The wave equation is an important tool to study the relation between spectral theory and geometry on manifolds. Let U R n be an open set and let

Size: px
Start display at page:

Download "The wave equation is an important tool to study the relation between spectral theory and geometry on manifolds. Let U R n be an open set and let"

Transcription

1 1. The wave equation The wave equation is an important tool to stuy the relation between spectral theory an geometry on manifols. Let U R n be an open set an let = n j=1 be the Eucliean Laplace operator. Then the wave equation on U is the following ifferential equation. ( ) 2 t u(x,t) = f(x,t), 2 u(x,0) =u 0 (x), Here f,u 0 an u 1 are given functions The wave equation on R n. 2 x 2 j u(x,t) = 0, x U, t > 0. t (x,0) = u 1(x). To unerstan the behavior of the solution of the wave equation we consier first the wave equation on the real line. On R we consier the following equation ( ) 2 t 2 u(x,t) = 0, 2 x 2 where g,h C 2 (R). u(x,0) = g(x), (x,0) = h(x), t The first equation can be factore as follows ( )( ) t + x t u = 0. x Put Then we get ( ) v(x,t): = t u(x,t). x t v(x,t)+ x v(x,t) = 0, x R, t > 0. 1

2 2 This is a transport equation with constant coefficients. To solve this equation, we apply the Fourier transform with respect to x. Let ˆv(ξ,t): = e iξx v(x,t)x. Then we have The solution is given by Hence we have Let a(x) = v(x,0). Then we get R = 0. tˆv(ξ,t)+iξˆv(ξ,t) ˆv(ξ,t) = e itξˆv(ξ,0). v(x,t) = v(x t,0). t u(x,t) u(x,t) = a(x t), x R, t > 0. x this is a non-homogeneous transport equation. It can be solve by a similar metho. The result is u(x,t) = If we use the inatrial conitions t 0 = 1 2 u(x,0) = g(x) an u t (x,0) = h(x), we get a(x+(t s) s) s+u(x+t,0) x+t x t a(y)y+u(x+t,0). a(x) = v(x,0) = u t (x,0) u x (x,0) = h(x) g (x) Inserting this formula for a in the above equation, we obtain the following final form for the solution (6.1) u(x,t) = 1 2 [g(x+t)+g(x t)]+ 1 2 x+t x t h(y)y, x R, t > 0. From this expression for the solution one can erive the following theorem. Theorem 6.1. Assume that g C 2 (R), h C 1 (R), an efine u(x,t) by (6.1). Then the following hols 1) u( C 2 (R [0, ]). ) 2) 2 2 u(x,t) = 0 in R R + t 2 x 2

3 3 3) lim (x,t) (x 0,0) t>0 lim (x,t) (x 0,0) t>0 u(x,t) = g(x 0 ) u t (x,t) = h(x 0 ) Assume that suppg,supph (r,r). Then it follows from (6.1) that suppu ( r t,r + t). This means that the wave equation on R has finite propagation spee. Similar formulars hol for all n 1. Namely consier on R n the wave equation. ( ) 2 t u(x,t) = 0, u(x,0) = g(x), u 2 t (x,0) = h(x). Let n 3 be o. Let m = (n + 1)/2, g C m+1 (R n ) an h C m (R n ). Let γ n = (n 2). Then the unique solution of the wave equation is given by [ ( u(x,t) = 1 1 γ n t t t + )n 3 2 ( t n 2 ( 1 t B(x,t) g S ) )n 3 ( 2 t n 2 hs t B(x,t) This formula also shows that the wave equation satisfies finite propagation spee. )] Energy methos. Energy methos are an important tool to establish finite propagation spee for the wave equation. We illustrate this for the Laplace operator. For x 0 R n, t 0 > 0, let { } C = (x,t): 0 t t 0, x x 0 t 0 t. Theorem 6.2. (Finite propagation spee). Assume that u(x,0) = u t (x,0) 0 on B(x 0,t 0 ). Then u 0 in C. Proof. Define the energy of the solution by (6.2) e(t) = 1 ) (u t (x,t) 2 + u(x,t) 2 x,0 t t 0. 2 B(x 0,t 0 t)

4 4 Then we have t e(t) = 1 2 = + = B(x 0,t 0 t) B(x 0,t 0 t) B(x 0,t 0 t) B(x 0,t 0 t) B(x 0,t 0 t) (u t u tt + u, u t )x (u 2 t + u 2 )s u t (u tt u)x ν u t s 1 ) 1 (u 2t u 2 S. 2 B(x 0,t 0 t) 2 ( ) ν u t 1 2 u2 t 1 u 2 S. 2 Now note that ν u t u t u 1 2 u t u 2. This implies that e(t) 0. t Thus e(t) e(0) = 0 for 0 t t 0. By (6.2) it follows that u t 0 an u 0 in C. This implies that u c an therefore, u = Graient an ivergence. As preparation for the stuy of the wave equation on manifols we recall some facts about the icergence an the graient on a Riemannian manifol. Let X be a Riemannian manifol. Let f C (X). Then the graient graf C (TX) of f is efine by graf(p),y p = Y(f)(p) = f(y)(p) for all Y C (TY). Let : C (TX) C (T x X TX) be the Levi-Civita connection associate to the Riemannian metric of X. Let Y C (TX). The ivergence ivy of the vector fiel Y is efine by ivy(p) = Tr(ξ T p X ξ Y T p X). In local coorinates graf an Y can escribe as follows. Let x 1,...,x n be local coorinates. Let n g = g ij x i x j i,j=1 be the Riemannian metric in these coorinates. Furthermore, let (g kl ) = (g ij ) 1, ḡ = et(g ij ).

5 5 an Then we have an graf = Y = n k=1 ivy = 1 ḡ n j=1 l=1 f j x j. ( ) n kl f g x l n j=1 x j x k ( ḡfj ) Lemma 6.3. For all f C (X) an Y C (TX) we have (graf,y) = (f,ivy). Proof. Using a partition of unity, the proof can be reuce to the case where suppf is containe in a coorinate chart U. Then ( n n n kl f ḡx n f ḡx (graf,y) = g )g kj f j = f j U x j=1 l k=1 l=1 U x j=1 j ( ) = f ḡ 1 n ḡ ḡx f j = f ivyµ(x) x j U = (f,ivy). j=1 U The Riemannian metric efines an isomorphism. φ: TX = T X. It inuces an isomorphism φ: C (TX) = Λ 1 (X). Lemma 6.4. (1) For all f C (X) we have (2) For all Y C (TX) we have φ(graf) = f. iv(y) = (φ(y)).

6 Symmetric hyperbolic systems. Let X be a Riemannian manifol an E X a Hermitian vector bunle over X. Denote by (, ) the inner prouct in Cc (E) inuce by the Riemannian metric an the fibre metric in E. Let D: C (E) C (E) be an elliptic ifferential operator of orer 1. Assume that D is formally self-ajoint. Example: The basic example is the Dirac operator D: C (S) C (S) on a spin manifol. Let π: T X X the cotangent bunle. Let σ D : π E π E be the principal symbol of D. We recall its efinition. Let x X, ξ T x X, an e E x. We choose f C (X) with f(x) = 0, f(x) = ξ, an ϕ C (E) with ϕ(x) = e. Then σ D (x,ξ)(e) = D(Fϕ)(x). Lemma 6.5. For any f C (X) an ϕ C (E) we have (6.3) D(fϕ) = σ D (f)(ϕ)+fϕ. Note that Definition 6.6. For Ω X let { c(ω): = sup σ D (x,ξ) t = σ (x,ξ). c(ω) is calle the propagation spee of D on Ω. σ D (x,ξ) : ξ T x, ξ, x Ω Now we consier the wave equation (6.4) t = idu, u(x,0) = u 0(x), where u 0 C (E). Proposition 6.7. Let x 0 X an suppose that B r (x 0 ) is a geoesic coorinate system. Let c: = c(b r (x 0 )). Let u C ([ T,T],C (E)) be a solution of t = id u. Then we have u(t) Br ct (x 0 ) u(0) Br(x 0 ) for 0 t < r/c. }.

7 7 Proof. We efine a smooth vector fiel Y t on X by Y t (f)(x) = i u(x,t),σ D (f x,x)(u(x,t)) x Let f Cc (X). Then by Lemma 6.4 we have ivy t (x) f(x)x = (ivy t,f) = (Y t,graf) = Y t (f). X By efinition of Y t (f) an (6.3) we get ivy t (x) f(x)x = i ( u(t),d(fu(t)) fdu(t) ) X = i ( Du(t),fu(t) ) i ( u(t),fdu(t) ) ( = i u(x,t),u(x,t) x u(x,t),du(x,t) x ) f(x)x. Since this equality hols for every f C c (X), it follows that X (6.5) ivy t (x) = i Du(x,t),u(x,t) x i u(x,t),du(x,t) x. Now u(x,t) 2 x t B r ct (x 0 ) ( = B r ct (x 0 ) t u(x,t),u(x,t) + u(x,t), ) x t u(x,t) x x c u(x,t) 2 x S(x) = i c B r ct (x 0 ) B r ct (x 0 ) B r ct (x 0 ) ( Du(x,t),u(x,t) u(x,t) 2 x S(x). x u(x,t),du(x,t) x For the last equality we use that u(x,t) satisfies the wave equation (6.6). Using (6.5) an the ivergence theorem it follows that u(x,t) 2 x t x = ivy t (x) u(x,t)x B r ct (x 0 ) B r ct (x 0 ) c u(x,t) 2 x S(x) = B r ct (x 0 ) B r ct (x 0 ) ) x Y t (x),ν(x) x S(x) c u(x,t) 2 x S(x), B r ct (x 0 )

8 8 where ν(x) enotes the exterior unit normal vector fiel. Now observe that by the efinition of c = c(b r (x 0 )) This implies that Thus we obtain Y t (x),ν(x) x = u(x,t),σ D (ν(x),x)(u(x,t)) x c u(x,t) 2. which conclues the proof. Let c = c(b r (x 0 )) an let u(x,t) 2 xx 0. t B r ct (x 0 ) u(t) Br ct (x 0 ) u(0) Br (x 0 ), C = {(t,x): t 0, (x,x 0 ) r ct} Corollary 6.8. Let u C ([ T,T],C (E)) be a solution of the equation t = idu on C. Suppose that u(0) = 0 on B r (x 0 ). Then u = 0 on C. Let U = B r (x 0 ) X be a normal coorinate chart an let φ: E U = U C N be a trivialization of E U. Let D U be restriction of D to C (U,E U ). Then t u = id U(u), u(0,x) = u 0 (x) is a hyperbolic system oforer 1 inr n. The usual theory for such systems implies existence of solutions with smooth initial conitions. In this way we get Proposition 6.9. For every x 0 X there exists r > 0 such that for u 0 C (B r (x 0,E)) there exists a unique solution of t = id(u), u(0,x) = u 0(x) on C 0 = {(x,t): t 0, (x,s 0 ) r ct}, where c = c(b r (x 0 )). The next proposition extens the above result to a larger region. Proposition Let S = B R (x 0 ) be a compact ball in X. Let c: c(s) an C 0 = {(x,t): t 0, (x,x 0 ) r ct} Let u 0 C (S,E). Then there is in C 0 a unique smooth solution of the equation t = id(u), u(0) = u 0.

9 Proof. Since S is compact, there exists r > 0 such for all y S the injectivity raius i(y) r. Thusforally S, B r (y)isanormalcoorinatechart. ItfollowsfromProposition (6.9) that for all y B R r (x 0 ) an u 0 C (B r (y),e), the wave equation t = id(u), u(0) = u 0, has a unique C -solution on the truncate cone C y = {(x,t): (x,y) r ct,0 t r/2c}. Byuniqueness, solutions agreeonc y C z. Therefore, we obtainasolutiononthetruncate cone {(x,t): (x,x 0 ) R ct, 0 t r/2c}. The solution u at time t = r/2c serves as initial conition on B(x 0,R r/2). If we repeat the above argument, we get a solution on the truncate cone an therefore, a solution on {(x,t): (x,x 0 ) R ct, r/2c t r/c} {(x,t): (x,x 0 ) R ct, 0 t r/c}. After a finite number of steps, we obtain a smooth solution on the cone with base S. Let x 0 X. Put c(r): = c(b r (x 0 )), r > 0. Theorem Let X be a complete Riemannian manifol. Suppose that r c(r) =. (6.6) 1) Uniqueness: Suppose that u C (X,E) is a solution of t = idu on [0,T] X with u(0) = 0. Then u 0. 2) Existence: Let u 0 C (X,E). Then the wave equation 0 t = idu, u(0) = u 0, has a unique solution on R X. Moreover, for fixe t, u(,t) has compact support. Proof. We first establish uniqueness. Let R > 0. Put S R = B R (x 0 ). We shall show that u(t) vanishes on S R. Of course, we also have that u(t ) vanishes for T < T. Let t R = c(r+1) 1,R > 0. By Proposition (6.10), the wave equation (6.6) on {(x,t): (x,x 0 ) R c(r+1)t,0 t t R } 9

10 10 with initial conition u 0 C (S R+1,E) has a unique solution. Hence u(t) on S R is etermine by u(t t R ) on S R+1. By the same argument u(t t R ) is etermine by u(t t R t R+1 ) ons R+2. Since thesets S R arecompact, this maybecontinue inefinitely. Now we have (6.7) t R+n =, n=0 because c(r) is monoton an r 1 c(r) = by assumption. Hence there exists N N such that T : = t R +t R+1 + +t R+N < T an T +t R+N+1 > T. From our consierations above follows that u(t) SR is etermine by u(t T ) SR+N. Let ε = (R+N +1)(T T ). Then it follows as above that u(t T ) SR+N is etermine by u(0) SR+N+ε. Note that T T t R+N+1. But u(0) = 0. Hence u(t T ) SR+N = 0. This implies that u(t) SR = 0. Next we establish existence. The argument is like the uniqueness proof run in reverse. Let u 0 C c (X,E). Let R > 0 such that suppu 0 S R. Since X is complete, S R is compact. By Proposition (6.10) there exists a C -solution of (6.6) in C = {(x,t): 0 t t R+2,(x,x 0 ) R+3 c(r+3)t} Moreover, it follows from the uniqueness part of Proposition (6.10) that the solution vanishes outsie S R+1. So we can exten it by 0 to a global solution on X which exists for time 0 t t R+2. Now we iterate this process. The solution at time t = t R+2 is supporte in S R+1. By the above argument, it extens to a solution for 0 t t R+2 + t R+3 with support in S R+2. Using again (6.7), we can exten the solution to any time t an for fixe t, u(t) has compact support. by For each t efine a map where u is the unique solution of U t : C c (X,E) C (X,E) U t (u 0 ) = u(t), t = idu, u(0) = u 0. Corollary Uner the assumptions of Theorem (6.11), {U t } is a one-parameter group. Moreover, if w C c (X,E), we have t (U t(u 0 ),w) = (idu t (u 0 ),w).

11 Let ψ H an suppose that ((A±i)(ϕ),ψ ) = 0, ϕ D. 11 Finally DU t (u 0 ) = U t (Du 0 ). Proof. Let u(t): = U t (u 0 ). Then u(t) C (X,E) an t = idu. Since w Cc (X,E), we can ifferentiate unter the integral which gives t (U t(u 0 ),w) = ( t,w ) = (idu t (u 0 ),w) Moreover, U s+t = U s U t an DU t = U t D follows from uniqueness. Note that U t is unitary. Inee we have ( u ) ( t u(t) 2 = t (t),u(t) + u(t), u ) t (t) ( ) ( ) = idu(t), u(t) + u(t), idu(t) ( ) ( ) = idu(t), u(t) id(t),u(t) = Essential self-ajointness. In this section we apply the results obtaine in the previous section to establish the essential self-ajointness of geometric operators. We begin with an abstract result. Lemma Let T be a symmetric operator in a Hilbert space H with ense omain D H. Suppose that T(D) D). Furthermore suppose that there is a one-parameter group U t of unitary operators on H such that U t (D) D, U t T = TU t on D an t U t(u) = itu t (u) for u D. Then every power of T is essentially self-aoint. Proof. Let n N an A: = T n. Then A: D H is symmetric. To show that A is essentially self-ajoint, it suffices to verify that (A±iI)(D) = H Then it follows that ψ D(A ) an A ψ = iψ.

12 12 We consier the case where A ψ = iψ. For u D efine f(t) = (U t (u),ψ), t R. Since U t is unitary, f(t) is boune. Furthermore we have n t nf(t) = (itn U t (u),ψ) = (iau t (u),ψ) = (i n U t (u),a ψ) = i n+1 (U t (u),ψ) = i n+1 f(t). Thus f(t) satisfies the orinary linear ifferential equation. n f (6.8) t (t) = n in+1 f(t). Let α j, j = 1,...,n, be the ifferent roots of the equation z n = i n+1. Then e αjt, j = 1,...,n, is a basis for the space of solutions of (6.8). Therefore f(t) can be written as n f(t) = c j e α jt j=1 for some constants c j C. Now observe that Re(α j ) 0 for j = 1,...,n. Since f is boune this implies that f 0. Hence we get (u,ψ) = f(0) = 0, u D. Since D H is ense, it follows that ψ = 0. The case A ψ = iψ can be treate in the same way. We can now state the main result about essential self-ajointness. Theorem Let X be a complete Riemannian manifol an E X a Hermitian vector bunle over X. Let D: C (X,E) C (X,E) be an elliptic ifferential operator of orer 1 which is formally self-ajoint. Assume that 1 r c(r) =. Let T : C c (X,E) L2 (X,E) be the operator which is efine by D. Then every power of T is essentially self-ajoint. Proof. Let U t : C c (X,E) C c (X,E) be the 1-parameter group, efine by Corollary For each t R we have U t (u) = u, u C c (X,E).

13 Inee, for u,w C c (X,E), we have t (U t(u),u t (w)) = (idu t (u),u t (w))+(u t (u),idu t (w)) ((id id)u t (u),u t (w)) = 0. Hence U t extens by continuity to a one-parameter family U t : L 2 (X,e) L 2 (X,E) of unitary operators. The assumptions of Lemma 6.13 are satisfie. This implies the theorem Applications. Now we are reay to apply the results of the previous section to geometric situations. Let X be a complete Riemannian manifol. Let D = + : Λ (X) Λ (X). Then D is formally self-ajoint. To etermine its principal symbol, fix p X,ξ T p X an v Λ T p X. Let f C (X) an ϕ Λ (X) be such that f(p) = 0,f p = ξ an ϕ(p) = v. Then we have σ (p,ξ)v = D(fϕ)(p) = (+ )(fϕ)(p) = f p ϕ(p) (f ϕ)(p) = ξ v i ξ (v), where i ξ : Λ Tp X Λ Tp X enotes interior multiplication by ξ. This implies that σ D (x,ξ) = ξ. Hence we have c(x) = 1, i.e. D has unite propagation spee. By Theorem 6.14 it follows that for all n N, the operator (+ ) n : Λ c (X) L2 Λ (X) is essentially self-ajoint. Now recall that the laplace operator is given by Thus it follows that for all n N, = (+ ) 2. n : Λ c(x) L 2 Λ (X) is essentially self-ajoint. The Laplace operator preserves Λ p (X) for every p. Therefore is essentially self-ajoint for all p = 0,...,n. n : Λ p c(x) L 2 Λ p (X) Next we consier a complex manifol equippe with a Hermitian metric, so that X, equippe with the associate Riemannian metric is complete. Let E X be a holomorphic Hermitian vector bunle over X. Then we efine the space of (p,q)-forms with values in E as the space of C -sections of Λ p T (1.0) (X) Λ q T (0,1) (X) E. The operator : Λ p,q (X,E) Λ p,q+1 (X,E) 13

14 14 is uniquely efine by emaning that (ω ϕ) = ( ω) ϕ for every ω Λ p,q (X) an every holomorphic section of E. In this way we get the Dolbeault complex Let D = ( + ). Then we have where π: T x Λ p,q (X,E) Λ p,q+1 (X,E) σ D (x,ξ)(ω ϕ) = (π(ξ) ω i π(ξ) (ω)) ϕ X C T (0,1) x X is the canonical projection. It follows that an hence, c(x) = 1/ 2. By Theorem 6.14, σ D (X,ξ) = π(ξ) ( + ) n : Λ p, c (X,E) L 2 Λ p, (X,E) is essentially self-ajoint for all p an all n N. References [Ch] Chernoff, Paul R. Essential self-ajointness of powers of generators of hyperbolic equations. J. Functional Analysis 12 (1973), [Ev] Evans, Lawrence C., Partial ifferential equations. Grauate Stuies in Mathematics, 19. American Mathematical Society, Provience, RI, 1998.

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

MATH 425, PRACTICE FINAL EXAM SOLUTIONS. MATH 45, PRACTICE FINAL EXAM SOLUTIONS. Exercise. a Is the operator L defined on smooth functions of x, y by L u := u xx + cosu linear? b Does the answer change if we replace the operator L by the operator

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 14 10/27/2008 MOMENT GENERATING FUNCTIONS

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 14 10/27/2008 MOMENT GENERATING FUNCTIONS MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 14 10/27/2008 MOMENT GENERATING FUNCTIONS Contents 1. Moment generating functions 2. Sum of a ranom number of ranom variables 3. Transforms

More information

it is easy to see that α = a

it is easy to see that α = a 21. Polynomial rings Let us now turn out attention to determining the prime elements of a polynomial ring, where the coefficient ring is a field. We already know that such a polynomial ring is a UF. Therefore

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

f(x) = a x, h(5) = ( 1) 5 1 = 2 2 1

f(x) = a x, h(5) = ( 1) 5 1 = 2 2 1 Exponential Functions an their Derivatives Exponential functions are functions of the form f(x) = a x, where a is a positive constant referre to as the base. The functions f(x) = x, g(x) = e x, an h(x)

More information

The Heat Equation. Lectures INF2320 p. 1/88

The Heat Equation. Lectures INF2320 p. 1/88 The Heat Equation Lectures INF232 p. 1/88 Lectures INF232 p. 2/88 The Heat Equation We study the heat equation: u t = u xx for x (,1), t >, (1) u(,t) = u(1,t) = for t >, (2) u(x,) = f(x) for x (,1), (3)

More information

Answers to the Practice Problems for Test 2

Answers to the Practice Problems for Test 2 Answers to the Practice Problems for Test 2 Davi Murphy. Fin f (x) if it is known that x [f(2x)] = x2. By the chain rule, x [f(2x)] = f (2x) 2, so 2f (2x) = x 2. Hence f (2x) = x 2 /2, but the lefthan

More information

Introduction to Finite Fields (cont.)

Introduction to Finite Fields (cont.) Chapter 6 Introduction to Finite Fields (cont.) 6.1 Recall Theorem. Z m is a field m is a prime number. Theorem (Subfield Isomorphic to Z p ). Every finite field has the order of a power of a prime number

More information

A Generalization of Sauer s Lemma to Classes of Large-Margin Functions

A Generalization of Sauer s Lemma to Classes of Large-Margin Functions A Generalization of Sauer s Lemma to Classes of Large-Margin Functions Joel Ratsaby University College Lonon Gower Street, Lonon WC1E 6BT, Unite Kingom J.Ratsaby@cs.ucl.ac.uk, WWW home page: http://www.cs.ucl.ac.uk/staff/j.ratsaby/

More information

Chapter 4, Arithmetic in F [x] Polynomial arithmetic and the division algorithm.

Chapter 4, Arithmetic in F [x] Polynomial arithmetic and the division algorithm. Chapter 4, Arithmetic in F [x] Polynomial arithmetic and the division algorithm. We begin by defining the ring of polynomials with coefficients in a ring R. After some preliminary results, we specialize

More information

Introduction to Algebraic Geometry. Bézout s Theorem and Inflection Points

Introduction to Algebraic Geometry. Bézout s Theorem and Inflection Points Introduction to Algebraic Geometry Bézout s Theorem and Inflection Points 1. The resultant. Let K be a field. Then the polynomial ring K[x] is a unique factorisation domain (UFD). Another example of a

More information

20. Product rule, Quotient rule

20. Product rule, Quotient rule 20. Prouct rule, 20.1. Prouct rule Prouct rule, Prouct rule We have seen that the erivative of a sum is the sum of the erivatives: [f(x) + g(x)] = x x [f(x)] + x [(g(x)]. One might expect from this that

More information

T ( a i x i ) = a i T (x i ).

T ( a i x i ) = a i T (x i ). Chapter 2 Defn 1. (p. 65) Let V and W be vector spaces (over F ). We call a function T : V W a linear transformation form V to W if, for all x, y V and c F, we have (a) T (x + y) = T (x) + T (y) and (b)

More information

Høgskolen i Narvik Sivilingeniørutdanningen STE6237 ELEMENTMETODER. Oppgaver

Høgskolen i Narvik Sivilingeniørutdanningen STE6237 ELEMENTMETODER. Oppgaver Høgskolen i Narvik Sivilingeniørutdanningen STE637 ELEMENTMETODER Oppgaver Klasse: 4.ID, 4.IT Ekstern Professor: Gregory A. Chechkin e-mail: chechkin@mech.math.msu.su Narvik 6 PART I Task. Consider two-point

More information

College of the Holy Cross, Spring 2009 Math 373, Partial Differential Equations Midterm 1 Practice Questions

College of the Holy Cross, Spring 2009 Math 373, Partial Differential Equations Midterm 1 Practice Questions College of the Holy Cross, Spring 29 Math 373, Partial Differential Equations Midterm 1 Practice Questions 1. (a) Find a solution of u x + u y + u = xy. Hint: Try a polynomial of degree 2. Solution. Use

More information

Mannheim curves in the three-dimensional sphere

Mannheim curves in the three-dimensional sphere Mannheim curves in the three-imensional sphere anju Kahraman, Mehmet Öner Manisa Celal Bayar University, Faculty of Arts an Sciences, Mathematics Department, Muraiye Campus, 5, Muraiye, Manisa, urkey.

More information

Pythagorean Triples Over Gaussian Integers

Pythagorean Triples Over Gaussian Integers International Journal of Algebra, Vol. 6, 01, no., 55-64 Pythagorean Triples Over Gaussian Integers Cheranoot Somboonkulavui 1 Department of Mathematics, Faculty of Science Chulalongkorn University Bangkok

More information

Extremal equilibria for reaction diffusion equations in bounded domains and applications.

Extremal equilibria for reaction diffusion equations in bounded domains and applications. Extremal equilibria for reaction diffusion equations in bounded domains and applications. Aníbal Rodríguez-Bernal Alejandro Vidal-López Departamento de Matemática Aplicada Universidad Complutense de Madrid,

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

The Quick Calculus Tutorial

The Quick Calculus Tutorial The Quick Calculus Tutorial This text is a quick introuction into Calculus ieas an techniques. It is esigne to help you if you take the Calculus base course Physics 211 at the same time with Calculus I,

More information

MSc. Econ: MATHEMATICAL STATISTICS, 1995 MAXIMUM-LIKELIHOOD ESTIMATION

MSc. Econ: MATHEMATICAL STATISTICS, 1995 MAXIMUM-LIKELIHOOD ESTIMATION MAXIMUM-LIKELIHOOD ESTIMATION The General Theory of M-L Estimation In orer to erive an M-L estimator, we are boun to make an assumption about the functional form of the istribution which generates the

More information

FACTORING POLYNOMIALS IN THE RING OF FORMAL POWER SERIES OVER Z

FACTORING POLYNOMIALS IN THE RING OF FORMAL POWER SERIES OVER Z FACTORING POLYNOMIALS IN THE RING OF FORMAL POWER SERIES OVER Z DANIEL BIRMAJER, JUAN B GIL, AND MICHAEL WEINER Abstract We consider polynomials with integer coefficients and discuss their factorization

More information

BV has the bounded approximation property

BV has the bounded approximation property The Journal of Geometric Analysis volume 15 (2005), number 1, pp. 1-7 [version, April 14, 2005] BV has the boune approximation property G. Alberti, M. Csörnyei, A. Pe lczyński, D. Preiss Abstract: We prove

More information

Factoring Dickson polynomials over finite fields

Factoring Dickson polynomials over finite fields Factoring Dickson polynomials over finite fiels Manjul Bhargava Department of Mathematics, Princeton University. Princeton NJ 08544 manjul@math.princeton.eu Michael Zieve Department of Mathematics, University

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

14.11. Geodesic Lines, Local Gauss-Bonnet Theorem

14.11. Geodesic Lines, Local Gauss-Bonnet Theorem 14.11. Geodesic Lines, Local Gauss-Bonnet Theorem Geodesics play a very important role in surface theory and in dynamics. One of the main reasons why geodesics are so important is that they generalize

More information

Limits and Continuity

Limits and Continuity Math 20C Multivariable Calculus Lecture Limits and Continuity Slide Review of Limit. Side limits and squeeze theorem. Continuous functions of 2,3 variables. Review: Limits Slide 2 Definition Given a function

More information

Critical Thresholds in Euler-Poisson Equations. Shlomo Engelberg Jerusalem College of Technology Machon Lev

Critical Thresholds in Euler-Poisson Equations. Shlomo Engelberg Jerusalem College of Technology Machon Lev Critical Thresholds in Euler-Poisson Equations Shlomo Engelberg Jerusalem College of Technology Machon Lev 1 Publication Information This work was performed with Hailiang Liu & Eitan Tadmor. These results

More information

Systems with Persistent Memory: the Observation Inequality Problems and Solutions

Systems with Persistent Memory: the Observation Inequality Problems and Solutions Chapter 6 Systems with Persistent Memory: the Observation Inequality Problems and Solutions Facts that are recalled in the problems wt) = ut) + 1 c A 1 s ] R c t s)) hws) + Ks r)wr)dr ds. 6.1) w = w +

More information

H/wk 13, Solutions to selected problems

H/wk 13, Solutions to selected problems H/wk 13, Solutions to selected problems Ch. 4.1, Problem 5 (a) Find the number of roots of x x in Z 4, Z Z, any integral domain, Z 6. (b) Find a commutative ring in which x x has infinitely many roots.

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

Notes on tangents to parabolas

Notes on tangents to parabolas Notes on tangents to parabolas (These are notes for a talk I gave on 2007 March 30.) The point of this talk is not to publicize new results. The most recent material in it is the concept of Bézier curves,

More information

Given three vectors A, B, andc. We list three products with formula (A B) C = B(A C) A(B C); A (B C) =B(A C) C(A B);

Given three vectors A, B, andc. We list three products with formula (A B) C = B(A C) A(B C); A (B C) =B(A C) C(A B); 1.1.4. Prouct of three vectors. Given three vectors A, B, anc. We list three proucts with formula (A B) C = B(A C) A(B C); A (B C) =B(A C) C(A B); a 1 a 2 a 3 (A B) C = b 1 b 2 b 3 c 1 c 2 c 3 where the

More information

Mathematical Physics, Lecture 9

Mathematical Physics, Lecture 9 Mathematical Physics, Lecture 9 Hoshang Heydari Fysikum April 25, 2012 Hoshang Heydari (Fysikum) Mathematical Physics, Lecture 9 April 25, 2012 1 / 42 Table of contents 1 Differentiable manifolds 2 Differential

More information

minimal polyonomial Example

minimal polyonomial Example Minimal Polynomials Definition Let α be an element in GF(p e ). We call the monic polynomial of smallest degree which has coefficients in GF(p) and α as a root, the minimal polyonomial of α. Example: We

More information

1 = (a 0 + b 0 α) 2 + + (a m 1 + b m 1 α) 2. for certain elements a 0,..., a m 1, b 0,..., b m 1 of F. Multiplying out, we obtain

1 = (a 0 + b 0 α) 2 + + (a m 1 + b m 1 α) 2. for certain elements a 0,..., a m 1, b 0,..., b m 1 of F. Multiplying out, we obtain Notes on real-closed fields These notes develop the algebraic background needed to understand the model theory of real-closed fields. To understand these notes, a standard graduate course in algebra is

More information

Sensitivity Analysis of Non-linear Performance with Probability Distortion

Sensitivity Analysis of Non-linear Performance with Probability Distortion Preprints of the 19th Worl Congress The International Feeration of Automatic Control Cape Town, South Africa. August 24-29, 214 Sensitivity Analysis of Non-linear Performance with Probability Distortion

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

Cyclotomic Extensions

Cyclotomic Extensions Chapter 7 Cyclotomic Extensions A cyclotomic extension Q(ζ n ) of the rationals is formed by adjoining a primitive n th root of unity ζ n. In this chapter, we will find an integral basis and calculate

More information

Rate of convergence towards Hartree dynamics

Rate of convergence towards Hartree dynamics Rate of convergence towards Hartree dynamics Benjamin Schlein, LMU München and University of Cambridge Universitá di Milano Bicocca, October 22, 2007 Joint work with I. Rodnianski 1. Introduction boson

More information

Coupled best proximity point theorems for proximally g-meir-keelertypemappings in partially ordered metric spaces

Coupled best proximity point theorems for proximally g-meir-keelertypemappings in partially ordered metric spaces Abkar et al. Fixe Point Theory an Applications 2015) 2015:107 DOI 10.1186/s13663-015-0355-9 R E S E A R C H Open Access Couple best proximity point theorems for proximally g-meir-keelertypemappings in

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

Exponential Functions: Differentiation and Integration. The Natural Exponential Function

Exponential Functions: Differentiation and Integration. The Natural Exponential Function 46_54.q //4 :59 PM Page 5 5 CHAPTER 5 Logarithmic, Eponential, an Other Transcenental Functions Section 5.4 f () = e f() = ln The inverse function of the natural logarithmic function is the natural eponential

More information

(2) the identity map id : S 1 S 1 to the symmetry S 1 S 1 : x x (here x is considered a complex number because the circle S 1 is {x C : x = 1}),

(2) the identity map id : S 1 S 1 to the symmetry S 1 S 1 : x x (here x is considered a complex number because the circle S 1 is {x C : x = 1}), Chapter VI Fundamental Group 29. Homotopy 29 1. Continuous Deformations of Maps 29.A. Is it possible to deform continuously: (1) the identity map id : R 2 R 2 to the constant map R 2 R 2 : x 0, (2) the

More information

Metric Spaces. Chapter 1

Metric Spaces. Chapter 1 Chapter 1 Metric Spaces Many of the arguments you have seen in several variable calculus are almost identical to the corresponding arguments in one variable calculus, especially arguments concerning convergence

More information

Buy Low and Sell High

Buy Low and Sell High Buy Low and Sell High Min Dai Hanqing Jin Yifei Zhong Xun Yu Zhou This version: Sep 009 Abstract In trading stocks investors naturally aspire to buy low and sell high (BLSH). This paper formalizes the

More information

Section 6.1 - Inner Products and Norms

Section 6.1 - Inner Products and Norms Section 6.1 - Inner Products and Norms Definition. Let V be a vector space over F {R, C}. An inner product on V is a function that assigns, to every ordered pair of vectors x and y in V, a scalar in F,

More information

Lecture 1: Schur s Unitary Triangularization Theorem

Lecture 1: Schur s Unitary Triangularization Theorem Lecture 1: Schur s Unitary Triangularization Theorem This lecture introduces the notion of unitary equivalence and presents Schur s theorem and some of its consequences It roughly corresponds to Sections

More information

Application of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain)

Application of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain) Application of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain) The Fourier Sine Transform pair are F. T. : U = 2/ u x sin x dx, denoted as U

More information

Chapter 5. Banach Spaces

Chapter 5. Banach Spaces 9 Chapter 5 Banach Spaces Many linear equations may be formulated in terms of a suitable linear operator acting on a Banach space. In this chapter, we study Banach spaces and linear operators acting on

More information

CHAPTER SIX IRREDUCIBILITY AND FACTORIZATION 1. BASIC DIVISIBILITY THEORY

CHAPTER SIX IRREDUCIBILITY AND FACTORIZATION 1. BASIC DIVISIBILITY THEORY January 10, 2010 CHAPTER SIX IRREDUCIBILITY AND FACTORIZATION 1. BASIC DIVISIBILITY THEORY The set of polynomials over a field F is a ring, whose structure shares with the ring of integers many characteristics.

More information

Lecture L25-3D Rigid Body Kinematics

Lecture L25-3D Rigid Body Kinematics J. Peraire, S. Winall 16.07 Dynamics Fall 2008 Version 2.0 Lecture L25-3D Rigi Boy Kinematics In this lecture, we consier the motion of a 3D rigi boy. We shall see that in the general three-imensional

More information

1.5. Factorisation. Introduction. Prerequisites. Learning Outcomes. Learning Style

1.5. Factorisation. Introduction. Prerequisites. Learning Outcomes. Learning Style Factorisation 1.5 Introduction In Block 4 we showed the way in which brackets were removed from algebraic expressions. Factorisation, which can be considered as the reverse of this process, is dealt with

More information

Strong solutions of the compressible nematic liquid crystal flow

Strong solutions of the compressible nematic liquid crystal flow Strong solutions of the compressible nematic liqui crystal flow Tao Huang Changyou Wang Huanyao Wen April 9, 11 Abstract We stuy strong solutions of the simplifie Ericksen-Leslie system moeling compressible

More information

NOTES ON LINEAR TRANSFORMATIONS

NOTES ON LINEAR TRANSFORMATIONS NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all

More information

SOME PROPERTIES OF FIBER PRODUCT PRESERVING BUNDLE FUNCTORS

SOME PROPERTIES OF FIBER PRODUCT PRESERVING BUNDLE FUNCTORS SOME PROPERTIES OF FIBER PRODUCT PRESERVING BUNDLE FUNCTORS Ivan Kolář Abstract. Let F be a fiber product preserving bundle functor on the category FM m of the proper base order r. We deduce that the r-th

More information

f(x + h) f(x) h as representing the slope of a secant line. As h goes to 0, the slope of the secant line approaches the slope of the tangent line.

f(x + h) f(x) h as representing the slope of a secant line. As h goes to 0, the slope of the secant line approaches the slope of the tangent line. Derivative of f(z) Dr. E. Jacobs Te erivative of a function is efine as a limit: f (x) 0 f(x + ) f(x) We can visualize te expression f(x+) f(x) as representing te slope of a secant line. As goes to 0,

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

Math 241, Exam 1 Information.

Math 241, Exam 1 Information. Math 241, Exam 1 Information. 9/24/12, LC 310, 11:15-12:05. Exam 1 will be based on: Sections 12.1-12.5, 14.1-14.3. The corresponding assigned homework problems (see http://www.math.sc.edu/ boylan/sccourses/241fa12/241.html)

More information

A PRIORI ESTIMATES FOR SEMISTABLE SOLUTIONS OF SEMILINEAR ELLIPTIC EQUATIONS. In memory of Rou-Huai Wang

A PRIORI ESTIMATES FOR SEMISTABLE SOLUTIONS OF SEMILINEAR ELLIPTIC EQUATIONS. In memory of Rou-Huai Wang A PRIORI ESTIMATES FOR SEMISTABLE SOLUTIONS OF SEMILINEAR ELLIPTIC EQUATIONS XAVIER CABRÉ, MANEL SANCHÓN, AND JOEL SPRUCK In memory of Rou-Huai Wang 1. Introduction In this note we consider semistable

More information

Lagrangian and Hamiltonian Mechanics

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

More information

Rolle s Theorem. q( x) = 1

Rolle s Theorem. q( x) = 1 Lecture 1 :The Mean Value Theorem We know that constant functions have derivative zero. Is it possible for a more complicated function to have derivative zero? In this section we will answer this question

More information

Irreducibility criteria for compositions and multiplicative convolutions of polynomials with integer coefficients

Irreducibility criteria for compositions and multiplicative convolutions of polynomials with integer coefficients DOI: 10.2478/auom-2014-0007 An. Şt. Univ. Ovidius Constanţa Vol. 221),2014, 73 84 Irreducibility criteria for compositions and multiplicative convolutions of polynomials with integer coefficients Anca

More information

Measures of distance between samples: Euclidean

Measures of distance between samples: Euclidean 4- Chapter 4 Measures of istance between samples: Eucliean We will be talking a lot about istances in this book. The concept of istance between two samples or between two variables is funamental in multivariate

More information

MATH PROBLEMS, WITH SOLUTIONS

MATH PROBLEMS, WITH SOLUTIONS MATH PROBLEMS, WITH SOLUTIONS OVIDIU MUNTEANU These are free online notes that I wrote to assist students that wish to test their math skills with some problems that go beyond the usual curriculum. These

More information

2.3 Convex Constrained Optimization Problems

2.3 Convex Constrained Optimization Problems 42 CHAPTER 2. FUNDAMENTAL CONCEPTS IN CONVEX OPTIMIZATION Theorem 15 Let f : R n R and h : R R. Consider g(x) = h(f(x)) for all x R n. The function g is convex if either of the following two conditions

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

2r 1. Definition (Degree Measure). Let G be a r-graph of order n and average degree d. Let S V (G). The degree measure µ(s) of S is defined by,

2r 1. Definition (Degree Measure). Let G be a r-graph of order n and average degree d. Let S V (G). The degree measure µ(s) of S is defined by, Theorem Simple Containers Theorem) Let G be a simple, r-graph of average egree an of orer n Let 0 < δ < If is large enough, then there exists a collection of sets C PV G)) satisfying: i) for every inepenent

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

Class Meeting # 1: Introduction to PDEs

Class Meeting # 1: Introduction to PDEs MATH 18.152 COURSE NOTES - CLASS MEETING # 1 18.152 Introduction to PDEs, Fall 2011 Professor: Jared Speck Class Meeting # 1: Introduction to PDEs 1. What is a PDE? We will be studying functions u = u(x

More information

FIELDS-MITACS Conference. on the Mathematics of Medical Imaging. Photoacoustic and Thermoacoustic Tomography with a variable sound speed

FIELDS-MITACS Conference. on the Mathematics of Medical Imaging. Photoacoustic and Thermoacoustic Tomography with a variable sound speed FIELDS-MITACS Conference on the Mathematics of Medical Imaging Photoacoustic and Thermoacoustic Tomography with a variable sound speed Gunther Uhlmann UC Irvine & University of Washington Toronto, Canada,

More information

Linear Maps. Isaiah Lankham, Bruno Nachtergaele, Anne Schilling (February 5, 2007)

Linear Maps. Isaiah Lankham, Bruno Nachtergaele, Anne Schilling (February 5, 2007) MAT067 University of California, Davis Winter 2007 Linear Maps Isaiah Lankham, Bruno Nachtergaele, Anne Schilling (February 5, 2007) As we have discussed in the lecture on What is Linear Algebra? one of

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

3. INNER PRODUCT SPACES

3. INNER PRODUCT SPACES . INNER PRODUCT SPACES.. Definition So far we have studied abstract vector spaces. These are a generalisation of the geometric spaces R and R. But these have more structure than just that of a vector space.

More information

UNIFIED BIJECTIONS FOR MAPS WITH PRESCRIBED DEGREES AND GIRTH

UNIFIED BIJECTIONS FOR MAPS WITH PRESCRIBED DEGREES AND GIRTH UNIFIED BIJECTIONS FOR MAPS WITH PRESCRIBED DEGREES AND GIRTH OLIVIER BERNARDI AND ÉRIC FUSY Abstract. This article presents unifie bijective constructions for planar maps, with control on the face egrees

More information

Chapter 6. Linear Transformation. 6.1 Intro. to Linear Transformation

Chapter 6. Linear Transformation. 6.1 Intro. to Linear Transformation Chapter 6 Linear Transformation 6 Intro to Linear Transformation Homework: Textbook, 6 Ex, 5, 9,, 5,, 7, 9,5, 55, 57, 6(a,b), 6; page 7- In this section, we discuss linear transformations 89 9 CHAPTER

More information

Notes V General Equilibrium: Positive Theory. 1 Walrasian Equilibrium and Excess Demand

Notes V General Equilibrium: Positive Theory. 1 Walrasian Equilibrium and Excess Demand Notes V General Equilibrium: Positive Theory In this lecture we go on considering a general equilibrium model of a private ownership economy. In contrast to the Notes IV, we focus on positive issues such

More information

Labeling outerplanar graphs with maximum degree three

Labeling outerplanar graphs with maximum degree three Labeling outerplanar graphs with maximum degree three Xiangwen Li 1 and Sanming Zhou 2 1 Department of Mathematics Huazhong Normal University, Wuhan 430079, China 2 Department of Mathematics and Statistics

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

WEAKLY DISSIPATIVE SEMILINEAR EQUATIONS OF VISCOELASTICITY. Monica Conti. Vittorino Pata. (Communicated by Alain Miranville)

WEAKLY DISSIPATIVE SEMILINEAR EQUATIONS OF VISCOELASTICITY. Monica Conti. Vittorino Pata. (Communicated by Alain Miranville) COMMUNICATIONS ON Website: http://aimsciences.org PURE AND APPLIED ANALYSIS Volume, Number, January 25 pp. 1 16 WEAKLY DISSIPATIVE SEMILINEAR EQUATIONS OF VISCOELASTICITY Monica Conti Dipartimento i Matematica

More information

Section 1.1. Introduction to R n

Section 1.1. Introduction to R n The Calculus of Functions of Several Variables Section. Introduction to R n Calculus is the study of functional relationships and how related quantities change with each other. In your first exposure to

More information

Math 230.01, Fall 2012: HW 1 Solutions

Math 230.01, Fall 2012: HW 1 Solutions Math 3., Fall : HW Solutions Problem (p.9 #). Suppose a wor is picke at ranom from this sentence. Fin: a) the chance the wor has at least letters; SOLUTION: All wors are equally likely to be chosen. The

More information

EVOLUTION OF CONVEX LENS-SHAPED NETWORKS UNDER CURVE SHORTENING FLOW

EVOLUTION OF CONVEX LENS-SHAPED NETWORKS UNDER CURVE SHORTENING FLOW EVOLUTION OF CONVEX LENS-SHAPED NETWORKS UNDER CURVE SHORTENING FLOW OLIVER C. SCHNÜRER, ABDERRAHIM AZOUANI, MARC GEORGI, JULIETTE HELL, NIHAR JANGLE, AMOS KOELLER, TOBIAS MARXEN, SANDRA RITTHALER, MARIEL

More information

Differentiability of Exponential Functions

Differentiability of Exponential Functions Differentiability of Exponential Functions Philip M. Anselone an John W. Lee Philip Anselone (panselone@actionnet.net) receive his Ph.D. from Oregon State in 1957. After a few years at Johns Hopkins an

More information

MICROLOCAL ANALYSIS OF THE BOCHNER-MARTINELLI INTEGRAL

MICROLOCAL ANALYSIS OF THE BOCHNER-MARTINELLI INTEGRAL PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 00, Number 0, Pages 000 000 S 0002-9939(XX)0000-0 MICROLOCAL ANALYSIS OF THE BOCHNER-MARTINELLI INTEGRAL NIKOLAI TARKHANOV AND NIKOLAI VASILEVSKI

More information

Sensor Network Localization from Local Connectivity : Performance Analysis for the MDS-MAP Algorithm

Sensor Network Localization from Local Connectivity : Performance Analysis for the MDS-MAP Algorithm Sensor Network Localization from Local Connectivity : Performance Analysis for the MDS-MAP Algorithm Sewoong Oh an Anrea Montanari Electrical Engineering an Statistics Department Stanfor University, Stanfor,

More information

16.3 Fredholm Operators

16.3 Fredholm Operators Lectures 16 and 17 16.3 Fredholm Operators A nice way to think about compact operators is to show that set of compact operators is the closure of the set of finite rank operator in operator norm. In this

More information

THREE DIMENSIONAL GEOMETRY

THREE DIMENSIONAL GEOMETRY Chapter 8 THREE DIMENSIONAL GEOMETRY 8.1 Introduction In this chapter we present a vector algebra approach to three dimensional geometry. The aim is to present standard properties of lines and planes,

More information

JON HOLTAN. if P&C Insurance Ltd., Oslo, Norway ABSTRACT

JON HOLTAN. if P&C Insurance Ltd., Oslo, Norway ABSTRACT OPTIMAL INSURANCE COVERAGE UNDER BONUS-MALUS CONTRACTS BY JON HOLTAN if P&C Insurance Lt., Oslo, Norway ABSTRACT The paper analyses the questions: Shoul or shoul not an iniviual buy insurance? An if so,

More information

Principle of Data Reduction

Principle of Data Reduction Chapter 6 Principle of Data Reduction 6.1 Introduction An experimenter uses the information in a sample X 1,..., X n to make inferences about an unknown parameter θ. If the sample size n is large, then

More information

VERTICES OF GIVEN DEGREE IN SERIES-PARALLEL GRAPHS

VERTICES OF GIVEN DEGREE IN SERIES-PARALLEL GRAPHS VERTICES OF GIVEN DEGREE IN SERIES-PARALLEL GRAPHS MICHAEL DRMOTA, OMER GIMENEZ, AND MARC NOY Abstract. We show that the number of vertices of a given degree k in several kinds of series-parallel labelled

More information

RIGIDITY OF HOLOMORPHIC MAPS BETWEEN FIBER SPACES

RIGIDITY OF HOLOMORPHIC MAPS BETWEEN FIBER SPACES RIGIDITY OF HOLOMORPHIC MAPS BETWEEN FIBER SPACES GAUTAM BHARALI AND INDRANIL BISWAS Abstract. In the study of holomorphic maps, the term rigidity refers to certain types of results that give us very specific

More information

Duality of linear conic problems

Duality of linear conic problems Duality of linear conic problems Alexander Shapiro and Arkadi Nemirovski Abstract It is well known that the optimal values of a linear programming problem and its dual are equal to each other if at least

More information

Chapter 2 Kinematics of Fluid Flow

Chapter 2 Kinematics of Fluid Flow Chapter 2 Kinematics of Flui Flow The stuy of kinematics has flourishe as a subject where one may consier isplacements an motions without imposing any restrictions on them; that is, there is no nee to

More information

3. Let A and B be two n n orthogonal matrices. Then prove that AB and BA are both orthogonal matrices. Prove a similar result for unitary matrices.

3. Let A and B be two n n orthogonal matrices. Then prove that AB and BA are both orthogonal matrices. Prove a similar result for unitary matrices. Exercise 1 1. Let A be an n n orthogonal matrix. Then prove that (a) the rows of A form an orthonormal basis of R n. (b) the columns of A form an orthonormal basis of R n. (c) for any two vectors x,y R

More information

L q -solutions to the Cosserat spectrum in bounded and exterior domains

L q -solutions to the Cosserat spectrum in bounded and exterior domains L q -solutions to the Cosserat spectrum in bounded exterior domains by Stephan Weyers, November 2005 Contents Introduction 3 Part I: Preliminaries 12 1 Notations 12 2 The space Ĥ1,q () 15 3 The space Ĥ2,q

More information

GROUPS ACTING ON A SET

GROUPS ACTING ON A SET GROUPS ACTING ON A SET MATH 435 SPRING 2012 NOTES FROM FEBRUARY 27TH, 2012 1. Left group actions Definition 1.1. Suppose that G is a group and S is a set. A left (group) action of G on S is a rule for

More information

Systems of Linear Equations

Systems of Linear Equations Systems of Linear Equations Beifang Chen Systems of linear equations Linear systems A linear equation in variables x, x,, x n is an equation of the form a x + a x + + a n x n = b, where a, a,, a n and

More information

Ideal Class Group and Units

Ideal Class Group and Units Chapter 4 Ideal Class Group and Units We are now interested in understanding two aspects of ring of integers of number fields: how principal they are (that is, what is the proportion of principal ideals

More information

RESULTANT AND DISCRIMINANT OF POLYNOMIALS

RESULTANT AND DISCRIMINANT OF POLYNOMIALS RESULTANT AND DISCRIMINANT OF POLYNOMIALS SVANTE JANSON Abstract. This is a collection of classical results about resultants and discriminants for polynomials, compiled mainly for my own use. All results

More information