COMPOSITION OF BINARY QUADRATIC FORMS: FROM GAUSS TO BHARGAVA. 1. Introduction

Size: px
Start display at page:

Download "COMPOSITION OF BINARY QUADRATIC FORMS: FROM GAUSS TO BHARGAVA. 1. Introduction"

Transcription

1 COMPOSITION OF BINARY QUADRATIC FORMS: FROM GAUSS TO BHARGAVA FRANÇOIS SÉGUIN Abstract. In is 004 article [], Barava introuces a new way to unerstan te composition law o interal binary quaratic orms trou wat e calls cubes o inteers. Te oal o tis article is to introuce te reaer to Barava s cubes an tis new composition law, as well as to relate it to te composition law as it is known classically. Trou a series o exercises, we will see a istorical exposition o te subject, rom Gauss to Barava, an see ow te ierent ormulations o te composition laws are equivalent. 1. Introuction Binary quaratic orms were alreay stuie in te seventeent an eiteent centuries. Oriinally te main questions ormulate in terms o binary quaratic orms were about representation o numbers. Given a binary quaratic orm x, y = ax + bxy + cy, we can ask wic inteers n can be written as n = x 0, y 0 or some x 0, y 0, in wic case is sai to represent n. Given an inteer n, we can also ask wic binary quaratic orms coul represent n. Finally, iven suc a representation, ow many oter representations can we in. It is interestin to note tat tese very questions will eventually come to play a role in subjects suc as Diopantine equations, quaratic reciprocity an even class iel teory. Matematicians like Fermat an Euler trie to classiy all te possible binary quaratic orms, but te biest results came rom Gauss in 1801 in is Disquisitiones Aritmeticae. Gauss spells out te unerlyin structure tat tose binary quaratic orms ave, structure tat will later came to be known as a roup. Wat is now known as Gauss composition law or binary quaratic orms as been moernize usin alebraic number teory trou te works o Diriclet amonst oters. Tis construction plays a critical role in number teory. In particular, it is one o te primary tools to unerstan class roups o quaratic number iels. Recently, Manjul Barava ormulate a bran new way to approac te composition law or binary quaratic orms. In is tesis an ten a series o articles 010 Matematics Subject Classiication. 11E16. Key wors an prases. Binary quaratic orms, Composition laws. 1

2 [], [3], [4], [5], Barava uses a eometrical approac to escribe te composition law, ivin insit into a new possible way to unerstan it. Barava also eneralizes te composition law to oter objects, establisin a corresponence wit structures in ier eree number iels. In tis article, we will explore ow te composition law came to be unerstoo by Gauss, Diriclet an inally Barava, as well as see ow tese ierent ormulations are really equivalent. We will o so trou a series o exercises esine to elp te reaer to ain a eeper unerstanin o te subject.. Preliminaries We eine an interal binary quaratic orm as a omoenous eree polynomial in two variables, i.e. o te orm F x, y = ax + bxy + cy were a, b, c Z. Since any binary quaratic orm is completely etermine by its tree coeicients a, b an c, we sometimes enote te above polynomial by a, b, c. Te iscriminant o a binary quaratic orm a, b, c is eine as Disca, b, c = b 4ac. Also, we say tat a binary quaratic orm is primitive i te tree coeicients are coprime, i.e. ca, b, c = 1 an positive einite i te binary quaratic orm takes only positive values, i.e. ax + bxy + cy > 0 or all x, y 0. Exercise 1. Sow tat te binary quaratic orm a, b, c is positive einite i an only i Disca, b, c < 0 an a, b > 0. From now on, we will use te term binary quaratic orms to mean interal primitive positive einite binary quaratic orms. Recall tat te roup SL Z is eine as { } a b SL Z := : a, b, c, Z, a bc = 1. c We eine te action o SL Z on a binary quaratic orm as ax + bxy + cy α β = aαx + βy + bαx + βyγx + δy + cγx + δy. γ δ Note tat tis is simply a cane o variable. An alternative way o expressin tis action is, or Qx, y a binary quaratic orm an M SL Z, Qx, y M = Qx, y were x x y = M. y

3 Exercise. Sow tat or any matrix M, Disc a, b, c M = etm Disca, b, c. From tis exercise, we can conclue tat te action o SL Z preserves te iscriminant. Exercise 3. Sow tat any binary quaratic orm tat is equivalent to a primitive binary quaratic orm, is primitive. We now ix a certain inteer D an consier all te possible binary quaratic orms o iscriminant D. On tis set, we eine te ollowin equivalence relation. I Q 1 an Q are binary quaratic orms o iscriminant D, ten Q 1 Q Q 1 M = Q or some M SL Z. We call te set o equivalence classes uner tis relation G D, i.e. G D = {a, b, c : a, b, c Z, Disca, b, c = D} /. We enote [a, b, c] te equivalence class containin a, b, c in G D. We say tat a binary quaratic orm a, b, c is reuce i b a c. Exercise 4. Sow tat tere are initely many reuce binary quaratic orms o a ixe iscriminant D. Ten sow tat every binary quaratic orm is equivalent to a unique reuce binary quaratic orm, wit te exception o a, b, a a, b, a an a, a, c a, a, c were te reuce orm is not unique. Conclue tat or any D, G D is inite. 3. Gauss s composition law We recall te ollowin ientity attribute to 7t century Inian matematician Bramaupta see [1]. Exercise 5. Sow tat or any inteers x 1, y 1, x, y, D, x 1 + Dy1 x + Dy = x1 x Dy 1 y + D x 1 y + x y 1. We can summarize tis previous ientity by sayin tat te numbers o te orm x +Dy are close uner multiplication. In 1801, Gauss aske in is Disquisitiones Aritmeticae weter it was possible to eneralize tis to numbers o a more eneral orm, namely ax + bxy + cy. He comes up wit te answer: yes! 3

4 Teorem 3.1 Gauss. Let a 1 x 1+b 1 x 1 y 1 +c 1 y1 an a x +b x y +c y be binary quaratic orms o iscriminant D. Ten, tere exists an explicit transormation cane o variables x 1 x X p 0 p 1 p p 3 x 1 y = Y q 0 q 1 q q 3 y 1 x y 1 y an inteers A, B an C suc tat a1 x 1 + b 1 x 1 y 1 + c 1 y1 a x + b x y + c y = AX + BXY + CY. Moreover, B 4AC = D. From tis, it is easy to conclue te ollowin. Exercise 6. Usin Teorem 3.1, sow tat G D is a inite abelian roup. It is wort notin tat te moern notion o a roup i not exist wen Gauss wrote is Disquisitiones. However, it is clear tat, witout usin our moern terms, tis is really wat e was ater. 4. Diriclet s unite orms We say tat two binary quaratic orms a 1, b 1, c 1 an a, b, c o iscriminant D are unite i c a 1, a, b 1 + b = 1. Exercise 7. Sow tat b 1 + b is always even. Proposition 4.1. I a 1, b 1, c 1 an a, b, c are unite orms, ten tere exist inteers B an C suc tat an a 1, b 1, c 1 a 1, B, a C a, b, c a, B, a 1 C. Exercise 8. I a 1, b 1, c 1 an a, b, c are unite orms, sow usin Proposition 4.1 an Teorem 3.1 tat in te roup G D, [a 1, b 1, c 1 ] [a, b, c ] = [a 1 a, B, C]. Exercise 8 allows us to compute some roup operations in a more eicient way tan wat is iven by Teorem 3.1. Exercise 9. Usin exercise 8, sow tat 4

5 [ ] 1, 0, D GD = [ ] 1, 1, 1 D 4 i D 0 mo 4 i D 1 mo 4 [a, b, c] 1 = [a, b, c] = [c, b, a]. Diriclet went on to use te notion o ieals in quaratic number iels to obtain te moern ormulation o te composition law, relyin on te ollowin teorem. Recall tat te narrow class roup o a number iel K, enote Cl + K, is te set o all te interal ieals o K moulo te principal ieals o positive norm. Teorem 4.. Te roup G D is isomorpic to te narrow class roup o K = Q D. More speciically, tere is an explicit isomorpism tat allows us to compute compositions o binary quaratic orms. To eac binary quaratic orm, we associate an ieal o O K in te ollowin way: a, b, c Φ az + b D Z. Conversly, or every ieal o O K, we associate a binary quaratic orm αx + βyαx + βy NA Ψ αz + βz = A were conjuation is eine by senin D to D. Exercise Sow tat Φ maps equivalent binary quaratic orms in G D to narrowly equivalent ieals in Cl + K. Sow tat Ψ maps narrowly equivalent ieals in Cl + K to equivalent binary quaratic orms in G D. 3 Sow tat Φ an Ψ are inverses o eac oter. Uner tis corresponence above, te composition o binary quaratic orms in G D correspons to te multiplication o ieals in Cl + K. Tereore, iven two binary quaratic orms o iscriminant D, say Q 1 an Q, we can compute Q 1 Q by 1 Finin ΦQ 1 an ΦQ, Finin a -elements basis or te ieal ΦQ 1 ΦQ as a Z-moule, say [α, β] one always exists since O K is a Deekin omain, 3 Computin Ψ[α, β], an inin a reuce representative i necessary. 5

6 Exercise 11. Let a 1, b 1, c 1 an a, b, c be unite orms. aloritm above tat Sow usin te [a 1, b 1, c 1 ] [a, b, c ] = [a 1 a, B, C] were B an C are te inteers rom Proposition Barava s cube Consier te ollowin cube o inteers, tat is a cube wit an inteer at every corner. e a b c Fiure 1. Barava s cube o inteers In Fiure 1, a, b, c,, e,,, are all inteers. We can cut te cube to obtain two squares in tree ways. 1 Front-Back: e a b c We ten eine te ollowin two matrices usin te two squares we et. a b e M 1 := N 1 :=. c We o te same or te next two cuts, rotatin te wole cube so tat a is always te top let entry o te irst matrix. 6

7 Let-Rit: e a b M := a e c N := b. 3 Up-Down: c e a b M 3 := a b e N 3 := c. c Now, we eine an action o te roup Γ = SL Z SL Z SL Z on te space C o all cubes o inteers. r s I γ Γ an is its it actor, 1 i 3, ten its action on a cube t u replaces M i, N i wit rm i + sn i, tm i + un i. In oter wors, eac actor o γ perorms a ace operation on te cube, similar to wat we woul o on a matrix wit row an column operations. Te irst actor perorms a ace operation on te ront an back aces, te secon actor on te let an rit aces, an te last on te up an own aces. Exercise 1. Sow tat te action o eac actor o γ Γ commutes wit eac oter. Given a cube C, we eine tree binary quaratic orms as or 1 i 3. Q C i = etm i x N i y Example 5.1. I we take C to be te cube o Fiure 1, ten Q C ax ey bx y 1 = et, cx y x y wic inee ives a binary quaratic orm. We say tat a cube C is projective i Q C 1, Q C, Q C 3 orms. are primitive binary quaratic Exercise 13. Sow tat or any cube C, Disc Q C 1 = Disc Q C = Disc Q C 3. 7

8 It tereore makes sense to eine DiscC or a cube C as te iscriminant o its associate binary quaratic orms. We now examine te action o Γ on tese newly eine binary quaratic orms. Exercise 14. Sow tat {1} SL Z SL Z acts trivially on Q C 1. Exercise 15. Sow tat γ = M 1 1 Γ acts on Q C 1 in te usual way, tat is Q C γ 1 = Q C 1 M. By symmetry, te above two exercises ol or te it actor o Γ an Q C i, 1 i 3. In particular, note tat we can conclue te ollowin corollary. Corollary 5.1. DiscC is invariant uner te action o Γ. From tere, we can impose a roup structure on te set o primitive binary quaratic orms o iscriminant D by eclarin tat or any triplet Q A 1, Q A, Q A 3 arisin rom a cube A o iscriminant D, Q A 1 + Q A + Q A 3 = 0. In oter wors we mo out tis relation on te ree abelian roup enerate by all binary quaratic orms o iscriminant D. Note tat we obtain te SL Z equivalence o binary quaratic orms or ree rom tis einition. Inee, i γ = M 1 1 Γ, Q A 1 + Q A + Q A 3 = 0 = Q A γ 1 + Q A γ + Q A γ 3 = Q A 1 M + Q A + Q A 3 Q A 1 = Q A 1 M. As it turns out, Barava prove te ollowin teorem Teorem 5. [, Tm 1]. Tere exists a projective cube A o iscriminant D wit Q A 1, Q A, Q A 3 i an only i [ ] [ ] [ ] Q A 1 Q A 1 Q A 1 = 1GD an tat cube is unique up to Γ-equivalence. We can ten sow tat tis composition law arees wit our previously eine composition. Start wit a projective cube C. e a b c 8

9 Since C is projective, we can sow tat ca, b, c,, e,,, = 1. As suc, we can in a Γ-equivalent cube suc tat a = 1. We ten use tis entry to clear entries b, c an e usin ace operations aain. We tereore ave te equivalent cube C Te tree binary quaratic orms associate to C are Te cube law tells us tat Q 1 = x + xy + y Q = x + xy + y Q 3 = x + xy + y [Q 1 ] [Q ] = [Q 3 ] 1. Let us now use Diriclet s unite orm to arrive at te same conclusion. Recall tat rom Exercise 9, Also, rom Exercise 8, we et [Q 3 ] 1 = [,, ]. [Q 1 ] [Q ] = [,, ] [,, ] = [,, ] = [Q 3 ] 1 by lettin a 1 =, a =, B = an C =. Tus, we conclue tat te two composition laws are equivalent. 6. Concluin remarks One o te most remarkable an surprisin aspect o tis new approac to te composition law mit be ow it eneralizes to ier compositions. Altou it was only briely mentione in te rest o tis article, Barava escribes in [] ow e eneralizes te cube law presente ere to retrieve some alebraic structure in ier eree number iels. Te corresponence between binary quaratic orms an te narrow class roup o quaratic iels was alreay well known, but ettin a anle on oter types o alebraic structures or ier eree is very important in alebraic number teory. In particular, see [], [3], [4], [5] or eneralizations. For a more involve introuction to te topic, we reer te reaer to [1]. Article 9

10 [11] also provies a oo introuction o te results arisin rom tis new teory o ier compositions. 7. Acknowlements I woul like to tank Proessor M. Ram Murty an Sii Patak or teir elpul comments an suestions on a previous version o tis article. 8. Appenix - Hints an solutions or exercises Exercise 1. I x, y = ax + bxy + cy o iscriminant D, ten 4ax, y = ax + by Dy. Exercise. Note tat or x, y = ax + bxy + cy o iscriminant D, a b/ x x, y = x y b/ c y an Tereore, x, y M = a b/ Discx, y = 4 b/ c. x an computin te eterminant we are one. y M T a b/ x M b/ c y Exercise 3. Consier te set o inteers tat can be written as Qx, y or a binary quaratic orm Q an x, y Z. Q is non-primitive i an only i tose inteers are all multiple o some N consier x, y = 1, 0, 0, 1 an 1, 1 or te reverse implication. However, since equivalence o binary quaratic orms is iven by a simple invertible cane o variables, any equivalent binary quaratic orms represent te same inteers. Exercise 4. Recall tat two enerators or SL Z are T = an S = Usin T n, we can sow tat a, b, c a, b + an, c 8.1 Note tat c is uniquely etermine rom te irst two entries by te act tat te iscriminant is ixe. Here, c = an + bn + c. Usin S, we ave a, b, c c, b, a

11 Usin 8.1 we can in a representative wit b a, an usin 8. we can insure tat a c. Uniqueness ollows rom te act tat T an S are enerators or SL Z, an any transormation can be expresse in terms o tese two. Exercise 5. Note tat Nx + y D = x + Dy. Tereore, x 1 + Dy1 x + Dy = N x 1 + y 1 D N x + y D = N x 1 x Dy 1 y + x 1 y + x y 1 D by te multiplicativity o te norm, an so = x 1 x Dy 1 y + D x 1 y + x y 1. Exercise 6. We nee to sow tat te composition law eine tis way is well x 1 x 1 eine on G D. Inee, te two canes o variables y 1 = M 1 an y 1 = M x y x y correspon to te cane o variable x 1x x 1 x x 1y y 1x = M x 1 y 1 M y 1 x y 1y y 1 y so te matrix p 0 p 1 p p 3 p 0 p 1 p p 3 q 0 q 1 q q 3 = M 1 M q 0 q 1 q q 3 will yiel te correct cane o variable or te multiplication o Q 1 x 1, y 1 an Q x, y. Exercise 7. D = b 1 4a 1 c 1 = b 4a c an so b 1 b mo 4 an b 1 b mo. Exercise 8. Consier te matrix C 0 a 1 a B in Teorem 3.1. Exercise 9. 1 We consier te case D 0 mo 4. Consier a, b, c o iscriminant D, we want to compute [a, b, c] [ ] 1, 0, D 4. Note tat b is even, say b = n. Usin notation rom te solution o Exercise 3, we can use T n to ave [ ] 1, 0, D 4 = [1, n, c ] = [1, b, c ]. Te last coeicient c is entirely etermine by 11

12 te irst two entries, an ere c = b D 4. Also, by te same reasonin c = b D 4a an so c = ac. So we ave [ [a, b, c] 1, 0, D ] = [a, b, c] [1, b, ac] = [a, b, c] 4 by Exercise 8. Case D 1 mo 4 is similar. We want to compute [a, b, c][c, b, a]. By exercise 8 wit B = b an C = 1, we et [a, b, c][c, b, a] = [ac, b, 1] = [1, b, ac] an applyin T n or a suitable n will retrieve te ientity rom te previous part. Exercise 10. See [8, Teorem 6.0] or te complete proo. Exercise 11. From Proposition 4.1, a 1, b 1, c 1 a 1, B, a C an a, b, c a, B, a 1 C or some B an C. Clearly ca 1, a, B = 1 see Exercise 3. Ten, we compute A = Φ a 1, B, a C Φ a, B, a 1 C B = [a D B D 1 a, a 1, a as a Z-basis o A. replace by B B D, B + D B ] D 4 Also, writin D = B 4a 1 a C, te last enerator can be. Finally, since ca 1, a, B = 1, we can in a linear combination o tem tat equals 1. As suc, we can easily see [ a 1 a, B ] D B [a D B D B ] D 1 a, a 1, a, B an since te reverse inclusion is trivial, we ave [ [a 1, B, a C][a, B, a 1 C] = Ψ a 1 a, B ] D = [a 1 a, B, C]. Exercise 1. Tis can be viewe simply as te analoue o row an column operation on matrices commutin wit eac oter. A moment s relection soul make tis clear. Exercise 13. From example 5.1, we can in a ormula or te iscriminant o as Q C 1 DiscQ C 1 = c +e +b +a ae+c+b bc+ce+be+bc 1

13 Ten, we notice tat we can retrieve M an N rom M 1 an N 1 by permutin te elements a, b, c,, e,,, as ollows: a b c e a c e b or in cycle notation ab c e. Actually, we notice tat we can also retrieve M 3 an N 3 rom M an N usin te same permutation. Finally, note tat te ormula above or te iscriminant is invariant uner tis permutation. Exercise 14. Let γ {1} SL Z SL Z act on te cube C. Suppose G is te secon actor o γ an G 3 te tir. Ten note tat G acts on M 1 an N 1 by column operation. Speciically, M 1 an N 1 become M 1 G an N 1 G respectively. On te oter an, G 3 act on M 1 G an N 1 G by row operations, an tey become G 3 M 1 G an G 3 M 1 G an G 3 N 1 G respectively. Tereore, we ave tat Q C γ 1 = et G 3 M 1 G x G 3 N 1 G y = etg 3 et M 1 x N 1 y etg = Q C 1. r s Exercise 15. Tis time, let γ = 1 1 act on C. Ten, t u Q C γ 1 x, y = et rm 1 + sn 1 x tm 1 + un 1 y = et M 1 rx ty N 1 uy sx = Q C 1 rx ty, uy sx = Q C r t 1. s u Reerences [1] Belabas, Karim. Paramétrisation e structures alébriques et ensité e iscriminants [ après Barava]. Seminaire Bourbaki Vol Astérisque No Exp. No. 935, ix, [] Barava, Manjul. Hier composition laws I: A new view on Gauss composition, an quaratic eneralizations. Annals o Matematics, : [3] Barava, Manjul. Hier composition laws II: On cubic analoues o Gauss composition. Annals o Matematics, : [4] Barava, Manjul. Hier composition laws III: Te parametrization o quartic rins. Annals o Matematics, : [5] Barava, Manjul. Hier composition laws IV: Te parametrization o quintic rins. Annals o Matematics, : [6] Barava, Manjul. Hier Composition Laws, P. D. Tesis, Princeton University, June 001. [7] Bucmann, Joannes; Vollmer, Ulric. Binary Quaratic Forms : An Aloritmic Approac. Berlin: Spriner-Verla, 007. [8] Buell, D.A. Binary Quaratic Forms : Classical Teory an Moern Computations. New York: Spriner-Verla, [9] Diriclet, P.G.L. Zalenteorie, 4t. eition, Viewe Brunswick,

14 [10] Gauss, C.F. Disquisitiones Aritmeticae, 1801 [11] Sankar, Arul; Wan, Xiaoen. Laws o composition an aritmetic statistics: From Gauss to Barava. Te Matematics Stuent, 84 nos , [1] Weil, Anré. Number Teory: An approac trou istory rom Hammurapi to Leenre. Basel: Birkäuser, 001. Department o Matematics, Queen s University, Kinston, Ontario K7L 3N6, Canaa. aress: rancois.seuin@queensu.ca 14

Differentiation Rules c 2002 Donald Kreider and Dwight Lahr

Differentiation Rules c 2002 Donald Kreider and Dwight Lahr Dierentiation Rules c 00 Donal Kreier an Dwigt Lar Te Power Rule is an example o a ierentiation rule. For unctions o te orm x r, were r is a constant real number, we can simply write own te erivative rater

More information

The tangent line and the velocity problems. The derivative at a point and rates of change. , such as the graph shown below:

The tangent line and the velocity problems. The derivative at a point and rates of change. , such as the graph shown below: Capter 3: Derivatives In tis capter we will cover: 3 Te tanent line an te velocity problems Te erivative at a point an rates o cane 3 Te erivative as a unction Dierentiability 3 Derivatives o constant,

More information

1 Lecture 13: The derivative as a function.

1 Lecture 13: The derivative as a function. 1 Lecture 13: Te erivative as a function. 1.1 Outline Definition of te erivative as a function. efinitions of ifferentiability. Power rule, erivative te exponential function Derivative of a sum an a multiple

More information

f(x + h) f(x) f (x) = lim

f(x + h) f(x) f (x) = lim Introuction 4.3 Some Very Basic Differentiation Formulas If a ifferentiable function f is quite simple, ten it is possible to fin f by using te efinition of erivative irectly: f () 0 f( + ) f() However,

More information

INTERSECTION THEORY CLASS 17

INTERSECTION THEORY CLASS 17 INTERSECTION THEORY CLASS 17 RAVI VAKIL CONTENTS 1. Were we are 1 1.1. Reined Gysin omomorpisms i! 2 1.2. Excess intersection ormula 4 2. Local complete intersection morpisms 6 Were we re oin, by popular

More information

Security Constrained Optimal Power Flow

Security Constrained Optimal Power Flow Security Constrained Optimal Power Flow 1. Introduction and notation Fiure 1 below compares te optimal power flow (OPF wit te security-constrained optimal power flow (SCOPF. Fi. 1 Some comments about tese

More information

Chapter Primer on Differentiation

Chapter Primer on Differentiation Capter 0.01 Primer on Differentiation After reaing tis capter, you soul be able to: 1. unerstan te basics of ifferentiation,. relate te slopes of te secant line an tangent line to te erivative of a function,.

More information

INJECTIVE AND PROJECTIVE PROPERTIES OF REPRESENTATIONS OF QUIVERS WITH n EDGES. Sangwon Park

INJECTIVE AND PROJECTIVE PROPERTIES OF REPRESENTATIONS OF QUIVERS WITH n EDGES. Sangwon Park Korean J. Mat. 16 (2008), No. 3, pp. 323 334 INJECTIVE AND PROJECTIVE PROPERTIES OF REPRESENTATIONS OF QUIVERS WITH n EDGES Sanwon Park Abstract. We define injective and projective representations of quivers

More information

Taylor Series and the Mean Value Theorem of Derivatives

Taylor Series and the Mean Value Theorem of Derivatives 1 - Taylor Series and te Mean Value Teorem o Derivatives Te numerical solution o engineering and scientiic problems described by matematical models oten requires solving dierential equations. Dierential

More information

4. The slope of the line 2x 7y = 8 is (a) 2/7 (b) 7/2 (c) 2 (d) 2/7 (e) None of these.

4. The slope of the line 2x 7y = 8 is (a) 2/7 (b) 7/2 (c) 2 (d) 2/7 (e) None of these. Mat 11. Test Form N Fall 016 Name. Instructions. Te first eleven problems are wort points eac. Te last six problems are wort 5 points eac. For te last six problems, you must use relevant metods of algebra

More information

General Solution of the Stress Potential Function in Lekhnitskii s Elastic Theory for Anisotropic and Piezoelectric Materials

General Solution of the Stress Potential Function in Lekhnitskii s Elastic Theory for Anisotropic and Piezoelectric Materials dv. Studies Teor. Pys. Vol. 007 no. 8 7 - General Solution o te Stress Potential Function in Lenitsii s Elastic Teory or nisotropic and Pieoelectric Materials Zuo-en Ou StateKey Laboratory o Explosion

More information

Solving Continuous Linear Least-Squares Problems by Iterated Projection

Solving Continuous Linear Least-Squares Problems by Iterated Projection Solving Continuous Linear Least-Squares Problems by Iterated Projection by Ral Juengling Department o Computer Science, Portland State University PO Box 75 Portland, OR 977 USA Email: juenglin@cs.pdx.edu

More information

Chapter 1D - Rational Expressions

Chapter 1D - Rational Expressions - Capter 1D Capter 1D - Rational Expressions Definition of a Rational Expression A rational expression is te quotient of two polynomials. (Recall: A function px is a polynomial in x of degree n, if tere

More information

160 Chapter 3: Differentiation

160 Chapter 3: Differentiation 3. Differentiation Rules 159 3. Differentiation Rules Tis section introuces a few rules tat allow us to ifferentiate a great variety of functions. By proving tese rules ere, we can ifferentiate functions

More information

Differential Calculus: Differentiation (First Principles, Rules) and Sketching Graphs (Grade 12) *

Differential Calculus: Differentiation (First Principles, Rules) and Sketching Graphs (Grade 12) * OpenStax-CNX moule: m39313 1 Differential Calculus: Differentiation (First Principles, Rules) an Sketcing Graps (Grae 12) * Free Hig Scool Science Texts Project Tis work is prouce by OpenStax-CNX an license

More information

MA455 Manifolds Solutions 1 May 2008

MA455 Manifolds Solutions 1 May 2008 MA455 Manifolds Solutions 1 May 2008 1. (i) Given real numbers a < b, find a diffeomorpism (a, b) R. Solution: For example first map (a, b) to (0, π/2) and ten map (0, π/2) diffeomorpically to R using

More information

Rules of Differentiation

Rules of Differentiation LECTURE 2 Rules of Differentiation At te en of Capter 2, we finally arrive at te following efinition of te erivative of a function f f x + f x x := x 0 oing so only after an extene iscussion as wat te

More information

ASSOCIATIVITY DATA IN AN (, 1)-CATEGORY

ASSOCIATIVITY DATA IN AN (, 1)-CATEGORY ASSOCIATIVITY DATA IN AN (, 1)-CATEGORY EMILY RIEHL A popular sloan is tat (, 1)-cateories (also called quasi-cateories or - cateories) sit somewere between cateories and spaces, combinin some o te eatures

More information

0.1 Differentiation Rules

0.1 Differentiation Rules 0.1 Differentiation Rules From our previous work we ve seen tat it can be quite a task to calculate te erivative of an arbitrary function. Just working wit a secon-orer polynomial tings get pretty complicate

More information

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point MA00 Capter 6 Calculus and Basic Linear Algebra I Limits, Continuity and Differentiability Te concept of its (p.7 p.9, p.4 p.49, p.55 p.56). Limits Consider te function determined by te formula f Note

More information

PROJECTIVE REPRESENTATIONS OF QUIVERS

PROJECTIVE REPRESENTATIONS OF QUIVERS IJMMS 31:2 22 97 11 II. S1611712218192 ttp://ijmms.indawi.com Hindawi ublisin Corp. ROJECTIVE RERESENTATIONS OF QUIVERS SANGWON ARK Received 3 Auust 21 We prove tat 2 is a projective representation o a

More information

Symmetry Labeling of Molecular Energies

Symmetry Labeling of Molecular Energies Capter 7. Symmetry Labeling of Molecular Energies Notes: Most of te material presented in tis capter is taken from Bunker and Jensen 1998, Cap. 6, and Bunker and Jensen 2005, Cap. 7. 7.1 Hamiltonian Symmetry

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition an Cain Rules James K. Peterson Department of Biological Sciences an Department of Matematical Sciences Clemson University November 2, 2018 Outline Function Composition an Continuity

More information

HOMEWORK HELP 2 FOR MATH 151

HOMEWORK HELP 2 FOR MATH 151 HOMEWORK HELP 2 FOR MATH 151 Here we go; te second round of omework elp. If tere are oters you would like to see, let me know! 2.4, 43 and 44 At wat points are te functions f(x) and g(x) = xf(x)continuous,

More information

GROWTH ANALYSIS OF ENTIRE FUNCTIONS OF TWO COMPLEX VARIABLES

GROWTH ANALYSIS OF ENTIRE FUNCTIONS OF TWO COMPLEX VARIABLES Sa Communications in Matematical Analysis (SCMA Vol. 3 No. 2 (2016 13-24 ttp://scma.marae.ac.ir GROWTH ANALYSIS OF ENTIRE FUNCTIONS OF TWO COMPLEX VARIABLES SANJIB KUMAR DATTA 1 AND TANMAY BISWAS 2 Abstract.

More information

Derivatives of trigonometric functions

Derivatives of trigonometric functions Derivatives of trigonometric functions 2 October 207 Introuction Toay we will ten iscuss te erivates of te si stanar trigonometric functions. Of tese, te most important are sine an cosine; te erivatives

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function

More information

A SHORT INTRODUCTION TO BANACH LATTICES AND

A SHORT INTRODUCTION TO BANACH LATTICES AND CHAPTER A SHORT INTRODUCTION TO BANACH LATTICES AND POSITIVE OPERATORS In tis capter we give a brief introduction to Banac lattices and positive operators. Most results of tis capter can be found, e.g.,

More information

REVIEW LAB ANSWER KEY

REVIEW LAB ANSWER KEY REVIEW LAB ANSWER KEY. Witout using SN, find te derivative of eac of te following (you do not need to simplify your answers): a. f x 3x 3 5x x 6 f x 3 3x 5 x 0 b. g x 4 x x x notice te trick ere! x x g

More information

THE AXIOMS FOR TRIANGULATED CATEGORIES

THE AXIOMS FOR TRIANGULATED CATEGORIES THE AIOMS FOR TRIANGULATED CATEGORIES J. P. MA Contents 1. Trianulated cateories 1 2. Weak pusouts and weak pullbacks 4 3. How to prove Verdier s axiom 6 Reerences 9 Tis is an edited extract rom my paper

More information

MATH1131/1141 Calculus Test S1 v8a

MATH1131/1141 Calculus Test S1 v8a MATH/ Calculus Test 8 S v8a October, 7 Tese solutions were written by Joann Blanco, typed by Brendan Trin and edited by Mattew Yan and Henderson Ko Please be etical wit tis resource It is for te use of

More information

1.5 Function Arithmetic

1.5 Function Arithmetic 76 Relations and Functions.5 Function Aritmetic In te previous section we used te newly deined unction notation to make sense o epressions suc as ) + 2 and 2) or a iven unction. It would seem natural,

More information

Computer Derivations of Numerical Differentiation Formulae. Int. J. of Math. Education in Sci. and Tech., V 34, No 2 (March-April 2003), pp

Computer Derivations of Numerical Differentiation Formulae. Int. J. of Math. Education in Sci. and Tech., V 34, No 2 (March-April 2003), pp Computer Derivations o Numerical Dierentiation Formulae By Jon H. Matews Department o Matematics Caliornia State University Fullerton USA Int. J. o Mat. Education in Sci. and Tec. V No (Marc-April ) pp.8-87.

More information

Reflection Symmetries of q-bernoulli Polynomials

Reflection Symmetries of q-bernoulli Polynomials Journal of Nonlinear Matematical Pysics Volume 1, Supplement 1 005, 41 4 Birtday Issue Reflection Symmetries of q-bernoulli Polynomials Boris A KUPERSHMIDT Te University of Tennessee Space Institute Tullaoma,

More information

(a 1 m. a n m = < a 1/N n

(a 1 m. a n m = < a 1/N n Notes on a an log a Mat 9 Fall 2004 Here is an approac to te eponential an logaritmic functions wic avois any use of integral calculus We use witout proof te eistence of certain limits an assume tat certain

More information

2.4 Exponential Functions and Derivatives (Sct of text)

2.4 Exponential Functions and Derivatives (Sct of text) 2.4 Exponential Functions an Derivatives (Sct. 2.4 2.6 of text) 2.4. Exponential Functions Definition 2.4.. Let a>0 be a real number ifferent tan. Anexponential function as te form f(x) =a x. Teorem 2.4.2

More information

DIFFERENTIAL POLYNOMIALS GENERATED BY SECOND ORDER LINEAR DIFFERENTIAL EQUATIONS

DIFFERENTIAL POLYNOMIALS GENERATED BY SECOND ORDER LINEAR DIFFERENTIAL EQUATIONS Journal o Applied Analysis Vol. 14, No. 2 2008, pp. 259 271 DIFFERENTIAL POLYNOMIALS GENERATED BY SECOND ORDER LINEAR DIFFERENTIAL EQUATIONS B. BELAÏDI and A. EL FARISSI Received December 5, 2007 and,

More information

Math 242: Principles of Analysis Fall 2016 Homework 7 Part B Solutions

Math 242: Principles of Analysis Fall 2016 Homework 7 Part B Solutions Mat 22: Principles of Analysis Fall 206 Homework 7 Part B Solutions. Sow tat f(x) = x 2 is not uniformly continuous on R. Solution. Te equation is equivalent to f(x) = 0 were f(x) = x 2 sin(x) 3. Since

More information

does NOT exist. WHAT IF THE NUMBER X APPROACHES CANNOT BE PLUGGED INTO F(X)??????

does NOT exist. WHAT IF THE NUMBER X APPROACHES CANNOT BE PLUGGED INTO F(X)?????? MATH 000 Miterm Review.3 Te it of a function f ( ) L Tis means tat in a given function, f(), as APPROACHES c, a constant, it will equal te value L. Tis is c only true if f( ) f( ) L. Tat means if te verticle

More information

The derivative function

The derivative function Roberto s Notes on Differential Calculus Capter : Definition of derivative Section Te derivative function Wat you need to know already: f is at a point on its grap and ow to compute it. Wat te derivative

More information

CMU Fall VLSI CAD

CMU Fall VLSI CAD CMU Fall 00 8-760 VLSI CAD [5 pts] HW 5. Out: Tue Nov 7, Due: Tu. Dec 0, in class. (V). Quadratic Placement [5 pts] Consider tis simple netlist wit fixed pins, wic as placeable objects. All te -point wires

More information

WYSE Academic Challenge 2004 Sectional Mathematics Solution Set

WYSE Academic Challenge 2004 Sectional Mathematics Solution Set WYSE Academic Callenge 00 Sectional Matematics Solution Set. Answer: B. Since te equation can be written in te form x + y, we ave a major 5 semi-axis of lengt 5 and minor semi-axis of lengt. Tis means

More information

Functions of the Complex Variable z

Functions of the Complex Variable z Capter 2 Functions of te Complex Variable z Introduction We wis to examine te notion of a function of z were z is a complex variable. To be sure, a complex variable can be viewed as noting but a pair of

More information

Math 102 TEST CHAPTERS 3 & 4 Solutions & Comments Fall 2006

Math 102 TEST CHAPTERS 3 & 4 Solutions & Comments Fall 2006 Mat 102 TEST CHAPTERS 3 & 4 Solutions & Comments Fall 2006 f(x+) f(x) 10 1. For f(x) = x 2 + 2x 5, find ))))))))) and simplify completely. NOTE: **f(x+) is NOT f(x)+! f(x+) f(x) (x+) 2 + 2(x+) 5 ( x 2

More information

1. Questions (a) through (e) refer to the graph of the function f given below. (A) 0 (B) 1 (C) 2 (D) 4 (E) does not exist

1. Questions (a) through (e) refer to the graph of the function f given below. (A) 0 (B) 1 (C) 2 (D) 4 (E) does not exist Mat 1120 Calculus Test 2. October 18, 2001 Your name Te multiple coice problems count 4 points eac. In te multiple coice section, circle te correct coice (or coices). You must sow your work on te oter

More information

1watt=1W=1kg m 2 /s 3

1watt=1W=1kg m 2 /s 3 Appendix A Matematics Appendix A.1 Units To measure a pysical quantity, you need a standard. Eac pysical quantity as certain units. A unit is just a standard we use to compare, e.g. a ruler. In tis laboratory

More information

ch (for some fixed positive number c) reaching c

ch (for some fixed positive number c) reaching c GSTF Journal of Matematics Statistics and Operations Researc (JMSOR) Vol. No. September 05 DOI 0.60/s4086-05-000-z Nonlinear Piecewise-defined Difference Equations wit Reciprocal and Cubic Terms Ramadan

More information

Differentiation in higher dimensions

Differentiation in higher dimensions Capter 2 Differentiation in iger dimensions 2.1 Te Total Derivative Recall tat if f : R R is a 1-variable function, and a R, we say tat f is differentiable at x = a if and only if te ratio f(a+) f(a) tends

More information

E E B B. over U is a full subcategory of the fiber of C,D over U. Given [B, B ], and h=θ over V, the Cartesian arrow M=f

E E B B. over U is a full subcategory of the fiber of C,D over U. Given [B, B ], and h=θ over V, the Cartesian arrow M=f ppendix : ibrational teory o L euivalence E E onsider ibrations P, P, and te category Fib[,] o all maps E @E 2 =(, ):@ :: P { P 2 () @ o ibrations; Fib[,] is a ull subcategory o [,] ; see [3]. Fib[,] is

More information

Polynomials 3: Powers of x 0 + h

Polynomials 3: Powers of x 0 + h near small binomial Capter 17 Polynomials 3: Powers of + Wile it is easy to compute wit powers of a counting-numerator, it is a lot more difficult to compute wit powers of a decimal-numerator. EXAMPLE

More information

3.4 Worksheet: Proof of the Chain Rule NAME

3.4 Worksheet: Proof of the Chain Rule NAME Mat 1170 3.4 Workseet: Proof of te Cain Rule NAME Te Cain Rule So far we are able to differentiate all types of functions. For example: polynomials, rational, root, and trigonometric functions. We are

More information

Math 31A Discussion Notes Week 4 October 20 and October 22, 2015

Math 31A Discussion Notes Week 4 October 20 and October 22, 2015 Mat 3A Discussion Notes Week 4 October 20 and October 22, 205 To prepare for te first midterm, we ll spend tis week working eamples resembling te various problems you ve seen so far tis term. In tese notes

More information

Combining functions: algebraic methods

Combining functions: algebraic methods Combining functions: algebraic metods Functions can be added, subtracted, multiplied, divided, and raised to a power, just like numbers or algebra expressions. If f(x) = x 2 and g(x) = x + 2, clearly f(x)

More information

Numerical Differentiation

Numerical Differentiation Numerical Differentiation Finite Difference Formulas for te first derivative (Using Taylor Expansion tecnique) (section 8.3.) Suppose tat f() = g() is a function of te variable, and tat as 0 te function

More information

This file is /conf/snippets/setheader.pg you can use it as a model for creating files which introduce each problem set.

This file is /conf/snippets/setheader.pg you can use it as a model for creating files which introduce each problem set. Yanimov Almog WeBWorK assignment number Sections 3. 3.2 is ue : 08/3/207 at 03:2pm CDT. Te (* replace wit url for te course ome page *) for te course contains te syllabus, graing policy an oter information.

More information

UNIT #6 EXPONENTS, EXPONENTS, AND MORE EXPONENTS REVIEW QUESTIONS

UNIT #6 EXPONENTS, EXPONENTS, AND MORE EXPONENTS REVIEW QUESTIONS Answer Key Name: Date: UNIT # EXPONENTS, EXPONENTS, AND MORE EXPONENTS REVIEW QUESTIONS Part I Questions. Te epression 0 can be simpliied to () () 0 0. Wic o te ollowing is equivalent to () () 8 8? 8.

More information

In Leibniz notation, we write this rule as follows. DERIVATIVE OF A CONSTANT FUNCTION. For n 4 we find the derivative of f x x 4 as follows: lim

In Leibniz notation, we write this rule as follows. DERIVATIVE OF A CONSTANT FUNCTION. For n 4 we find the derivative of f x x 4 as follows: lim .1 DERIVATIVES OF POLYNOIALS AND EXPONENTIAL FUNCTIONS c =c slope=0 0 FIGURE 1 Te grap of ƒ=c is te line =c, so fª()=0. In tis section we learn ow to ifferentiate constant functions, power functions, polnomials,

More information

2.1 THE DEFINITION OF DERIVATIVE

2.1 THE DEFINITION OF DERIVATIVE 2.1 Te Derivative Contemporary Calculus 2.1 THE DEFINITION OF DERIVATIVE 1 Te grapical idea of a slope of a tangent line is very useful, but for some uses we need a more algebraic definition of te derivative

More information

Polynomial Interpolation

Polynomial Interpolation Capter 4 Polynomial Interpolation In tis capter, we consider te important problem of approximatinga function fx, wose values at a set of distinct points x, x, x,, x n are known, by a polynomial P x suc

More information

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT LIMITS AND DERIVATIVES Te limit of a function is defined as te value of y tat te curve approaces, as x approaces a particular value. Te limit of f (x) as x approaces a is written as f (x) approaces, as

More information

Energy-preserving affine connections

Energy-preserving affine connections 2 A. D. Lewis Enery-preservin affine connections Anrew D. Lewis 28/07/1997 Abstract A Riemannian affine connection on a Riemannian manifol has the property that is preserves the kinetic enery associate

More information

Lecture Notes Di erentiating Trigonometric Functions page 1

Lecture Notes Di erentiating Trigonometric Functions page 1 Lecture Notes Di erentiating Trigonometric Functions age (sin ) 7 sin () sin 8 cos 3 (tan ) sec tan + 9 tan + 4 (cot ) csc cot 0 cot + 5 sin (sec ) cos sec tan sec jj 6 (csc ) sin csc cot csc jj c Hiegkuti,

More information

Lab 6 Derivatives and Mutant Bacteria

Lab 6 Derivatives and Mutant Bacteria Lab 6 Derivatives and Mutant Bacteria Date: September 27, 20 Assignment Due Date: October 4, 20 Goal: In tis lab you will furter explore te concept of a derivative using R. You will use your knowledge

More information

Efficient algorithms for for clone items detection

Efficient algorithms for for clone items detection Efficient algoritms for for clone items detection Raoul Medina, Caroline Noyer, and Olivier Raynaud Raoul Medina, Caroline Noyer and Olivier Raynaud LIMOS - Université Blaise Pascal, Campus universitaire

More information

Chapter 2 Limits and Continuity. Section 2.1 Rates of Change and Limits (pp ) Section Quick Review 2.1

Chapter 2 Limits and Continuity. Section 2.1 Rates of Change and Limits (pp ) Section Quick Review 2.1 Section. 6. (a) N(t) t (b) days: 6 guppies week: 7 guppies (c) Nt () t t t ln ln t ln ln ln t 8. 968 Tere will be guppies ater ln 8.968 days, or ater nearly 9 days. (d) Because it suggests te number o

More information

Pre-Calculus Review Preemptive Strike

Pre-Calculus Review Preemptive Strike Pre-Calculus Review Preemptive Strike Attaced are some notes and one assignment wit tree parts. Tese are due on te day tat we start te pre-calculus review. I strongly suggest reading troug te notes torougly

More information

ALGEBRA AND TRIGONOMETRY REVIEW by Dr TEBOU, FIU. A. Fundamental identities Throughout this section, a and b denotes arbitrary real numbers.

ALGEBRA AND TRIGONOMETRY REVIEW by Dr TEBOU, FIU. A. Fundamental identities Throughout this section, a and b denotes arbitrary real numbers. ALGEBRA AND TRIGONOMETRY REVIEW by Dr TEBOU, FIU A. Fundamental identities Trougout tis section, a and b denotes arbitrary real numbers. i) Square of a sum: (a+b) =a +ab+b ii) Square of a difference: (a-b)

More information

Continuity. Example 1

Continuity. Example 1 Continuity MATH 1003 Calculus and Linear Algebra (Lecture 13.5) Maoseng Xiong Department of Matematics, HKUST A function f : (a, b) R is continuous at a point c (a, b) if 1. x c f (x) exists, 2. f (c)

More information

Analytic Functions. Differentiable Functions of a Complex Variable

Analytic Functions. Differentiable Functions of a Complex Variable Analytic Functions Differentiable Functions of a Complex Variable In tis capter, we sall generalize te ideas for polynomials power series of a complex variable we developed in te previous capter to general

More information

Continuity and Differentiability of the Trigonometric Functions

Continuity and Differentiability of the Trigonometric Functions [Te basis for te following work will be te definition of te trigonometric functions as ratios of te sides of a triangle inscribed in a circle; in particular, te sine of an angle will be defined to be te

More information

Using the definition of the derivative of a function is quite tedious. f (x + h) f (x)

Using the definition of the derivative of a function is quite tedious. f (x + h) f (x) Derivative Rules Using te efinition of te erivative of a function is quite teious. Let s prove some sortcuts tat we can use. Recall tat te efinition of erivative is: Given any number x for wic te limit

More information

Notes on wavefunctions II: momentum wavefunctions

Notes on wavefunctions II: momentum wavefunctions Notes on wavefunctions II: momentum wavefunctions and uncertainty Te state of a particle at any time is described by a wavefunction ψ(x). Tese wavefunction must cange wit time, since we know tat particles

More information

MATH745 Fall MATH745 Fall

MATH745 Fall MATH745 Fall MATH745 Fall 5 MATH745 Fall 5 INTRODUCTION WELCOME TO MATH 745 TOPICS IN NUMERICAL ANALYSIS Instructor: Dr Bartosz Protas Department of Matematics & Statistics Email: bprotas@mcmasterca Office HH 36, Ext

More information

Preface. Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed.

Preface. Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed. Preface Here are my online notes for my course tat I teac ere at Lamar University. Despite te fact tat tese are my class notes, tey sould be accessible to anyone wanting to learn or needing a refreser

More information

Zachary Scherr Math 503 HW 3 Due Friday, Feb 12

Zachary Scherr Math 503 HW 3 Due Friday, Feb 12 Zachary Scherr Math 503 HW 3 Due Friay, Feb 1 1 Reaing 1. Rea sections 7.5, 7.6, 8.1 of Dummit an Foote Problems 1. DF 7.5. Solution: This problem is trivial knowing how to work with universal properties.

More information

BARYCENTRIC SUBDIVISION AND ISOMORPHISMS OF GROUPOIDS

BARYCENTRIC SUBDIVISION AND ISOMORPHISMS OF GROUPOIDS BARYCENTRIC SUBDIVISION AND ISOMORPHISMS OF GROUPOIDS JASHA SOMMER-SIMPSON Abstract Given roupoids G and H as well as an isomorpism Ψ : Sd G = Sd H between subdivisions, we construct an isomorpism P :

More information

How to Find the Derivative of a Function: Calculus 1

How to Find the Derivative of a Function: Calculus 1 Introduction How to Find te Derivative of a Function: Calculus 1 Calculus is not an easy matematics course Te fact tat you ave enrolled in suc a difficult subject indicates tat you are interested in te

More information

AMS 147 Computational Methods and Applications Lecture 09 Copyright by Hongyun Wang, UCSC. Exact value. Effect of round-off error.

AMS 147 Computational Methods and Applications Lecture 09 Copyright by Hongyun Wang, UCSC. Exact value. Effect of round-off error. Lecture 09 Copyrigt by Hongyun Wang, UCSC Recap: Te total error in numerical differentiation fl( f ( x + fl( f ( x E T ( = f ( x Numerical result from a computer Exact value = e + f x+ Discretization error

More information

Continuity and Differentiability

Continuity and Differentiability Continuity and Dierentiability Tis capter requires a good understanding o its. Te concepts o continuity and dierentiability are more or less obvious etensions o te concept o its. Section - INTRODUCTION

More information

Bob Brown Math 251 Calculus 1 Chapter 3, Section 1 Completed 1 CCBC Dundalk

Bob Brown Math 251 Calculus 1 Chapter 3, Section 1 Completed 1 CCBC Dundalk Bob Brown Mat 251 Calculus 1 Capter 3, Section 1 Completed 1 Te Tangent Line Problem Te idea of a tangent line first arises in geometry in te context of a circle. But before we jump into a discussion of

More information

Conductance from Transmission Probability

Conductance from Transmission Probability Conductance rom Transmission Probability Kelly Ceung Department o Pysics & Astronomy University o Britis Columbia Vancouver, BC. Canada, V6T1Z1 (Dated: November 5, 005). ntroduction For large conductors,

More information

5.1 introduction problem : Given a function f(x), find a polynomial approximation p n (x).

5.1 introduction problem : Given a function f(x), find a polynomial approximation p n (x). capter 5 : polynomial approximation and interpolation 5 introduction problem : Given a function f(x), find a polynomial approximation p n (x) Z b Z application : f(x)dx b p n(x)dx, a a one solution : Te

More information

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems Essential Microeconomics -- 5.2: EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, irst and second welare teorems A general model 2 First welare Teorem 7 Second welare teorem

More information

Notes on Lie Groups, Lie algebras, and the Exponentiation Map Mitchell Faulk

Notes on Lie Groups, Lie algebras, and the Exponentiation Map Mitchell Faulk Notes on Lie Groups, Lie algebras, an the Exponentiation Map Mitchell Faulk 1. Preliminaries. In these notes, we concern ourselves with special objects calle matrix Lie groups an their corresponing Lie

More information

The tangent line and the velocity problems. The derivative at a point and rates of change. , such as the graph shown below:

The tangent line and the velocity problems. The derivative at a point and rates of change. , such as the graph shown below: Cpter 3: Derivtives In tis cpter we will cover: 3 Te tnent line n te velocity problems Te erivtive t point n rtes o cne 3 Te erivtive s unction Dierentibility 3 Derivtives o constnt, power, polynomils

More information

University Mathematics 2

University Mathematics 2 University Matematics 2 1 Differentiability In tis section, we discuss te differentiability of functions. Definition 1.1 Differentiable function). Let f) be a function. We say tat f is differentiable at

More information

A GENERAL CONSTRUCTION OF INTERNAL SHEAVES IN ALGEBRAIC SET THEORY

A GENERAL CONSTRUCTION OF INTERNAL SHEAVES IN ALGEBRAIC SET THEORY A GENERAL CONSTRUCTION OF INTERNAL SHEAVES IN ALGEBRAIC SET THEORY S. AWODEY, N. GAMBINO, P. L. LUMSDAINE, AND M. A. WARREN Abstract. We present a solution to te problem o deining a counterpart in Algebraic

More information

Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014

Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014 Solutions to te Multivariable Calculus and Linear Algebra problems on te Compreensive Examination of January 3, 24 Tere are 9 problems ( points eac, totaling 9 points) on tis portion of te examination.

More information

Finding and Using Derivative The shortcuts

Finding and Using Derivative The shortcuts Calculus 1 Lia Vas Finding and Using Derivative Te sortcuts We ave seen tat te formula f f(x+) f(x) (x) = lim 0 is manageable for relatively simple functions like a linear or quadratic. For more complex

More information

Differential Calculus Definitions, Rules and Theorems

Differential Calculus Definitions, Rules and Theorems Precalculus Review Differential Calculus Definitions, Rules an Teorems Sara Brewer, Alabama Scool of Mat an Science Functions, Domain an Range f: X Y a function f from X to Y assigns to eac x X a unique

More information

MAT 1339-S14 Class 2

MAT 1339-S14 Class 2 MAT 1339-S14 Class 2 July 07, 2014 Contents 1 Rate of Cange 1 1.5 Introduction to Derivatives....................... 1 2 Derivatives 5 2.1 Derivative of Polynomial function.................... 5 2.2 Te

More information

lecture 26: Richardson extrapolation

lecture 26: Richardson extrapolation 43 lecture 26: Ricardson extrapolation 35 Ricardson extrapolation, Romberg integration Trougout numerical analysis, one encounters procedures tat apply some simple approximation (eg, linear interpolation)

More information

Dynamics and Relativity

Dynamics and Relativity Dynamics and Relativity Stepen Siklos Lent term 2011 Hand-outs and examples seets, wic I will give out in lectures, are available from my web site www.damtp.cam.ac.uk/user/stcs/dynamics.tml Lecture notes,

More information

Some Review Problems for First Midterm Mathematics 1300, Calculus 1

Some Review Problems for First Midterm Mathematics 1300, Calculus 1 Some Review Problems for First Midterm Matematics 00, Calculus. Consider te trigonometric function f(t) wose grap is sown below. Write down a possible formula for f(t). Tis function appears to be an odd,

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson JUST THE MATHS UNIT NUMBER 10.2 DIFFERENTIATION 2 (Rates of change) by A.J.Hobson 10.2.1 Introuction 10.2.2 Average rates of change 10.2.3 Instantaneous rates of change 10.2.4 Derivatives 10.2.5 Exercises

More information

Math 1210 Midterm 1 January 31st, 2014

Math 1210 Midterm 1 January 31st, 2014 Mat 110 Midterm 1 January 1st, 01 Tis exam consists of sections, A and B. Section A is conceptual, wereas section B is more computational. Te value of every question is indicated at te beginning of it.

More information

*Agbo, F. I. and # Olowu, O.O. *Department of Production Engineering, University of Benin, Benin City, Nigeria.

*Agbo, F. I. and # Olowu, O.O. *Department of Production Engineering, University of Benin, Benin City, Nigeria. REDUCING REDUCIBLE LINEAR ORDINARY DIFFERENTIAL EQUATIONS WITH FUNCTION COEFFICIENTS TO LINEAR ORDINARY DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS ABSTRACT *Abo, F. I. an # Olowu, O.O. *Department

More information

Lecture XVII. Abstract We introduce the concept of directional derivative of a scalar function and discuss its relation with the gradient operator.

Lecture XVII. Abstract We introduce the concept of directional derivative of a scalar function and discuss its relation with the gradient operator. Lecture XVII Abstract We introduce te concept of directional derivative of a scalar function and discuss its relation wit te gradient operator. Directional derivative and gradient Te directional derivative

More information

Polynomial Functions. Linear Functions. Precalculus: Linear and Quadratic Functions

Polynomial Functions. Linear Functions. Precalculus: Linear and Quadratic Functions Concepts: definition of polynomial functions, linear functions tree representations), transformation of y = x to get y = mx + b, quadratic functions axis of symmetry, vertex, x-intercepts), transformations

More information

INTRODUCTION AND MATHEMATICAL CONCEPTS

INTRODUCTION AND MATHEMATICAL CONCEPTS Capter 1 INTRODUCTION ND MTHEMTICL CONCEPTS PREVIEW Tis capter introduces you to te basic matematical tools for doing pysics. You will study units and converting between units, te trigonometric relationsips

More information