Srednicki Chapter 20

Size: px
Start display at page:

Download "Srednicki Chapter 20"

Transcription

1 Srednicki Chaper QFT Problems & Solions. George Ocober 4, Srednicki.. Verify eqaion.7. Using eqaion.7,., and he fac ha m = in his limi, or ask is o evalae his inegral:! x x x dx dx dx x sx + x + x + x x + x These are all dmmy indices, so le s swap x x in he inegrand:! I is rivial ha: x x x dx dx So we solve his inegral o find:! dx x sx + x + x + x x + x dx x + = x + x [ dx dx x x sx + x + x + x x + x ] [ x + x x + x ] Using properies of he logarihm o simplify his, we find ha:! If we le = x sx, we have:! dx x x = x dx d x = dx s + x x x sx sx +sx Le s noice ha he denominaors in boh logarihms cancel sing properies of he logarihm. Then,! x = x sx dx d + sx x =

2 This firs inegral is easy o evalae:! + s dx sx s sx x = x x = d + sx.. The second inegral needs o be evalaed on Mahemaica and simplified by hand; we find ha: d + sx = sx Polylog sx Now le s go back o x so we can apply he endpoins: d + sx = x sx sx Polylog x sx sx nd applying he endpoins: x = x x = d + sx = x sx sx Polylog x sx sx sx sx + Polylog sx sx Simplifying, and sing he definiion of he polylogarihm in he las erm, we find: x = x d + sx x sx = sx Polylog sx x sx + π sx x = which is: x = x x = d + sx Using his in eqaion..: + s = s sx + s sx Polylog s sx + π! dx Polylog + s s π sx.. Now le s redefine some hings for simpliciy. We ll ake x x, = +, and =. s s We ll also sppress he!/, hogh i will be very imporan o add i in laer. Finally, le s ignore he endpoins of he inegral for now, defining he indefinie inegral o be a fncion insead. Then, fx = dxpolylog x This can be evalaed on Mahemaica: fx = xpolylog + + x x x x + + x x +

3 + x x x x + x x Polylog + Polylog Using eqaion.., or inegral is eqal o: Firs le s evalae f:! [f f π ].. f = Polylog Polylog + Polylog I is easy o see sing properies of logs ha here are no infiniies in he hird-o-las erm, so ses he enire erm o zero: f = Polylog Polylog + Polylog Le s disribe he erms on he second line: f = Polylog Polylog + Polylog Nex, noe ha if we spli he nmeraor from he denominaor on he firs erm of he second line, here is a cancellaion. Hence: f = Polylog Polylog + Polylog Now, noe ha =. This les s simplify many erms: f = Polylog + + +

4 Polylog + Polylog This las erm vanishes: f = Polylog Polylog Using he definiion of he Polylog, we find he vale of his firs erm: f = π Polylog Now le s go back o he definiion of fx o calclae f: fx = xpolylog + + x x x x + + x x + + x x x x + x x Polylog + Polylog The firs erm vanishes as x. The easies way o verify his is o ry a few vales on Mahemaica, or check he graph. I also makes sense concepally, since he polylog is in some sense a heavy-dy logarihm, which will grow mch slower han x shrinks. Le s plg in where possible on he oher erms, leaving he erms ha appear o diverge as x for he momen: f = x + x Polylog + Polylog We know ha Polylog =. We can also combine he wo added logarihms on he firs line. This gives: f = + + x + x + Polylog The hird and firs erms can now be combined, sing he properies of logarihms: f = x x Polylog Seing he las remaining xs o, we have: + f = 4 + Polylog

5 Now we re ready o combine hese: f f = π Polylog Polylog Le s separae he denominaor in he second erm inside he braces: f f = π Polylog Polylog Combining he firs and hird erms: f f = π Polylog Polylog Combining he firs and fifh erms: f f = π Polylog Polylog Combining he firs and forh erms: f f = π Polylog =, so he firs erm becomes: f f = π + Polylog + + Polylog Polylog 5

6 The second erm has wo componens mliplied ogeher: he firs forces he fncion oward, he oher oward. Using L hôpial s rle or anoher means, we see ha his vanishes. Then, f f = π + Polylog Polylog Using his in.., he vale of he inegral is: Polylog / = /s +, so: which implies: s + s + Polylog s + s + + Polylog s s + Polylog s s s s + s + iπ + Polylog + Polylog s Now we need o se an ideniy, which holds when x <. π = iπ x + PolyLog + /x + PolyLog + x + x I can find a saemen of his ideniy anywhere. Mahemaically proving his ideniy orselves wold be very difficl, b fornaely we re no mahemaicians. We re convinced if we js look a a graph of he righ hand side: where he ble is he real par and he prple is he imaginary par. Indeed, he ideniy appears o be re for x <. Using his in or expression, wih x = s/, we obain eqaion.7: df 4 D 4 s, = π + [s/] s +

7 Noe: Srednicki s solion presens an easier way o derive his. Criosly enogh, by comparing his answer wih my answer, we are able o mahemaically prove he ideniy I saed above since or answers are eqivalen if and only if he ideniy is re. I presened his solion insead, becase I hink i is nlikely ha he rick Srednicki sed wold be obvios o a sden wiho frher help. Of corse, I have had o pay dearly for his recide my solion is mch more complicaed han Srednicki s! Noe : gain, I m nsre wha he poin of his problem was. Calcls pracice? I is sefl o pracice Feynman s Formla and he inrodcion o polylogarihms was cerainly ineresing b his seems like a very difficl problem wih very lile prpose. Perhaps some leading hins cold have a leas allowed s o spend mch less ime on his problem. Srednicki.. Compe he Oα correcion o he wo-paricle scaering amplide a hreshold, ha is, for s = 4m and = =, corresponding o zero hree-momenm for boh he incoming and ogoing paricles. ll we have o do is evalae some npleasan inegrals. Le s sar wih V : V = g gα! We can rewrie his as: V = g gα x dx dx [ x + x x x ] x dx dx [ x + x x + x + x ] This inegral is an absole mess, b afer doing a lo of simplificaion, and sing Mahemaica, we find ha: [ V = g gα dx + x + π x an x ] x + x Ping his on Mahemaica, we find: V = g + gα π Nex we ll do V 4m. Noice ha he only difference is an exra erm of 4x x m. Then, V 4m = g gα x dx dx [ x + x x + x + x ] gain, afer inegraing and doing a lo of simplificaion, we re lef wih: [ V 4m = g gα dx + x + + x 4x 8x an an 8x 8x 7

8 Ping his on Mahemaica, we find + 4x 4x + 4x + + x x + x ] V 4m = g + gα 8 π The for-poin verex fncion is given by: V 4 4m,, = g α x x x dx m dx dx 4x x + x + x x x + x + x x x + 4x x x x + x + x x x I is bes o do his on Mahemaica; he resl is: V 4 4m,, = g α m 5π 8 Noe: In an earlier version of his solion, I had a Mahemaica workbook ha replicaed Srednicki s solion hogh he answer did no seem iniive. year laer, I received an from a reader who had yped in exacly he same hing, and goen a differen b more iniive resl o he firs inegral, resling in a slighly differen answer. I ended p reprodcing his resl, hogh I see no reason for he discrepency. Maybe Mahemaica was pdaed, and he bg was fixed? In any case, please see he aached workbook, pdaed, for a derivaion of his answer noe ha i does slighly disagree wih Srednicki s solion. Thanks o gso Medeiros Washingon Universiy in S Lois for bringing his o my aenion. The self-energy a zero is given by: Using Mahemaica: which gives: Π = αm dx x + x + Π = αm = m αm [ π ] [ π ] Simplifying, and expanding he denominaor o firs order in α, we have: = m [ + α π ] 8

9 Finally, he self-energy a 4m is given by: Π 4m = α dx4x 4x + Doing he inegral and simplifying, we find ha: which gives: Expanding o firs order in α: αm π 9 4x 4x + α x x + m 4m = [ m + α ] π 4 [ 4m = + α m 4 ] π Now we re ready o combine hese sing eqaion.: g τ loop = m + g α 8m 4 π 5 + g m + g α 5 π m + g α m 5π 8 Simplifying: τ loop = [ ] g 8m 8 + α489 4 π s a fn fac, we can wrie his as: [ ] τ loop = 8g + α489 4 π 8m 8 8g 8m.59g showing ha hese one-order correcions have an absolely iny impac on he overall scaering amplide. In ligh of his, or decision o neglec all erms higher han Oα seems exremely reasonable. Noe: David Griffihs once wroe a problem prefaced by he commen for masochiss only. Srednicki wold do well o add sch a disclaimer o his problem. 9

10 In[]:= Inegrae 4 x x x x x x x x x x 4 x x x x x x x x, x,, x x O[]= CondiionalExpression x x x x x x x x x x x x x rctan xx xx x x, x x x x x x Im Im Re x x x x x x && x x x x x x x x x x Reals Re x x x x x x Re && x x x x x x x x Reals x Re x x x x x x Re x x x x x In[4]:= O[4]= Inegrae x x x x x x x x x^ x x x x rctan x x Sqrx x Sqrx x, x rctan rctan x x x x x x rctan 8 x 8 x x x x x rctan x x Log x x x x x x 4 x rctan 8 x x x 8 x In[]:= Fx_, x_ : Sqr rctansqr x x rctan x x Sqr Sqr rctan x x Sqr 8 x Sqr 8 x 4 x rctan x x Sqr 8 x Sqr 8 x Sqrx x rctan x x Sqrx x Log x x^ x x x x^

11 Sred.nb In[7]:= Fx, x Fx, rctan O[7]= rctan x x rctan x x rctan x x x rctan x x rctan x 8 x 8 x 4 x rctan 8 x x 8 x x x rctan 8 x 8 x 4 x rctan 8 x Log x x Log x x x x x x 8 x In[8]:= O[8]= In[9]:= O[9]= FllSimplify 8 8 x 5 Π 9 4 x 8 x 9 4 x rcco 8 x x x rctan x 8 4 x rctan x 8 x rctan 4 x 8 x 8 x x rctan Log x Log x x Inegrae 8 Sqr 8 x 5 Π Sqr9 4 x 8 Sqr9 4 x rcco x Sqr Sqr 8 x Sqrx rctan x Sqrx 8 4 x rctan x Sqr 8 x rctan 4 x Sqr 8 x Sqr 8 x Sqr rctan x Sqr Log x^ Log x x, x,, 5 Π 8

4.2 Continuous-Time Systems and Processes Problem Definition Let the state variable representation of a linear system be

4.2 Continuous-Time Systems and Processes Problem Definition Let the state variable representation of a linear system be 4 COVARIANCE ROAGAION 41 Inrodcion Now ha we have compleed or review of linear sysems and random processes, we wan o eamine he performance of linear sysems ecied by random processes he sandard approach

More information

MATH 31B: MIDTERM 2 REVIEW. x 2 e x2 2x dx = 1. ue u du 2. x 2 e x2 e x2] + C 2. dx = x ln(x) 2 2. ln x dx = x ln x x + C. 2, or dx = 2u du.

MATH 31B: MIDTERM 2 REVIEW. x 2 e x2 2x dx = 1. ue u du 2. x 2 e x2 e x2] + C 2. dx = x ln(x) 2 2. ln x dx = x ln x x + C. 2, or dx = 2u du. MATH 3B: MIDTERM REVIEW JOE HUGHES. Inegraion by Pars. Evaluae 3 e. Soluion: Firs make he subsiuion u =. Then =, hence 3 e = e = ue u Now inegrae by pars o ge ue u = ue u e u + C and subsiue he definiion

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

PH2130 Mathematical Methods Lab 3. z x

PH2130 Mathematical Methods Lab 3. z x PH130 Mahemaical Mehods Lab 3 This scrip shold keep yo bsy for he ne wo weeks. Yo shold aim o creae a idy and well-srcred Mahemaica Noebook. Do inclde plenifl annoaions o show ha yo know wha yo are doing,

More information

Derivatives of Inverse Trig Functions

Derivatives of Inverse Trig Functions Derivaives of Inverse Trig Fncions Ne we will look a he erivaives of he inverse rig fncions. The formlas may look complicae, b I hink yo will fin ha hey are no oo har o se. Yo will js have o be carefl

More information

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities: Mah 4 Eam Review Problems Problem. Calculae he 3rd Taylor polynomial for arcsin a =. Soluion. Le f() = arcsin. For his problem, we use he formula f() + f () + f ()! + f () 3! for he 3rd Taylor polynomial

More information

Predator - Prey Model Trajectories and the nonlinear conservation law

Predator - Prey Model Trajectories and the nonlinear conservation law Predaor - Prey Model Trajecories and he nonlinear conservaion law James K. Peerson Deparmen of Biological Sciences and Deparmen of Mahemaical Sciences Clemson Universiy Ocober 28, 213 Ouline Drawing Trajecories

More information

Scalar Conservation Laws

Scalar Conservation Laws MATH-459 Nmerical Mehods for Conservaion Laws by Prof. Jan S. Heshaven Solion se : Scalar Conservaion Laws Eercise. The inegral form of he scalar conservaion law + f ) = is given in Eq. below. ˆ 2, 2 )

More information

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes Some common engineering funcions 2.7 Inroducion This secion provides a caalogue of some common funcions ofen used in Science and Engineering. These include polynomials, raional funcions, he modulus funcion

More information

Sequences Arising From Prudent Self-Avoiding Walks Shanzhen Gao, Heinrich Niederhausen Florida Atlantic University, Boca Raton, Florida 33431

Sequences Arising From Prudent Self-Avoiding Walks Shanzhen Gao, Heinrich Niederhausen Florida Atlantic University, Boca Raton, Florida 33431 Seqences Arising From Prden Self-Avoiding Walks Shanzhen Gao, Heinrich Niederhasen Florida Alanic Universiy, Boca Raon, Florida 33431 Absrac A self-avoiding walk (SAW) is a seqence of moves on a laice

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

SMT 2014 Calculus Test Solutions February 15, 2014 = 3 5 = 15.

SMT 2014 Calculus Test Solutions February 15, 2014 = 3 5 = 15. SMT Calculus Tes Soluions February 5,. Le f() = and le g() =. Compue f ()g (). Answer: 5 Soluion: We noe ha f () = and g () = 6. Then f ()g () =. Plugging in = we ge f ()g () = 6 = 3 5 = 5.. There is a

More information

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k Challenge Problems DIS 03 and 0 March 6, 05 Choose one of he following problems, and work on i in your group. Your goal is o convince me ha your answer is correc. Even if your answer isn compleely correc,

More information

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details!

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details! MAT 257, Handou 6: Ocober 7-2, 20. I. Assignmen. Finish reading Chaper 2 of Spiva, rereading earlier secions as necessary. handou and fill in some missing deails! II. Higher derivaives. Also, read his

More information

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence MATH 433/533, Fourier Analysis Secion 6, Proof of Fourier s Theorem for Poinwise Convergence Firs, some commens abou inegraing periodic funcions. If g is a periodic funcion, g(x + ) g(x) for all real x,

More information

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4. PHY1 Elecriciy Topic 7 (Lecures 1 & 11) Elecric Circuis n his opic, we will cover: 1) Elecromoive Force (EMF) ) Series and parallel resisor combinaions 3) Kirchhoff s rules for circuis 4) Time dependence

More information

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes Half-Range Series 2.5 Inroducion In his Secion we address he following problem: Can we find a Fourier series expansion of a funcion defined over a finie inerval? Of course we recognise ha such a funcion

More information

HYPOTHESIS TESTING. four steps. 1. State the hypothesis and the criterion. 2. Compute the test statistic. 3. Compute the p-value. 4.

HYPOTHESIS TESTING. four steps. 1. State the hypothesis and the criterion. 2. Compute the test statistic. 3. Compute the p-value. 4. Inrodcion o Saisics in Psychology PSY Professor Greg Francis Lecre 24 Hypohesis esing for correlaions Is here a correlaion beween homework and exam grades? for seps. Sae he hypohesis and he crierion 2.

More information

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality Marix Versions of Some Refinemens of he Arihmeic-Geomeric Mean Inequaliy Bao Qi Feng and Andrew Tonge Absrac. We esablish marix versions of refinemens due o Alzer ], Carwrigh and Field 4], and Mercer 5]

More information

DESIGN OF TENSION MEMBERS

DESIGN OF TENSION MEMBERS CHAPTER Srcral Seel Design LRFD Mehod DESIGN OF TENSION MEMBERS Third Ediion A. J. Clark School of Engineering Deparmen of Civil and Environmenal Engineering Par II Srcral Seel Design and Analysis 4 FALL

More information

SOLUTIONS TO ECE 3084

SOLUTIONS TO ECE 3084 SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

!!#$%&#'()!#&'(*%)+,&',-)./0)1-*23) "#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5

More information

Homework sheet Exercises done during the lecture of March 12, 2014

Homework sheet Exercises done during the lecture of March 12, 2014 EXERCISE SESSION 2A FOR THE COURSE GÉOMÉTRIE EUCLIDIENNE, NON EUCLIDIENNE ET PROJECTIVE MATTEO TOMMASINI Homework shee 3-4 - Exercises done during he lecure of March 2, 204 Exercise 2 Is i rue ha he parameerized

More information

Notes for Lecture 17-18

Notes for Lecture 17-18 U.C. Berkeley CS278: Compuaional Complexiy Handou N7-8 Professor Luca Trevisan April 3-8, 2008 Noes for Lecure 7-8 In hese wo lecures we prove he firs half of he PCP Theorem, he Amplificaion Lemma, up

More information

Unit Root Time Series. Univariate random walk

Unit Root Time Series. Univariate random walk Uni Roo ime Series Univariae random walk Consider he regression y y where ~ iid N 0, he leas squares esimae of is: ˆ yy y y yy Now wha if = If y y hen le y 0 =0 so ha y j j If ~ iid N 0, hen y ~ N 0, he

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

KEY. Math 334 Midterm I Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

KEY. Math 334 Midterm I Fall 2008 sections 001 and 003 Instructor: Scott Glasgow 1 KEY Mah 4 Miderm I Fall 8 secions 1 and Insrucor: Sco Glasgow Please do NOT wrie on his eam. No credi will be given for such work. Raher wrie in a blue book, or on our own paper, preferabl engineering

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

Today: Falling. v, a

Today: Falling. v, a Today: Falling. v, a Did you ge my es email? If no, make sure i s no in your junk box, and add sbs0016@mix.wvu.edu o your address book! Also please email me o le me know. I will be emailing ou pracice

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

Matlab and Python programming: how to get started

Matlab and Python programming: how to get started Malab and Pyhon programming: how o ge sared Equipping readers he skills o wrie programs o explore complex sysems and discover ineresing paerns from big daa is one of he main goals of his book. In his chaper,

More information

Chapter 7: Solving Trig Equations

Chapter 7: Solving Trig Equations Haberman MTH Secion I: The Trigonomeric Funcions Chaper 7: Solving Trig Equaions Le s sar by solving a couple of equaions ha involve he sine funcion EXAMPLE a: Solve he equaion sin( ) The inverse funcions

More information

The expectation value of the field operator.

The expectation value of the field operator. The expecaion value of he field operaor. Dan Solomon Universiy of Illinois Chicago, IL dsolom@uic.edu June, 04 Absrac. Much of he mahemaical developmen of quanum field heory has been in suppor of deermining

More information

5.1 - Logarithms and Their Properties

5.1 - Logarithms and Their Properties Chaper 5 Logarihmic Funcions 5.1 - Logarihms and Their Properies Suppose ha a populaion grows according o he formula P 10, where P is he colony size a ime, in hours. When will he populaion be 2500? We

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms 6- Chaper 6. Laplace Tranform 6.4 Shor Impule. Dirac Dela Funcion. Parial Fracion 6.5 Convoluion. Inegral Equaion 6.6 Differeniaion and Inegraion of Tranform 6.7 Syem of ODE 6.4 Shor Impule. Dirac Dela

More information

FITTING EQUATIONS TO DATA

FITTING EQUATIONS TO DATA TANTON S TAKE ON FITTING EQUATIONS TO DATA CURRICULUM TIDBITS FOR THE MATHEMATICS CLASSROOM MAY 013 Sandard algebra courses have sudens fi linear and eponenial funcions o wo daa poins, and quadraic funcions

More information

Echocardiography Project and Finite Fourier Series

Echocardiography Project and Finite Fourier Series Echocardiography Projec and Finie Fourier Series 1 U M An echocardiagram is a plo of how a porion of he hear moves as he funcion of ime over he one or more hearbea cycles If he hearbea repeas iself every

More information

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2.

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2. THE BERNOULLI NUMBERS The Bernoulli numbers are defined here by he exponenial generaing funcion ( e The firs one is easy o compue: (2 and (3 B 0 lim 0 e lim, 0 e ( d B lim 0 d e +e e lim 0 (e 2 lim 0 2(e

More information

Math 333 Problem Set #2 Solution 14 February 2003

Math 333 Problem Set #2 Solution 14 February 2003 Mah 333 Problem Se #2 Soluion 14 February 2003 A1. Solve he iniial value problem dy dx = x2 + e 3x ; 2y 4 y(0) = 1. Soluion: This is separable; we wrie 2y 4 dy = x 2 + e x dx and inegrae o ge The iniial

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Solutions from Chapter 9.1 and 9.2

Solutions from Chapter 9.1 and 9.2 Soluions from Chaper 9 and 92 Secion 9 Problem # This basically boils down o an exercise in he chain rule from calculus We are looking for soluions of he form: u( x) = f( k x c) where k x R 3 and k is

More information

Chapter Q1. We need to understand Classical wave first. 3/28/2004 H133 Spring

Chapter Q1. We need to understand Classical wave first. 3/28/2004 H133 Spring Chaper Q1 Inroducion o Quanum Mechanics End of 19 h Cenury only a few loose ends o wrap up. Led o Relaiviy which you learned abou las quarer Led o Quanum Mechanics (1920 s-30 s and beyond) Behavior of

More information

Robotics I. April 11, The kinematics of a 3R spatial robot is specified by the Denavit-Hartenberg parameters in Tab. 1.

Robotics I. April 11, The kinematics of a 3R spatial robot is specified by the Denavit-Hartenberg parameters in Tab. 1. Roboics I April 11, 017 Exercise 1 he kinemaics of a 3R spaial robo is specified by he Denavi-Harenberg parameers in ab 1 i α i d i a i θ i 1 π/ L 1 0 1 0 0 L 3 0 0 L 3 3 able 1: able of DH parameers of

More information

4 Sequences of measurable functions

4 Sequences of measurable functions 4 Sequences of measurable funcions 1. Le (Ω, A, µ) be a measure space (complee, afer a possible applicaion of he compleion heorem). In his chaper we invesigae relaions beween various (nonequivalen) convergences

More information

HYPOTHESIS TESTING. four steps. 1. State the hypothesis. 2. Set the criterion for rejecting. 3. Compute the test statistics. 4. Interpret the results.

HYPOTHESIS TESTING. four steps. 1. State the hypothesis. 2. Set the criterion for rejecting. 3. Compute the test statistics. 4. Interpret the results. Inrodcion o Saisics in Psychology PSY Professor Greg Francis Lecre 23 Hypohesis esing for correlaions Is here a correlaion beween homework and exam grades? for seps. Sae he hypohesis. 2. Se he crierion

More information

ES.1803 Topic 22 Notes Jeremy Orloff

ES.1803 Topic 22 Notes Jeremy Orloff ES.83 Topic Noes Jeremy Orloff Fourier series inroducion: coninued. Goals. Be able o compue he Fourier coefficiens of even or odd periodic funcion using he simplified formulas.. Be able o wrie and graph

More information

CHAPTER 12 DIRECT CURRENT CIRCUITS

CHAPTER 12 DIRECT CURRENT CIRCUITS CHAPTER 12 DIRECT CURRENT CIUITS DIRECT CURRENT CIUITS 257 12.1 RESISTORS IN SERIES AND IN PARALLEL When wo resisors are conneced ogeher as shown in Figure 12.1 we said ha hey are conneced in series. As

More information

4.1 - Logarithms and Their Properties

4.1 - Logarithms and Their Properties Chaper 4 Logarihmic Funcions 4.1 - Logarihms and Their Properies Wha is a Logarihm? We define he common logarihm funcion, simply he log funcion, wrien log 10 x log x, as follows: If x is a posiive number,

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

Circuit Variables. AP 1.1 Use a product of ratios to convert two-thirds the speed of light from meters per second to miles per second: 1 ft 12 in

Circuit Variables. AP 1.1 Use a product of ratios to convert two-thirds the speed of light from meters per second to miles per second: 1 ft 12 in Circui Variables 1 Assessmen Problems AP 1.1 Use a produc of raios o conver wo-hirds he speed of ligh from meers per second o miles per second: ( ) 2 3 1 8 m 3 1 s 1 cm 1 m 1 in 2.54 cm 1 f 12 in 1 mile

More information

ACE 562 Fall Lecture 5: The Simple Linear Regression Model: Sampling Properties of the Least Squares Estimators. by Professor Scott H.

ACE 562 Fall Lecture 5: The Simple Linear Regression Model: Sampling Properties of the Least Squares Estimators. by Professor Scott H. ACE 56 Fall 005 Lecure 5: he Simple Linear Regression Model: Sampling Properies of he Leas Squares Esimaors by Professor Sco H. Irwin Required Reading: Griffihs, Hill and Judge. "Inference in he Simple

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Sysems Prof. Mark Fowler Noe Se #2 Wha are Coninuous-Time Signals??? Reading Assignmen: Secion. of Kamen and Heck /22 Course Flow Diagram The arrows here show concepual flow beween ideas.

More information

HOMEWORK # 2: MATH 211, SPRING Note: This is the last solution set where I will describe the MATLAB I used to make my pictures.

HOMEWORK # 2: MATH 211, SPRING Note: This is the last solution set where I will describe the MATLAB I used to make my pictures. HOMEWORK # 2: MATH 2, SPRING 25 TJ HITCHMAN Noe: This is he las soluion se where I will describe he MATLAB I used o make my picures.. Exercises from he ex.. Chaper 2.. Problem 6. We are o show ha y() =

More information

k B 2 Radiofrequency pulses and hardware

k B 2 Radiofrequency pulses and hardware 1 Exra MR Problems DC Medical Imaging course April, 214 he problems below are harder, more ime-consuming, and inended for hose wih a more mahemaical background. hey are enirely opional, bu hopefully will

More information

From Complex Fourier Series to Fourier Transforms

From Complex Fourier Series to Fourier Transforms Topic From Complex Fourier Series o Fourier Transforms. Inroducion In he previous lecure you saw ha complex Fourier Series and is coeciens were dened by as f ( = n= C ne in! where C n = T T = T = f (e

More information

ON THE OSCILLATION OF THIRD ORDER FUNCTIONAL DIFFERENTIAL EQUATIONS. Cairo University, Orman, Giza 12221, Egypt

ON THE OSCILLATION OF THIRD ORDER FUNCTIONAL DIFFERENTIAL EQUATIONS. Cairo University, Orman, Giza 12221, Egypt a 1/α s)ds < Indian J. pre appl. Mah., 396): 491-507, December 2008 c Prined in India. ON THE OSCILLATION OF THIRD ORDER FUNCTIONAL DIFFERENTIAL EQUATIONS SAID R. GRACE 1, RAVI P. AGARWAL 2 AND MUSTAFA

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Sysems Prof. Mark Fowler Noe Se # Wha are Coninuous-Time Signals??? /6 Coninuous-Time Signal Coninuous Time (C-T) Signal: A C-T signal is defined on he coninuum of ime values. Tha is:

More information

Math 106: Review for Final Exam, Part II. (x x 0 ) 2 = !

Math 106: Review for Final Exam, Part II. (x x 0 ) 2 = ! Mah 6: Review for Final Exam, Par II. Use a second-degree Taylor polynomial o esimae 8. We choose f(x) x and x 7 because 7 is he perfec cube closes o 8. f(x) x / f(7) f (x) x / f (7) x / 7 / 7 f (x) 9

More information

Instructor: Barry McQuarrie Page 1 of 5

Instructor: Barry McQuarrie Page 1 of 5 Procedure for Solving radical equaions 1. Algebraically isolae one radical by iself on one side of equal sign. 2. Raise each side of he equaion o an appropriae power o remove he radical. 3. Simplify. 4.

More information

Linear Time-invariant systems, Convolution, and Cross-correlation

Linear Time-invariant systems, Convolution, and Cross-correlation Linear Time-invarian sysems, Convoluion, and Cross-correlaion (1) Linear Time-invarian (LTI) sysem A sysem akes in an inpu funcion and reurns an oupu funcion. x() T y() Inpu Sysem Oupu y() = T[x()] An

More information

Starting from a familiar curve

Starting from a familiar curve In[]:= NoebookDirecory Ou[]= C:\Dropbox\Work\myweb\Courses\Mah_pages\Mah_5\ You can evaluae he enire noebook by using he keyboard shorcu Al+v o, or he menu iem Evaluaion Evaluae Noebook. Saring from a

More information

BBP-type formulas, in general bases, for arctangents of real numbers

BBP-type formulas, in general bases, for arctangents of real numbers Noes on Number Theory and Discree Mahemaics Vol. 19, 13, No. 3, 33 54 BBP-ype formulas, in general bases, for arcangens of real numbers Kunle Adegoke 1 and Olawanle Layeni 2 1 Deparmen of Physics, Obafemi

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

A Mathematical model to Solve Reaction Diffusion Equation using Differential Transformation Method

A Mathematical model to Solve Reaction Diffusion Equation using Differential Transformation Method Inernaional Jornal of Mahemaics Trends and Technology- Volme Isse- A Mahemaical model o Solve Reacion Diffsion Eqaion sing Differenial Transformaion Mehod Rahl Bhadaria # A.K. Singh * D.P Singh # #Deparmen

More information

5.2. The Natural Logarithm. Solution

5.2. The Natural Logarithm. Solution 5.2 The Naural Logarihm The number e is an irraional number, similar in naure o π. Is non-erminaing, non-repeaing value is e 2.718 281 828 59. Like π, e also occurs frequenly in naural phenomena. In fac,

More information

Section 5: Chain Rule

Section 5: Chain Rule Chaper The Derivaive Applie Calculus 11 Secion 5: Chain Rule There is one more ype of complicae funcion ha we will wan o know how o iffereniae: composiion. The Chain Rule will le us fin he erivaive of

More information

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow KEY Mah 334 Miderm III Fall 28 secions and 3 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

Laplace transfom: t-translation rule , Haynes Miller and Jeremy Orloff

Laplace transfom: t-translation rule , Haynes Miller and Jeremy Orloff Laplace ransfom: -ranslaion rule 8.03, Haynes Miller and Jeremy Orloff Inroducory example Consider he sysem ẋ + 3x = f(, where f is he inpu and x he response. We know is uni impulse response is 0 for

More information

Chapter 8 The Complete Response of RL and RC Circuits

Chapter 8 The Complete Response of RL and RC Circuits Chaper 8 The Complee Response of RL and RC Circuis Seoul Naional Universiy Deparmen of Elecrical and Compuer Engineering Wha is Firs Order Circuis? Circuis ha conain only one inducor or only one capacior

More information

Section 4.4 Logarithmic Properties

Section 4.4 Logarithmic Properties Secion. Logarihmic Properies 5 Secion. Logarihmic Properies In he previous secion, we derived wo imporan properies of arihms, which allowed us o solve some asic eponenial and arihmic equaions. Properies

More information

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an

More information

Practice Problems: Improper Integrals

Practice Problems: Improper Integrals Pracice Problem: Improper Inegral Wrien by Vicoria Kala vkala@mah.cb.ed December 6, Solion o he pracice problem poed on November 3. For each of he folloing problem: a Eplain hy he inegral are improper.

More information

k 1 k 2 x (1) x 2 = k 1 x 1 = k 2 k 1 +k 2 x (2) x k series x (3) k 2 x 2 = k 1 k 2 = k 1+k 2 = 1 k k 2 k series

k 1 k 2 x (1) x 2 = k 1 x 1 = k 2 k 1 +k 2 x (2) x k series x (3) k 2 x 2 = k 1 k 2 = k 1+k 2 = 1 k k 2 k series Final Review A Puzzle... Consider wo massless springs wih spring consans k 1 and k and he same equilibrium lengh. 1. If hese springs ac on a mass m in parallel, hey would be equivalen o a single spring

More information

Brock University Physics 1P21/1P91 Fall 2013 Dr. D Agostino. Solutions for Tutorial 3: Chapter 2, Motion in One Dimension

Brock University Physics 1P21/1P91 Fall 2013 Dr. D Agostino. Solutions for Tutorial 3: Chapter 2, Motion in One Dimension Brock Uniersiy Physics 1P21/1P91 Fall 2013 Dr. D Agosino Soluions for Tuorial 3: Chaper 2, Moion in One Dimension The goals of his uorial are: undersand posiion-ime graphs, elociy-ime graphs, and heir

More information

Mat 267 Engineering Calculus III Updated on 04/30/ x 4y 4z 8x 16y / 4 0. x y z x y. 4x 4y 4z 24x 16y 8z.

Mat 267 Engineering Calculus III Updated on 04/30/ x 4y 4z 8x 16y / 4 0. x y z x y. 4x 4y 4z 24x 16y 8z. Ma 67 Engineering Calcls III Updaed on 04/0/0 r. Firoz Tes solion:. a) Find he cener and radis of he sphere 4 4 4z 8 6 0 z ( ) ( ) z / 4 The cener is a (, -, 0), and radis b) Find he cener and radis of

More information

Fishing limits and the Logistic Equation. 1

Fishing limits and the Logistic Equation. 1 Fishing limis and he Logisic Equaion. 1 1. The Logisic Equaion. The logisic equaion is an equaion governing populaion growh for populaions in an environmen wih a limied amoun of resources (for insance,

More information

Miscellanea Miscellanea

Miscellanea Miscellanea Miscellanea Miscellanea Miscellanea Miscellanea Miscellanea CENRAL EUROPEAN REVIEW OF ECONOMICS & FINANCE Vol., No. (4) pp. -6 bigniew Śleszński USING BORDERED MARICES FOR DURBIN WASON D SAISIC EVALUAION

More information

Lecture 10: The Poincaré Inequality in Euclidean space

Lecture 10: The Poincaré Inequality in Euclidean space Deparmens of Mahemaics Monana Sae Universiy Fall 215 Prof. Kevin Wildrick n inroducion o non-smooh analysis and geomery Lecure 1: The Poincaré Inequaliy in Euclidean space 1. Wha is he Poincaré inequaliy?

More information

This document was generated at 1:04 PM, 09/10/13 Copyright 2013 Richard T. Woodward. 4. End points and transversality conditions AGEC

This document was generated at 1:04 PM, 09/10/13 Copyright 2013 Richard T. Woodward. 4. End points and transversality conditions AGEC his documen was generaed a 1:4 PM, 9/1/13 Copyrigh 213 Richard. Woodward 4. End poins and ransversaliy condiions AGEC 637-213 F z d Recall from Lecure 3 ha a ypical opimal conrol problem is o maimize (,,

More information

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow KEY Mah 334 Miderm III Winer 008 secion 00 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

Applied Mathematics Letters. Oscillation results for fourth-order nonlinear dynamic equations

Applied Mathematics Letters. Oscillation results for fourth-order nonlinear dynamic equations Applied Mahemaics Leers 5 (0) 058 065 Conens liss available a SciVerse ScienceDirec Applied Mahemaics Leers jornal homepage: www.elsevier.com/locae/aml Oscillaion resls for forh-order nonlinear dynamic

More information

ACE 564 Spring Lecture 7. Extensions of The Multiple Regression Model: Dummy Independent Variables. by Professor Scott H.

ACE 564 Spring Lecture 7. Extensions of The Multiple Regression Model: Dummy Independent Variables. by Professor Scott H. ACE 564 Spring 2006 Lecure 7 Exensions of The Muliple Regression Model: Dumm Independen Variables b Professor Sco H. Irwin Readings: Griffihs, Hill and Judge. "Dumm Variables and Varing Coefficien Models

More information

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles Diebold, Chaper 7 Francis X. Diebold, Elemens of Forecasing, 4h Ediion (Mason, Ohio: Cengage Learning, 006). Chaper 7. Characerizing Cycles Afer compleing his reading you should be able o: Define covariance

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

The Fundamental Theorems of Calculus

The Fundamental Theorems of Calculus FunamenalTheorems.nb 1 The Funamenal Theorems of Calculus You have now been inrouce o he wo main branches of calculus: ifferenial calculus (which we inrouce wih he angen line problem) an inegral calculus

More information

Bernoulli numbers. Francesco Chiatti, Matteo Pintonello. December 5, 2016

Bernoulli numbers. Francesco Chiatti, Matteo Pintonello. December 5, 2016 UNIVERSITÁ DEGLI STUDI DI PADOVA, DIPARTIMENTO DI MATEMATICA TULLIO LEVI-CIVITA Bernoulli numbers Francesco Chiai, Maeo Pinonello December 5, 206 During las lessons we have proved he Las Ferma Theorem

More information

, u denotes uxt (,) and u. mean first partial derivatives of u with respect to x and t, respectively. Equation (1.1) can be simply written as

, u denotes uxt (,) and u. mean first partial derivatives of u with respect to x and t, respectively. Equation (1.1) can be simply written as Proceedings of he rd IMT-GT Regional Conference on Mahemaics Saisics and Applicaions Universii Sains Malaysia ANALYSIS ON () + () () = G( ( ) ()) Jessada Tanhanch School of Mahemaics Insie of Science Sranaree

More information

The Brock-Mirman Stochastic Growth Model

The Brock-Mirman Stochastic Growth Model c December 3, 208, Chrisopher D. Carroll BrockMirman The Brock-Mirman Sochasic Growh Model Brock and Mirman (972) provided he firs opimizing growh model wih unpredicable (sochasic) shocks. The social planner

More information

PROBLEMS FOR MATH 162 If a problem is starred, all subproblems are due. If only subproblems are starred, only those are due. SLOPES OF TANGENT LINES

PROBLEMS FOR MATH 162 If a problem is starred, all subproblems are due. If only subproblems are starred, only those are due. SLOPES OF TANGENT LINES PROBLEMS FOR MATH 6 If a problem is sarred, all subproblems are due. If onl subproblems are sarred, onl hose are due. 00. Shor answer quesions. SLOPES OF TANGENT LINES (a) A ball is hrown ino he air. Is

More information

Limits at Infinity. Limit at negative infinity. Limit at positive infinity. Definition of Limits at Infinity Let L be a real number.

Limits at Infinity. Limit at negative infinity. Limit at positive infinity. Definition of Limits at Infinity Let L be a real number. 0_005.qd //0 : PM Page 98 98 CHAPTER Applicaions of Differeniaion f() as Secion.5 f() = + f() as The i of f as approaches or is. Figure. Limis a Infini Deermine (finie) is a infini. Deermine he horizonal

More information

Lecture Notes 2. The Hilbert Space Approach to Time Series

Lecture Notes 2. The Hilbert Space Approach to Time Series Time Series Seven N. Durlauf Universiy of Wisconsin. Basic ideas Lecure Noes. The Hilber Space Approach o Time Series The Hilber space framework provides a very powerful language for discussing he relaionship

More information

Feynman Diagrams in Quantum Mechanics

Feynman Diagrams in Quantum Mechanics Feynman Diagrams in Quanum Mechanics Timohy G. Abbo Absrac We explain he use of Feynman diagrams o do perurbaion heory in quanum mechanics. Feynman diagrams are a valuable ool for organizing and undersanding

More information

Notes 04 largely plagiarized by %khc

Notes 04 largely plagiarized by %khc Noes 04 largely plagiarized by %khc Convoluion Recap Some ricks: x() () =x() x() (, 0 )=x(, 0 ) R ț x() u() = x( )d x() () =ẋ() This hen ells us ha an inegraor has impulse response h() =u(), and ha a differeniaor

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signals & Sysems Prof. Mark Fowler Noe Se #1 C-T Sysems: Convoluion Represenaion Reading Assignmen: Secion 2.6 of Kamen and Heck 1/11 Course Flow Diagram The arrows here show concepual flow beween

More information

LAB # 2 - Equilibrium (static)

LAB # 2 - Equilibrium (static) AB # - Equilibrium (saic) Inroducion Isaac Newon's conribuion o physics was o recognize ha despie he seeming compleiy of he Unierse, he moion of is pars is guided by surprisingly simple aws. Newon's inspiraion

More information

) were both constant and we brought them from under the integral.

) were both constant and we brought them from under the integral. YIELD-PER-RECRUIT (coninued The yield-per-recrui model applies o a cohor, bu we saw in he Age Disribuions lecure ha he properies of a cohor do no apply in general o a collecion of cohors, which is wha

More information

15. Vector Valued Functions

15. Vector Valued Functions 1. Vecor Valued Funcions Up o his poin, we have presened vecors wih consan componens, for example, 1, and,,4. However, we can allow he componens of a vecor o be funcions of a common variable. For example,

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information