The Many Guises of Induction
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Chapter 3 Induction and Recursion
Chapter 3 Induction and Recursion 3.1 Induction: An informal introduction This section is intended as a somewhat informal introduction to The Principle of Mathematical Induction (PMI): a theorem that establishes the validity of the proof method which goes by the same name. There is a particular format for writing the proofs which makes it clear that PMI is being used. We will not explicitly use this format when introducing the method, but will do so for the large number of different examples given later. Suppose you are given a large supply of L-shaped tiles as shown on the left of the figure below. The question you are asked to answer is whether these tiles can be used to exactly cover the squares of an 2n × 2n punctured grid { a 2n × 2n grid that has had one square cut out { say the 8 × 8 example shown in the right of the figure. 1 2 CHAPTER 3. INDUCTION AND RECURSION In order for this to be possible at all, the number of squares in the punctured grid has to be a multiple of three. It is. The number of squares is 2n2n − 1 = 22n − 1 = 4n − 1 ≡ 1n − 1 ≡ 0 (mod 3): But that does not mean we can tile the punctured grid. In order to get some traction on what to do, let's try some small examples. The tiling is easy to find if n = 1 because 2 × 2 punctured grid is exactly covered by one tile. Let's try n = 2, so that our punctured grid is 4 × 4. -
Properties of N-Sided Regular Polygons
PROPERTIES OF N-SIDED REGULAR POLYGONS When students are first exposed to regular polygons in middle school, they learn their properties by looking at individual examples such as the equilateral triangles(n=3), squares(n=4), and hexagons(n=6). A generalization is usually not given, although it would be straight forward to do so with just a min imum of trigonometry and algebra. It also would help students by showing how one obtains generalization in mathematics. We show here how to carry out such a generalization for regular polynomials of side length s. Our starting point is the following schematic of an n sided polygon- We see from the figure that any regular n sided polygon can be constructed by looking at n isosceles triangles whose base angles are θ=(1-2/n)(π/2) since the vertex angle of the triangle is just ψ=2π/n, when expressed in radians. The area of the grey triangle in the above figure is- 2 2 ATr=sh/2=(s/2) tan(θ)=(s/2) tan[(1-2/n)(π/2)] so that the total area of any n sided regular convex polygon will be nATr, , with s again being the side-length. With this generalized form we can construct the following table for some of the better known regular polygons- Name Number of Base Angle, Non-Dimensional 2 sides, n θ=(π/2)(1-2/n) Area, 4nATr/s =tan(θ) Triangle 3 π/6=30º 1/sqrt(3) Square 4 π/4=45º 1 Pentagon 5 3π/10=54º sqrt(15+20φ) Hexagon 6 π/3=60º sqrt(3) Octagon 8 3π/8=67.5º 1+sqrt(2) Decagon 10 2π/5=72º 10sqrt(3+4φ) Dodecagon 12 5π/12=75º 144[2+sqrt(3)] Icosagon 20 9π/20=81º 20[2φ+sqrt(3+4φ)] Here φ=[1+sqrt(5)]/2=1.618033989… is the well known Golden Ratio. -
The First Treatments of Regular Star Polygons Seem to Date Back to The
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Archivio istituzionale della ricerca - Università di Palermo FROM THE FOURTEENTH CENTURY TO CABRÌ: CONVOLUTED CONSTRUCTIONS OF STAR POLYGONS INTRODUCTION The first treatments of regular star polygons seem to date back to the fourteenth century, but a comprehensive theory on the subject was presented only in the nineteenth century by the mathematician Louis Poinsot. After showing how star polygons are closely linked to the concept of prime numbers, I introduce here some constructions, easily reproducible with geometry software that allow us to investigate and see some nice and hidden property obtained by the scholars of the fourteenth century onwards. Regular star polygons and prime numbers Divide a circumference into n equal parts through n points; if we connect all the points in succession, through chords, we get what we recognize as a regular convex polygon. If we choose to connect the points, starting from any one of them in regular steps, two by two, or three by three or, generally, h by h, we get what is called a regular star polygon. It is evident that we are able to create regular star polygons only for certain values of h. Let us divide the circumference, for example, into 15 parts and let's start by connecting the points two by two. In order to close the figure, we return to the starting point after two full turns on the circumference. The polygon that is formed is like the one in Figure 1: a polygon of “order” 15 and “species” two. -
Simple Polygons Scribe: Michael Goldwasser
CS268: Geometric Algorithms Handout #5 Design and Analysis Original Handout #15 Stanford University Tuesday, 25 February 1992 Original Lecture #6: 28 January 1991 Topics: Triangulating Simple Polygons Scribe: Michael Goldwasser Algorithms for triangulating polygons are important tools throughout computa- tional geometry. Many problems involving polygons are simplified by partitioning the complex polygon into triangles, and then working with the individual triangles. The applications of such algorithms are well documented in papers involving visibility, motion planning, and computer graphics. The following notes give an introduction to triangulations and many related definitions and basic lemmas. Most of the definitions are based on a simple polygon, P, containing n edges, and hence n vertices. However, many of the definitions and results can be extended to a general arrangement of n line segments. 1 Diagonals Definition 1. Given a simple polygon, P, a diagonal is a line segment between two non-adjacent vertices that lies entirely within the interior of the polygon. Lemma 2. Every simple polygon with jPj > 3 contains a diagonal. Proof: Consider some vertex v. If v has a diagonal, it’s party time. If not then the only vertices visible from v are its neighbors. Therefore v must see some single edge beyond its neighbors that entirely spans the sector of visibility, and therefore v must be a convex vertex. Now consider the two neighbors of v. Since jPj > 3, these cannot be neighbors of each other, however they must be visible from each other because of the above situation, and thus the segment connecting them is indeed a diagonal. -
Mathematical Induction
Mathematical Induction Lecture 10-11 Menu • Mathematical Induction • Strong Induction • Recursive Definitions • Structural Induction Climbing an Infinite Ladder Suppose we have an infinite ladder: 1. We can reach the first rung of the ladder. 2. If we can reach a particular rung of the ladder, then we can reach the next rung. From (1), we can reach the first rung. Then by applying (2), we can reach the second rung. Applying (2) again, the third rung. And so on. We can apply (2) any number of times to reach any particular rung, no matter how high up. This example motivates proof by mathematical induction. Principle of Mathematical Induction Principle of Mathematical Induction: To prove that P(n) is true for all positive integers n, we complete these steps: Basis Step: Show that P(1) is true. Inductive Step: Show that P(k) → P(k + 1) is true for all positive integers k. To complete the inductive step, assuming the inductive hypothesis that P(k) holds for an arbitrary integer k, show that must P(k + 1) be true. Climbing an Infinite Ladder Example: Basis Step: By (1), we can reach rung 1. Inductive Step: Assume the inductive hypothesis that we can reach rung k. Then by (2), we can reach rung k + 1. Hence, P(k) → P(k + 1) is true for all positive integers k. We can reach every rung on the ladder. Logic and Mathematical Induction • Mathematical induction can be expressed as the rule of inference (P(1) ∧ ∀k (P(k) → P(k + 1))) → ∀n P(n), where the domain is the set of positive integers. -
Chapter 4 Induction and Recursion
Chapter 4 Induction and Recursion 4.1 Induction: An informal introduction This section is intended as a somewhat informal introduction to The Principle of Mathematical Induction (PMI): a theorem that establishes the validity of the proof method which goes by the same name. There is a particular format for writing the proofs which makes it clear that PMI is being used. We will not explicitly use this format when introducing the method, but will do so for the large number of different examples given later. Suppose you are given a large supply of L-shaped tiles as shown on the left of the figure below. The question you are asked to answer is whether these tiles can be used to exactly cover the squares of an 2n × 2n punctured grid { a 2n × 2n grid that has had one square cut out { say the 8 × 8 example shown in the right of the figure. 1 2 CHAPTER 4. INDUCTION AND RECURSION In order for this to be possible at all, the number of squares in the punctured grid has to be a multiple of three. By direct calculation we can see that it is true when n = 1; 2 or 3, and these are the cases we're interested in here. It turns out to be true in general; this is easy to show using congruences, which we will study later, and also can be shown using methods in this chapter. But that does not mean we can tile the punctured grid. In order to get some traction on what to do, let's try some small examples. -
Chapter 7. Induction and Recursion
Chapter 7. Induction and Recursion Part 1. Mathematical Induction The principle of mathematical induction is this: to establish an infinite sequence of propositions P1,P2,P3,...,Pn,... (or, simply put, Pn (n 1)), it is enough to verify the following two things ≥ (1) P1, and (2) Pk Pk ; (that is, assuming Pk vaild, we can rpove the validity of Pk ). ⇒ + 1 + 1 These two things will give a “domino effect” for the validity of all Pn (n 1). Indeed, ≥ step (1) tells us that P1 is true. Applying (2) to the case n = 1, we know that P2 is true. Knowing that P2 is true and applying (2) to the case n = 2 we know that P3 is true. Continue in this manner, we see that P4 is true, P5 is true, etc. This argument can go on and on. Now you should be convinced that Pn is true, no matter how big is n. We give some examples to show how this induction principle works. Example 1. Use mathematical induction to show 1 + 3 + 5 + + (2n 1) = n2. ··· − (Remember: in mathematics, “show” means “prove”.) Answer: For n = 1, the identity becomes 1 = 12, which is obviously true. Now assume the validity of the identity for n = k: 1 + 3 + 5 + + (2k 1) = k2. ··· − For n = k + 1, the left hand side of the identity is 1 + 3 + 5 + + (2k 1) + (2(k + 1) 1) = k2 + (2k + 1) = (k + 1)2 ··· − − which is the right hand side for n = k + 1. The proof is complete. 1 Example 2. Use mathematical induction to show the following formula for a geometric series: 1 xn+ 1 1 + x + x2 + + xn = − . -
A Survey of Engineering of Formally Verified Software
The version of record is available at: http://dx.doi.org/10.1561/2500000045 QED at Large: A Survey of Engineering of Formally Verified Software Talia Ringer Karl Palmskog University of Washington University of Texas at Austin [email protected] [email protected] Ilya Sergey Milos Gligoric Yale-NUS College University of Texas at Austin and [email protected] National University of Singapore [email protected] Zachary Tatlock University of Washington [email protected] arXiv:2003.06458v1 [cs.LO] 13 Mar 2020 Errata for the present version of this paper may be found online at https://proofengineering.org/qed_errata.html The version of record is available at: http://dx.doi.org/10.1561/2500000045 Contents 1 Introduction 103 1.1 Challenges at Scale . 104 1.2 Scope: Domain and Literature . 105 1.3 Overview . 106 1.4 Reading Guide . 106 2 Proof Engineering by Example 108 3 Why Proof Engineering Matters 111 3.1 Proof Engineering for Program Verification . 112 3.2 Proof Engineering for Other Domains . 117 3.3 Practical Impact . 124 4 Foundations and Trusted Bases 126 4.1 Proof Assistant Pre-History . 126 4.2 Proof Assistant Early History . 129 4.3 Proof Assistant Foundations . 130 4.4 Trusted Computing Bases of Proofs and Programs . 137 5 Between the Engineer and the Kernel: Languages and Automation 141 5.1 Styles of Automation . 142 5.2 Automation in Practice . 156 The version of record is available at: http://dx.doi.org/10.1561/2500000045 6 Proof Organization and Scalability 162 6.1 Property Specification and Encodings . -
3 Mathematical Induction
Hardegree, Metalogic, Mathematical Induction page 1 of 27 3 Mathematical Induction 1. Introduction.......................................................................................................................................2 2. Explicit Definitions ..........................................................................................................................2 3. Inductive Definitions ........................................................................................................................3 4. An Aside on Terminology.................................................................................................................3 5. Induction in Arithmetic .....................................................................................................................3 6. Inductive Proofs in Arithmetic..........................................................................................................4 7. Inductive Proofs in Meta-Logic ........................................................................................................5 8. Expanded Induction in Arithmetic.....................................................................................................7 9. Expanded Induction in Meta-Logic...................................................................................................8 10. How Induction Captures ‘Nothing Else’...........................................................................................9 11. Exercises For Chapter 3 .................................................................................................................11 -
Angles of Polygons
5.3 Angles of Polygons How can you fi nd a formula for the sum of STATES the angle measures of any polygon? STANDARDS MA.8.G.2.3 1 ACTIVITY: The Sum of the Angle Measures of a Polygon Work with a partner. Find the sum of the angle measures of each polygon with n sides. a. Sample: Quadrilateral: n = 4 A Draw a line that divides the quadrilateral into two triangles. B Because the sum of the angle F measures of each triangle is 180°, the sum of the angle measures of the quadrilateral is 360°. C D E (A + B + C ) + (D + E + F ) = 180° + 180° = 360° b. Pentagon: n = 5 c. Hexagon: n = 6 d. Heptagon: n = 7 e. Octagon: n = 8 196 Chapter 5 Angles and Similarity 2 ACTIVITY: The Sum of the Angle Measures of a Polygon Work with a partner. a. Use the table to organize your results from Activity 1. Sides, n 345678 Angle Sum, S b. Plot the points in the table in a S coordinate plane. 1080 900 c. Write a linear equation that relates S to n. 720 d. What is the domain of the function? 540 Explain your reasoning. 360 180 e. Use the function to fi nd the sum of 1 2 3 4 5 6 7 8 n the angle measures of a polygon −180 with 10 sides. −360 3 ACTIVITY: The Sum of the Angle Measures of a Polygon Work with a partner. A polygon is convex if the line segment connecting any two vertices lies entirely inside Convex the polygon. -
Some Polygon Facts Student Understanding the Following Facts Have Been Taken from Websites of Polygons
eachers assume that by the end of primary school, students should know the essentials Tregarding shape. For example, the NSW Mathematics K–6 syllabus states by year six students should be able manipulate, classify and draw two- dimensional shapes and describe side and angle properties. The reality is, that due to the pressure for students to achieve mastery in number, teachers often spend less time teaching about the other aspects of mathematics, especially shape (Becker, 2003; Horne, 2003). Hence, there is a need to modify the focus of mathematics education to incorporate other aspects of JILLIAN SCAHILL mathematics including shape and especially polygons. The purpose of this article is to look at the teaching provides some and learning of polygons in primary classrooms by providing some essential information about polygons teaching ideas and some useful teaching strategies and resources. to increase Some polygon facts student understanding The following facts have been taken from websites of polygons. and so are readily accessible to both teachers and students. “The word ‘polygon’ derives from the Greek word ‘poly’, meaning ‘many’ and ‘gonia’, meaning ‘angle’” (Nation Master, 2004). “A polygon is a closed plane figure with many sides. If all sides and angles of a polygon are equal measures then the polygon is called regular” 30 APMC 11 (1) 2006 Teaching polygons (Weisstein, 1999); “a polygon whose sides and angles that are not of equal measures are called irregular” (Cahir, 1999). “Polygons can be convex, concave or star” (Weisstein, 1999). A star polygon is a figure formed by connecting straight lines at every second point out of regularly spaced points lying on a circumference. -
Convex Polytopes and Tilings with Few Flag Orbits
Convex Polytopes and Tilings with Few Flag Orbits by Nicholas Matteo B.A. in Mathematics, Miami University M.A. in Mathematics, Miami University A dissertation submitted to The Faculty of the College of Science of Northeastern University in partial fulfillment of the requirements for the degree of Doctor of Philosophy April 14, 2015 Dissertation directed by Egon Schulte Professor of Mathematics Abstract of Dissertation The amount of symmetry possessed by a convex polytope, or a tiling by convex polytopes, is reflected by the number of orbits of its flags under the action of the Euclidean isometries preserving the polytope. The convex polytopes with only one flag orbit have been classified since the work of Schläfli in the 19th century. In this dissertation, convex polytopes with up to three flag orbits are classified. Two-orbit convex polytopes exist only in two or three dimensions, and the only ones whose combinatorial automorphism group is also two-orbit are the cuboctahedron, the icosidodecahedron, the rhombic dodecahedron, and the rhombic triacontahedron. Two-orbit face-to-face tilings by convex polytopes exist on E1, E2, and E3; the only ones which are also combinatorially two-orbit are the trihexagonal plane tiling, the rhombille plane tiling, the tetrahedral-octahedral honeycomb, and the rhombic dodecahedral honeycomb. Moreover, any combinatorially two-orbit convex polytope or tiling is isomorphic to one on the above list. Three-orbit convex polytopes exist in two through eight dimensions. There are infinitely many in three dimensions, including prisms over regular polygons, truncated Platonic solids, and their dual bipyramids and Kleetopes. There are infinitely many in four dimensions, comprising the rectified regular 4-polytopes, the p; p-duoprisms, the bitruncated 4-simplex, the bitruncated 24-cell, and their duals.