Activity 2-17: Zeroes of a Recurrence Relation www.carom-maths.co.uk.

Slides:



Advertisements
Similar presentations
Ch 3.2: Solutions of Linear Homogeneous Equations; Wronskian
Advertisements

Chapter 2 Solutions of Systems of Linear Equations / Matrix Inversion
Ch. 10: What is a number?. MAIN DEFINITION OF THE COURSE: A symmetry of an object (in the plane or space) means a rigid motion (of the plane or space)
Activity 1-16: The Distribution Of Prime Numbers
INFINITE SEQUENCES AND SERIES
1.5 Elementary Matrices and a Method for Finding
Orthogonality and Least Squares
Activity 2-14: The ABC Conjecture
6 6.3 © 2012 Pearson Education, Inc. Orthogonality and Least Squares ORTHOGONAL PROJECTIONS.
7.5 Use Recursive Rules with Sequences and Functions
1 10. Joint Moments and Joint Characteristic Functions Following section 6, in this section we shall introduce various parameters to compactly represent.
Geometric Sequences and Series Part III. Geometric Sequences and Series The sequence is an example of a Geometric sequence A sequence is geometric if.
Activity 2-17 : The ABC Conjecture
Applied Discrete Mathematics Week 9: Relations
7.2 Solving Recurrence Relations. Definition 1 (p. 460)- LHRR-K Def: A linear homogeneous recurrence relations of degree k with constant coefficients.
Advanced Counting Techniques
Activity 1-15: Ergodic mathematics
Finding Rational Zeros.
MA2213 Lecture 4 Numerical Integration. Introduction Definition is the limit of Riemann sums I(f)
9.1 Sequences. A sequence is a list of numbers written in an explicit order. n th term Any real-valued function with domain a subset of the positive integers.
Mathematics Review Exponents Logarithms Series Modular arithmetic Proofs.
Chapter 8. Section 8. 1 Section Summary Introduction Modeling with Recurrence Relations Fibonacci Numbers The Tower of Hanoi Counting Problems Algorithms.
Copyright © Cengage Learning. All rights reserved. CHAPTER 5 SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION SEQUENCES, MATHEMATICAL INDUCTION, AND RECURSION.
Advanced Counting Techniques CSC-2259 Discrete Structures Konstantin Busch - LSU1.
Section 2.4. Section Summary Sequences. Examples: Geometric Progression, Arithmetic Progression Recurrence Relations Example: Fibonacci Sequence Summations.
Chapter 8 With Question/Answer Animations 1. Chapter Summary Applications of Recurrence Relations Solving Linear Recurrence Relations Homogeneous Recurrence.
Adjoint matrix Yes! The array of algebraic complements!
Linear Equations in Linear Algebra
1 1.7 © 2016 Pearson Education, Inc. Linear Equations in Linear Algebra LINEAR INDEPENDENCE.
Activity 2-2: Mapping a set to itself
Activity 2-4: Tangles You need four people for this, A, B, C and D, and two ropes, starting like this:
Sequences and Summations
11.2 Series In this section, we will learn about: Various types of series. INFINITE SEQUENCES AND SERIES.
Activity 1-7: The Overlapping Circles
Activity 2-10: Inversion There are some transformations of the plane we know all about: Reflection Rotation Enlargement.
Activity 2-12: Hikorski Triples
Activity 1-19: The Propositional Calculus
Sequences and Summations Section 2.4. Section Summary Sequences. – Examples: Geometric Progression, Arithmetic Progression Recurrence Relations – Example:
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Advanced Counting Techniques CSC-2259 Discrete Structures Konstantin Busch - LSU1.
If various terms of a sequence are formed by adding a fixed number to the previous term or the difference between two successive terms is a fixed number,
Activity 2-15: Elliptic curves
The Four Colour Theorem
Activity 1-17: Infinity.
Sullivan Algebra and Trigonometry: Section 12.3 Objectives of this Section Write the Augmented Matrix of a System of Linear Equations Write the System.
Activity 1-8: Repunits 111, 11111, , are all repunits. They have received a lot of attention down the.
Matrices and linear transformations For grade 1, undergraduate students For grade 1, undergraduate students Made by Department of Math.,Anqing Teachers.
Foundations of Discrete Mathematics Chapters 5 By Dr. Dalia M. Gil, Ph.D.
7.2 Solving Linear Recurrence Relations Some of these recurrence relations can be solved using iteration or some other ad hoc technique. However, one important.
Activity 1-4 : The Least Road Problem
Asymptotics and Recurrence Equations Prepared by John Reif, Ph.D. Analysis of Algorithms.
Activity 1-13: Descent This problem is due to Euler. Task: Show that the equation x 3 + 2y 3 + 4z 3 = 0 has the sole solution (0,
CSE 2813 Discrete Structures Solving Recurrence Relations Section 6.2.
Sequences & Series. Sequence: A function whose domain is a set of consecutive integers. The domain gives the relative position of each term of the sequence:
STROUD Worked examples and exercises are in the text Programme 10: Sequences PROGRAMME 10 SEQUENCES.
Activity 2-11: Quadratic Reciprocity
Finite Element Method. History Application Consider the two point boundary value problem.
Activity 1-12 : Multiple-free sets
9.3 Geometric Sequences and Series. Common Ratio In the sequence 2, 10, 50, 250, 1250, ….. Find the common ratio.
Activity 2-9: The Logistic Map and Chaos
Homogeneous Linear Recurrences To solve such recurrences we must first know how to solve an easier type of recurrence relation: DEF: A linear recurrence.
Activity 1-3: Coincidences
Advanced Algorithms Analysis and Design By Dr. Nazir Ahmad Zafar Dr Nazir A. Zafar Advanced Algorithms Analysis and Design.
CSE 20: Discrete Mathematics for Computer Science Prof. Shachar Lovett
Activity 2-18: Cyclotomic polynomials
Activity 2-15: Elliptic curves
Linear Algebra Lecture 3.
Zeroes of a Recurrence Relation
Recurrence Relations Discrete Structures.
Activity 2-18: Cyclotomic polynomials
Presentation transcript:

Activity 2-17: Zeroes of a Recurrence Relation

We all know the Fibonacci sequence, 1, 1, 2, 3, 5, 8, We can write this as u n+1 = u n + u n-1, with u 1 = 1, u 2 = 1. So the next term is the sum of the previous two, and we have some initial conditions. We have here an example of a Linear Recurrence Relation (or LRS).

u n+1 = a n u n + a n-1 u n-1 + a n-2 u n a n-k+1 u n-k+1 is the general LRS of order k. So the next term is a linear combination of the last k terms (we also need initial conditions). Now there is a way to calculate future terms for an LRS using a matrix. Let’s demonstrate this using the Fibonacci sequence. We will only be looking at the cases where every a i is an integer: we will call these ‘integer LRSs’.

So it is clear that If we have some computer help, in taking the powers of a matrix, we have a good way of calculating future terms of an LRS.

Task: use the spreadsheet below to find the 21st term, that’s F 21, in the Fibonacci sequence. Powers of a Matrix spreadsheet The 21st term in the Fibonacci sequence is carom/carom-files/carom-2-18.xls

Task: given the LRS u n+1 = u n + u n-1 + u n-2 with u 1 = 1, u 2 = 1, u 3 = 1, find the 22nd term. Using a 3 x 3 matrix this time: The 22nd term in this order-3 integer LRS sequence is

Now we can note that it makes perfect sense to run the Fibonacci sequence backwards....5, -3, 2, -1, 1, 0, 1, 1, 2, 3, 5, 8, So u 0 = 0, u -1 = 1, u -2 = -1, and so on: the rule still holds. Now a further question: how many 0s are there in the Fibonacci sequence? It seems clear that there can only be one. In that case, how many 0s can any order-2 integer LRS have? Can it have an infinite number? Or is there a maximum?

It is easy to construct an LRS that does have an infinite number of 0s. Consider u n+2 = 2u n, with u 1 = 0, u 2 = 2. This gives us the sequence 0, 2, 0, 4, 0, 8, 0, This clearly has an infinite number of 0s, BUT we call this type of LRS degenerate. The LRS u n+1 = a n u n + a n-1 u n-1 has associated with it the characteristic equation 2 = a n + a n-1. This has two roots, 1 and 2, and if their ratio is a root of unity, we say the LRS is degenerate.

So for our example u n+2 = 2u n, the characteristic equation is 2 = 2, and so 1, 2 are ±√2, and their ratio is -1. So for our Fibonacci sequence, the characteristic equation is 2   1 = 0, In general, the solution to an LRS is u n = A 1 n + B 2 n. We can find A and B from the initial conditions. which gives solutions 1, 2 = Using u 1 = 1, u 2 = 1, we find A =, B =, and so F n = Task: test this out for various n.

So let’s go back to our question and rephrase it: how many 0s can a non-degenerate order-2 integer LRS have? Theorem: Skolem-Mahler-Lech (proved in 1953). Any non-degenerate integer LRS has a finite number of 0s. It can also be proved that the largest number of 0s an order-2 non-degenerate integer LRS can have is 1, (so the Fibonacci sequence has the maximum). How can we prove this?

The order-2 LRS u n+1 = a n u n + a n-1 u n-1 has associated with it the characteristic equation 2 = a n + a n-1. Suppose the roots are 1, 2. So we have u n = A 1 n + B 2 n. Suppose u n = 0 for n = p and n = q, with p > q. 0 = A 1 p + B 2 p  Similarly, Subtracting, we have, and thus the ratio of the roots is a root of unity, and the LRS is degenerate. So the largest number of 0s an order-2 non-degenerate integer LRS can have is 1.

What is the largest number of 0s an order-3 non-degenerate integer LRS can have? Beukers has proved (1991) that the answer is 6. Can we find an order-3 integer LRS with six 0s ? The mathematician Berstel managed to do exactly that.

Task: using our matrix spreadsheet, see if you can find all six zeroes there are to be found. So we have zeroes for a 0, a 1, a 4, a 6, a 13, and rather surprisingly, for a 52 (!)

With thanks to: Graham Everest and Tom Ward. Carom is written by Jonny Griffiths,