1.1 Modular arithmetic on CPUs ......................................... 51 7.1.2 Getting random numbers .......................................... 52 7.1.3 Reverse Engineering ............................................. 53 7.2 Remainder of division ................................................ 53 7.2.1 Remainder of division by modulo 2n .................................... 53 7.3 Modulo inverse, part I ................................................ 54 7.3.1 No remainder? ................................................ 55 7.4 Modulo inverse, part II ................................................ 55 7.5 Reversible linear congruential generator ...................................... 57 7.6 Getting magic number using extended Euclidean algorithm ............................ 58 8 Probability 60 8.1 Text strings right in the middle of compressed data ................................ 60 8.2 Autocomplete using Markov chains ......................................... 62 8.2.1 Dissociated press .............................................. 62 8.2.2 Autocomplete ................................................ 66 8.2.3 Further work ................................................. 73 8.2.4 The files .................................................... 73 8.2.5 Read more .................................................. 73 8.2.6 Another thought-provoking example .................................... 73 8.3 random.choices() in Python 3 ............................................ 76 9 Combinatorics 78 9.1 Soldering a headphones cable ............................................ 78 9.2 Vehicle license plate ................................................. 79 9.3 Forgotten password ................................................. 79 9.4 Executable file watermarking/steganography using Lehmer code and factorial number system ......... 85 9.5 De Bruijn sequences; leading/trailing zero bits counting .............................. 89 9.5.1 Introduction ................................................. 89 9.5.2 Trailing zero bits counting .......................................... 90 9.5.3 Leading zero bits counting .......................................... 93 2Rivest–Shamir–Adleman cryptosystem If you noticed a typo, error or have any suggestions, do not hesitate to drop me a note: <[email protected]>. Thanks! 3 9.5.4 Performance ................................................. 94 9.5.5 Applications ................................................. 94 9.5.6 Generation of De Bruijn sequences ..................................... 94 9.5.7 Other articles ................................................. 94 10 Galois Fields, GF(2) and yet another explanation of CRC3 95 10.1 What is wrong with checksum? ........................................... 95 10.2 Division by prime ................................................... 95 10.3 (Binary) long divison ................................................. 95 10.4 (Binary) long division, version 2 ........................................... 97 10.5 Shortest possible introduction into GF(2) ...................................... 98 10.6 CRC32 ......................................................... 99 10.7 Rationale ....................................................... 100 10.8 Further reading .................................................... 101 11 Logarithms 102 11.1 Introduction ..................................................... 102 11.1.1 Children’s approach ............................................. 102 11.1.2 Scientists’ and engineers’ approach .................................... 102 11.2 Logarithmic scale ................................................... 103 11.2.1 In human perception ............................................. 103 11.2.2 In electronics engineering .......................................... 103 11.2.3 In IT ...................................................... 105 11.2.4 Web 2.0 .................................................... 106 11.2.5 Errors of TeX ................................................. 106 11.2.6 Moore’s Law ................................................. 107 11.2.7 Money .................................................... 107 11.2.8 Sizes, values, weights... ........................................... 107 11.3 Multiplication and division using addition and subtraction ............................ 108 11.3.1 Logarithmic slide rule ............................................ 108 11.3.2 Logarithmic tables .............................................. 109 11.3.3
Recommended publications
  • Generalizing Zeckendorf's Theorem to F-Decompositions
    GENERALIZING ZECKENDORF’S THEOREM TO f-DECOMPOSITIONS PHILIPPE DEMONTIGNY, THAO DO, ARCHIT KULKARNI, STEVEN J. MILLER, DAVID MOON, AND UMANG VARMA ABSTRACT. A beautiful theorem of Zeckendorf states that every positive integer can be uniquely decomposed as a sum of non-consecutive Fibonacci numbers fFng, where F1 = 1, F2 = 2 and Fn+1 = Fn + Fn−1. For general recurrences fGng with non-negative coefficients, there is a notion of a legal decomposition which again leads to a unique representation, and the number of sum- mands in the representations of uniformly randomly chosen m 2 [Gn;Gn+1) converges to a normal distribution as n ! 1. We consider the converse question: given a notion of legal decomposition, is it possible to con- struct a sequence fang such that every positive integer can be decomposed as a sum of terms from the sequence? We encode a notion of legal decomposition as a function f : N0 ! N0 and say that if an is in an “f-decomposition”, then the decomposition cannot contain the f(n) terms immediately before an in the sequence; special choices of f yield many well known decompositions (including base-b, Zeckendorf and factorial). We prove that for any f : N0 ! N0, there exists a sequence 1 fangn=0 such that every positive integer has a unique f-decomposition using fang. Further, if f is periodic, then the unique increasing sequence fang that corresponds to f satisfies a linear recurrence relation. Previous research only handled recurrence relations with no negative coefficients. We find a function f that yields a sequence that cannot be described by such a recurrence relation.
    [Show full text]
  • A Robust Software Watermarking for Copyright Protection
    computers & security 28 (2009) 395–409 available at www.sciencedirect.com journal homepage: www.elsevier.com/locate/cose A robust software watermarking for copyright protection Ibrahim Kamela,*, Qutaiba Albluwib aDepartment of Computer Engineering Sharjah University, P.O. Box 27272, United Arab Emirates bSchool of Computing, Queens University, Canada article info abstract Article history: This paper advocates protecting software copyright through hiding watermarks in various Received 18 August 2008 data structures used by the code, e.g., Bþ-trees, R-trees, linked lists, etc. Prior proposals Received in revised form hide the watermarks in dummy data structures, e.g., linked lists and graphs that are 13 January 2009 created, solely for this reason, during the execution of the hosting software. This makes Accepted 30 January 2009 them vulnerable to subtractive attacks, because the attacker can remove the dummy data structures without altering the functionality or the semantic of the software program. We Keywords: argue that hiding watermarks in one or more data structures that are used by the program Information security would make the watermark more robust because disturbing the watermark would affect R-trees the semantic and the functionality of the underlying software. The challenge is that the Watermarking insertion of the watermark should have a minimal effect on the operations and perfor- Multimedia indexes mance of the data structure. Spatial data structures This paper proposes a novel method for watermarking R-tree data structure and its variants. Copyright protection The proposed watermarking technique does not change the values of the stored data objects. It takes advantage of the redundancy in the order of entries inside the R-tree nodes.
    [Show full text]
  • THÈSE DOCTEUR DE L'université DU LUXEMBOURG EN INFORMATIQUE ET DOCTEUR DE L'université LILLE1 EN INFORMATIQUE Malika Mehd
    PhD-FSTC-2011-17 Faculté des Sciences, de la Technologie et de Faculté des Sciences et Technologies de Lille la Communication THÈSE Soutenue le 20/10/2011 à Luxembourg En vue de l’obtention du grade académique de DOCTEUR DE L’UNIVERSITÉ DU LUXEMBOURG EN INFORMATIQUE ET DOCTEUR DE L’UNIVERSITÉ LILLE1 EN INFORMATIQUE par Malika Mehdi née le 10 septembre 1981 à Bejaia PARALLEL HYBRID OPTIMIZATION METHODS FOR PERMUTATION BASED PROBLEMS Jury de thèse Prof. Dr. Pascal Bouvry, directeur de thèse Professeur, Université du Luxembourg Prof. Dr. El-Ghazali Talbi, directeur de thèse Professeur, Université Lille1 Prof. Dr. Nouredine Melab, co-directeur de thèse Professeur, Université Lille1 Prof. Dr. Raymond Bisdorff, président Professeur, Université du Luxembourg Prof. Dr. Enrique Alba, membre Professeur, Université de Malaga Dr. Didier El-Baz, membre HDR, LAAS-CNRS, Toulouse Abstract Solving efficiently large benchmarks of NP-hard permutation-based problems re- quires the development of hybrid methods combining different classes of optimiza- tion methods. Indeed, it is now acknowledged that such methods perform better than traditional optimization methods when used separately. The key challenge is how to find connections between the divergent search strategies used in each class of methods in order to build efficient hybridization strategies. Genetic algorithms (GAs) are very popular population-based metaheuristics based on stochastic evo- lutionary operators. The hybridization of GAs with tree-based exact methods such as Branch-and-Bound is a promising research trend. B&B algorithms are based on an implicit enumeration of the solution space represented as a tree. Our hybridization approach consists in providing a common solution and search space coding and associated search operators enabling an efficient cooperation between the two methods.
    [Show full text]
  • Version 13.0 Release Notes
    Release Notes The tool of thought for expert programming Version 13.0 Dyalog is a trademark of Dyalog Limited Copyright 1982-2011 by Dyalog Limited. All rights reserved. Version 13.0 First Edition April 2011 No part of this publication may be reproduced in any form by any means without the prior written permission of Dyalog Limited. Dyalog Limited makes no representations or warranties with respect to the contents hereof and specifically disclaims any implied warranties of merchantability or fitness for any particular purpose. Dyalog Limited reserves the right to revise this publication without notification. TRADEMARKS: SQAPL is copyright of Insight Systems ApS. UNIX is a registered trademark of The Open Group. Windows, Windows Vista, Visual Basic and Excel are trademarks of Microsoft Corporation. All other trademarks and copyrights are acknowledged. iii Contents C H A P T E R 1 Introduction .................................................................................... 1 Summary........................................................................................................................... 1 System Requirements ....................................................................................................... 2 Microsoft Windows .................................................................................................... 2 Microsoft .Net Interface .............................................................................................. 2 Unix and Linux ..........................................................................................................
    [Show full text]
  • IJR-1, Mathematics for All ... Syed Samsul Alam
    January 31, 2015 [IISRR-International Journal of Research ] MATHEMATICS FOR ALL AND FOREVER Prof. Syed Samsul Alam Former Vice-Chancellor Alaih University, Kolkata, India; Former Professor & Head, Department of Mathematics, IIT Kharagpur; Ch. Md Koya chair Professor, Mahatma Gandhi University, Kottayam, Kerala , Dr. S. N. Alam Assistant Professor, Department of Metallurgical and Materials Engineering, National Institute of Technology Rourkela, Rourkela, India This article briefly summarizes the journey of mathematics. The subject is expanding at a fast rate Abstract and it sometimes makes it essential to look back into the history of this marvelous subject. The pillars of this subject and their contributions have been briefly studied here. Since early civilization, mathematics has helped mankind solve very complicated problems. Mathematics has been a common language which has united mankind. Mathematics has been the heart of our education system right from the school level. Creating interest in this subject and making it friendlier to students’ right from early ages is essential. Understanding the subject as well as its history are both equally important. This article briefly discusses the ancient, the medieval, and the present age of mathematics and some notable mathematicians who belonged to these periods. Mathematics is the abstract study of different areas that include, but not limited to, numbers, 1.Introduction quantity, space, structure, and change. In other words, it is the science of structure, order, and relation that has evolved from elemental practices of counting, measuring, and describing the shapes of objects. Mathematicians seek out patterns and formulate new conjectures. They resolve the truth or falsity of conjectures by mathematical proofs, which are arguments sufficient to convince other mathematicians of their validity.
    [Show full text]
  • Unranking Combinations Lexicographically: an Efficient New Strategy Compared with Others Cyann Donnot, Antoine Genitrini, Yassine Herida
    Unranking Combinations Lexicographically: an efficient new strategy compared with others Cyann Donnot, Antoine Genitrini, Yassine Herida To cite this version: Cyann Donnot, Antoine Genitrini, Yassine Herida. Unranking Combinations Lexicographically: an efficient new strategy compared with others. 2020. hal-02462764 HAL Id: hal-02462764 https://hal.sorbonne-universite.fr/hal-02462764 Preprint submitted on 31 Jan 2020 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. Unranking Combinations Lexicographically: an efficient new strategy compared with others Cyann Donnot1, Antoine Genitrini2, and Yassine Herida1 1 Full-time master student at Sorbonne University 2 Sorbonne University, LIP6. [email protected] Abstract. We propose a comparative study of four algorithms dedi- cated to the lexicographic unranking of combinations. The three first ones are algorithms from the literature. We give some key ideas how to analyze them in average and describe their strengths and weaknesses. We then introduce a new algorithm based on a new strategy inside the classical factorial numeral system (or factoradics). We conclude the pa- per with an experimental study, in particular when n = 10000; k = 5000, our algorithm is 36 (resp. 53) times as fast as our C++ implementation of Matlab’s (resp.
    [Show full text]
  • Music and Measurement
    Music and Measurement: On the Eidetic Principles of Harmony and Motion Jeffrey C. Kalb, Jr. Released into the public domain: The Feast of St. Cecilia November 22, 2016 Beatae Mariae Semper Virgini, Mediatrici, Coredemptrici, et Advocatae ταὐτὸν γὰρ ποιοῦσι τοῖς ἐν τῇ ἀστρονομίᾳ· τοὺς γὰρ ἐν ταύταις ταῖς συμφωνίαις ταῖς ακουομέναις ἀριθμοὺς ζητοῦσιν, ἀλλ᾽ οὐκ εἰς προβλήματα ἀνίασιν ἐπισκοπεῖν, τίνες ξύμφωνοι ἀριθμοὶ καὶ τίνες οὔ, καὶ διὰ τί ἑκάτεροι.1 For they do the same thing as those in astronomy: they seek the numbers in these harmonies being heard, but they do not ascend to contemplate the problems of which numbers harmonize and which do not, and the reason for each. ― Plato, Republic Index 1. Musica Abscondita 1 1.1 The Definition of Music 3 1.2 Mathematical, Physical, and Intermediate Sciences of Music 5 Figure 1: The Decomposition of a Periodic Waveform into Harmonics 5 1.3 Against the Beat Theory of Harmony 8 Figure 2: The Formation of Beats 9 Figure 3: Standing Waves Formed on a Vibrating String 10 1.4 The Classical Theory of Number and Magnitude 12 1.5 Theoretical Logistic 13 1.6 Common Axioms 15 1.7 Symbolic Mathematics 17 1.8 The Stepwise Symbolic Origin of Algebra 19 1.9 Symbolic Abstraction and the Problem of Measurement 21 1.10 The Act of Measurement 22 Figure 4: Failure in Measurement 22 1.11 Fraction and Meter 23 1.12 A Critique of Metrical Theories of Harmony 24 1.13 The Meaning of Exponents 26 Figure 5: The Classical and Modern Expressions of Area 26 1.14 The Algebraic Division of Operation 28 1.15 Algebra as Confused Music 29 Table 1: The Harmonic Intervals of Simon Stevin 31 2.
    [Show full text]
  • Math Book from Wikipedia
    Math book From Wikipedia PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Mon, 25 Jul 2011 10:39:12 UTC Contents Articles 0.999... 1 1 (number) 20 Portal:Mathematics 24 Signed zero 29 Integer 32 Real number 36 References Article Sources and Contributors 44 Image Sources, Licenses and Contributors 46 Article Licenses License 48 0.999... 1 0.999... In mathematics, the repeating decimal 0.999... (which may also be written as 0.9, , 0.(9), or as 0. followed by any number of 9s in the repeating decimal) denotes a real number that can be shown to be the number one. In other words, the symbols 0.999... and 1 represent the same number. Proofs of this equality have been formulated with varying degrees of mathematical rigour, taking into account preferred development of the real numbers, background assumptions, historical context, and target audience. That certain real numbers can be represented by more than one digit string is not limited to the decimal system. The same phenomenon occurs in all integer bases, and mathematicians have also quantified the ways of writing 1 in non-integer bases. Nor is this phenomenon unique to 1: every nonzero, terminating decimal has a twin with trailing 9s, such as 8.32 and 8.31999... The terminating decimal is simpler and is almost always the preferred representation, contributing to a misconception that it is the only representation. The non-terminating form is more convenient for understanding the decimal expansions of certain fractions and, in base three, for the structure of the ternary Cantor set, a simple fractal.
    [Show full text]
  • The Statistic Pinv for Number System∗
    Applied Mathematics E-Notes, 20(2020), 230-235 c ISSN 1607-2510 Available free at mirror sites of http://www.math.nthu.edu.tw/ amen/ The Statistic Pinv For Number System Fanomezantsoa Patrick Rabarisony, Hery Randriamaroz Received 19 April 2019 Abstract The number of inversions is a statistic on permutation groups measuring the degree to which the entries of a permutation are out of order. We provide a generalization of that statistic by introducing the statistic number of pseudoinversions on the colored permutation groups. The main motivation for studying that statistic is the possibility to use it to define a number system and a numeral system on the colored permutation groups. By means of the statistic number of i-pseudoinversions, we construct our number system, and a bijection between the set of positive integers and the colored permutation groups. 1 Introduction A statistic over a group is a function from that group to the set of nonnegative integers. One of the most studied statistics is the number of inversions, defined by inv := # (i, j) [n]2 i < j, (i) > (j) , 2 j on the symmetric group Sn over [n]. A well-known result is the equidistribution of inv with the statistic major index proved by Foata [3]. Besides, the Lehmer code is based on that statistic. It is a particular way to encode each permutation of n numbers, and an instance of a scheme for numbering permutations. Remark that Vajnovszki provided several permutation codes directly related to the Lehmer code [5]. In this article, we give a generalization of the statistic inv on the colored permutation group in order to create a more general code.
    [Show full text]
  • Zot-Binary: a New Numbering System with an Application on Big-Integer Multiplication
    Journal of Theoretical and Applied Information Technology 10th February 2013. Vol. 48 No.1 © 2005 - 2013 JATIT & LLS. All rights reserved. ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 ZOT-BINARY: A NEW NUMBERING SYSTEM WITH AN APPLICATION ON BIG-INTEGER MULTIPLICATION 1SHAHRAM JAHANI, 2AZMAN SAMSUDIN 1,2 School of Computer Sciences, Universiti Sains Malaysia,Pulau Penang, Malaysia E-mail: [email protected], [email protected] ABSTRACT In this paper we present a new numbering system with an efficient application on Big-Integer multiplication. The paper starts with an introduction to a new redundant positional numbering system known as “Big-Digit Numbering System” (BDNS). With BDNS, a new non-redundant positional numbering system known as ZOT-Binary is proposed. ZOT-Binary has a low Hamming weight with an average of 23.8% nonzero symbols, and therefore is highly suitable for Big-Integer calculation, especially for Big- Integer multiplication. To harvest such benefit from the ZOT-Binary representation, a new Big-Integer multiplication algorithm, ZOT-CM, which is based on the Classical multiplication algorithm, is proposed. Our result shows that when compared with the Classical multiplication algorithm, ZOT-CM is about 12 times faster for multiplying 128 bits numbers and at least 16 times faster for multiplying numbers that are bigger than 32,000 bits long. Our result also shows that ZOT-CM is about 20 to 3 times faster than Karatsuba multiplication algorithm, for multiplying numbers that are ranging from 128 bits to 32,000 bits long. From the findings, it is clear that ZOT-CM is a valuable addition to Big-Integer multiplication algorithm, and it is also believed that ZOT-Binary representation can benefit many other Big-Integer calculations.
    [Show full text]
  • Floating Point
    Contents Articles Floating point 1 Positional notation 22 References Article Sources and Contributors 32 Image Sources, Licenses and Contributors 33 Article Licenses License 34 Floating point 1 Floating point In computing, floating point describes a method of representing an approximation of a real number in a way that can support a wide range of values. The numbers are, in general, represented approximately to a fixed number of significant digits (the significand) and scaled using an exponent. The base for the scaling is normally 2, 10 or 16. The typical number that can be represented exactly is of the form: Significant digits × baseexponent The idea of floating-point representation over intrinsically integer fixed-point numbers, which consist purely of significand, is that An early electromechanical programmable computer, expanding it with the exponent component achieves greater range. the Z3, included floating-point arithmetic (replica on display at Deutsches Museum in Munich). For instance, to represent large values, e.g. distances between galaxies, there is no need to keep all 39 decimal places down to femtometre-resolution (employed in particle physics). Assuming that the best resolution is in light years, only the 9 most significant decimal digits matter, whereas the remaining 30 digits carry pure noise, and thus can be safely dropped. This represents a savings of 100 bits of computer data storage. Instead of these 100 bits, much fewer are used to represent the scale (the exponent), e.g. 8 bits or 2 A diagram showing a representation of a decimal decimal digits. Given that one number can encode both astronomic floating-point number using a mantissa and an and subatomic distances with the same nine digits of accuracy, but exponent.
    [Show full text]
  • Non-Power Positional Number Representation Systems, Bijective Numeration, and the Mesoamerican Discovery of Zero
    Non-Power Positional Number Representation Systems, Bijective Numeration, and the Mesoamerican Discovery of Zero Berenice Rojo-Garibaldia, Costanza Rangonib, Diego L. Gonz´alezb;c, and Julyan H. E. Cartwrightd;e a Posgrado en Ciencias del Mar y Limnolog´ıa, Universidad Nacional Aut´onomade M´exico, Av. Universidad 3000, Col. Copilco, Del. Coyoac´an,Cd.Mx. 04510, M´exico b Istituto per la Microelettronica e i Microsistemi, Area della Ricerca CNR di Bologna, 40129 Bologna, Italy c Dipartimento di Scienze Statistiche \Paolo Fortunati", Universit`adi Bologna, 40126 Bologna, Italy d Instituto Andaluz de Ciencias de la Tierra, CSIC{Universidad de Granada, 18100 Armilla, Granada, Spain e Instituto Carlos I de F´ısicaTe´oricay Computacional, Universidad de Granada, 18071 Granada, Spain Keywords: Zero | Maya | Pre-Columbian Mesoamerica | Number rep- resentation systems | Bijective numeration Abstract Pre-Columbian Mesoamerica was a fertile crescent for the development of number systems. A form of vigesimal system seems to have been present from the first Olmec civilization onwards, to which succeeding peoples made contributions. We discuss the Maya use of the representational redundancy present in their Long Count calendar, a non-power positional number representation system with multipliers 1, 20, 18× 20, :::, 18× arXiv:2005.10207v2 [math.HO] 23 Mar 2021 20n. We demonstrate that the Mesoamericans did not need to invent positional notation and discover zero at the same time because they were not afraid of using a number system in which the same number can be written in different ways. A Long Count number system with digits from 0 to 20 is seen later to pass to one using digits 0 to 19, which leads us to propose that even earlier there may have been an initial zeroless bijective numeration system whose digits ran from 1 to 20.
    [Show full text]