Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling.

Size: px
Start display at page:

Download "Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling."

Transcription

1 Chapter 8 Analytic Functions Stuents nee encouragement. So if a stuent gets an answer right, tell them it was a lucky guess. That way, they evelop a goo, lucky feeling Complex Derivatives -Jack Haney Functions of a Real Variable. The erivative of a function of a real variable is f(x + x) f(x) f(x). x x 0 x If the limit exists then the function is ifferentiable at the point x. Note that x can approach zero from above or below. The limit cannot epen on the irection in which x vanishes. Consier f(x) = x. The function is not ifferentiable at x = 0 since 1 Quote slightly moifie. 0 + x 0 lim x 0 + x = 1 360

2 an 0 + x 0 lim x 0 x = 1. Analyticity. The complex erivative, (or simply erivative if the context is clear), is efine, f(z) z z 0 f(z + z) f(z). z The complex erivative exists if this limit exists. This means that the value of the limit is inepenent of the manner in which z 0. If the complex erivative exists at a point, then we say that the function is complex ifferentiable there. A function of a complex variable is analytic at a point z 0 if the complex erivative exists in a neighborhoo about that point. The function is analytic in an open set if it has a complex erivative at each point in that set. Note that complex ifferentiable has a ifferent meaning than analytic. Analyticity refers to the behavior of a function on an open set. A function can be complex ifferentiable at isolate points, but the function woul not be analytic at those points. Analytic functions are also calle regular or holomorphic. If a function is analytic everywhere in the finite complex plane, it is calle entire. Example Consier z n, n Z +, Is the function ifferentiable? Is it analytic? What is the value of the erivative? We etermine ifferentiability by trying to ifferentiate the function. We use the limit efinition of ifferentiation. We will use Newton s binomial formula to expan (z + z) n. (z + z) n z n z zn z 0 ( z ) z n + nz n 1 z + n(n 1) z n 2 z z n z n 2 z 0 z 0 = nz n 1 ( nz n 1 + z ) n(n 1) z n 2 z + + z n

3 The erivative exists everywhere. The function is analytic in the whole complex plane so it is entire. The value of the erivative is z = nzn 1. Example We will show that f(z) = z is not ifferentiable. Consier its erivative. f(z) z z 0 f(z + z) f(z). z z z z + z z z 0 z z 0 z z First we take z = x an evaluate the limit. Then we take z = ı y. x lim x 0 x = 1 ı y lim y 0 ı y = 1 Since the limit epens on the way that z 0, the function is nowhere ifferentiable. Thus the function is not analytic. Complex Derivatives in Terms of Plane Coorinates. Let z = ζ(ξ, ψ) be a system of coorinates in the complex plane. (For example, we coul have Cartesian coorinates z = ζ(x, y) = x + ıy or polar coorinates z = ζ(r, θ) = r e ıθ ). Let f(z) = φ(ξ, ψ) be a complex-value function. (For example we might have a function in the form φ(x, y) = u(x, y) + ıv(x, y) or φ(r, θ) = R(r, θ) e ıθ(r,θ).) If f(z) = φ(ξ, ψ) is analytic, its complex erivative is 362

4 equal to the erivative in any irection. In particular, it is equal to the erivatives in the coorinate irections. ( ) 1 f z f(z + z) f(z) φ(ξ + ξ, ψ) φ(ξ, ψ) ζ φ ξ 0, ψ=0 z ξ 0 ζ ξ = ξ ξ ξ f z f(z + z) f(z) ξ=0, ψ 0 z φ(ξ, ψ + ψ) φ(ξ, ψ) ψ 0 ζ ψ = ψ ( ζ ψ ) 1 φ ψ Example Consier the Cartesian coorinates z = x + ıy. We write the complex erivative as erivatives in the coorinate irections for f(z) = φ(x, y). ( ) 1 f (x + ıy) z = φ x x = φ x ( ) 1 f (x + ıy) z = φ y y = ı φ y We write this in operator notation. z = x = ı y. Example In Example we showe that z n, n Z +, is an entire function an that z zn = nz n 1. Now we corroborate this by calculating the complex erivative in the Cartesian coorinate irections. z zn = (x + ıy)n x = n(x + ıy) n 1 = nz n 1 z zn = ı (x + ıy)n y = ıın(x + ıy) n 1 = nz n 1 363

5 Complex Derivatives are Not the Same as Partial Derivatives Recall from calculus that f(x, y) = g(s, t) f x = g s s x + g t t x Do not make the mistake of using a similar formula for functions of a complex variable. If f(z) = φ(x, y) then f z φ x x z + φ y y z. This is because the operator means The erivative in any irection in the complex plane. Since f(z) is analytic, z f (z) is the same no matter in which irection we take the erivative. Rules of Differentiation. For an analytic function efine in terms of z we can calculate the complex erivative using all the usual rules of ifferentiation that we know from calculus like the prouct rule, z f(z)g(z) = f (z)g(z) + f(z)g (z), or the chain rule, z f(g(z)) = f (g(z))g (z). This is because the complex erivative erives its properties from properties of limits, just like its real variable counterpart. 364

6 Result The complex erivative is, f(z) z z 0 f(z + z) f(z). z The complex erivative is efine if the limit exists an is inepenent of the manner in which z 0. A function is analytic at a point if the complex erivative exists in a neighborhoo of that point. Let z = ζ(ξ, ψ) efine coorinates in the complex plane. The complex erivative in the coorinate irections is z = ( ) 1 ( ) 1 ζ ζ ξ ξ = ψ ψ. In Cartesian coorinates, this is z = x = ı y. In polar coorinates, this is z = e ıθ r = ı r e ıθ θ Since the complex erivative is efine with the same limit formula as real erivatives, all the rules from the calculus of functions of a real variable may be use to ifferentiate functions of a complex variable. Example We have shown that z n, n Z +, is an entire function. Now we corroborate that z zn = nz n 1 by 365

7 calculating the complex erivative in the polar coorinate irections. z zn = e ıθ r rn e ınθ = e ıθ nr n 1 e ınθ = nr n 1 e ı(n 1)θ = nz n 1 z zn = ı r e ıθ θ rn e ınθ = ı r e ıθ r n ın e ınθ = nr n 1 e ı(n 1)θ = nz n 1 Analytic Functions can be Written in Terms of z. Consier an analytic function expresse in terms of x an y, φ(x, y). We can write φ as a function of z = x + ıy an z = x ıy. ( z + z f (z, z) = φ 2, z z ) ı2 We treat z an z as inepenent variables. We fin the partial erivatives with respect to these variables. z = x z x + y z y = 1 ( 2 x ı ) y z = x z x + y z y = 1 ( 2 x + ı ) y Since φ is analytic, the complex erivatives in the x an y irections are equal. φ x = ı φ y 366

8 The partial erivative of f (z, z) with respect to z is zero. f z = 1 2 ( φ x + ı φ y ) = 0 Thus f (z, z) has no functional epenence on z, it can be written as a function of z alone. If we were consiering an analytic function expresse in polar coorinates φ(r, θ), then we coul write it in Cartesian coorinates with the substitutions: r = x 2 + y 2, θ = arctan(x, y). Thus we coul write φ(r, θ) as a function of z alone. Result Any analytic function φ(x, y) or φ(r, θ) can be written as a function of z alone. 8.2 Cauchy-Riemann Equations If we know that a function is analytic, then we have a convenient way of etermining its complex erivative. We just express the complex erivative in terms of the erivative in a coorinate irection. However, we on t have a nice way of etermining if a function is analytic. The efinition of complex erivative in terms of a limit is cumbersome to work with. In this section we remey this problem. A necessary conition for analyticity. Consier a function f(z) = φ(x, y). If f(z) is analytic, the complex erivative is equal to the erivatives in the coorinate irections. We equate the erivatives in the x an y irections to obtain the Cauchy-Riemann equations in Cartesian coorinates. φ x = ıφ y (8.1) This equation is a necessary conition for the analyticity of f(z). Let φ(x, y) = u(x, y) + ıv(x, y) where u an v are real-value functions. We equate the real an imaginary parts of Equation 8.1 to obtain another form for the Cauchy-Riemann equations in Cartesian coorinates. u x = v y, u y = v x. 367

9 Note that this is a necessary an not a sufficient conition for analyticity of f(z). That is, u an v may satisfy the Cauchy-Riemann equations but f(z) may not be analytic. At this point, Cauchy-Riemann equations give us an easy test for etermining if a function is not analytic. Example In Example we showe that z is not analytic using the efinition of complex ifferentiation. Now we obtain the same result using the Cauchy-Riemann equations. u x = 1, z = x ıy v y = 1 We see that the first Cauchy-Riemann equation is not satisfie; the function is not analytic at any point. A sufficient conition for analyticity. A sufficient conition for f(z) = φ(x, y) to be analytic at a point z 0 = (x 0, y 0 ) is that the partial erivatives of φ(x, y) exist an are continuous in some neighborhoo of z 0 an satisfy the Cauchy-Riemann equations there. If the partial erivatives of φ exist an are continuous then φ(x + x, y + y) = φ(x, y) + xφ x (x, y) + yφ y (x, y) + o( x) + o( y). Here the notation o( x) means terms smaller than x. We calculate the erivative of f(z). f f(z + z) f(z) (z) z 0 z x, y 0 x, y 0 x, y 0 φ(x + x, y + y) φ(x, y) x + ı y φ(x, y) + xφ x (x, y) + yφ y (x, y) + o( x) + o( y) φ(x, y) x + ı y xφ x (x, y) + yφ y (x, y) + o( x) + o( y) x + ı y 368

10 Here we use the Cauchy-Riemann equations. ( x + ı y)φ x (x, y) o( x) + o( y) + lim x, y 0 x + ı y x, y 0 x + ı y = φ x (x, y) Thus we see that the erivative is well efine. Cauchy-Riemann Equations in General Coorinates Let z = ζ(ξ, ψ) be a system of coorinates in the complex plane. Let φ(ξ, ψ) be a function which we write in terms of these coorinates, A necessary conition for analyticity of φ(ξ, ψ) is that the complex erivatives in the coorinate irections exist an are equal. Equating the erivatives in the ξ an ψ irections gives us the Cauchy-Riemann equations. ( ) 1 ( ) 1 ζ φ ζ ξ ξ = φ ψ ψ We coul separate this into two equations by equating the real an imaginary parts or the moulus an argument. 369

11 Result A necessary conition for analyticity of φ(ξ, ψ), where z = ζ(ξ, ψ), at z = z 0 is that the Cauchy-Riemann equations are satisfie in a neighborhoo of z = z 0. ( ) 1 ( ) 1 ζ φ ζ ξ ξ = φ ψ ψ. (We coul equate the real an imaginary parts or the moulus an argument of this to obtain two equations.) A sufficient conition for analyticity of f(z) is that the Cauchy-Riemann equations hol an the first partial erivatives of φ exist an are continuous in a neighborhoo of z = z 0. Below are the Cauchy-Riemann equations for various forms of f(z). f(z) = φ(x, y), φ x = ıφ y f(z) = u(x, y) + ıv(x, y), u x = v y, u y = v x f(z) = φ(r, θ), φ r = ı r φ θ f(z) = u(r, θ) + ıv(r, θ), u r = 1 r v θ, u θ = rv r f(z) = R(r, θ) e ıθ(r,θ), R r = R r Θ θ, 1 r R θ = RΘ r f(z) = R(x, y) e ıθ(x,y), R x = RΘ y, R y = RΘ x Example Consier the Cauchy-Riemann equations for f(z) = u(r, θ) + ıv(r, θ). From Exercise 8.3 we know that the complex erivative in the polar coorinate irections is z = e ıθ r = ı r e ıθ θ. 370

12 From Result we have the equation, e ıθ r [u + ıv] = ı r e ıθ [u + ıv]. θ We multiply by e ıθ an equate the real an imaginary components to obtain the Cauchy-Riemann equations. u r = 1 r v θ, u θ = rv r Example Consier the exponential function. e z = φ(x, y) = e x (cosy + ı sin(y)) We use the Cauchy-Riemann equations to show that the function is entire. φ x = ıφ y e x (cosy + ı sin(y)) = ı e x ( sin y + ı cos(y)) e x (cosy + ı sin(y)) = e x (cosy + ı sin(y)) Since the function satisfies the Cauchy-Riemann equations an the first partial erivatives are continuous everywhere in the finite complex plane, the exponential function is entire. Now we fin the value of the complex erivative. z ez = φ x = ex (cosy + ı sin(y)) = e z The ifferentiability of the exponential function implies the ifferentiability of the trigonometric functions, as they can be written in terms of the exponential. In Exercise 8.13 you can show that the logarithm log z is ifferentiable for z 0. This implies the ifferentiability of z α an the inverse trigonometric functions as they can be written in terms of the logarithm. 371

13 Example We compute the erivative of z z. z (zz ) = log z ez z = (1 + log z) e z log z = (1 + log z)z z = z z + z z log z 8.3 Harmonic Functions A function u is harmonic if its secon partial erivatives exist, are continuous an satisfy Laplace s equation u = 0. 2 (In Cartesian coorinates the Laplacian is u u xx + u yy.) If f(z) = u + ıv is an analytic function then u an v are harmonic functions. To see why this is so, we start with the Cauchy-Riemann equations. u x = v y, u y = v x We ifferentiate the first equation with respect to x an the secon with respect to y. (We assume that u an v are twice continuously ifferentiable. We will see later that they are infinitely ifferentiable.) u xx = v xy, u yy = v yx Thus we see that u is harmonic. One can use the same metho to show that v = 0. u u xx + u yy = v xy v yx = 0 If u is harmonic on some simply-connecte omain, then there exists a harmonic function v such that f(z) = u + ıv is analytic in the omain. v is calle the harmonic conjugate of u. The harmonic conjugate is unique up to an aitive 2 The capital Greek letter is use to enote the Laplacian, like u(x, y), an ifferentials, like x. 372

14 constant. To emonstrate this, let w be another harmonic conjugate of u. Both the pair u an v an the pair u an w satisfy the Cauchy-Riemann equations. We take the ifference of these equations. u x = v y, u y = v x, u x = w y, u y = w x v x w x = 0, v y w y = 0 On a simply connecte omain, the ifference between v an w is thus a constant. To prove the existence of the harmonic conjugate, we first write v as an integral. v(x, y) = v (x 0, y 0 ) + (x,y) (x 0,y 0 ) v x x + v y y On a simply connecte omain, the integral is path inepenent an efines a unique v in terms of v x an v y. We use the Cauchy-Riemann equations to write v in terms of u x an u y. v(x, y) = v (x 0, y 0 ) + (x,y) (x 0,y 0 ) u y x + u x y Changing the starting point (x 0, y 0 ) changes v by an aitive constant. The harmonic conjugate of u to within an aitive constant is v(x, y) = u y x + u x y. This proves the existence 3 of the harmonic conjugate. This is not the formula one woul use to construct the harmonic conjugate of a u. One accomplishes this by solving the Cauchy-Riemann equations. 3 A mathematician returns to his office to fin that a cigarette tosse in the trash has starte a small fire. Being calm an a quick thinker he notes that there is a fire extinguisher by the winow. He then closes the oor an walks away because the solution exists. 373

15 Result If f(z) = u + ıv is an analytic function then u an v are harmonic functions. That is, the Laplacians of u an v vanish u = v = 0. The Laplacian in Cartesian an polar coorinates is = 2 x y 2, = 1 r ( r ) + 1r 2 r r 2 θ 2. Given a harmonic function u in a simply connecte omain, there exists a harmonic function v, (unique up to an aitive constant), such that f(z) = u + ıv is analytic in the omain. One can construct v by solving the Cauchy-Riemann equations. Example Is x 2 the real part of an analytic function? The Laplacian of x 2 is [x 2 ] = x 2 is not harmonic an thus is not the real part of an analytic function. Example Show that u = e x (x sin y y cosy) is harmonic. u x = e x sin y e x (x sin y y cosy) = e x sin y x e x sin y + y e x cosy 2 u x 2 = e x sin y e x sin y + x e x sin y y e x cosy = 2 e x sin y + x e x sin y y e x cosy u y = e x (x cosy cosy + y sin y) 374

16 Thus we see that 2 u x u y 2 = 0 an u is harmonic. 2 u y 2 = e x ( x sin y + siny + y cosy + siny) = x e x sin y + 2 e x sin y + y e x cosy Example Consier u = cos x cosh y. This function is harmonic. u xx + u yy = cosxcosh y + cosxcosh y = 0 Thus it is the real part of an analytic function, f(z). We fin the harmonic conjugate, v, with the Cauchy-Riemann equations. We integrate the first Cauchy-Riemann equation. v y = u x = sin x cosh y v = sin x sinh y + a(x) Here a(x) is a constant of integration. We substitute this into the secon Cauchy-Riemann equation to etermine a(x). Here c is a real constant. Thus the harmonic conjugate is v x = u y cosxsinh y + a (x) = cosxsinh y a (x) = 0 a(x) = c v = sin x sinh y + c. The analytic function is We recognize this as f(z) = cosxcosh y ı sin x sinh y + ıc f(z) = cosz + ıc. 375

17 Example Here we consier an example that emonstrates the nee for a simply connecte omain. Consier u = Log r in the multiply connecte omain, r > 0. u is harmonic. Log r = 1 (r r ) r r Log r + 1r 2 2 θ Log r = 0 2 We solve the Cauchy-Riemann equations to try to fin the harmonic conjugate. u r = 1 r v θ, u θ = rv r v r = 0, v θ = 1 v = θ + c We are able to solve for v, but it is multi-value. Any single-value branch of θ that we choose will not be continuous on the omain. Thus there is no harmonic conjugate of u = Log r for the omain r > 0. If we ha instea consiere the simply-connecte omain r > 0, arg(z) < π then the harmonic conjugate woul be v = Arg(z) + c. The corresponing analytic function is f(z) = Log z + ıc. Example Consier u = x 3 3xy 2 + x. This function is harmonic. u xx + u yy = 6x 6x = 0 Thus it is the real part of an analytic function, f(z). We fin the harmonic conjugate, v, with the Cauchy-Riemann equations. We integrate the first Cauchy-Riemann equation. v y = u x = 3x 2 3y v = 3x 2 y y 3 + y + a(x) Here a(x) is a constant of integration. We substitute this into the secon Cauchy-Riemann equation to etermine a(x). v x = u y 6xy + a (x) = 6xy a (x) = 0 a(x) = c 376

18 Here c is a real constant. The harmonic conjugate is v = 3x 2 y y 3 + y + c. The analytic function is f(z) = x 3 3xy 2 + x + ı ( 3x 2 y y 3 + y ) + ıc f(z) = x 3 + ı3x 2 y 3xy 2 ıy 2 + x + ıy + ıc f(z) = z 3 + z + ıc 8.4 Singularities Any point at which a function is not analytic is calle a singularity. In this section we will classify the ifferent flavors of singularities. Result Singularities. If a function is not analytic at a point, then that point is a singular point or a singularity of the function Categorization of Singularities Branch Points. If f(z) has a branch point at z 0, then we cannot efine a branch of f(z) that is continuous in a neighborhoo of z 0. Continuity is necessary for analyticity. Thus all branch points are singularities. Since function are iscontinuous across branch cuts, all points on a branch cut are singularities. Example Consier f(z) = z 3/2. The origin an infinity are branch points an are thus singularities of f(z). We choose the branch g(z) = z 3. All the points on the negative real axis, incluing the origin, are singularities of g(z). Removable Singularities. 377

19 Example Consier f(z) = sin z z. This function is unefine at z = 0 because f(0) is the ineterminate form 0/0. f(z) is analytic everywhere in the finite complex plane except z = 0. Note that the limit as z 0 of f(z) exists. sin z lim z 0 z z 0 cosz 1 If we were to fill in the hole in the efinition of f(z), we coul make it ifferentiable at z = 0. Consier the function g(z) = = 1 { sin z z z 0, 1 z = 0. We calculate the erivative at z = 0 to verify that g(z) is analytic there. f (0) z 0 f(0) f(z) z z 0 1 sin(z)/z z z 0 z sin(z) z 2 1 cos(z) z 0 2z sin(z) z 0 2 = 0 We call the point at z = 0 a removable singularity of sin(z)/z because we can remove the singularity by efining the value of the function to be its limiting value there. 378

20 Consier a function f(z) that is analytic in a elete neighborhoo of z = z 0. If f(z) is not analytic at z 0, but lim z z0 f(z) exists, then the function has a removable singularity at z 0. The function { f(z) z z 0 g(z) = lim z z0 f(z) z = z 0 is analytic in a neighborhoo of z = z 0. We show this by calculating g (z 0 ). g g (z 0 ) g(z) (z 0 ) z z0 z 0 z g (z) z z0 1 f (z) z z0 This limit exists because f(z) is analytic in a elete neighborhoo of z = z 0. Poles. If a function f(z) behaves like c/ (z z 0 ) n near z = z 0 then the function has an n th orer pole at that point. More mathematically we say lim z z 0 (z z 0 ) n f(z) = c 0. We require the constant c to be nonzero so we know that it is not a pole of lower orer. We can enote a removable singularity as a pole of orer zero. Another way to say that a function has an n th orer pole is that f(z) is not analytic at z = z 0, but (z z 0 ) n f(z) is either analytic or has a removable singularity at that point. Example / sin (z 2 ) has a secon orer pole at z = 0 an first orer poles at z = (nπ) 1/2, n Z ±. lim z 0 z 2 sin (z 2 ) z 0 2z 2z cos (z 2 ) z cos (z 2 ) 4z 2 sin (z 2 ) = 1 379

21 z (nπ) 1/2 lim z (nπ) 1/2 sin (z 2 ) 1 z (nπ) 1/2 2z cos (z 2 ) 1 = 2(nπ) 1/2 ( 1) n Example e 1/z is singular at z = 0. The function is not analytic as lim z 0 e 1/z oes not exist. We check if the function has a pole of orer n at z = 0. lim z 0 zn e 1/z e ζ ζ ζ n e ζ ζ n! Since the limit oes not exist for any value of n, the singularity is not a pole. We coul say that e 1/z is more singular than any power of 1/z. Essential Singularities. If a function f(z) is singular at z = z 0, but the singularity is not a branch point, or a pole, the the point is an essential singularity of the function. The point at infinity. We can consier the point at infinity z by making the change of variables z = 1/ζ an consiering ζ 0. If f(1/ζ) is analytic at ζ = 0 then f(z) is analytic at infinity. We have encountere branch points at infinity before (Section 7.9). Assume that f(z) is not analytic at infinity. If lim z f(z) exists then f(z) has a removable singularity at infinity. If lim z f(z)/z n = c 0 then f(z) has an n th orer pole at infinity. 380

22 Result Categorization of Singularities. Consier a function f(z) that has a singularity at the point z = z 0. Singularities come in four flavors: Branch Points. Branch points of multi-value functions are singularities. Removable Singularities. If lim z z0 f(z) exists, then z 0 is a removable singularity. It is thus name because the singularity coul be remove an thus the function mae analytic at z 0 by reefining the value of f (z 0 ). Poles. If lim z z0 (z z 0 ) n f(z) = const 0 then f(z) has an n th orer pole at z 0. Essential Singularities. Instea of efining what an essential singularity is, we say what it is not. If z 0 neither a branch point, a removable singularity nor a pole, it is an essential singularity. A pole may be calle a non-essential singularity. This is because multiplying the function by an integral power of z z 0 will make the function analytic. Then an essential singularity is a point z 0 such that there oes not exist an n such that (z z 0 ) n f(z) is analytic there Isolate an Non-Isolate Singularities Result Isolate an Non-Isolate Singularities. Suppose f(z) has a singularity at z 0. If there exists a elete neighborhoo of z 0 containing no singularities then the point is an isolate singularity. Otherwise it is a non-isolate singularity. 381

23 If you on t like the abstract notion of a elete neighborhoo, you can work with a elete circular neighborhoo. However, this will require the introuction of more math symbols an a Greek letter. z = z 0 is an isolate singularity if there exists a δ > 0 such that there are no singularities in 0 < z z 0 < δ. Example We classify the singularities of f(z) = z/ sin z. z has a simple zero at z = 0. sin z has simple zeros at z = nπ. Thus f(z) has a removable singularity at z = 0 an has first orer poles at z = nπ for n Z ±. We can corroborate this by taking limits. lim f(z) z 0 z 0 z sin z z 0 1 cosz = 1 (z nπ)z lim (z nπ)f(z) z nπ z nπ sin z z nπ = nπ ( 1) n 0 2z nπ cosz Now to examine the behavior at infinity. There is no neighborhoo of infinity that oes not contain first orer poles of f(z). (Another way of saying this is that there oes not exist an R such that there are no singularities in R < z <.) Thus z = is a non-isolate singularity. We coul also etermine this by setting ζ = 1/z an examining the point ζ = 0. f(1/ζ) has first orer poles at ζ = 1/(nπ) for n Z \ {0}. These first orer poles come arbitrarily close to the point ζ = 0 There is no elete neighborhoo of ζ = 0 which oes not contain singularities. Thus ζ = 0, an hence z = is a non-isolate singularity. The point at infinity is an essential singularity. It is certainly not a branch point or a removable singularity. It is not a pole, because there is no n such that lim z z n f(z) = const 0. z n f(z) has first orer poles in any neighborhoo of infinity, so this limit oes not exist. 382

24 8.5 Application: Potential Flow Example We consier 2 imensional uniform flow in a given irection. The flow correspons to the complex potential Φ(z) = v 0 e ıθ 0 z, where v 0 is the flui spee an θ 0 is the irection. We fin the velocity potential φ an stream function ψ. φ = v 0 (cos(θ 0 )x + sin(θ 0 )y), These are plotte in Figure 8.1 for θ 0 = π/6. Φ(z) = φ + ıψ ψ = v 0 ( sin(θ 0 )x + cos(θ 0 )y) Figure 8.1: The velocity potential φ an stream function ψ for Φ(z) = v 0 e ıθ 0 z. Next we fin the stream lines, ψ = c. v 0 ( sin(θ 0 )x + cos(θ 0 )y) = c c y = v 0 cos(θ 0 ) + tan(θ 0)x 383

25 Figure 8.2: Streamlines for ψ = v 0 ( sin(θ 0 )x + cos(θ 0 )y). Figure 8.2 shows how the streamlines go straight along the θ 0 irection. Next we fin the velocity fiel. v = φ v = φ xˆx + φ y ŷ v = v 0 cos(θ 0 )ˆx + v 0 sin(θ 0 )ŷ The velocity fiel is shown in Figure 8.3. Example Steay, incompressible, invisci, irrotational flow is governe by the Laplace equation. We consier flow aroun an infinite cyliner of raius a. Because the flow oes not vary along the axis of the cyliner, this is a two-imensional problem. The flow correspons to the complex potential ( ) Φ(z) = v 0 z + a2. z 384

26 Figure 8.3: Velocity fiel an velocity irection fiel for φ = v 0 (cos(θ 0 )x + sin(θ 0 )y). We fin the velocity potential φ an stream function ψ. φ = v 0 ( r + a2 r Φ(z) = φ + ıψ ) cosθ, ψ = v 0 (r a2 r ) sin θ These are plotte in Figure

27 ( ) Figure 8.4: The velocity potential φ an stream function ψ for Φ(z) = v 0 z + a2. z Next we fin the stream lines, ψ = c. ( ) v 0 r a2 sin θ = c r r = c ± c 2 + 4v 0 sin 2 θ 2v 0 sin θ Figure 8.5 shows how the streamlines go aroun the cyliner. Next we fin the velocity fiel. 386

28 ( ) Figure 8.5: Streamlines for ψ = v 0 r a2 sin θ. r The velocity fiel is shown in Figure 8.6. v = φ v = φ rˆr + φ θ r ˆθ ( ) ) v = v 0 1 a2 cosθˆr v r 2 0 (1 + a2 sin θˆθ r 2 387

Chapter 9. Analytic Continuation. 9.1 Analytic Continuation. For every complex problem, there is a solution that is simple, neat, and wrong.

Chapter 9. Analytic Continuation. 9.1 Analytic Continuation. For every complex problem, there is a solution that is simple, neat, and wrong. Chapter 9 Analytic Continuation For every complex problem, there is a solution that is simple, neat, and wrong. - H. L. Mencken 9.1 Analytic Continuation Suppose there is a function, f 1 (z) that is analytic

More information

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x) Y. D. Chong (2016) MH2801: Complex Methos for the Sciences 1. Derivatives The erivative of a function f(x) is another function, efine in terms of a limiting expression: f (x) f (x) lim x δx 0 f(x + δx)

More information

Section 7.2. The Calculus of Complex Functions

Section 7.2. The Calculus of Complex Functions Section 7.2 The Calculus of Complex Functions In this section we will iscuss limits, continuity, ifferentiation, Taylor series in the context of functions which take on complex values. Moreover, we will

More information

12.11 Laplace s Equation in Cylindrical and

12.11 Laplace s Equation in Cylindrical and SEC. 2. Laplace s Equation in Cylinrical an Spherical Coorinates. Potential 593 2. Laplace s Equation in Cylinrical an Spherical Coorinates. Potential One of the most important PDEs in physics an engineering

More information

Euler equations for multiple integrals

Euler equations for multiple integrals Euler equations for multiple integrals January 22, 2013 Contents 1 Reminer of multivariable calculus 2 1.1 Vector ifferentiation......................... 2 1.2 Matrix ifferentiation........................

More information

Lecture XII. where Φ is called the potential function. Let us introduce spherical coordinates defined through the relations

Lecture XII. where Φ is called the potential function. Let us introduce spherical coordinates defined through the relations Lecture XII Abstract We introuce the Laplace equation in spherical coorinates an apply the metho of separation of variables to solve it. This will generate three linear orinary secon orer ifferential equations:

More information

Final Exam Study Guide and Practice Problems Solutions

Final Exam Study Guide and Practice Problems Solutions Final Exam Stuy Guie an Practice Problems Solutions Note: These problems are just some of the types of problems that might appear on the exam. However, to fully prepare for the exam, in aition to making

More information

Partial Differential Equations

Partial Differential Equations Chapter Partial Differential Equations. Introuction Have solve orinary ifferential equations, i.e. ones where there is one inepenent an one epenent variable. Only orinary ifferentiation is therefore involve.

More information

Math 342 Partial Differential Equations «Viktor Grigoryan

Math 342 Partial Differential Equations «Viktor Grigoryan Math 342 Partial Differential Equations «Viktor Grigoryan 6 Wave equation: solution In this lecture we will solve the wave equation on the entire real line x R. This correspons to a string of infinite

More information

Math Notes on differentials, the Chain Rule, gradients, directional derivative, and normal vectors

Math Notes on differentials, the Chain Rule, gradients, directional derivative, and normal vectors Math 18.02 Notes on ifferentials, the Chain Rule, graients, irectional erivative, an normal vectors Tangent plane an linear approximation We efine the partial erivatives of f( xy, ) as follows: f f( x+

More information

Differentiation ( , 9.5)

Differentiation ( , 9.5) Chapter 2 Differentiation (8.1 8.3, 9.5) 2.1 Rate of Change (8.2.1 5) Recall that the equation of a straight line can be written as y = mx + c, where m is the slope or graient of the line, an c is the

More information

Quantum Mechanics in Three Dimensions

Quantum Mechanics in Three Dimensions Physics 342 Lecture 20 Quantum Mechanics in Three Dimensions Lecture 20 Physics 342 Quantum Mechanics I Monay, March 24th, 2008 We begin our spherical solutions with the simplest possible case zero potential.

More information

Exam 2 Review Solutions

Exam 2 Review Solutions Exam Review Solutions 1. True or False, an explain: (a) There exists a function f with continuous secon partial erivatives such that f x (x, y) = x + y f y = x y False. If the function has continuous secon

More information

1 Lecture 20: Implicit differentiation

1 Lecture 20: Implicit differentiation Lecture 20: Implicit ifferentiation. Outline The technique of implicit ifferentiation Tangent lines to a circle Derivatives of inverse functions by implicit ifferentiation Examples.2 Implicit ifferentiation

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 Chapter 2 Essentials of Calculus by James Stewart Prepared by Jason Gaddis

Math Chapter 2 Essentials of Calculus by James Stewart Prepared by Jason Gaddis Math 231 - Chapter 2 Essentials of Calculus by James Stewart Prepare by Jason Gais Chapter 2 - Derivatives 21 - Derivatives an Rates of Change Definition A tangent to a curve is a line that intersects

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Thus far, the functions we have been concerne with have been efine explicitly. A function is efine explicitly if the output is given irectly in terms of the input. For instance,

More information

3 Elementary Functions

3 Elementary Functions 3 Elementary Functions 3.1 The Exponential Function For z = x + iy we have where Euler s formula gives The note: e z = e x e iy iy = cos y + i sin y When y = 0 we have e x the usual exponential. When z

More information

Linear First-Order Equations

Linear First-Order Equations 5 Linear First-Orer Equations Linear first-orer ifferential equations make up another important class of ifferential equations that commonly arise in applications an are relatively easy to solve (in theory)

More information

The Exact Form and General Integrating Factors

The Exact Form and General Integrating Factors 7 The Exact Form an General Integrating Factors In the previous chapters, we ve seen how separable an linear ifferential equations can be solve using methos for converting them to forms that can be easily

More information

IMPLICIT DIFFERENTIATION

IMPLICIT DIFFERENTIATION IMPLICIT DIFFERENTIATION CALCULUS 3 INU0115/515 (MATHS 2) Dr Arian Jannetta MIMA CMath FRAS Implicit Differentiation 1/ 11 Arian Jannetta Explicit an implicit functions Explicit functions An explicit function

More information

Solutions to Math 41 Second Exam November 4, 2010

Solutions to Math 41 Second Exam November 4, 2010 Solutions to Math 41 Secon Exam November 4, 2010 1. (13 points) Differentiate, using the metho of your choice. (a) p(t) = ln(sec t + tan t) + log 2 (2 + t) (4 points) Using the rule for the erivative of

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Implicit Differentiation Using the Chain Rule In the previous section we focuse on the erivatives of composites an saw that THEOREM 20 (Chain Rule) Suppose that u = g(x) is ifferentiable

More information

Math 185 Homework Exercises II

Math 185 Homework Exercises II Math 185 Homework Exercises II Instructor: Andrés E. Caicedo Due: July 10, 2002 1. Verify that if f H(Ω) C 2 (Ω) is never zero, then ln f is harmonic in Ω. 2. Let f = u+iv H(Ω) C 2 (Ω). Let p 2 be an integer.

More information

MATH 452. SAMPLE 3 SOLUTIONS May 3, (10 pts) Let f(x + iy) = u(x, y) + iv(x, y) be an analytic function. Show that u(x, y) is harmonic.

MATH 452. SAMPLE 3 SOLUTIONS May 3, (10 pts) Let f(x + iy) = u(x, y) + iv(x, y) be an analytic function. Show that u(x, y) is harmonic. MATH 45 SAMPLE 3 SOLUTIONS May 3, 06. (0 pts) Let f(x + iy) = u(x, y) + iv(x, y) be an analytic function. Show that u(x, y) is harmonic. Because f is holomorphic, u and v satisfy the Cauchy-Riemann equations:

More information

MATH243 First Semester 2013/14. Exercises 1

MATH243 First Semester 2013/14. Exercises 1 Complex Functions Dr Anna Pratoussevitch MATH43 First Semester 013/14 Exercises 1 Submit your solutions to questions marked with [HW] in the lecture on Monday 30/09/013 Questions or parts of questions

More information

Unit #6 - Families of Functions, Taylor Polynomials, l Hopital s Rule

Unit #6 - Families of Functions, Taylor Polynomials, l Hopital s Rule Unit # - Families of Functions, Taylor Polynomials, l Hopital s Rule Some problems an solutions selecte or aapte from Hughes-Hallett Calculus. Critical Points. Consier the function f) = 54 +. b) a) Fin

More information

Math 423/823 Exam 1 Topics Covered

Math 423/823 Exam 1 Topics Covered Math 423/823 Exam 1 Topics Covered Complex numbers: C: z = x+yi, where i 2 = 1; addition and multiplication behaves like reals. Formally, x + yi (x,y), with (x,y) + (a,b) = (x + a,y + b) and (x,y)(a,b)

More information

Math 1271 Solutions for Fall 2005 Final Exam

Math 1271 Solutions for Fall 2005 Final Exam Math 7 Solutions for Fall 5 Final Eam ) Since the equation + y = e y cannot be rearrange algebraically in orer to write y as an eplicit function of, we must instea ifferentiate this relation implicitly

More information

constant ρ constant θ

constant ρ constant θ Answers to Problem Set Number 3 for 8.04. MIT (Fall 999) Contents Roolfo R. Rosales Λ Boris Schlittgen y Zhaohui Zhang ẓ October 9, 999 Problems from the book by Saff an Snier. 2. Problem 04 in section

More information

VIBRATIONS OF A CIRCULAR MEMBRANE

VIBRATIONS OF A CIRCULAR MEMBRANE VIBRATIONS OF A CIRCULAR MEMBRANE RAM EKSTROM. Solving the wave equation on the isk The ynamics of vibrations of a two-imensional isk D are given by the wave equation..) c 2 u = u tt, together with the

More information

PDE Notes, Lecture #11

PDE Notes, Lecture #11 PDE Notes, Lecture # from Professor Jalal Shatah s Lectures Febuary 9th, 2009 Sobolev Spaces Recall that for u L loc we can efine the weak erivative Du by Du, φ := udφ φ C0 If v L loc such that Du, φ =

More information

Implicit Differentiation. Lecture 16.

Implicit Differentiation. Lecture 16. Implicit Differentiation. Lecture 16. We are use to working only with functions that are efine explicitly. That is, ones like f(x) = 5x 3 + 7x x 2 + 1 or s(t) = e t5 3, in which the function is escribe

More information

Lecture Notes Complex Analysis. Complex Variables and Applications 7th Edition Brown and Churchhill

Lecture Notes Complex Analysis. Complex Variables and Applications 7th Edition Brown and Churchhill Lecture Notes omplex Analysis based on omplex Variables and Applications 7th Edition Brown and hurchhill Yvette Fajardo-Lim, Ph.D. Department of Mathematics De La Salle University - Manila 2 ontents THE

More information

Linear and quadratic approximation

Linear and quadratic approximation Linear an quaratic approximation November 11, 2013 Definition: Suppose f is a function that is ifferentiable on an interval I containing the point a. The linear approximation to f at a is the linear function

More information

Math 115 Section 018 Course Note

Math 115 Section 018 Course Note Course Note 1 General Functions Definition 1.1. A function is a rule that takes certain numbers as inputs an assigns to each a efinite output number. The set of all input numbers is calle the omain of

More information

23 Implicit differentiation

23 Implicit differentiation 23 Implicit ifferentiation 23.1 Statement The equation y = x 2 + 3x + 1 expresses a relationship between the quantities x an y. If a value of x is given, then a corresponing value of y is etermine. For

More information

Math 185 Fall 2015, Sample Final Exam Solutions

Math 185 Fall 2015, Sample Final Exam Solutions Math 185 Fall 2015, Sample Final Exam Solutions Nikhil Srivastava December 12, 2015 1. True or false: (a) If f is analytic in the annulus A = {z : 1 < z < 2} then there exist functions g and h such that

More information

Chapter 3 Elementary Functions

Chapter 3 Elementary Functions Chapter 3 Elementary Functions In this chapter, we will consier elementary functions of a complex variable. We will introuce complex exponential, trigonometric, hyperbolic, an logarithmic functions. 23.

More information

Assignment 2 - Complex Analysis

Assignment 2 - Complex Analysis Assignment 2 - Complex Analysis MATH 440/508 M.P. Lamoureux Sketch of solutions. Γ z dz = Γ (x iy)(dx + idy) = (xdx + ydy) + i Γ Γ ( ydx + xdy) = (/2)(x 2 + y 2 ) endpoints + i [( / y) y ( / x)x]dxdy interiorγ

More information

Free rotation of a rigid body 1 D. E. Soper 2 University of Oregon Physics 611, Theoretical Mechanics 5 November 2012

Free rotation of a rigid body 1 D. E. Soper 2 University of Oregon Physics 611, Theoretical Mechanics 5 November 2012 Free rotation of a rigi boy 1 D. E. Soper 2 University of Oregon Physics 611, Theoretical Mechanics 5 November 2012 1 Introuction In this section, we escribe the motion of a rigi boy that is free to rotate

More information

θ x = f ( x,t) could be written as

θ x = f ( x,t) could be written as 9. Higher orer PDEs as systems of first-orer PDEs. Hyperbolic systems. For PDEs, as for ODEs, we may reuce the orer by efining new epenent variables. For example, in the case of the wave equation, (1)

More information

Outline. MS121: IT Mathematics. Differentiation Rules for Differentiation: Part 1. Outline. Dublin City University 4 The Quotient Rule

Outline. MS121: IT Mathematics. Differentiation Rules for Differentiation: Part 1. Outline. Dublin City University 4 The Quotient Rule MS2: IT Mathematics Differentiation Rules for Differentiation: Part John Carroll School of Mathematical Sciences Dublin City University Pattern Observe You may have notice the following pattern when we

More information

Complex Variables. Chapter 2. Analytic Functions Section Harmonic Functions Proofs of Theorems. March 19, 2017

Complex Variables. Chapter 2. Analytic Functions Section Harmonic Functions Proofs of Theorems. March 19, 2017 Complex Variables Chapter 2. Analytic Functions Section 2.26. Harmonic Functions Proofs of Theorems March 19, 2017 () Complex Variables March 19, 2017 1 / 5 Table of contents 1 Theorem 2.26.1. 2 Theorem

More information

Curvature, Conformal Mapping, and 2D Stationary Fluid Flows. Michael Taylor

Curvature, Conformal Mapping, and 2D Stationary Fluid Flows. Michael Taylor Curvature, Conformal Mapping, an 2D Stationary Flui Flows Michael Taylor 1. Introuction Let Ω be a 2D Riemannian manifol possibly with bounary). Assume Ω is oriente, with J enoting counterclockwise rotation

More information

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1 Assignment 1 Golstein 1.4 The equations of motion for the rolling isk are special cases of general linear ifferential equations of constraint of the form g i (x 1,..., x n x i = 0. i=1 A constraint conition

More information

Math 300 Winter 2011 Advanced Boundary Value Problems I. Bessel s Equation and Bessel Functions

Math 300 Winter 2011 Advanced Boundary Value Problems I. Bessel s Equation and Bessel Functions Math 3 Winter 2 Avance Bounary Value Problems I Bessel s Equation an Bessel Functions Department of Mathematical an Statistical Sciences University of Alberta Bessel s Equation an Bessel Functions We use

More information

Chapter 2 Lagrangian Modeling

Chapter 2 Lagrangian Modeling Chapter 2 Lagrangian Moeling The basic laws of physics are use to moel every system whether it is electrical, mechanical, hyraulic, or any other energy omain. In mechanics, Newton s laws of motion provie

More information

2. Complex Analytic Functions

2. Complex Analytic Functions 2. Complex Analytic Functions John Douglas Moore July 6, 2011 Recall that if A and B are sets, a function f : A B is a rule which assigns to each element a A a unique element f(a) B. In this course, we

More information

Table of Common Derivatives By David Abraham

Table of Common Derivatives By David Abraham Prouct an Quotient Rules: Table of Common Derivatives By Davi Abraham [ f ( g( ] = [ f ( ] g( + f ( [ g( ] f ( = g( [ f ( ] g( g( f ( [ g( ] Trigonometric Functions: sin( = cos( cos( = sin( tan( = sec

More information

Sturm-Liouville Theory

Sturm-Liouville Theory LECTURE 5 Sturm-Liouville Theory In the three preceing lectures I emonstrate the utility of Fourier series in solving PDE/BVPs. As we ll now see, Fourier series are just the tip of the iceberg of the theory

More information

d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0.

d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0. Calculus refresher Disclaimer: I claim no original content on this ocument, which is mostly a summary-rewrite of what any stanar college calculus book offers. (Here I ve use Calculus by Dennis Zill.) I

More information

Math 417 Midterm Exam Solutions Friday, July 9, 2010

Math 417 Midterm Exam Solutions Friday, July 9, 2010 Math 417 Midterm Exam Solutions Friday, July 9, 010 Solve any 4 of Problems 1 6 and 1 of Problems 7 8. Write your solutions in the booklet provided. If you attempt more than 5 problems, you must clearly

More information

Vectors in two dimensions

Vectors in two dimensions Vectors in two imensions Until now, we have been working in one imension only The main reason for this is to become familiar with the main physical ieas like Newton s secon law, without the aitional complication

More information

February 21 Math 1190 sec. 63 Spring 2017

February 21 Math 1190 sec. 63 Spring 2017 February 21 Math 1190 sec. 63 Spring 2017 Chapter 2: Derivatives Let s recall the efinitions an erivative rules we have so far: Let s assume that y = f (x) is a function with c in it s omain. The erivative

More information

The Principle of Least Action

The Principle of Least Action Chapter 7. The Principle of Least Action 7.1 Force Methos vs. Energy Methos We have so far stuie two istinct ways of analyzing physics problems: force methos, basically consisting of the application of

More information

1 Heisenberg Representation

1 Heisenberg Representation 1 Heisenberg Representation What we have been ealing with so far is calle the Schröinger representation. In this representation, operators are constants an all the time epenence is carrie by the states.

More information

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs Lectures - Week 10 Introuction to Orinary Differential Equations (ODES) First Orer Linear ODEs When stuying ODEs we are consiering functions of one inepenent variable, e.g., f(x), where x is the inepenent

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

(z 0 ) = lim. = lim. = f. Similarly along a vertical line, we fix x = x 0 and vary y. Setting z = x 0 + iy, we get. = lim. = i f

(z 0 ) = lim. = lim. = f. Similarly along a vertical line, we fix x = x 0 and vary y. Setting z = x 0 + iy, we get. = lim. = i f . Holomorphic Harmonic Functions Basic notation. Considering C as R, with coordinates x y, z = x + iy denotes the stard complex coordinate, in the usual way. Definition.1. Let f : U C be a complex valued

More information

Math 251 Notes. Part I.

Math 251 Notes. Part I. Math 251 Notes. Part I. F. Patricia Meina May 6, 2013 Growth Moel.Consumer price inex. [Problem 20, page 172] The U.S. consumer price inex (CPI) measures the cost of living base on a value of 100 in the

More information

Review of Differentiation and Integration for Ordinary Differential Equations

Review of Differentiation and Integration for Ordinary Differential Equations Schreyer Fall 208 Review of Differentiation an Integration for Orinary Differential Equations In this course you will be expecte to be able to ifferentiate an integrate quickly an accurately. Many stuents

More information

0.1 The Chain Rule. db dt = db

0.1 The Chain Rule. db dt = db 0. The Chain Rule A basic illustration of the chain rules comes in thinking about runners in a race. Suppose two brothers, Mark an Brian, hol an annual race to see who is the fastest. Last year Mark won

More information

there is no special reason why the value of y should be fixed at y = 0.3. Any y such that

there is no special reason why the value of y should be fixed at y = 0.3. Any y such that 25. More on bivariate functions: partial erivatives integrals Although we sai that the graph of photosynthesis versus temperature in Lecture 16 is like a hill, in the real worl hills are three-imensional

More information

Pure Further Mathematics 1. Revision Notes

Pure Further Mathematics 1. Revision Notes Pure Further Mathematics Revision Notes June 20 2 FP JUNE 20 SDB Further Pure Complex Numbers... 3 Definitions an arithmetical operations... 3 Complex conjugate... 3 Properties... 3 Complex number plane,

More information

Section 2.7 Derivatives of powers of functions

Section 2.7 Derivatives of powers of functions Section 2.7 Derivatives of powers of functions (3/19/08) Overview: In this section we iscuss the Chain Rule formula for the erivatives of composite functions that are forme by taking powers of other functions.

More information

The Three-dimensional Schödinger Equation

The Three-dimensional Schödinger Equation The Three-imensional Schöinger Equation R. L. Herman November 7, 016 Schröinger Equation in Spherical Coorinates We seek to solve the Schröinger equation with spherical symmetry using the metho of separation

More information

Final Exam: Sat 12 Dec 2009, 09:00-12:00

Final Exam: Sat 12 Dec 2009, 09:00-12:00 MATH 1013 SECTIONS A: Professor Szeptycki APPLIED CALCULUS I, FALL 009 B: Professor Toms C: Professor Szeto NAME: STUDENT #: SECTION: No ai (e.g. calculator, written notes) is allowe. Final Exam: Sat 1

More information

Differentiation Rules Derivatives of Polynomials and Exponential Functions

Differentiation Rules Derivatives of Polynomials and Exponential Functions Derivatives of Polynomials an Exponential Functions Differentiation Rules Derivatives of Polynomials an Exponential Functions Let s start with the simplest of all functions, the constant function f(x)

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

Math 1B, lecture 8: Integration by parts

Math 1B, lecture 8: Integration by parts Math B, lecture 8: Integration by parts Nathan Pflueger 23 September 2 Introuction Integration by parts, similarly to integration by substitution, reverses a well-known technique of ifferentiation an explores

More information

Laplace s Equation in Cylindrical Coordinates and Bessel s Equation (II)

Laplace s Equation in Cylindrical Coordinates and Bessel s Equation (II) Laplace s Equation in Cylinrical Coorinates an Bessel s Equation (II Qualitative properties of Bessel functions of first an secon kin In the last lecture we foun the expression for the general solution

More information

Solving the Schrödinger Equation for the 1 Electron Atom (Hydrogen-Like)

Solving the Schrödinger Equation for the 1 Electron Atom (Hydrogen-Like) Stockton Univeristy Chemistry Program, School of Natural Sciences an Mathematics 101 Vera King Farris Dr, Galloway, NJ CHEM 340: Physical Chemistry II Solving the Schröinger Equation for the 1 Electron

More information

Exercises for Part 1

Exercises for Part 1 MATH200 Complex Analysis. Exercises for Part Exercises for Part The following exercises are provided for you to revise complex numbers. Exercise. Write the following expressions in the form x + iy, x,y

More information

2 Complex Functions and the Cauchy-Riemann Equations

2 Complex Functions and the Cauchy-Riemann Equations 2 Complex Functions and the Cauchy-Riemann Equations 2.1 Complex functions In one-variable calculus, we study functions f(x) of a real variable x. Likewise, in complex analysis, we study functions f(z)

More information

SYDE 112, LECTURE 1: Review & Antidifferentiation

SYDE 112, LECTURE 1: Review & Antidifferentiation SYDE 112, LECTURE 1: Review & Antiifferentiation 1 Course Information For a etaile breakown of the course content an available resources, see the Course Outline. Other relevant information for this section

More information

Mathematical Review Problems

Mathematical Review Problems Fall 6 Louis Scuiero Mathematical Review Problems I. Polynomial Equations an Graphs (Barrante--Chap. ). First egree equation an graph y f() x mx b where m is the slope of the line an b is the line's intercept

More information

Leplace s Equations. Analyzing the Analyticity of Analytic Analysis DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING. Engineering Math EECE

Leplace s Equations. Analyzing the Analyticity of Analytic Analysis DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING. Engineering Math EECE Leplace s Analyzing the Analyticity of Analytic Analysis Engineering Math EECE 3640 1 The Laplace equations are built on the Cauchy- Riemann equations. They are used in many branches of physics such as

More information

UNDERSTANDING INTEGRATION

UNDERSTANDING INTEGRATION UNDERSTANDING INTEGRATION Dear Reaer The concept of Integration, mathematically speaking, is the "Inverse" of the concept of result, the integration of, woul give us back the function f(). This, in a way,

More information

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim QF101: Quantitative Finance September 5, 2017 Week 3: Derivatives Facilitator: Christopher Ting AY 2017/2018 I recoil with ismay an horror at this lamentable plague of functions which o not have erivatives.

More information

S10.G.1. Fluid Flow Around the Brownian Particle

S10.G.1. Fluid Flow Around the Brownian Particle Rea Reichl s introuction. Tables & proofs for vector calculus formulas can be foun in the stanar textbooks G.Arfken s Mathematical Methos for Physicists an J.D.Jackson s Classical Electroynamics. S0.G..

More information

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold CHAPTER 1 : DIFFERENTIABLE MANIFOLDS 1.1 The efinition of a ifferentiable manifol Let M be a topological space. This means that we have a family Ω of open sets efine on M. These satisfy (1), M Ω (2) the

More information

4.2 First Differentiation Rules; Leibniz Notation

4.2 First Differentiation Rules; Leibniz Notation .. FIRST DIFFERENTIATION RULES; LEIBNIZ NOTATION 307. First Differentiation Rules; Leibniz Notation In this section we erive rules which let us quickly compute the erivative function f (x) for any polynomial

More information

Part IB. Complex Analysis. Year

Part IB. Complex Analysis. Year Part IB Complex Analysis Year 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2018 Paper 1, Section I 2A Complex Analysis or Complex Methods 7 (a) Show that w = log(z) is a conformal

More information

Problem set 2: Solutions Math 207B, Winter 2016

Problem set 2: Solutions Math 207B, Winter 2016 Problem set : Solutions Math 07B, Winter 016 1. A particle of mass m with position x(t) at time t has potential energy V ( x) an kinetic energy T = 1 m x t. The action of the particle over times t t 1

More information

Chapter 2 Derivatives

Chapter 2 Derivatives Chapter Derivatives Section. An Intuitive Introuction to Derivatives Consier a function: Slope function: Derivative, f ' For each, the slope of f is the height of f ' Where f has a horizontal tangent line,

More information

Lecture 2 Lagrangian formulation of classical mechanics Mechanics

Lecture 2 Lagrangian formulation of classical mechanics Mechanics Lecture Lagrangian formulation of classical mechanics 70.00 Mechanics Principle of stationary action MATH-GA To specify a motion uniquely in classical mechanics, it suffices to give, at some time t 0,

More information

Here are brief notes about topics covered in class on complex numbers, focusing on what is not covered in the textbook.

Here are brief notes about topics covered in class on complex numbers, focusing on what is not covered in the textbook. Phys374, Spring 2008, Prof. Ted Jacobson Department of Physics, University of Maryland Complex numbers version 5/21/08 Here are brief notes about topics covered in class on complex numbers, focusing on

More information

Step 1. Analytic Properties of the Riemann zeta function [2 lectures]

Step 1. Analytic Properties of the Riemann zeta function [2 lectures] Step. Analytic Properties of the Riemann zeta function [2 lectures] The Riemann zeta function is the infinite sum of terms /, n. For each n, the / is a continuous function of s, i.e. lim s s 0 n = s n,

More information

Topic 2 Notes Jeremy Orloff

Topic 2 Notes Jeremy Orloff Topic 2 Notes Jeremy Orloff 2 Analytic functions 2.1 Introduction The main goal of this topic is to define and give some of the important properties of complex analytic functions. A function f(z) is analytic

More information

MATH 31BH Homework 5 Solutions

MATH 31BH Homework 5 Solutions MATH 3BH Homework 5 Solutions February 4, 204 Problem.8.2 (a) Let x t f y = x 2 + y 2 + 2z 2 and g(t) = t 2. z t 3 Then by the chain rule a a a D(g f) b = Dg f b Df b c c c = [Dg(a 2 + b 2 + 2c 2 )] [

More information

Lagrangian and Hamiltonian Mechanics

Lagrangian and Hamiltonian Mechanics Lagrangian an Hamiltonian Mechanics.G. Simpson, Ph.. epartment of Physical Sciences an Engineering Prince George s Community College ecember 5, 007 Introuction In this course we have been stuying classical

More information

Calculus and optimization

Calculus and optimization Calculus an optimization These notes essentially correspon to mathematical appenix 2 in the text. 1 Functions of a single variable Now that we have e ne functions we turn our attention to calculus. A function

More information

II. First variation of functionals

II. First variation of functionals II. First variation of functionals The erivative of a function being zero is a necessary conition for the etremum of that function in orinary calculus. Let us now tackle the question of the equivalent

More information

1 Holomorphic functions

1 Holomorphic functions Robert Oeckl CA NOTES 1 15/09/2009 1 1 Holomorphic functions 11 The complex derivative The basic objects of complex analysis are the holomorphic functions These are functions that posses a complex derivative

More information

The Chain Rule. d dx x(t) dx. dt (t)

The Chain Rule. d dx x(t) dx. dt (t) The Chain Rule The Problem You alreay routinely use the one imensional chain rule t f xt = f x xt x t t in oing computations like t sint2 = cost 2 2t In this example, fx = sinx an xt = t 2. We now generalize

More information

Math 210 Midterm #1 Review

Math 210 Midterm #1 Review Math 20 Miterm # Review This ocument is intene to be a rough outline of what you are expecte to have learne an retaine from this course to be prepare for the first miterm. : Functions Definition: A function

More information

1 z n = 1. 9.(Problem) Evaluate each of the following, that is, express each in standard Cartesian form x + iy. (2 i) 3. ( 1 + i. 2 i.

1 z n = 1. 9.(Problem) Evaluate each of the following, that is, express each in standard Cartesian form x + iy. (2 i) 3. ( 1 + i. 2 i. . 5(b). (Problem) Show that z n = z n and z n = z n for n =,,... (b) Use polar form, i.e. let z = re iθ, then z n = r n = z n. Note e iθ = cos θ + i sin θ =. 9.(Problem) Evaluate each of the following,

More information

Math 11 Fall 2016 Section 1 Monday, September 19, Definition: A vector parametric equation for the line parallel to vector v = x v, y v, z v

Math 11 Fall 2016 Section 1 Monday, September 19, Definition: A vector parametric equation for the line parallel to vector v = x v, y v, z v Math Fall 06 Section Monay, September 9, 06 First, some important points from the last class: Definition: A vector parametric equation for the line parallel to vector v = x v, y v, z v passing through

More information

18.04 Practice problems exam 2, Spring 2018 Solutions

18.04 Practice problems exam 2, Spring 2018 Solutions 8.04 Practice problems exam, Spring 08 Solutions Problem. Harmonic functions (a) Show u(x, y) = x 3 3xy + 3x 3y is harmonic and find a harmonic conjugate. It s easy to compute: u x = 3x 3y + 6x, u xx =

More information