NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES

Size: px
Start display at page:

Download "NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES"

Transcription

1 NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES EDUARDO CALOOY ROQUE Abstract. Ths paper shows the General Formulas for Pythagorean trples that were derved from the dfferences of the sdes of a rght trangle. In addton, as computatonal proof, tables were made wth a C++ scrpt showng prmtve Pythagorean trples and ncluded as text fles and screenshots. Furthermore, to enable readers to check and verfy them, the C++ scrpt whch wll nteractvely generate tables of Pythagorean trples from the computer console command lne s attached. It can be run n Clng and ROOT C/C++ nterpreters or compled. 1. Introducton I beleve t would be best to proceed mmedately to the problem at hand,.e. to fnd general formulas for Pythagorean trples, rather than dscuss many thngs and go n crcles. So gong straght to the pont we wll derve and prove the relevant theorem then derve from t the formulas gven by the Greeks, Plato and Pythagoras. Then we wll show the general formulas that generates Pythagorean trples. At ths pont, the pattern wll manfest. Next we wll provde tables from a C++ scrpt to demonstrate valdty. In concluson, attached the C++ scrpt nstead of typesettng verbatm so that the document wll not look unnecessarly large. 2. Pythagorean Trples Defnton. If a, b, c N and a < b < c or b < a < c then a Pythagorean trple s a trple of natural numbers such that a 2 + b 2 = c 2. It s sad to be prmtve f (a, b, c) s parwse relatvely prme and the partes of a and b are always oppostes whle c s always odd. Theorem 1. If (a, b, c) s a Pythagorean trple then there exsts α, β, γ Z, k, n N where α = b a, β = c a, γ = c b, β = α + γ, k = n, n = 1, 2, 3,... such that (a γ) 2 = 2γβ γβ = 2k 2 a = γ + 2k b = β + 2k c = γ + β + 2k Date: November 21,

2 2 EDUARDO CALOOY ROQUE Proof. a 2 + b 2 = c 2 a 2 + (a + α) 2 = (a + β) 2 a 2 + (a 2 + 2aα + α 2 ) = a 2 + 2aβ + β 2 a 2 + 2a(α β) = β 2 α 2 a 2 2a(β α) = (β + α)(β α) a 2 2γa = [(α + γ) + α]γ (a γ) 2 = γ(2α + γ) + γ 2 (a γ) 2 = 2γ(α + γ) (a γ) 2 = 2γβ It s evdent that (a γ) 2 = 2γβ has even party and hence of the form 4k 2 where k, n N, k = n, n = 1, 2, 3,... Thus (a γ) 2 = 4k 2 and γβ = 2k 2. We now see that a = γ + 2k. Now β α = (c a) (b a) = c b. Ths s γ thus α + γ = β. From b a = α we get b = a + α = β + 2k and snce c b = γ we also get c = b + γ = γ + β + 2k. Theorem 2. If (a, b, c) s a Pythagorean trple then there exsts α, β, γ Z, k, n N where α = b a, β = c a, γ = c b, β = α + γ, (a γ) 2 = 2γβ, γβ = 2k 2, k = n, n = 1, 2, 3,... such that γ = 1, β = 2k 2, a = 2k + 1 b = 2k(k + 1) c = 2k 2 + 2k + 1 γ = 2, β = k 2, a = 2(k + 1) b = k(k + 2) c = k 2 + 2k + 2 Proof. From Theorem1, we have β = 2k2 γ and so Pythagorean trples are generated by a = γ + 2k, b = 2k2 γ + 2k, c = γ + 2k2 γ + 2k It s seen then that ntegral values can be obtaned for γ = 1, 2. If γ = 1 then β = 2k 2 and a = 2k + 1, b = 2k(k + 1), c = 2k 2 + 2k + 1. If γ = 2 then β = k 2 and a = 2(k + 1), b = k(k + 2), c = k 2 + 2k + 2.

3 NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES 3 Corollary 2.1. If γ = 1, 2 then prmtve Pythagorean trples are generated by γ = 1, β = 2n 2, a = 2n + 1 γ = 2, β = n 2, a = 4n b = 2n(n + 1) c = 2n 2 + 2n + 1 b = 4n 2 1 c = 4n Proof. From Theorem2, f γ = 1, β = 2k 2 then a b, a c, b c and gcd(a, b, c) = 1. Thus prmtve Pythagorean trples can be found for k = n. If γ = 2, β = k 2 then we need to consder when k s even and when t s odd. If k s even let k = 2n then a = 2(2n+1), b = 4n(n+1), c = 2(2n 2 +2n+1) thus a b, a c, b c and gcd(a, b, c) = 2. Hence non-prmtve Pythagorean trples are found when k s even. If k s odd let k = 2n 1 then a = 4n, b = 4n 2 1, c = 4n thus a b, a c, b c and gcd(a, b, c) = 1. Hence prmtve Pythagorean trples can be found when k s odd. From these results the corollary s proved. 3. General formulas for Pythagorean Trples Theorem 3. If (a, b, c) s a Pythagorean trple then there exsts α, β, γ Z, k, m, n N where α = b a, β = c a, γ = c b, beta = α + γ, (a γ) 2 = 2γβ, γβ = 2k 2, k = mn, m = 1, 2, 3,..., n = 1, 2, 3,... such that γ = m 2, β = 2n 2, a = m(m + 2n) b = 2n(n + m) c = m 2 + 2mn + 2n 2 γ = 2m 2, β = n 2, a = 2m(m + n) b = n(n + 2m) c = 2m 2 + 2mn + n 2 Proof. If n N, n = 1, 2, 3,... then n = 1(1), 1(2), 2(1), 3(1), 2(2), 5(1),2(3),..., 41(3), 31(4),... We see that n can be expressed as the product of two natural numbers. Therefore f k, m, n N and k = mn where m = 1, 2, 3,..., n = 1, 2, 3,... then snce γβ = 2k 2 we have γβ = 2m 2 n 2. At ths pont, we see that (γ, β) s {(m 2, 2n 2 ), (2m 2, n 2 )}. Thus by Theorem1 we get the general formulas. Observe that f m = 1 they become the formulas n Theorem 2. Corollary 3.1. If γ = m 2 and β = 2n 2 then prmtve Pythagorean trples are generated f m = 1 and m > 1 where m n, m s odd and gcd(m, n) = 1. Proof. If m = 1 they become the formulas n Theorem 2. If m > 1 and f q, t N, q = 1, 2, 3,..., t = 1, 2, 3,..., γ = m 2, m n, m = t then let m = 2t 1 and we have a = (2t 1)[(2t 1) + 2n], b = 2n[n + (2t 1)], c = (2t 1) 2 + 2n[n + (2t 1)], gcd(a, b, c) = 1. Now let m = 2t and we have a = 4(t)(t+n), b = 2(n)(2t+n), c = 2[2t 2 +2tn+n 2 ], gcd(a, b, c) = 2. If n = qm, then a = 2(1+q)m 2, b = q(2+q)m 2, c = (2+2q+q 2 )m 2. We see that gcd(a, b, c) = m 2 therefore consderng all of these, we conclude that prmtve Pythagorean trples are found f m = 1 and f m > 1, m n, m s odd and gcd(m, n) = 1.

4 4 EDUARDO CALOOY ROQUE Corollary 3.2. If γ = 2m 2 and β = n 2 then prmtve Pythagorean trples are generated f m = 1 and m > 1 where m n, n s odd and gcd(m, n) = 1. Proof. If m = 1 they become the formulas n Theorem 2. If m > 1 and f q, t N, q = 1, 2, 3,..., t = 1, 2, 3,..., γ = m 2, m n, m = t then let m = 2t 1 and we have a = 2(2t 1)[(2t 1)+n], b = n[n+2(2t 1)], c = 2(2t 1) 2 +n[n+2(2t 1)], gcd(a, b, c) = 1. Now let m = 2t and we have a = 2(2t)[2t+n], b = n[n+2(2t)], c = 2(2t) 2 +n[n+2(2t)], gcd(a, b, c) = 1. Snce both have gcd(a, b, c) = 1 we consder n. A quck mental calculaton wll tell us that gcd(a, b, c) = 2 f n s even but gcd(a, b, c) = 1 f n s odd. If q N, n = qm, q = 1, 2, 3,... then a = (2 + q)m 2, b = q(q + 2)m 2, c = (2 + 2q + q 2 )m 2. We see that gcd(a, b, c) = m 2 thus consderng all of these we conclude that prmtve Pythagorean trples are found f m = 1 and f m > 1, m n, n s odd and gcd(m, n) = 1. Corollary 3.3. If a < b then n > m 2 for γ = m 2, β = 2n 2 and n > m 2 for γ = 2m 2, β = n 2. Proof. If a < b then α > 0 and so β > γ. Thus for γ = m 2, β = 2n 2 we have m 2 > 2n 2 whch s n > m 2. And for γ = 2m 2, β = n 2 we have 2m 2 > n 2 whch s n > m Extra Theorem 4. If (a, b, c) s a Pythagorean trple and t N, t = 3, 4, 5,... then a t + b t c t. Proof. By Theorem 1 and the Bnomal Theorem we have Thus by Theorem 3 a t + b t c t (γ + 2k) t + (β + 2k) t [(γ + β) + 2k] t (γ) (t ) (2k) + (β) (t ) (2k) (γ + β) (t ) (2k) γ = m 2, β = 2n 2, (m 2 ) (t ) (2mn) + γ = 2m 2, β = n 2, (2m 2 ) (t ) (2mn) + (2n 2 ) (t ) (2mn) (n 2 ) (t ) (2mn) (m 2 + 2n 2 ) (t ) (2mn) (2m 2 + n 2 ) (t ) (2mn) where Z and k, m, n, t N, k = mn, t = 3, 4, 5,..., m = 1, 2, 3,..., n = 1, 2, 3,... Corollary 4.1. If (a, b, c) s a Pythagorean trple then a 3 + b 3 c 3.

5 NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES 5 Proof. From Theorem 4, f t = 3 then γ = m 2, β = 2n 2 a 3 = m 6 + 6m 5 n + 12m 4 n 2 + 8m 3 n 3 b 3 = 8n n 5 m + 24n 4 m 2 + 8n 3 m 3 c 3 = m 6 + 6m 5 n + 18m 4 n m 3 n m 2 n mn 5 + 8n 6 γ = 2m 2, β = n 2 a 3 = 8m m 5 n + 24m 4 n 2 + 8m 3 n 3 b 3 = n 6 + 6n 5 m + 12n 4 m 2 + 8n 3 m 3 c 3 = 8m m 5 n + 36m 4 n m 3 n m 2 n 4 + 6mn 5 + n 6 Thus we have for γ = m 2, β = 2n 2 a 3 + b 3 = m 6 + 6m 5 n + 12m 4 n m 3 n m 2 n mn 5 + 8n 6 c 3 = m 6 + 6m 5 n + 18m 4 n m 3 n m 2 n mn 5 + 8n 6 and for γ = 2m 2, β = n 2 a 3 + b 3 = 8m m 5 n + 24m 4 n m 3 n m 2 n 4 + 6mn 5 + n 6 c 3 = 8m m 5 n + 36m 4 n m 3 n m 2 n 4 + 6mn 5 + n 6 We see that a 3 + b 3 c 3 n both sets. The 3rd, 4th, and 5th terms dffer. Corollary 4.2. If (a, b, c) s a Pythagorean trple then a 4 + b 4 c 4. Proof. From Theorem 4, f t = 4 then γ = m 2, β = 2n 2 a 4 = m 8 + 8m 7 n + 32m 6 n m 5 n 3 + m 4 n 4 b 4 = 16n n 7 m + 128n 6 m n 5 m n 4 m 4 c 4 = m 8 + 8m 7 n + 32m 6 n m 5 n m 4 n m 3 n m 2 n mn n 8 γ = 2m 2, β = n 2 a 4 = 16m m 7 n + 128m 6 n m 5 n m 4 n 4 b 4 = n 8 + 8n 7 m + 32n 6 m n 5 m n 4 m 4 c 4 = 16m m 7 n + 128m 6 n m 5 n m 4 n m 3 n m 2 n 6 + 8mn 7 + n 8 Thus we have for γ = m 2, β = 2n 2 a 4 + b 4 = m 8 + 8m 7 n + 32m 6 n m 5 n m 4 n m 3 n m 2 n mn n 8 c 4 = m 8 + 8m 7 n + 32m 6 n m 5 n m 4 n m 3 n m 2 n mn n 8 and for γ = 2m 2, β = n 2 a 4 + b 4 = 16 m m 7 n + 128m 6 n m 5 n m 4 n m 3 n m 2 n 6 + 8mn 7 + n 8 c 4 = 16m m 7 n + 128m 6 n m 5 n m 4 n m 3 n m 2 n 6 + 8mn 7 + n 8 We also see that a 4 + b 4 c 4 n both sets. The 4th, 5th, and 6th terms dffer.

6 6 EDUARDO CALOOY ROQUE 5. Concluson We have found general formulas for Pythagorean trples and shown that they are vald. A glance between them and the formulas studed by the Greeks shows that the latter s a specal case. It s also evdent from these formulas that Pythagorean trples are nfnte and grouped nto two nfnte sets. As an extra, we found an applcaton for the formulas. It was shown that they could be used to prove that a t + b t c t for t 3 f (a, b, c) s a Pythagorean trple. Proofs for cases, t = 3, 4 were shown ndcatng that hgher values for t s also vald. The reason s that the terms around the mddle of the bnomal expansons wll always dffer for all t. A C++ scrpt that can be run n Clng and ROOT C/C++ nterpreters s attached here nstead of typesettng t verbatm.it s just a smple nteractve command lne nterface program. I also attached tables for γ = 1, 2, 2(2) 2, 3 2, 77 2, 2(77 2 ) wth n up to here: Wth hope that ths humble work be of beneft to fellowmen, we conclude wth these words: Proverbs 3:13 Happy s the man that fnds wsdom, and the man that gets understandng. Proverbs 9:10 The fear of the Lord s the begnnng of knowledge: and the knowledge of the Holy One s understandng.

7 NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES 7 6. Screenshots of C++ scrpt Fgure 1. S et 1 : γ = m 2, β = 2n 2

8 8 EDUARDO CALOOY ROQUE Fgure 2. S et 2 : γ = 2m 2, β = n 2

9 NEW GENERAL FORMULAS FOR PYTHAGOREAN TRIPLES 9 References [1] James Tattersall: Elementary Number Theory n Nne Chapters, (1999) [2] G. H. Hardy, E.M. Wrght: An Introducton to the Theory of Numbers, 4th ed., (1960) [3] M. Rchardson: College Algebra, 3rd ed., (1966) [4] Bjarne Stroustrup: C++ Programmng Language, 3rd ed. (1997) [5] Rene Brun, Fons Rademakers: ROOT User s Gude, (2007) [6] Vassl Vasslev: Clng The LLVM-based nterpreter, (2011) Phlppnes E-mal address: eddeboyroque@gmal.com

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

(2mn, m 2 n 2, m 2 + n 2 )

(2mn, m 2 n 2, m 2 + n 2 ) MATH 16T Homewk Solutons 1. Recall that a natural number n N s a perfect square f n = m f some m N. a) Let n = p α even f = 1,,..., k. be the prme factzaton of some n. Prove that n s a perfect square f

More information

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

Spectral Graph Theory and its Applications September 16, Lecture 5

Spectral Graph Theory and its Applications September 16, Lecture 5 Spectral Graph Theory and ts Applcatons September 16, 2004 Lecturer: Danel A. Spelman Lecture 5 5.1 Introducton In ths lecture, we wll prove the followng theorem: Theorem 5.1.1. Let G be a planar graph

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens THE CHINESE REMAINDER THEOREM KEITH CONRAD We should thank the Chnese for ther wonderful remander theorem. Glenn Stevens 1. Introducton The Chnese remander theorem says we can unquely solve any par of

More information

On the set of natural numbers

On the set of natural numbers On the set of natural numbers by Jalton C. Ferrera Copyrght 2001 Jalton da Costa Ferrera Introducton The natural numbers have been understood as fnte numbers, ths wor tres to show that the natural numbers

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

Dummy variables in multiple variable regression model

Dummy variables in multiple variable regression model WESS Econometrcs (Handout ) Dummy varables n multple varable regresson model. Addtve dummy varables In the prevous handout we consdered the followng regresson model: y x 2x2 k xk,, 2,, n and we nterpreted

More information

MA 323 Geometric Modelling Course Notes: Day 13 Bezier Curves & Bernstein Polynomials

MA 323 Geometric Modelling Course Notes: Day 13 Bezier Curves & Bernstein Polynomials MA 323 Geometrc Modellng Course Notes: Day 13 Bezer Curves & Bernsten Polynomals Davd L. Fnn Over the past few days, we have looked at de Casteljau s algorthm for generatng a polynomal curve, and we have

More information

The Second Eigenvalue of Planar Graphs

The Second Eigenvalue of Planar Graphs Spectral Graph Theory Lecture 20 The Second Egenvalue of Planar Graphs Danel A. Spelman November 11, 2015 Dsclamer These notes are not necessarly an accurate representaton of what happened n class. The

More information

Assortment Optimization under MNL

Assortment Optimization under MNL Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.

More information

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP C O L L O Q U I U M M A T H E M A T I C U M VOL. 80 1999 NO. 1 FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP BY FLORIAN K A I N R A T H (GRAZ) Abstract. Let H be a Krull monod wth nfnte class

More information

Spin-rotation coupling of the angularly accelerated rigid body

Spin-rotation coupling of the angularly accelerated rigid body Spn-rotaton couplng of the angularly accelerated rgd body Loua Hassan Elzen Basher Khartoum, Sudan. Postal code:11123 E-mal: louaelzen@gmal.com November 1, 2017 All Rghts Reserved. Abstract Ths paper s

More information

An efficient algorithm for multivariate Maclaurin Newton transformation

An efficient algorithm for multivariate Maclaurin Newton transformation Annales UMCS Informatca AI VIII, 2 2008) 5 14 DOI: 10.2478/v10065-008-0020-6 An effcent algorthm for multvarate Maclaurn Newton transformaton Joanna Kapusta Insttute of Mathematcs and Computer Scence,

More information

The internal structure of natural numbers and one method for the definition of large prime numbers

The internal structure of natural numbers and one method for the definition of large prime numbers The nternal structure of natural numbers and one method for the defnton of large prme numbers Emmanul Manousos APM Insttute for the Advancement of Physcs and Mathematcs 3 Poulou str. 53 Athens Greece Abstract

More information

18.781: Solution to Practice Questions for Final Exam

18.781: Solution to Practice Questions for Final Exam 18.781: Soluton to Practce Questons for Fnal Exam 1. Fnd three solutons n postve ntegers of x 6y = 1 by frst calculatng the contnued fracton expanson of 6. Soluton: We have 1 6=[, ] 6 6+ =[, ] 1 =[,, ]=[,,

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

REGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction

REGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction REGULAR POSITIVE TERNARY QUADRATIC FORMS BYEONG-KWEON OH Abstract. A postve defnte quadratc form f s sad to be regular f t globally represents all ntegers that are represented by the genus of f. In 997

More information

Electrical double layer: revisit based on boundary conditions

Electrical double layer: revisit based on boundary conditions Electrcal double layer: revst based on boundary condtons Jong U. Km Department of Electrcal and Computer Engneerng, Texas A&M Unversty College Staton, TX 77843-318, USA Abstract The electrcal double layer

More information

Chapter 9: Statistical Inference and the Relationship between Two Variables

Chapter 9: Statistical Inference and the Relationship between Two Variables Chapter 9: Statstcal Inference and the Relatonshp between Two Varables Key Words The Regresson Model The Sample Regresson Equaton The Pearson Correlaton Coeffcent Learnng Outcomes After studyng ths chapter,

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

Bézier curves. Michael S. Floater. September 10, These notes provide an introduction to Bézier curves. i=0

Bézier curves. Michael S. Floater. September 10, These notes provide an introduction to Bézier curves. i=0 Bézer curves Mchael S. Floater September 1, 215 These notes provde an ntroducton to Bézer curves. 1 Bernsten polynomals Recall that a real polynomal of a real varable x R, wth degree n, s a functon of

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Module 14: THE INTEGRAL Exploring Calculus

Module 14: THE INTEGRAL Exploring Calculus Module 14: THE INTEGRAL Explorng Calculus Part I Approxmatons and the Defnte Integral It was known n the 1600s before the calculus was developed that the area of an rregularly shaped regon could be approxmated

More information

MULTIPLICATIVE FUNCTIONS: A REWRITE OF ANDREWS CHAPTER 6

MULTIPLICATIVE FUNCTIONS: A REWRITE OF ANDREWS CHAPTER 6 MULTIPLICATIVE FUNCTIONS: A REWRITE OF ANDREWS CHAPTER 6 In these notes we offer a rewrte of Andrews Chapter 6. Our am s to replace some of the messer arguments n Andrews. To acheve ths, we need to change

More information

and problem sheet 2

and problem sheet 2 -8 and 5-5 problem sheet Solutons to the followng seven exercses and optonal bonus problem are to be submtted through gradescope by :0PM on Wednesday th September 08. There are also some practce problems,

More information

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

More information

On quasiperfect numbers

On quasiperfect numbers Notes on Number Theory and Dscrete Mathematcs Prnt ISSN 1310 5132, Onlne ISSN 2367 8275 Vol. 23, 2017, No. 3, 73 78 On quasperfect numbers V. Sva Rama Prasad 1 and C. Suntha 2 1 Nalla Malla Reddy Engneerng

More information

FREQUENCY DISTRIBUTIONS Page 1 of The idea of a frequency distribution for sets of observations will be introduced,

FREQUENCY DISTRIBUTIONS Page 1 of The idea of a frequency distribution for sets of observations will be introduced, FREQUENCY DISTRIBUTIONS Page 1 of 6 I. Introducton 1. The dea of a frequency dstrbuton for sets of observatons wll be ntroduced, together wth some of the mechancs for constructng dstrbutons of data. Then

More information

Chapter 3 Differentiation and Integration

Chapter 3 Differentiation and Integration MEE07 Computer Modelng Technques n Engneerng Chapter Derentaton and Integraton Reerence: An Introducton to Numercal Computatons, nd edton, S. yakowtz and F. zdarovsky, Mawell/Macmllan, 990. Derentaton

More information

Example: (13320, 22140) =? Solution #1: The divisors of are 1, 2, 3, 4, 5, 6, 9, 10, 12, 15, 18, 20, 27, 30, 36, 41,

Example: (13320, 22140) =? Solution #1: The divisors of are 1, 2, 3, 4, 5, 6, 9, 10, 12, 15, 18, 20, 27, 30, 36, 41, The greatest common dvsor of two ntegers a and b (not both zero) s the largest nteger whch s a common factor of both a and b. We denote ths number by gcd(a, b), or smply (a, b) when there s no confuson

More information

MTH 263 Practice Test #1 Spring 1999

MTH 263 Practice Test #1 Spring 1999 Pat Ross MTH 6 Practce Test # Sprng 999 Name. Fnd the area of the regon bounded by the graph r =acos (θ). Observe: Ths s a crcle of radus a, for r =acos (θ) r =a ³ x r r =ax x + y =ax x ax + y =0 x ax

More information

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence Remarks on the Propertes of a Quas-Fbonacc-lke Polynomal Sequence Brce Merwne LIU Brooklyn Ilan Wenschelbaum Wesleyan Unversty Abstract Consder the Quas-Fbonacc-lke Polynomal Sequence gven by F 0 = 1,

More information

The path of ants Dragos Crisan, Andrei Petridean, 11 th grade. Colegiul National "Emil Racovita", Cluj-Napoca

The path of ants Dragos Crisan, Andrei Petridean, 11 th grade. Colegiul National Emil Racovita, Cluj-Napoca Ths artcle s wrtten by students. It may nclude omssons and mperfectons, whch were dentfed and reported as mnutely as possble by our revewers n the edtoral notes. The path of ants 07-08 Students names and

More information

Volume 18 Figure 1. Notation 1. Notation 2. Observation 1. Remark 1. Remark 2. Remark 3. Remark 4. Remark 5. Remark 6. Theorem A [2]. Theorem B [2].

Volume 18 Figure 1. Notation 1. Notation 2. Observation 1. Remark 1. Remark 2. Remark 3. Remark 4. Remark 5. Remark 6. Theorem A [2]. Theorem B [2]. Bulletn of Mathematcal Scences and Applcatons Submtted: 016-04-07 ISSN: 78-9634, Vol. 18, pp 1-10 Revsed: 016-09-08 do:10.1805/www.scpress.com/bmsa.18.1 Accepted: 016-10-13 017 ScPress Ltd., Swtzerland

More information

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0 Bezer curves Mchael S. Floater August 25, 211 These notes provde an ntroducton to Bezer curves. 1 Bernsten polynomals Recall that a real polynomal of a real varable x R, wth degree n, s a functon of the

More information

Randić Energy and Randić Estrada Index of a Graph

Randić Energy and Randić Estrada Index of a Graph EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 5, No., 202, 88-96 ISSN 307-5543 www.ejpam.com SPECIAL ISSUE FOR THE INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND ALGEBRA 29 JUNE -02JULY 20, ISTANBUL

More information

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2 Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to

More information

Anti-van der Waerden numbers of 3-term arithmetic progressions.

Anti-van der Waerden numbers of 3-term arithmetic progressions. Ant-van der Waerden numbers of 3-term arthmetc progressons. Zhanar Berkkyzy, Alex Schulte, and Mchael Young Aprl 24, 2016 Abstract The ant-van der Waerden number, denoted by aw([n], k), s the smallest

More information

arxiv: v1 [math.co] 12 Sep 2014

arxiv: v1 [math.co] 12 Sep 2014 arxv:1409.3707v1 [math.co] 12 Sep 2014 On the bnomal sums of Horadam sequence Nazmye Ylmaz and Necat Taskara Department of Mathematcs, Scence Faculty, Selcuk Unversty, 42075, Campus, Konya, Turkey March

More information

REDUCTION MODULO p. We will prove the reduction modulo p theorem in the general form as given by exercise 4.12, p. 143, of [1].

REDUCTION MODULO p. We will prove the reduction modulo p theorem in the general form as given by exercise 4.12, p. 143, of [1]. REDUCTION MODULO p. IAN KIMING We wll prove the reducton modulo p theorem n the general form as gven by exercse 4.12, p. 143, of [1]. We consder an ellptc curve E defned over Q and gven by a Weerstraß

More information

Chapter Twelve. Integration. We now turn our attention to the idea of an integral in dimensions higher than one. Consider a real-valued function f : D

Chapter Twelve. Integration. We now turn our attention to the idea of an integral in dimensions higher than one. Consider a real-valued function f : D Chapter Twelve Integraton 12.1 Introducton We now turn our attenton to the dea of an ntegral n dmensons hgher than one. Consder a real-valued functon f : R, where the doman s a nce closed subset of Eucldean

More information

CHAPTER IV RESEARCH FINDING AND ANALYSIS

CHAPTER IV RESEARCH FINDING AND ANALYSIS CHAPTER IV REEARCH FINDING AND ANALYI A. Descrpton of Research Fndngs To fnd out the dfference between the students who were taught by usng Mme Game and the students who were not taught by usng Mme Game

More information

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification E395 - Pattern Recognton Solutons to Introducton to Pattern Recognton, Chapter : Bayesan pattern classfcaton Preface Ths document s a soluton manual for selected exercses from Introducton to Pattern Recognton

More information

Important Instructions to the Examiners:

Important Instructions to the Examiners: Summer 0 Examnaton Subject & Code: asc Maths (70) Model Answer Page No: / Important Instructons to the Examners: ) The Answers should be examned by key words and not as word-to-word as gven n the model

More information

CHAPTER 14 GENERAL PERTURBATION THEORY

CHAPTER 14 GENERAL PERTURBATION THEORY CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves

More information

Beyond Zudilin s Conjectured q-analog of Schmidt s problem

Beyond Zudilin s Conjectured q-analog of Schmidt s problem Beyond Zudln s Conectured q-analog of Schmdt s problem Thotsaporn Ae Thanatpanonda thotsaporn@gmalcom Mathematcs Subect Classfcaton: 11B65 33B99 Abstract Usng the methodology of (rgorous expermental mathematcs

More information

2 More examples with details

2 More examples with details Physcs 129b Lecture 3 Caltech, 01/15/19 2 More examples wth detals 2.3 The permutaton group n = 4 S 4 contans 4! = 24 elements. One s the dentty e. Sx of them are exchange of two objects (, j) ( to j and

More information

Singular Value Decomposition: Theory and Applications

Singular Value Decomposition: Theory and Applications Sngular Value Decomposton: Theory and Applcatons Danel Khashab Sprng 2015 Last Update: March 2, 2015 1 Introducton A = UDV where columns of U and V are orthonormal and matrx D s dagonal wth postve real

More information

2.3 Nilpotent endomorphisms

2.3 Nilpotent endomorphisms s a block dagonal matrx, wth A Mat dm U (C) In fact, we can assume that B = B 1 B k, wth B an ordered bass of U, and that A = [f U ] B, where f U : U U s the restrcton of f to U 40 23 Nlpotent endomorphsms

More information

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1 Problem Set 4 Suggested Solutons Problem (A) The market demand functon s the soluton to the followng utlty-maxmzaton roblem (UMP): The Lagrangean: ( x, x, x ) = + max U x, x, x x x x st.. x + x + x y x,

More information

Introductory Cardinality Theory Alan Kaylor Cline

Introductory Cardinality Theory Alan Kaylor Cline Introductory Cardnalty Theory lan Kaylor Clne lthough by name the theory of set cardnalty may seem to be an offshoot of combnatorcs, the central nterest s actually nfnte sets. Combnatorcs deals wth fnte

More information

Affine transformations and convexity

Affine transformations and convexity Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/

More information

Dirichlet s Theorem In Arithmetic Progressions

Dirichlet s Theorem In Arithmetic Progressions Drchlet s Theorem In Arthmetc Progressons Parsa Kavkan Hang Wang The Unversty of Adelade February 26, 205 Abstract The am of ths paper s to ntroduce and prove Drchlet s theorem n arthmetc progressons,

More information

Bernoulli Numbers and Polynomials

Bernoulli Numbers and Polynomials Bernoull Numbers and Polynomals T. Muthukumar tmk@tk.ac.n 17 Jun 2014 The sum of frst n natural numbers 1, 2, 3,..., n s n n(n + 1 S 1 (n := m = = n2 2 2 + n 2. Ths formula can be derved by notng that

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

Physics 181. Particle Systems

Physics 181. Particle Systems Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system

More information

The Number of Ways to Write n as a Sum of ` Regular Figurate Numbers

The Number of Ways to Write n as a Sum of ` Regular Figurate Numbers Syracuse Unversty SURFACE Syracuse Unversty Honors Program Capstone Projects Syracuse Unversty Honors Program Capstone Projects Sprng 5-1-01 The Number of Ways to Wrte n as a Sum of ` Regular Fgurate Numbers

More information

Note on EM-training of IBM-model 1

Note on EM-training of IBM-model 1 Note on EM-tranng of IBM-model INF58 Language Technologcal Applcatons, Fall The sldes on ths subject (nf58 6.pdf) ncludng the example seem nsuffcent to gve a good grasp of what s gong on. Hence here are

More information

On the number of regions in an m-dimensional space cut by n hyperplanes

On the number of regions in an m-dimensional space cut by n hyperplanes 6 On the nuber of regons n an -densonal space cut by n hyperplanes Chungwu Ho and Seth Zeran Abstract In ths note we provde a unfor approach for the nuber of bounded regons cut by n hyperplanes n general

More information

Learning Theory: Lecture Notes

Learning Theory: Lecture Notes Learnng Theory: Lecture Notes Lecturer: Kamalka Chaudhur Scrbe: Qush Wang October 27, 2012 1 The Agnostc PAC Model Recall that one of the constrants of the PAC model s that the data dstrbuton has to be

More information

Lecture 5 Decoding Binary BCH Codes

Lecture 5 Decoding Binary BCH Codes Lecture 5 Decodng Bnary BCH Codes In ths class, we wll ntroduce dfferent methods for decodng BCH codes 51 Decodng the [15, 7, 5] 2 -BCH Code Consder the [15, 7, 5] 2 -code C we ntroduced n the last lecture

More information

Calculation of time complexity (3%)

Calculation of time complexity (3%) Problem 1. (30%) Calculaton of tme complexty (3%) Gven n ctes, usng exhaust search to see every result takes O(n!). Calculaton of tme needed to solve the problem (2%) 40 ctes:40! dfferent tours 40 add

More information

MAT 578 Functional Analysis

MAT 578 Functional Analysis MAT 578 Functonal Analyss John Qugg Fall 2008 Locally convex spaces revsed September 6, 2008 Ths secton establshes the fundamental propertes of locally convex spaces. Acknowledgment: although I wrote these

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

= 1.23 m/s 2 [W] Required: t. Solution:!t = = 17 m/s [W]! m/s [W] (two extra digits carried) = 2.1 m/s [W]

= 1.23 m/s 2 [W] Required: t. Solution:!t = = 17 m/s [W]! m/s [W] (two extra digits carried) = 2.1 m/s [W] Secton 1.3: Acceleraton Tutoral 1 Practce, page 24 1. Gven: 0 m/s; 15.0 m/s [S]; t 12.5 s Requred: Analyss: a av v t v f v t a v av f v t 15.0 m/s [S] 0 m/s 12.5 s 15.0 m/s [S] 12.5 s 1.20 m/s 2 [S] Statement:

More information

Exercise Solutions to Real Analysis

Exercise Solutions to Real Analysis xercse Solutons to Real Analyss Note: References refer to H. L. Royden, Real Analyss xersze 1. Gven any set A any ɛ > 0, there s an open set O such that A O m O m A + ɛ. Soluton 1. If m A =, then there

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

Edge Isoperimetric Inequalities

Edge Isoperimetric Inequalities November 7, 2005 Ross M. Rchardson Edge Isopermetrc Inequaltes 1 Four Questons Recall that n the last lecture we looked at the problem of sopermetrc nequaltes n the hypercube, Q n. Our noton of boundary

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

Graph Reconstruction by Permutations

Graph Reconstruction by Permutations Graph Reconstructon by Permutatons Perre Ille and Wllam Kocay* Insttut de Mathémathques de Lumny CNRS UMR 6206 163 avenue de Lumny, Case 907 13288 Marselle Cedex 9, France e-mal: lle@ml.unv-mrs.fr Computer

More information

Turing Machines (intro)

Turing Machines (intro) CHAPTER 3 The Church-Turng Thess Contents Turng Machnes defntons, examples, Turng-recognzable and Turng-decdable languages Varants of Turng Machne Multtape Turng machnes, non-determnstc Turng Machnes,

More information

Temperature. Chapter Heat Engine

Temperature. Chapter Heat Engine Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the

More information

Restricted divisor sums

Restricted divisor sums ACTA ARITHMETICA 02 2002) Restrcted dvsor sums by Kevn A Broughan Hamlton) Introducton There s a body of work n the lterature on varous restrcted sums of the number of dvsors of an nteger functon ncludng

More information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

A New Refinement of Jacobi Method for Solution of Linear System Equations AX=b

A New Refinement of Jacobi Method for Solution of Linear System Equations AX=b Int J Contemp Math Scences, Vol 3, 28, no 17, 819-827 A New Refnement of Jacob Method for Soluton of Lnear System Equatons AX=b F Naem Dafchah Department of Mathematcs, Faculty of Scences Unversty of Gulan,

More information

Math1110 (Spring 2009) Prelim 3 - Solutions

Math1110 (Spring 2009) Prelim 3 - Solutions Math 1110 (Sprng 2009) Solutons to Prelm 3 (04/21/2009) 1 Queston 1. (16 ponts) Short answer. Math1110 (Sprng 2009) Prelm 3 - Solutons x a 1 (a) (4 ponts) Please evaluate lm, where a and b are postve numbers.

More information

Chapter 3 Describing Data Using Numerical Measures

Chapter 3 Describing Data Using Numerical Measures Chapter 3 Student Lecture Notes 3-1 Chapter 3 Descrbng Data Usng Numercal Measures Fall 2006 Fundamentals of Busness Statstcs 1 Chapter Goals To establsh the usefulness of summary measures of data. The

More information

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009 College of Computer & Informaton Scence Fall 2009 Northeastern Unversty 20 October 2009 CS7880: Algorthmc Power Tools Scrbe: Jan Wen and Laura Poplawsk Lecture Outlne: Prmal-dual schema Network Desgn:

More information

Unit 5: Quadratic Equations & Functions

Unit 5: Quadratic Equations & Functions Date Perod Unt 5: Quadratc Equatons & Functons DAY TOPIC 1 Modelng Data wth Quadratc Functons Factorng Quadratc Epressons 3 Solvng Quadratc Equatons 4 Comple Numbers Smplfcaton, Addton/Subtracton & Multplcaton

More information

Group Theory Worksheet

Group Theory Worksheet Jonathan Loss Group Theory Worsheet Goals: To ntroduce the student to the bascs of group theory. To provde a hstorcal framewor n whch to learn. To understand the usefulness of Cayley tables. To specfcally

More information

One Dimension Again. Chapter Fourteen

One Dimension Again. Chapter Fourteen hapter Fourteen One Dmenson Agan 4 Scalar Lne Integrals Now we agan consder the dea of the ntegral n one dmenson When we were ntroduced to the ntegral back n elementary school, we consdered only functons

More information

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS Journal of Mathematcal Scences: Advances and Applcatons Volume 25, 2014, Pages 1-12 A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS JIA JI, WEN ZHANG and XIAOFEI QI Department of Mathematcs

More information

A CLASS OF RECURSIVE SETS. Florentin Smarandache University of New Mexico 200 College Road Gallup, NM 87301, USA

A CLASS OF RECURSIVE SETS. Florentin Smarandache University of New Mexico 200 College Road Gallup, NM 87301, USA A CLASS OF RECURSIVE SETS Florentn Smarandache Unversty of New Mexco 200 College Road Gallup, NM 87301, USA E-mal: smarand@unmedu In ths artcle one bulds a class of recursve sets, one establshes propertes

More information

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding.

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding. Physcs 53 Rotatonal Moton 3 Sr, I have found you an argument, but I am not oblged to fnd you an understandng. Samuel Johnson Angular momentum Wth respect to rotatonal moton of a body, moment of nerta plays

More information

Statistical Inference. 2.3 Summary Statistics Measures of Center and Spread. parameters ( population characteristics )

Statistical Inference. 2.3 Summary Statistics Measures of Center and Spread. parameters ( population characteristics ) Ismor Fscher, 8//008 Stat 54 / -8.3 Summary Statstcs Measures of Center and Spread Dstrbuton of dscrete contnuous POPULATION Random Varable, numercal True center =??? True spread =???? parameters ( populaton

More information

International Mathematical Olympiad. Preliminary Selection Contest 2012 Hong Kong. Outline of Solutions

International Mathematical Olympiad. Preliminary Selection Contest 2012 Hong Kong. Outline of Solutions Internatonal Mathematcal Olympad Prelmnary Selecton ontest Hong Kong Outlne of Solutons nswers: 7 4 7 4 6 5 9 6 99 7 6 6 9 5544 49 5 7 4 6765 5 6 6 7 6 944 9 Solutons: Snce n s a two-dgt number, we have

More information

MATH 281A: Homework #6

MATH 281A: Homework #6 MATH 28A: Homework #6 Jongha Ryu Due date: November 8, 206 Problem. (Problem 2..2. Soluton. If X,..., X n Bern(p, then T = X s a complete suffcent statstc. Our target s g(p = p, and the nave guess suggested

More information

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski EPR Paradox and the Physcal Meanng of an Experment n Quantum Mechancs Vesseln C Nonnsk vesselnnonnsk@verzonnet Abstract It s shown that there s one purely determnstc outcome when measurement s made on

More information

2 Finite difference basics

2 Finite difference basics Numersche Methoden 1, WS 11/12 B.J.P. Kaus 2 Fnte dfference bascs Consder the one- The bascs of the fnte dfference method are best understood wth an example. dmensonal transent heat conducton equaton T

More information

10. Canonical Transformations Michael Fowler

10. Canonical Transformations Michael Fowler 10. Canoncal Transformatons Mchael Fowler Pont Transformatons It s clear that Lagrange s equatons are correct for any reasonable choce of parameters labelng the system confguraton. Let s call our frst

More information

Some Consequences. Example of Extended Euclidean Algorithm. The Fundamental Theorem of Arithmetic, II. Characterizing the GCD and LCM

Some Consequences. Example of Extended Euclidean Algorithm. The Fundamental Theorem of Arithmetic, II. Characterizing the GCD and LCM Example of Extended Eucldean Algorthm Recall that gcd(84, 33) = gcd(33, 18) = gcd(18, 15) = gcd(15, 3) = gcd(3, 0) = 3 We work backwards to wrte 3 as a lnear combnaton of 84 and 33: 3 = 18 15 [Now 3 s

More information

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry Workshop: Approxmatng energes and wave functons Quantum aspects of physcal chemstry http://quantum.bu.edu/pltl/6/6.pdf Last updated Thursday, November 7, 25 7:9:5-5: Copyrght 25 Dan Dll (dan@bu.edu) Department

More information

1 Matrix representations of canonical matrices

1 Matrix representations of canonical matrices 1 Matrx representatons of canoncal matrces 2-d rotaton around the orgn: ( ) cos θ sn θ R 0 = sn θ cos θ 3-d rotaton around the x-axs: R x = 1 0 0 0 cos θ sn θ 0 sn θ cos θ 3-d rotaton around the y-axs:

More information

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

COMPLEX NUMBERS AND QUADRATIC EQUATIONS COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not

More information

Randomness and Computation

Randomness and Computation Randomness and Computaton or, Randomzed Algorthms Mary Cryan School of Informatcs Unversty of Ednburgh RC 208/9) Lecture 0 slde Balls n Bns m balls, n bns, and balls thrown unformly at random nto bns usually

More information

RECEIVED. Negative Transverse Impedance

RECEIVED. Negative Transverse Impedance RECEVED SEP 2 3 996 OSTt > LS- 4 O C a f L W. Chou March 2, 989 (Rev. June 2, 9S9) Negatve Transverse mpedance ntroducton n Ref. ( we report an observaton that the horzontal and the vertcal loss factors

More information