5. Taylor and Laurent series. Complex sequences and series

Size: px
Start display at page:

Download "5. Taylor and Laurent series. Complex sequences and series"

Transcription

1 5. Taylor and Laurent series Complex sequences and series An infinite sequence of complex numbers, denoted by {z n }, can be considered as a function defined on a set of positive integers into the unextended complex plane. For example, we take z n = n + so that the complex sequence is {z n } = Convergence of complex sequences { + i 2, 2 + i 2 2, 3 + i 2 3, Given a complex sequence {z n }, if for each positive quantity ǫ, there exists a positive integer N such that z n z < ǫ whenever n > N, then the sequence is said to converge to the limt z. We write lim n z n = z. }. 2 n

2 In general, the choice of N depends on ǫ. The definition implies that every ǫ-neighborhood of z contains all but a finite number of members of the sequence. The limit of a convergent sequence is unique. If the sequence fails to converge, it is said to be divergent. Suppose we write z n = x n + iy n and z = x + iy, then x n x z n z x n x + y n y, y n y z n z x n x + y n y. Suppose lim = x and lim y n n n = y exist, then for any ǫ > 0, there exist N x and N y such that x n x < ǫ 2 y n y < ǫ 2 whenever n > N x whenever n > N y. Choose n > max(n x, N y ), then z n z x n x + y n y < ǫ 2 + ǫ 2 = ǫ. 2

3 Using the above inequalities, it is easy to show that lim n z n = z lim x n n = x and lim y n n = y. Therefore, the study of the convergence of a complex sequence is equivalent to the consideration of two real sequences. The above theorem enables us to write lim n (x n + iy n ) = lim x n n + i lim y n n whenever we know that both limits on the right exist or the one on the left exists. 3

4 For example, the sequence converges to i since lim ( lim n n 3 + i z n = + i, n =,2,, n3 n ) and lim n3 n exist, so = lim n n 3 + i n lim = 0 + i = i. One can show that for each positive number ǫ z n i < ǫ whenever n > 3 ǫ. 4

5 Infinite series of complex numbers An infinite series of complex numbers z, z 2, z 3, is the infinite sum of the sequence {z n } given by z + z 2 + z 3 + = lim n n z k. k= To study the properties of an infinite series, we define the sequence of partial sums {S n } by S n = n k= z k. If the limit of the sequence {S n } converges to S, then the series is said to be convergent and S is its sum; otherwise, the series is divergent. The consideration of an infinite series is relegated to that of an infinite sequence of partial sums. 5

6 Remainder after n terms Suppose an infinite series converges. We define the remainder after n terms by and obviously R n = S S n lim n R n = 0. Conversely, suppose lim R n n = 0, then for any ǫ > 0, there exists N(ǫ) such that R n < ǫ for n > N(ǫ). This is equivalent to hence S n S < ǫ for n > N(ǫ), S = lim n S n. 6

7 A necessary condition for the convergence of a complex series is that This is obvious since lim n z n = 0. lim n z n = lim (R n n R n ) = lim R n n lim R n n = 0. Comparison Test If j= M j is a convergent series with real nonnegative terms and for all j larger than some number J, z j M j, then the series converges also. This is easily seen since S n = increasing sequence, so it must have a limit. n j= j= z j z j is a bounded 7

8 Absolute convergence The complex series n= z n is absolutely convergent if z n con- verges. Note that z n = x 2 n + y2 n and since x n x 2 n + yn 2 and y n x 2 n + yn, 2 n= then from the comparison test, the two series n= x n and n= must converge. Thus, absolute convergence in a complex sequence implies convergence in that sequence. The converse may not hold. If Σz n converges but Σ z n does not, the series Σz n is said to be conditionally convergent. For example, Log( e iθ ) = is conditionally convergent. n= e inθ y n n, θ 0, 8

9 Example Show that the series j= (3 + 2i)/(j + ) j converges. Solution We compare the series j= 3 + 2i (3 + 2i) = + (j + ) j 9 with the convergent geometric series (3 + 2i) 64 + (A) j= 2 j = (B) Since 3 + 2i = 3 < 4, one can easily verify that for j i (j + ) j < 4 (j + ) j 2 j. The terms of (B) dominate those of (A), hence (A) converges. 9

10 Limit superior Consider a sequence {x n } of real numbers, and let S denote the set of all of its limit points. The limit superior of {x n } is the supremum (least upper bound) of S. For example, x n = 3+( ) n, n =,2,, the limit points are 2 and 4 so that Root test lim n x n = max(2,4) = 4. Suppose the limit superior of { z n /n } equals L, the series Σz n converges absolutely if L < and diverges if L >. The root test fails when L =. 0

11 Ratio test z n+ Suppose lim n z n converges to L, then Σz n is absolutely convergent if L < and divergent if L >. When L =, the ratio test fails. Gauss test Suppose z n+ z n admits the following asymptotic expansion z n+ z n = k n + α n n 2 +, where α n is bounded for all n > N for some sufficiently large N, then Σz n converges absolutely if k >, and diverges or converges conditionally if k.

12 Proof of the Ratio Test z n+ Suppose lim converges to L, L <, then we can choose an n z n integer N such that for n N, we have Now, we have z n+ z n r, where L < r <. z N+ r z N, z N+2 r z N+ r 2 z N, and so forth, z N+ + z N+2 + z N (r + r 2 + ). Thus, n= z n converges absolutely by virtue of the comparison test. 2

13 Sequences of complex functions Let f (z),, f n (z),, denoted by {f n (z)}, be a sequence of complex functions of z that are defined and single-valued in a region R in the complex plane. For some point z 0 R, {f n (z 0 )} becomes a sequence of complex numbers. Supposing {f n (z 0 )} converges, the limit is unique. The value of the limit depends on z 0, and we write f(z 0 ) = lim n f n (z 0 ). If this holds for every z R, the sequence {f n (z)} defines a complex function f(z) in R. We write f(z) = lim n f n (z). This is usually called pointwise convergence. 3

14 Definition A sequence of complex functions {f n (z)} defined in a region R is said to converge to a complex function f(z) defined in the same region if and only if, for any given small positive quantity ǫ, we can find a positive integer N(ǫ; z) [in general, N(ǫ; z) depends on ǫ and z] such that f(z) f n (z) < ǫ for all n > N(ǫ; z). The region R is called the region of convergence of the sequence of complex functions. In general, we may not be able to find a single N(ǫ) that works for all point in R. However, when this is possible, {f n (z)} is said to converge uniformly to f(z) in R. 4

15 Convergence of series of complex functions An infinite series of complex functions f (z) + f 2 (z) + f 3 (z) + = k= is related to the sequence of partial sum {S n (z)} S n (z) = n k= f k (z). The infinite series is said to be convergent if f k (z) lim n S n(z) = S(z), where S(z) is called the sum; otherwise the series is divergent. 5

16 Many of the properties related to convergence of complex functions can be extended from their counterparts of complex numbers. For example, a necessary but not sufficient condition for the infinite series of complex functions to converge is that lim f k(z) = 0, k for all z in the region of convergence. Example Consider the complex series k= sin kz k 2, show that it is absolutely convergent when z is real but it becomes divergent when z is non-real. 6

17 Solution (i) When z is real, we have Since sin kz k 2 k= k2, for all positive integer values of k. /k 2 is known to be convergent, then k= sin kz/k 2 is absolutely convergent for all z by virtue of the comparison test. (ii) When z is non-real, we let z = x + iy, y 0. From the relation we deduce that Since sin kz/k2 sin kz k 2 = e ky e ikx e ky e ikx 2k 2, i sin kz k 2 ek y e k y 2k 2 as k. is unbounded as k, the series is divergent. 7

18 Uniform convergence of an infinite series of complex functions Let R n (z) = S(z) n k= f k (z) = S(z) S n (z). The infinite series Σf k (z) converges uniformly to S(z) in some region R iff for any ǫ > 0, there exists N which is independent of z such that for all z R R n (z) < ǫ whenever n > N. Weierstrass M-test If f k (z) M k where M k is independent of z in R and the series ΣM k converges, then Σf k (z) is uniformly convergent in R. 8

19 Proof of the Weierstrass M-test The remainder of the series f k (z) after n terms is Now, R n (z) = f n+ (z) + f n+2 (z) +. R n (z) f n+ (z) + f n+2 (z) + M n+ + M n+2 +. Since M k converges, M n+ + M n+2 + can be made less than ǫ > 0 by choosing n > N for some N = N(ǫ). As N is clearly independent of z, we have R n (z) < ǫ for n > N, so the series is uniformly convergent. We also have absolute convergence of the series. 9

20 Test for uniform convergence using the M-test. 2. n= z n n, z. n + Note that f n (z) = z n n n + n 3/2 if z. Take M n = and note that M n converges. n= n 2 + z2, < z < 2. n 3/2 Omit the first two terms since it does not affect the uniform convergence property. For n 3 and < z < 2, we have n 2 + z 2 n 2 z 2 n 2 4 n2 Take M n = 2 n 2 and note that n=3 2 so that 2 n 2 converges. n 2 + z 2 2 n 2. 20

21 Example Prove that the series z( z) + z 2 ( z) + z 3 ( z) + converges for z < and find its sum. Solution S n (z) = z( z) + + z n ( z) = z z 2 + z 2 z z n z n+ = z z n+. For z <, consider S n (z) z = z n+ = z n+ < ǫ. In order that this is true, we choose n such that (n + )ln z < ln ǫ so that n + > ln ǫ ln z or n > ln ǫ ln z When z = 0, S n (0) = 0 so S n (0) 0 < ǫ for all n. Hence, lim n S n (z) = z for all z such that z <., z 0. 2

22 Questions. Does the series converge uniformly to z for z 2? Yes. If z 2, the largest value of ln ǫ ln z occurs when z = 2 and is given by ln ǫ ln 2. Take N(ǫ) to be the largest integer smaller than ln ǫ ln 2. It then follows that S n (z) z < ǫ for n > N where N depends only on ǫ and not on the particular z in z. Hence, we have uniform 2 convergence of the series for z 2. 22

23 2. Does the series converge uniformly for z? The same argument given in Qn () serves to show uniform convergence for z 0.9 or z 0.99 by using ( ) ( ) ln ǫ ln ǫ N = fl ln0.9 and N = fl ln0.99, respectively. However, if we apply the argument to z, this would require ( ) ln ǫ N = fl ln, which is infinite. The series does not converge uniformly for z. 23

24 Example Show that the geometric series z n converges uniformly to n=0 z on any closed subdisk z r < of the open unit disk z <. Solution To establish the uniform convergence of the series for z r <, we apply the Weierstrass M-test. We have f n (z) = z n r n = M n for all z r. Since n= the series M n = n= n=0 r n is convergent if 0 r <, we conclude that z n converges uniformly for z r. 24

25 For uniformly convergent infinite series of complex functions, properties such as continuity and analyticity of the continuous functions f k (z) are carried over to the sum S(z). More precisely, suppose f k (z), k =,2,, are all continuous (analytic) in the region of convergence, then f k (z) is also continuous (analytic) in the same region. Further, an uniform convergent infinite series allows for termwise differentiation and integration, that is, C d dz k= k= f k (z) dz = f k (z) = k= k= f k (z). C f k(z) dz 25

26 Power series The choice of f n (z) = a n (z z 0 ) n leads to the power series expanded at z = z 0. A power series defines a function f(z) for those points z at which it converges. Given a power series n= a n (z z 0 ) n, there exists a non-negative real number R, R can be zero or infinity, such that the power series converges absolutely for z z 0 < R, and diverges for z z 0 > R. R is called the radius of convergence z z 0 < R is called the circle of convergence. Convergence of the power series must be determined for each point on the circle of convergence. 26

27 Ratio test as applied to the infinite power series The radius of convergence R is given by lim n limit exists. a n a n+, given that the Consider the ratio a n+ z z 0 n+ a a n z z 0 n and suppose lim n n a exists, n+ then the power series converges absolutely when z z 0 satisfies lim n a n+ a n z z 0 < z z 0 < lim a n n a. n+ 27

28 (i) R = when lim n plane. (ii) R = 0 when lim n any z other than z 0. a n+ a n a n a n+ = 0. The series converges in the whole = 0. The series does not converges for Root test as applied to the infinite power series The radius of convergence can also be found by R = Note that, which is a consequence of the root test. n lim n a n lim n n a n z z 0 < z z 0 < lim n n. a n 28

29 Example Find the circle of convergence for each of the following power series: (a) (b) (c) (d) k= k= ( z k= k= k (z i)k, k ln k (z 2) k, k ) k, ( + ) k 2 z k. k 29

30 Solution (a) By the ratio test, we have R = lim k /k /(k + ) = ; so the circle of convergence is z i =. (b) Using the root test, we have R = lim k k a k = lim k ln k. k k To evaluate the limit, we consider the logarithm, so ln lim k k k ln k = lim k ln k k ln k = lim k (ln k) 2 k R = lim k k k ln k = e 0 =. The circle of convergence is z 2 =. = 0; 30

31 (c) By the ratio test, we have R = lim k ( k ) k ( ) k+ = lim (k + ) k k+ ( + k) k = ; so the circle of convergence is the whole complex plane. (d) By the root test, we have R = lim k ( k + k ) k 2 so the circle of convergence is z = /e. ( = lim + k = e, k k) 3

32 Theorem If z is a point inside the circle of convergence z z 0 = R of a power series n=0 a n (z z 0 ) n then the power series must be uniformly convergent in the closed disk z z 0 R, where R = z z 0. Some useful results Let S(z) denote the sum of the infinite power series inside the circle of convergence. Then (i) S(z) represents a continuous function at each point interior to its circle of convergence. (ii) S (z) = n= convergence. na n (z z 0 ) n at each point z inside the circle of 32

33 Power series of f(z) Suppose a power series represents the function f(z) inside the circle of convergence, that is, f(z) = n=0 a n (z z 0 ) n. It is known that a power series can be differentiated termwise so that f (z) = f (z) = n= n=2 na n (z z 0 ) n Putting z = z 0 successively, we obtain n(n )a n (z z 0 ) n 2,. a n = f(n) (z 0 ), n = 0,,2, n! f (n) (z f(z) = 0 ) (z z 0 ) n. n! n=0 33

34 A power series represents an analytic function inside its circle of convergence. Can we expand an analytic function in Taylor series and how is the domain of analyticity related to the circle of convergence? Taylor series theorem Let f(z) be analytic in a domain D with boundary D and z 0 D. Determine R such that R = min{ z z 0, Then there exists a power series k=0 z D}. a k (z z 0 ) k which converges to f(z) for z z 0 < R. The coefficients a k are given by a k = 2πi C f(ζ) (ζ z 0 ) k+ dζ = f(k) (z 0 ), k = 0,,2,, k! C is any closed contour around z 0 and lying completely inside D. 34

35 Proof Take a point z such that z z 0 = r < R. A circle is drawn around z 0 with radius R, where r < R < R. Since z lies inside C, by virtue of the Cauchy Integral Theorem, we have f(z) = 2πi C f(ζ) ζ z dζ. The circle C lies completely inside D. 35

36 The trick is to express the integrand f(ζ) ζ z in powers of z z 0 ζ z 0. Recall u = + u + u2 + + u n + un+ u. ζ z = ζ z 0 z z 0 = ζ z 0 ζ z 0 + z z 0 ζ z (z z 0) n (ζ z 0 ) n + We then multiply by f(ζ) 2πi and integrate along C. ( z z0 ζ z 0 ) n+ z z 0 ζ z 0. 36

37 By observing the property we obtain 2πi C f(ζ) (ζ z 0 ) k+ dζ = f(k) (z 0 ), k! f(z) = n k=0 where the remainder is given by f (k) (z) (z z 0 ) k + R n, k! R n = ( f(ζ) z z0 2πi C ζ z ζ z 0 To complete the proof, it suffices to show that lim n R n = 0. ) n+ dζ. (i) f(ζ) M for ζ C since f(z) is continuous inside D. (ii) ζ z = (ζ z 0 ) (z z 0 ) ζ z 0 z z 0 = R r 37

38 so that f(ζ) ζ z z z 0 ζ z 0 n+ M R r ( r R ) n+. Finally R n 2πi M R r ( r R ) n+ 2πR }{{} arc length = MR R r ( r R ) n+ 0 as n. The Taylor coefficients are given by a k = 2πi = 2πi C C f(ζ) dζ, k = 0,,2, (ζ z 0 ) k+ f(ζ) (ζ z 0 ) k+ dζ, where C is replaced by C and C is any simple closed contour enclosing z 0 and lying completely inside D [by virtue of Corollary 3 of the Cauchy-Goursat Theorem]. 38

39 Example Consider the function, the Taylor series at z = 0 is given by z z = n=0 z n, z <. The function has a singularity at z =. The maximum distance from z = 0 to the nearest singularity is one, so the radius of convergence is one. Alternatively, the radius of convergence can be found by the ratio test, where R = lim k a k a k+ =. 39

40 If we integrate along the contour C inside the circle of convergence z < from the origin to an arbitrary point z, we obtain C ζ dζ = Log( z) = n=0 n=0 C ζn dζ z n+ n + = n= The radius of convergence is again one (checked by the ratio test). y z n n. 0 x x C z x 40

41 Example Consider the Taylor series of the real function: + x 2 = x2 + x 4 x 6 + What is the interval of convergence? + x 2 The Taylor series converges only for x <. This is because the complex extension has singularities on the circle z = so + z2 that the radius of convergence of the infinite series n=0 ( ) n z 2n is one. The above infinite power series diverges for points outside the circle of convergence, including points on the real axis, where x >. When x =, the series becomes + with alternating terms. It is known to be divergent. 4

42 Example Find the Taylor expansion of f(z) = at z =. The function + z2 is analytic inside z < 2. + z 2 = 2i = 2i = ( z i z + i ) i + z n=0( ) n 2i i [ + i + z +i ( i) n+ ( + i) n+ ] (z ) n. By observing i = 2e iπ/4 and + i = 2e iπ/4, we obtain + z 2 = = n=0 n=0 ( ) nei(n+)π/4 e i(n+)π/4 (z ) n (2i)2 (n+)/2 ( ) nsin(n + )π 4 2 (n+)/2 (z )n. 42

43 Example Find the Maclaurin expansion of f(z) = (z + ) /2, where the principal branch of the function is used. Where is the expansion valid? Solution The required branch is identical to e 2 Log(z+), whose derivative is given by Deductively, we have e 2 Log(z+) 2(z + ) = (z + )/2 2(z + ). f (z) = 2 (z + ) 2, f (z) = 2 2 (z + ) 2 2,, f (n) (z) = ( ) [ ] 2 2 (n ) (z + ) 2 n, n, 2 where (z + ) 2 n = (z + ) 2 (z + ) n = e 2 Log(z+) (z + ) n. 43 ( )

44 The principal branch of Log(z+) is taken to have branch cut along the negative real axis with branch points at z = and z =. When z = 0, e 2 Log = so that the Maclaurin coefficients are c 0 =, c n = [( ) ( ) ( ) ( )] n! n, n. The singularity of (z+) /2 nearest to the origin is the branch point z =. Hence, the circle of convergence is z <. Remark An analytic branch of a multi-valued function can be expanded in a Taylor series about any point within the domain of analyticity of the branch, provided that one takes care to use this branch consistently in obtaining the coefficients of the series. 44

45 Laurent series Consider an infinite power series with negative power terms n= b n (z z 0 ) n, how to find the region of convergence? Set w =, the series z z 0 becomes exists, then n= b n w n, a Taylor series in w. Suppose R = lim n= b n w n converges for w < R z z 0 > R. b n n b n+ 45

46 Special cases: (i) R = 0 and (ii) R = 0. b n b n+. When R n = lim = 0, the infinite series b n n (z z 0 ) n n does not converge for any z, not even at z = z When R = lim n terms in n= b n+ b n = 0, we consider the ratio of successive b n w n and observe that lim n b n+ b n w < is satisfied for all w (except w = since the infinite series Σb n (z z 0 ) n is not defined at z = z 0 ). By virtue of the ratio test, the region of convergence is the whole complex plane except at z = z 0, that is, z z 0 > 0. 46

47 For the more general case (Laurent series at z 0 ) n=0 a n (z z 0 ) n + b n (z z 0 ) n, n= }{{} principal part a n a n+ suppose R = lim and n R = lim then inside the annular domain { z : b n n b n+ R < z z 0 < R the Laurent series is convergent. } exists, and RR >, When RR, the intersection of the two regions: z z 0 < R and z z 0 > R is the empty set. This is because the combination of z z 0 > R and RR implies z z 0 R, which contradicts with z z 0 < R. 47

48 The annulus degenerates into (i) hollow plane if R = (ii) punctured disc if R =. 48

49 Remarks. When R = 0, n=0 a n (z z 0 ) n does not converge for any z other than the trivial point z 0. However, z = z 0 is a singularity for the principal part. Actually, when R = 0, RR > can never be satisfied. 2. A Laurent series defines a function f(z) in its annular region of convergence. The Laurent series theorem states that a function analytic in an annulus can be expanded in a Laurent series expansion. 49

50 Laurent series theorem Let f(z) be analytic in the annulus A : R < z z 0 < R 2, then f(z) can be represented by the Laurent series, f(z) = k= c k (z z 0 ) k, which converges to f(z) throughout the annulus. The Laurent coefficients are given by c k = 2πi C f(ζ) dζ, k = 0, ±, ±2,, (ζ z 0 ) k+ where C is any simple closed contour lying completely inside the annulus and going around the point z 0. 50

51 Remarks. Suppose f(z) is analytic in the full disc: z z 0 < R 2 (without the punctured hole), then the integrand in calculating c k for negative k becomes analytic in z z 0 < R 2. Hence, c k = 0 for k =, 2,. The Laurent series is reduced to a Taylor series. 2. When k =, c = 2πi f(ζ) dζ. We may find c by any C means, so a contour integral can be evaluated without resort to direct integration. 5

52 Example The Laurent expansion of e /z at z = 0 is given by e /z = n=0 n!z n. The function e /z is analytic everywhere except at z = 0 so that the annulus of convergence is z > 0. We observe lim n b n+ b n n = lim /(n + )! /n! = 0 so that R = 0. Lastly, we consider C e/z dz, where the contour C is z =. Since C lies completely inside the punctured disc z > 0, we have C e/z dz = 2πi(coefficient of in Laurent expansion) = 2πi z 52

53 Example Find the Laurent expansion of ( f(z) = sin z ). z The function has a singularity at z = 0 so that the annulus of convergence is z > 0. The Laurent coefficient c n is given by c n = sin ( z z 2πi C z n+ dz, n = 0, ±, ±2, where C is chosen to be the unit circle z =. ) 53

54 Take z = e iθ so that dz = ie iθ dθ, then c n = 2πi = 2π π π π π sin(2isin θ)ie iθ e i(n+)θ dθ isinh(2sin θ)(cos nθ isin nθ) dθ. Note that sinh(2sin θ) is an odd function in θ, hence π sinh(2sin θ)cos nθ dθ = 0. Finally, c n = 2π π π π sinh(2sin θ)sin nθ dθ, n = 0, ±, ±2,. 54

55 Example Find the Laurent expansion of the function f(z) = z k that is valid inside the domain z > k, where k is real and k <. Using the Laurent expansion, deduce that n= n= k n cos nθ = k n sin nθ = kcos θ k 2 2k cos θ + k 2, ksin θ 2k cos θ + k 2. 55

56 Solution For z > k, where k <, we have z k = z ( k z = z ( ) + k z + k2 z 2 + y ) for z = e i k z <. k x 56

57 Take the point z = e iθ, which lies inside the region of convergence of the above Laurent series. Substituting into the infinite series e iθ k = e iθ( + ke iθ + k 2 e 2iθ + + k n e inθ + ). Rearranging the terms e iθ (e iθ k) (e iθ k)(e iθ k) = k(cos θ + isin θ) ( 2k cos θ + k2 ) 2kcos θ + k 2 = k cos θ k2 iksin θ 2kcos θ + k 2 = n= k n cos nθ i n= k n sin nθ. Equating the real and imaginary parts, we obtain the desired results. 57

58 Example By evaluating the contour integral show that Solution 2π 0 On z =, z = e iθ, I = z = ( z + ) 2n dz z z, cos 2n 3 5 (2n ) θ dθ = 2π n ( z + ) 2n = 2 2n cos 2n θ, dz z z = i dθ. ( z + ) 2n dz 2π z z = 22n i cos 2n θ dθ. 0 z = On the other hand, the integrand can be expanded as ( ) z 2n + 2n C z 2n n C n + + 2n C 2n z z 2n, 0 < z <. 58

59 Since the integrand is analytic everywhere except at z = 0, the above expansion is the Laurent series of the integrand valid in the annulus: z > 0. z = ( z + ) 2n dz z z = 2πi (coefficient of z ) in the Laurent series = 2πi 2n C n. Hence, 2π 0 cos 2n θ dθ = 2π 2n C n 2 2n = 2π (2n)! (n!) 2 2 2n = 2π 3 (2n )(2n n!) (2 n n!)(2 n n!) 3 (2n ) = 2π n. 59

60 The shaded region is z > 0. The circle C : z = lies completely inside the annulus of convergence and goes around z = 0. This is a punctured complex plane with a single deleted point. 60

61 Example Find all the possible Taylor and Laurent series expansions of f(z) = (z i)(z 2) at z 0 = 0. Specify the region of convergence (solid disc or annulus) of each of the above series. 6

62 Solution There are two isolated singularities, namely, at z = i and z = 2. The possible circular or annular regions of analyticity are (i) z <, (ii) < z < 2, (iii) z > 2. (i) For z < = i z i z ( i z 2 = 2 f(z) = i 2 = i 2 = i ) [ + z i + + ( z n = 2 z ( z i n=0 [ ( i i n ) + ] for z < ( ) [ + z ( ) z n ] ) = i i 2 z 2 ) n + 2 n+ n=0 ( z i ) n + 2 n=0 for z < 2 ( ) z n This is a Taylor series which converges inside the solid disc z <. ] z n. 2 62

63 (ii) For < z < 2 (iii) For z > 2 z i = z z i = z z 2 = f(z) = i 2 z n n=0 z i = n=0 n=0 ( i z ) n valid for z > 2 n+ valid for z < 2 n=0 z 2 = z 2 z f(z) = i 2 ( i n ) zn + zn+ 2 n+ valid for < z < 2. i n z n+ valid for z > = n=0 n=0 2 n z n+ valid for z > 2 (i n 2 n ) z n+ valid for z > 2. 63

64 Example Find all possible Laurent series of Solution f(z) = z 2 at the point α =. The function has two isolated singular points at z = and z =. There exist two annular regions (i) 0 < z + < 2 and (ii) z + > 2 where the function is analytic everywhere inside the respective region. 64

65 (i) 0 < z + < 2 z 2 = 2(z + ) ( z+ = = 2 ) (z + ) k 2(z + ) k=0 2(z + ) (z + ) (z + ) k The above expansion is valid provided z + 2 < and z+ 0. Given that 0 < z + < 2, the above requirement is satisfied. For any simple closed curve C lying completely inside z+ < 2 and encircling the point z =, we have c = 2πi C z 2 dz = 2. 65

66 (ii) z + > 2 z 2 = (z + ) 2 ( 2 = (z + ) 2 = [ k=0 z+ ) 2 k (z + ) k since 2 z + < (z + ) (z + ) (z + ) 4 + For any simple closed curve C 2 encircling the circle: z + = 2, we have c = dz = 0. 2πi C 2 z2 ]. 66

67 Example Suppose f(z) is analytic inside the annulus: r < z < r, r < and satisfies f as f(z) = ( ) z k= = f(z). Write the Laurent expansion of f(z) at z = 0 a k z k. Show that (a) a k = a k, (b) f(z) is real on z =. 67

68 Solution (a) Consider f f ( ) z ( ) z = f(z) = = f(z) a k = a k. k= k= a k z k = a k z k k= a k z k (b) It suffices to show f(z) = f(z) when z satisfies zz =. This is obviously satisfied from the given property f z lying inside the annulus: r < z < r. ( ) z = f(z), for all 68

69 Example From the Maclaurin series expansion of e z, it follows that the Laurent series expansion of e /z about 0 is e /z = The Laurent coefficients are n=0 z n, z > 0. n! e /z b n = dz 2πi C z n where C is chosen to be the circle z =. Such choice of C is feasible since the circle z = lies completely inside the annulus region of convergence of e /z and it goes around the point z = 0. By comparing the coefficients, we obtain C e /z z n dz = 2πi n!, n N. 69

70 On z =, z = e iθ, π θ π, so that the complex integral can be expressed as giving π π π exp(e iθ ) e ( n)iθ ieiθ dθ = π π ie(cos θ isin θ+inθ) dθ = 2πi n! π ecos θ [cos(nθ sin θ) + isin(nθ sin θ)] dθ = 2π n!. Comparing the real parts on both sides, we obtain π π ecos θ cos(nθ sin θ) dθ = 2π, for all n N. n! Equating the imaginary parts gives π π ecos θ sin(nθ sin θ) dθ = 0. The above result is obvious since the integrand e cos θ sin(nθ sin θ) is an odd function. 70

71 Classification of singularities and residue calculus Singular point of a function f(z) is a point at which f(z) is not analytic. Isolated singularity Existence of a neighborhood of z 0 in which z 0 is the only singular point of f(z). e.g. f(z) = z 2 + has ±i as isolated singularities. Singularities of csc z are all isolated and they are simply the zeros of sin z, namely, z = kπ, k is any integer. Non-isolated singularities f(z) = z is nowhere analytic so that every point in C is a non-isolated singularity. 7

72 Consider f(z) = csc π, all points z = /n, n = ±, ±2,, are isolated singularities, while the origin is a non-isolated z singularity. Suppose z 0 is an isolated singularity, then there exists a positive number R such that f(z) is analytic inside the deleted neighborhood 0 < z z 0 < R. This forms an annular domain within which the Laurent series theorem is applicable, where f(z) = n=0 a n (z z 0 ) n + n= b n (z z 0 ) n, 0 < z z 0 < R. The isolated singularity z 0 is classified according to the property of the principal part of the Laurent series expanded in the deleted neighborhood of z 0 where f is analytic. A singular point must be either a removable singularity, an essential singularity or a pole. 72

73 Removable singularity The principal part vanishes and the Laurent series is essentially a Taylor series. The series represents an analytic function in z z 0 < R. For example, cos z z 2 is undefined at z = 0. The Laurent expansion of cos z z 2 in a deleted neighborhood of z = 0 is cos z z 2 = z 2 = 2! z2 4! + z4 6! Note that lim z 0 cos z z 2 [ ( z2 2! + z4 4! +, 0 < z <, )] =. The singularity at z = 0 can be re- 2! moved by defining f(0) = 2. The function f(z) = { ( cos z)/z 2, z 0 /2, z = 0 admits the above Taylor series expansion valid for z <. 73

74 Essential singularity The principal part has infinitely many non-zero terms. For example, consider z 2 e /z. Inside the annular region 0 < z <, the Laurent series of z 2 e /z is z 2 e /z = z 2 + z + 2! + 3! z + +, 0 < z <. 4! z2 Pole of order k The Laurent expansion in the deleted neighborhood of z 0 is f(z) = n=0 a n (z z 0 ) n + b z z 0 + b 2 (z z 0 ) b k (z z 0 ) k, with b k 0. It is called a simple pole when k =. For example, z = ±i are simple poles of + z 2. 74

75 Example Observe that cos z z 5 = z 3 [ ] 2! z2 4! + z4 6!, 0 < z <, so that ( cos z)/z 5 has a pole of order 3 at z = 0. Example The function f(z) = has a pole of order 2 at z =. It z(z ) 2 admits the following Laurent expansion z(z ) 2 = (z ) 3 (z ) 4 + +, z >. (z ) 5 It is incorrect to conclude that z = is an essential singularity by observing that the above Laurent expansion has infinitely many negative power terms. This is because the annulus of convergence of the series is not a deleted neighborhood of z =. 75

76 Example The Laurent expansion n= z n + n=0 z n 2 n+ contains infinitely many negative power terms of z. Is z = 0 an essential singularity of the function represented by the series? /z The first sum converges to /z = for z > and the z /2 second sum converges to z/2 = for z < 2. 2 z Hence, the Laurent series converges to f(z) = z + 2 z = z 2 in < z < 2. 3z + 2 The annulus of convergence is not a deleted neighborhood of z = 0. Hence, we cannot make any claim about whether z = 0 is an essential singularity of f(z) simply through the examination of the above series. 76

77 Simple method of finding the order of a pole If z 0 is a pole of order k, then lim z z 0 (z z 0 ) k f(z) = b k, b k 0. In general, if we multiply f(z) by (z z 0 ) m and take the limit z z 0, then lim (z z z z 0 ) m f(z) = 0 For example, take f(z) = cos z z 5. cos z lim zm z 0 z 5 = b k m = k 0 m > k m < k 2 m = 3 0 m > 3 m < 3 Hence, z = 0 is a pole of order 3 of ( cos z)/z

78 Example Suppose z = 0 is a pole of order n and m, respectively, of the functions f (z) and f 2 (z), find the possible order of z = 0 as a pole for f (z) + f 2 (z). Without loss of generality, we assume n m. (i) When n > m f (z) = f 2 (z) = n k= m k= b () k z k + b (2) k z k + k=0 k=0 a () k zk, b () n 0, a (2) k zk, b (2) m 0, so f (z) + f 2 (z) must contain negative power terms up to z n. (ii) When n = m, in general, z = 0 is a pole of order n for f (z) + f 2 (z). However, it is possible that f (z) = f 2 (z)+ zl,0 l n. In this case, z = 0 is a pole of order l. When l = 0, z = 0 is not an isolated singularity. 78

79 Behavior of f near isolated singularities. If z 0 is a pole of f, then lim z z 0 f(z) =. To show the claim, suppose f has a pole of order m at z 0, then f(z) = φ(z) (z z 0 ) m where φ(z) is analytic and non-zero at z 0. Since lim z z 0 f(z) = z z lim (z z 0 ) m 0 φ(z) = lim (z z z z 0 ) m 0 lim φ(z) z z 0 = 0 φ(z 0 ) = 0, hence lim z z0 f(z) =. 79

80 2. If z 0 is a removable singularity of f, then f admits a Taylor series in some deleted neighborhood 0 < z z 0 < δ of z 0, so it is analytic and bounded in that neighborhood. 3. In each deleted neighborhood of an essential singularity, the function assumes values that come arbitrarily close to any given number. Casorati-Weierstrass Theorem Suppose that z 0 is an essential singularity of a function f, and let w 0 be any complex number. Then, for any positive number ǫ, f(z) w 0 < ǫ (A) is satisfied at some point z in each deleted neighborhood of z 0. 80

81 Proof Take any deleted neighborhood of z 0. Since z 0 is an isolated singularity, the neighborhood itself or a subset of which will have the property that f is analytic inside 0 < z z 0 < δ for some value of δ. Assume that inequality (A) is not satisfied for any z in the neighborhood 0 < z z 0 < δ (inside which f is analytic). Thus, Define f(z) w 0 ǫ when 0 < z z 0 < δ. g(z) = f(z) w 0, 0 < z z 0 < δ, which is bounded and analytic. Hence, z 0 is a removable singularity of g. We let g be defined at z 0 such that it is analytic there. We use the following result: Suppose f is analytic and bounded in 0 < z z 0 < ǫ. If f is not analytic at z 0, then it has a removable singularity at z 0. 8

82 We consider the following two cases: (i) If g(z 0 ) 0, then f(z) = g(z) + w 0, 0 < z z 0 < δ, (B) becomes analytic at z 0 if f(z 0 ) = g(z 0 ) + w 0. This means that z 0 is a removable singularity of f, not an essential one. We have a contradiction. (ii) If g(z 0 ) = 0, then g must have a zero of some finite order m at z 0 since g(z) is not identically equal to zero in the neighborhood z z 0 < δ. Write g(z) = (z z 0 ) m ψ(z 0 ), where ψ(z 0 ) 0. In this case, f has a pole of order m since lim f(z)(z z z z 0 ) m (z z = lim 0 ) m 0 z z0 g(z) which is finite. Again, there is a contradiction. = ψ(z 0 ) 82

83 Example Classify the zeros and singularities of the function sin( z ). Solution Since the zeros of sin w occur only when w is an integer multiple of π, the function sin( z ) has zeros when z = nπ, i.e., at z =, n = 0, ±, ±2,. nπ 83

84 Furthermore, the zeros are simple because the derivative at these points is d dz sin( z ) z=( nπ) = z 2 cos( z ) = ( nπ) 2 cos nπ 0. z=( nπ) The only singularity of sin( z ) appears at z = 0. Suppose we let z approach 0 through positive values, sin( z ) oscillates between ±. Such behavior can only characterize an essential singularity. 84

4. Complex integration: Cauchy integral theorem and Cauchy integral formulas. Definite integral of a complex-valued function of a real variable

4. Complex integration: Cauchy integral theorem and Cauchy integral formulas. Definite integral of a complex-valued function of a real variable 4. Complex integration: Cauchy integral theorem and Cauchy integral formulas Definite integral of a complex-valued function of a real variable Consider a complex valued function f(t) of a real variable

More information

6. Define log(z) so that π < I log(z) π. Discuss the identities e log(z) = z and log(e w ) = w.

6. Define log(z) so that π < I log(z) π. Discuss the identities e log(z) = z and log(e w ) = w. hapter omplex integration. omplex number quiz. Simplify 3+4i. 2. Simplify 3+4i. 3. Find the cube roots of. 4. Here are some identities for complex conjugate. Which ones need correction? z + w = z + w,

More information

1 if 1 x 0 1 if 0 x 1

1 if 1 x 0 1 if 0 x 1 Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or

More information

5.3 Improper Integrals Involving Rational and Exponential Functions

5.3 Improper Integrals Involving Rational and Exponential Functions Section 5.3 Improper Integrals Involving Rational and Exponential Functions 99.. 3. 4. dθ +a cos θ =, < a

More information

DEFINITION 5.1.1 A complex number is a matrix of the form. x y. , y x

DEFINITION 5.1.1 A complex number is a matrix of the form. x y. , y x Chapter 5 COMPLEX NUMBERS 5.1 Constructing the complex numbers One way of introducing the field C of complex numbers is via the arithmetic of matrices. DEFINITION 5.1.1 A complex number is a matrix of

More information

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e. CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e. This chapter contains the beginnings of the most important, and probably the most subtle, notion in mathematical analysis, i.e.,

More information

Metric Spaces. Chapter 7. 7.1. Metrics

Metric Spaces. Chapter 7. 7.1. Metrics Chapter 7 Metric Spaces A metric space is a set X that has a notion of the distance d(x, y) between every pair of points x, y X. The purpose of this chapter is to introduce metric spaces and give some

More information

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics Undergraduate Notes in Mathematics Arkansas Tech University Department of Mathematics An Introductory Single Variable Real Analysis: A Learning Approach through Problem Solving Marcel B. Finan c All Rights

More information

Solutions to Homework 10

Solutions to Homework 10 Solutions to Homework 1 Section 7., exercise # 1 (b,d): (b) Compute the value of R f dv, where f(x, y) = y/x and R = [1, 3] [, 4]. Solution: Since f is continuous over R, f is integrable over R. Let x

More information

Lectures 5-6: Taylor Series

Lectures 5-6: Taylor Series Math 1d Instructor: Padraic Bartlett Lectures 5-: Taylor Series Weeks 5- Caltech 213 1 Taylor Polynomials and Series As we saw in week 4, power series are remarkably nice objects to work with. In particular,

More information

x a x 2 (1 + x 2 ) n.

x a x 2 (1 + x 2 ) n. Limits and continuity Suppose that we have a function f : R R. Let a R. We say that f(x) tends to the limit l as x tends to a; lim f(x) = l ; x a if, given any real number ɛ > 0, there exists a real number

More information

Mathematical Methods of Engineering Analysis

Mathematical Methods of Engineering Analysis Mathematical Methods of Engineering Analysis Erhan Çinlar Robert J. Vanderbei February 2, 2000 Contents Sets and Functions 1 1 Sets................................... 1 Subsets.............................

More information

TOPIC 4: DERIVATIVES

TOPIC 4: DERIVATIVES TOPIC 4: DERIVATIVES 1. The derivative of a function. Differentiation rules 1.1. The slope of a curve. The slope of a curve at a point P is a measure of the steepness of the curve. If Q is a point on the

More information

3 Contour integrals and Cauchy s Theorem

3 Contour integrals and Cauchy s Theorem 3 ontour integrals and auchy s Theorem 3. Line integrals of complex functions Our goal here will be to discuss integration of complex functions = u + iv, with particular regard to analytic functions. Of

More information

n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n + 1 +...

n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n + 1 +... 6 Series We call a normed space (X, ) a Banach space provided that every Cauchy sequence (x n ) in X converges. For example, R with the norm = is an example of Banach space. Now let (x n ) be a sequence

More information

MATH 52: MATLAB HOMEWORK 2

MATH 52: MATLAB HOMEWORK 2 MATH 52: MATLAB HOMEWORK 2. omplex Numbers The prevalence of the complex numbers throughout the scientific world today belies their long and rocky history. Much like the negative numbers, complex numbers

More information

2 Fourier Analysis and Analytic Functions

2 Fourier Analysis and Analytic Functions 2 Fourier Analysis and Analytic Functions 2.1 Trigonometric Series One of the most important tools for the investigation of linear systems is Fourier analysis. Let f L 1 be a complex-valued Lebesgue-integrable

More information

A power series about x = a is the series of the form

A power series about x = a is the series of the form POWER SERIES AND THE USES OF POWER SERIES Elizabeth Wood Now we are finally going to start working with a topic that uses all of the information from the previous topics. The topic that we are going to

More information

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A RAJALAKSHMI ENGINEERING COLLEGE MA 26 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS. Solve (D 2 + D 2)y = 0. 2. Solve (D 2 + 6D + 9)y = 0. PART A 3. Solve (D 4 + 4)x = 0 where D = d dt 4. Find Particular Integral:

More information

MOP 2007 Black Group Integer Polynomials Yufei Zhao. Integer Polynomials. June 29, 2007 Yufei Zhao yufeiz@mit.edu

MOP 2007 Black Group Integer Polynomials Yufei Zhao. Integer Polynomials. June 29, 2007 Yufei Zhao yufeiz@mit.edu Integer Polynomials June 9, 007 Yufei Zhao yufeiz@mit.edu We will use Z[x] to denote the ring of polynomials with integer coefficients. We begin by summarizing some of the common approaches used in dealing

More information

Complex Function Theory. Second Edition. Donald Sarason >AMS AMERICAN MATHEMATICAL SOCIETY

Complex Function Theory. Second Edition. Donald Sarason >AMS AMERICAN MATHEMATICAL SOCIETY Complex Function Theory Second Edition Donald Sarason >AMS AMERICAN MATHEMATICAL SOCIETY Contents Preface to the Second Edition Preface to the First Edition ix xi Chapter I. Complex Numbers 1 1.1. Definition

More information

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

More information

Taylor and Maclaurin Series

Taylor and Maclaurin Series Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions

More information

sin(x) < x sin(x) x < tan(x) sin(x) x cos(x) 1 < sin(x) sin(x) 1 < 1 cos(x) 1 cos(x) = 1 cos2 (x) 1 + cos(x) = sin2 (x) 1 < x 2

sin(x) < x sin(x) x < tan(x) sin(x) x cos(x) 1 < sin(x) sin(x) 1 < 1 cos(x) 1 cos(x) = 1 cos2 (x) 1 + cos(x) = sin2 (x) 1 < x 2 . Problem Show that using an ɛ δ proof. sin() lim = 0 Solution: One can see that the following inequalities are true for values close to zero, both positive and negative. This in turn implies that On the

More information

LIMITS AND CONTINUITY

LIMITS AND CONTINUITY LIMITS AND CONTINUITY 1 The concept of it Eample 11 Let f() = 2 4 Eamine the behavior of f() as approaches 2 2 Solution Let us compute some values of f() for close to 2, as in the tables below We see from

More information

Practice Final Math 122 Spring 12 Instructor: Jeff Lang

Practice Final Math 122 Spring 12 Instructor: Jeff Lang Practice Final Math Spring Instructor: Jeff Lang. Find the limit of the sequence a n = ln (n 5) ln (3n + 8). A) ln ( ) 3 B) ln C) ln ( ) 3 D) does not exist. Find the limit of the sequence a n = (ln n)6

More information

MATH 132: CALCULUS II SYLLABUS

MATH 132: CALCULUS II SYLLABUS MATH 32: CALCULUS II SYLLABUS Prerequisites: Successful completion of Math 3 (or its equivalent elsewhere). Math 27 is normally not a sufficient prerequisite for Math 32. Required Text: Calculus: Early

More information

DRAFT. Further mathematics. GCE AS and A level subject content

DRAFT. Further mathematics. GCE AS and A level subject content Further mathematics GCE AS and A level subject content July 2014 s Introduction Purpose Aims and objectives Subject content Structure Background knowledge Overarching themes Use of technology Detailed

More information

Understanding Poles and Zeros

Understanding Poles and Zeros MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MECHANICAL ENGINEERING 2.14 Analysis and Design of Feedback Control Systems Understanding Poles and Zeros 1 System Poles and Zeros The transfer function

More information

The Math Circle, Spring 2004

The Math Circle, Spring 2004 The Math Circle, Spring 2004 (Talks by Gordon Ritter) What is Non-Euclidean Geometry? Most geometries on the plane R 2 are non-euclidean. Let s denote arc length. Then Euclidean geometry arises from the

More information

How To Prove The Dirichlet Unit Theorem

How To Prove The Dirichlet Unit Theorem Chapter 6 The Dirichlet Unit Theorem As usual, we will be working in the ring B of algebraic integers of a number field L. Two factorizations of an element of B are regarded as essentially the same if

More information

Sequences and Series

Sequences and Series Sequences and Series Consider the following sum: 2 + 4 + 8 + 6 + + 2 i + The dots at the end indicate that the sum goes on forever. Does this make sense? Can we assign a numerical value to an infinite

More information

3. Reaction Diffusion Equations Consider the following ODE model for population growth

3. Reaction Diffusion Equations Consider the following ODE model for population growth 3. Reaction Diffusion Equations Consider the following ODE model for population growth u t a u t u t, u 0 u 0 where u t denotes the population size at time t, and a u plays the role of the population dependent

More information

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)! Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following

More information

4.5 Linear Dependence and Linear Independence

4.5 Linear Dependence and Linear Independence 4.5 Linear Dependence and Linear Independence 267 32. {v 1, v 2 }, where v 1, v 2 are collinear vectors in R 3. 33. Prove that if S and S are subsets of a vector space V such that S is a subset of S, then

More information

Lies My Calculator and Computer Told Me

Lies My Calculator and Computer Told Me Lies My Calculator and Computer Told Me 2 LIES MY CALCULATOR AND COMPUTER TOLD ME Lies My Calculator and Computer Told Me See Section.4 for a discussion of graphing calculators and computers with graphing

More information

Reference: Introduction to Partial Differential Equations by G. Folland, 1995, Chap. 3.

Reference: Introduction to Partial Differential Equations by G. Folland, 1995, Chap. 3. 5 Potential Theory Reference: Introduction to Partial Differential Equations by G. Folland, 995, Chap. 3. 5. Problems of Interest. In what follows, we consider Ω an open, bounded subset of R n with C 2

More information

Numerical Analysis Lecture Notes

Numerical Analysis Lecture Notes Numerical Analysis Lecture Notes Peter J. Olver 5. Inner Products and Norms The norm of a vector is a measure of its size. Besides the familiar Euclidean norm based on the dot product, there are a number

More information

General Theory of Differential Equations Sections 2.8, 3.1-3.2, 4.1

General Theory of Differential Equations Sections 2.8, 3.1-3.2, 4.1 A B I L E N E C H R I S T I A N U N I V E R S I T Y Department of Mathematics General Theory of Differential Equations Sections 2.8, 3.1-3.2, 4.1 Dr. John Ehrke Department of Mathematics Fall 2012 Questions

More information

2. Length and distance in hyperbolic geometry

2. Length and distance in hyperbolic geometry 2. Length and distance in hyperbolic geometry 2.1 The upper half-plane There are several different ways of constructing hyperbolic geometry. These different constructions are called models. In this lecture

More information

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS STEVEN P. LALLEY AND ANDREW NOBEL Abstract. It is shown that there are no consistent decision rules for the hypothesis testing problem

More information

U.C. Berkeley CS276: Cryptography Handout 0.1 Luca Trevisan January, 2009. Notes on Algebra

U.C. Berkeley CS276: Cryptography Handout 0.1 Luca Trevisan January, 2009. Notes on Algebra U.C. Berkeley CS276: Cryptography Handout 0.1 Luca Trevisan January, 2009 Notes on Algebra These notes contain as little theory as possible, and most results are stated without proof. Any introductory

More information

ON DEGREE OF APPROXIMATION ON A JORDAN CURVE TO A FUNCTION ANALYTIC INTERIOR TO THE CURVE BY FUNCTIONS NOT NECESSARILY ANALYTIC INTERIOR TO THE CURVE

ON DEGREE OF APPROXIMATION ON A JORDAN CURVE TO A FUNCTION ANALYTIC INTERIOR TO THE CURVE BY FUNCTIONS NOT NECESSARILY ANALYTIC INTERIOR TO THE CURVE ON DEGREE OF APPROXIMATION ON A JORDAN CURVE TO A FUNCTION ANALYTIC INTERIOR TO THE CURVE BY FUNCTIONS NOT NECESSARILY ANALYTIC INTERIOR TO THE CURVE J. L. WALSH It is our object here to consider the subject

More information

The General Cauchy Theorem

The General Cauchy Theorem Chapter 3 The General Cauchy Theorem In this chapter, we consider two basic questions. First, for a given open set Ω, we try to determine which closed paths in Ω have the property that f(z) dz = 0for every

More information

COMPLEX NUMBERS AND SERIES. Contents

COMPLEX NUMBERS AND SERIES. Contents COMPLEX NUMBERS AND SERIES MIKE BOYLE Contents 1. Complex Numbers Definition 1.1. A complex number is a number z of the form z = x + iy, where x and y are real numbers, and i is another number such that

More information

MATH 381 HOMEWORK 2 SOLUTIONS

MATH 381 HOMEWORK 2 SOLUTIONS MATH 38 HOMEWORK SOLUTIONS Question (p.86 #8). If g(x)[e y e y ] is harmonic, g() =,g () =, find g(x). Let f(x, y) = g(x)[e y e y ].Then Since f(x, y) is harmonic, f + f = and we require x y f x = g (x)[e

More information

Notes on metric spaces

Notes on metric spaces Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.

More information

Metric Spaces Joseph Muscat 2003 (Last revised May 2009)

Metric Spaces Joseph Muscat 2003 (Last revised May 2009) 1 Distance J Muscat 1 Metric Spaces Joseph Muscat 2003 (Last revised May 2009) (A revised and expanded version of these notes are now published by Springer.) 1 Distance A metric space can be thought of

More information

FEGYVERNEKI SÁNDOR, PROBABILITY THEORY AND MATHEmATICAL

FEGYVERNEKI SÁNDOR, PROBABILITY THEORY AND MATHEmATICAL FEGYVERNEKI SÁNDOR, PROBABILITY THEORY AND MATHEmATICAL STATIsTICs 4 IV. RANDOm VECTORs 1. JOINTLY DIsTRIBUTED RANDOm VARIABLEs If are two rom variables defined on the same sample space we define the joint

More information

FIRST YEAR CALCULUS. Chapter 7 CONTINUITY. It is a parabola, and we can draw this parabola without lifting our pencil from the paper.

FIRST YEAR CALCULUS. Chapter 7 CONTINUITY. It is a parabola, and we can draw this parabola without lifting our pencil from the paper. FIRST YEAR CALCULUS WWLCHENW L c WWWL W L Chen, 1982, 2008. 2006. This chapter originates from material used by the author at Imperial College, University of London, between 1981 and 1990. It It is is

More information

DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents

DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents DIFFERENTIABILITY OF COMPLEX FUNCTIONS Contents 1. Limit definition of a derivative 1 2. Holomorphic functions, the Cauchy-Riemann equations 3 3. Differentiability of real functions 5 4. A sufficient condition

More information

Estimated Pre Calculus Pacing Timeline

Estimated Pre Calculus Pacing Timeline Estimated Pre Calculus Pacing Timeline 2010-2011 School Year The timeframes listed on this calendar are estimates based on a fifty-minute class period. You may need to adjust some of them from time to

More information

Algebra 2 Chapter 1 Vocabulary. identity - A statement that equates two equivalent expressions.

Algebra 2 Chapter 1 Vocabulary. identity - A statement that equates two equivalent expressions. Chapter 1 Vocabulary identity - A statement that equates two equivalent expressions. verbal model- A word equation that represents a real-life problem. algebraic expression - An expression with variables.

More information

www.mathsbox.org.uk ab = c a If the coefficients a,b and c are real then either α and β are real or α and β are complex conjugates

www.mathsbox.org.uk ab = c a If the coefficients a,b and c are real then either α and β are real or α and β are complex conjugates Further Pure Summary Notes. Roots of Quadratic Equations For a quadratic equation ax + bx + c = 0 with roots α and β Sum of the roots Product of roots a + b = b a ab = c a If the coefficients a,b and c

More information

MATH 4330/5330, Fourier Analysis Section 11, The Discrete Fourier Transform

MATH 4330/5330, Fourier Analysis Section 11, The Discrete Fourier Transform MATH 433/533, Fourier Analysis Section 11, The Discrete Fourier Transform Now, instead of considering functions defined on a continuous domain, like the interval [, 1) or the whole real line R, we wish

More information

CONTRIBUTIONS TO ZERO SUM PROBLEMS

CONTRIBUTIONS TO ZERO SUM PROBLEMS CONTRIBUTIONS TO ZERO SUM PROBLEMS S. D. ADHIKARI, Y. G. CHEN, J. B. FRIEDLANDER, S. V. KONYAGIN AND F. PAPPALARDI Abstract. A prototype of zero sum theorems, the well known theorem of Erdős, Ginzburg

More information

a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.

a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2. Chapter 1 LINEAR EQUATIONS 1.1 Introduction to linear equations A linear equation in n unknowns x 1, x,, x n is an equation of the form a 1 x 1 + a x + + a n x n = b, where a 1, a,..., a n, b are given

More information

Inner Product Spaces

Inner Product Spaces Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and

More information

10.2 Series and Convergence

10.2 Series and Convergence 10.2 Series and Convergence Write sums using sigma notation Find the partial sums of series and determine convergence or divergence of infinite series Find the N th partial sums of geometric series and

More information

ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE

ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE i93 c J SYSTEMS OF CURVES 695 ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE BY C H. ROWE. Introduction. A system of co 2 curves having been given on a surface, let us consider a variable curvilinear

More information

Mathematics Course 111: Algebra I Part IV: Vector Spaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are

More information

An example of a computable

An example of a computable An example of a computable absolutely normal number Verónica Becher Santiago Figueira Abstract The first example of an absolutely normal number was given by Sierpinski in 96, twenty years before the concept

More information

Real Roots of Univariate Polynomials with Real Coefficients

Real Roots of Univariate Polynomials with Real Coefficients Real Roots of Univariate Polynomials with Real Coefficients mostly written by Christina Hewitt March 22, 2012 1 Introduction Polynomial equations are used throughout mathematics. When solving polynomials

More information

Mathematics for Econometrics, Fourth Edition

Mathematics for Econometrics, Fourth Edition Mathematics for Econometrics, Fourth Edition Phoebus J. Dhrymes 1 July 2012 1 c Phoebus J. Dhrymes, 2012. Preliminary material; not to be cited or disseminated without the author s permission. 2 Contents

More information

Practice with Proofs

Practice with Proofs Practice with Proofs October 6, 2014 Recall the following Definition 0.1. A function f is increasing if for every x, y in the domain of f, x < y = f(x) < f(y) 1. Prove that h(x) = x 3 is increasing, using

More information

Roots of Polynomials

Roots of Polynomials Roots of Polynomials (Com S 477/577 Notes) Yan-Bin Jia Sep 24, 2015 A direct corollary of the fundamental theorem of algebra is that p(x) can be factorized over the complex domain into a product a n (x

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete

More information

Representation of functions as power series

Representation of functions as power series Representation of functions as power series Dr. Philippe B. Laval Kennesaw State University November 9, 008 Abstract This document is a summary of the theory and techniques used to represent functions

More information

MA4001 Engineering Mathematics 1 Lecture 10 Limits and Continuity

MA4001 Engineering Mathematics 1 Lecture 10 Limits and Continuity MA4001 Engineering Mathematics 1 Lecture 10 Limits and Dr. Sarah Mitchell Autumn 2014 Infinite limits If f(x) grows arbitrarily large as x a we say that f(x) has an infinite limit. Example: f(x) = 1 x

More information

About the Gamma Function

About the Gamma Function About the Gamma Function Notes for Honors Calculus II, Originally Prepared in Spring 995 Basic Facts about the Gamma Function The Gamma function is defined by the improper integral Γ) = The integral is

More information

BANACH AND HILBERT SPACE REVIEW

BANACH AND HILBERT SPACE REVIEW BANACH AND HILBET SPACE EVIEW CHISTOPHE HEIL These notes will briefly review some basic concepts related to the theory of Banach and Hilbert spaces. We are not trying to give a complete development, but

More information

PUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5.

PUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5. PUTNAM TRAINING POLYNOMIALS (Last updated: November 17, 2015) Remark. This is a list of exercises on polynomials. Miguel A. Lerma Exercises 1. Find a polynomial with integral coefficients whose zeros include

More information

36 CHAPTER 1. LIMITS AND CONTINUITY. Figure 1.17: At which points is f not continuous?

36 CHAPTER 1. LIMITS AND CONTINUITY. Figure 1.17: At which points is f not continuous? 36 CHAPTER 1. LIMITS AND CONTINUITY 1.3 Continuity Before Calculus became clearly de ned, continuity meant that one could draw the graph of a function without having to lift the pen and pencil. While this

More information

88 CHAPTER 2. VECTOR FUNCTIONS. . First, we need to compute T (s). a By definition, r (s) T (s) = 1 a sin s a. sin s a, cos s a

88 CHAPTER 2. VECTOR FUNCTIONS. . First, we need to compute T (s). a By definition, r (s) T (s) = 1 a sin s a. sin s a, cos s a 88 CHAPTER. VECTOR FUNCTIONS.4 Curvature.4.1 Definitions and Examples The notion of curvature measures how sharply a curve bends. We would expect the curvature to be 0 for a straight line, to be very small

More information

The Graphical Method: An Example

The Graphical Method: An Example The Graphical Method: An Example Consider the following linear program: Maximize 4x 1 +3x 2 Subject to: 2x 1 +3x 2 6 (1) 3x 1 +2x 2 3 (2) 2x 2 5 (3) 2x 1 +x 2 4 (4) x 1, x 2 0, where, for ease of reference,

More information

1 Introduction. Linear Programming. Questions. A general optimization problem is of the form: choose x to. max f(x) subject to x S. where.

1 Introduction. Linear Programming. Questions. A general optimization problem is of the form: choose x to. max f(x) subject to x S. where. Introduction Linear Programming Neil Laws TT 00 A general optimization problem is of the form: choose x to maximise f(x) subject to x S where x = (x,..., x n ) T, f : R n R is the objective function, S

More information

Lecture Notes on Polynomials

Lecture Notes on Polynomials Lecture Notes on Polynomials Arne Jensen Department of Mathematical Sciences Aalborg University c 008 Introduction These lecture notes give a very short introduction to polynomials with real and complex

More information

Mathematical Induction

Mathematical Induction Mathematical Induction (Handout March 8, 01) The Principle of Mathematical Induction provides a means to prove infinitely many statements all at once The principle is logical rather than strictly mathematical,

More information

Prime numbers and prime polynomials. Paul Pollack Dartmouth College

Prime numbers and prime polynomials. Paul Pollack Dartmouth College Prime numbers and prime polynomials Paul Pollack Dartmouth College May 1, 2008 Analogies everywhere! Analogies in elementary number theory (continued fractions, quadratic reciprocity, Fermat s last theorem)

More information

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all.

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all. 1. Differentiation The first derivative of a function measures by how much changes in reaction to an infinitesimal shift in its argument. The largest the derivative (in absolute value), the faster is evolving.

More information

Properties of BMO functions whose reciprocals are also BMO

Properties of BMO functions whose reciprocals are also BMO Properties of BMO functions whose reciprocals are also BMO R. L. Johnson and C. J. Neugebauer The main result says that a non-negative BMO-function w, whose reciprocal is also in BMO, belongs to p> A p,and

More information

Answer Key for California State Standards: Algebra I

Answer Key for California State Standards: Algebra I Algebra I: Symbolic reasoning and calculations with symbols are central in algebra. Through the study of algebra, a student develops an understanding of the symbolic language of mathematics and the sciences.

More information

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES I GROUPS: BASIC DEFINITIONS AND EXAMPLES Definition 1: An operation on a set G is a function : G G G Definition 2: A group is a set G which is equipped with an operation and a special element e G, called

More information

Preliminary Version: December 1998

Preliminary Version: December 1998 On the Number of Prime Numbers less than a Given Quantity. (Ueber die Anzahl der Primzahlen unter einer gegebenen Grösse.) Bernhard Riemann [Monatsberichte der Berliner Akademie, November 859.] Translated

More information

Probability Generating Functions

Probability Generating Functions page 39 Chapter 3 Probability Generating Functions 3 Preamble: Generating Functions Generating functions are widely used in mathematics, and play an important role in probability theory Consider a sequence

More information

Cardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set.

Cardinality. The set of all finite strings over the alphabet of lowercase letters is countable. The set of real numbers R is an uncountable set. Section 2.5 Cardinality (another) Definition: The cardinality of a set A is equal to the cardinality of a set B, denoted A = B, if and only if there is a bijection from A to B. If there is an injection

More information

INTRODUCTORY SET THEORY

INTRODUCTORY SET THEORY M.Sc. program in mathematics INTRODUCTORY SET THEORY Katalin Károlyi Department of Applied Analysis, Eötvös Loránd University H-1088 Budapest, Múzeum krt. 6-8. CONTENTS 1. SETS Set, equal sets, subset,

More information

NOV - 30211/II. 1. Let f(z) = sin z, z C. Then f(z) : 3. Let the sequence {a n } be given. (A) is bounded in the complex plane

NOV - 30211/II. 1. Let f(z) = sin z, z C. Then f(z) : 3. Let the sequence {a n } be given. (A) is bounded in the complex plane Mathematical Sciences Paper II Time Allowed : 75 Minutes] [Maximum Marks : 100 Note : This Paper contains Fifty (50) multiple choice questions. Each question carries Two () marks. Attempt All questions.

More information

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS KEITH CONRAD 1. Introduction The Fundamental Theorem of Algebra says every nonconstant polynomial with complex coefficients can be factored into linear

More information

THE SINE PRODUCT FORMULA AND THE GAMMA FUNCTION

THE SINE PRODUCT FORMULA AND THE GAMMA FUNCTION THE SINE PRODUCT FORMULA AND THE GAMMA FUNCTION ERICA CHAN DECEMBER 2, 2006 Abstract. The function sin is very important in mathematics and has many applications. In addition to its series epansion, it

More information

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 A. Miller 1. Introduction. The definitions of metric space and topological space were developed in the early 1900 s, largely

More information

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1. MATH10212 Linear Algebra Textbook: D. Poole, Linear Algebra: A Modern Introduction. Thompson, 2006. ISBN 0-534-40596-7. Systems of Linear Equations Definition. An n-dimensional vector is a row or a column

More information

What is Linear Programming?

What is Linear Programming? Chapter 1 What is Linear Programming? An optimization problem usually has three essential ingredients: a variable vector x consisting of a set of unknowns to be determined, an objective function of x to

More information

Doug Ravenel. October 15, 2008

Doug Ravenel. October 15, 2008 Doug Ravenel University of Rochester October 15, 2008 s about Euclid s Some s about primes that every mathematician should know (Euclid, 300 BC) There are infinitely numbers. is very elementary, and we

More information

MA107 Precalculus Algebra Exam 2 Review Solutions

MA107 Precalculus Algebra Exam 2 Review Solutions MA107 Precalculus Algebra Exam 2 Review Solutions February 24, 2008 1. The following demand equation models the number of units sold, x, of a product as a function of price, p. x = 4p + 200 a. Please write

More information

Mechanics 1: Conservation of Energy and Momentum

Mechanics 1: Conservation of Energy and Momentum Mechanics : Conservation of Energy and Momentum If a certain quantity associated with a system does not change in time. We say that it is conserved, and the system possesses a conservation law. Conservation

More information

The Mean Value Theorem

The Mean Value Theorem The Mean Value Theorem THEOREM (The Extreme Value Theorem): If f is continuous on a closed interval [a, b], then f attains an absolute maximum value f(c) and an absolute minimum value f(d) at some numbers

More information

Rotation Rate of a Trajectory of an Algebraic Vector Field Around an Algebraic Curve

Rotation Rate of a Trajectory of an Algebraic Vector Field Around an Algebraic Curve QUALITATIVE THEORY OF DYAMICAL SYSTEMS 2, 61 66 (2001) ARTICLE O. 11 Rotation Rate of a Trajectory of an Algebraic Vector Field Around an Algebraic Curve Alexei Grigoriev Department of Mathematics, The

More information

Adaptive Online Gradient Descent

Adaptive Online Gradient Descent Adaptive Online Gradient Descent Peter L Bartlett Division of Computer Science Department of Statistics UC Berkeley Berkeley, CA 94709 bartlett@csberkeleyedu Elad Hazan IBM Almaden Research Center 650

More information

Homework # 3 Solutions

Homework # 3 Solutions Homework # 3 Solutions February, 200 Solution (2.3.5). Noting that and ( + 3 x) x 8 = + 3 x) by Equation (2.3.) x 8 x 8 = + 3 8 by Equations (2.3.7) and (2.3.0) =3 x 8 6x2 + x 3 ) = 2 + 6x 2 + x 3 x 8

More information