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

Size: px
Start display at page:

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

Transcription

1 CHAPTER 1 : DIFFERENTIABLE MANIFOLDS 1.1 The efinition of a ifferentiable manifol Let M be a topological space. This means that we have a family Ω of open sets efine on M. These satisfy (1), M Ω (2) the union of any family of open sets is open (3) the intersection of a finite family of open sets is open We normally assume also the Hausorff property: For any pair x, y of istinct points there is a pair of nonoverlapping open sets U, V such that x U an y V. In any topological space one can efine the notion of convergence. A sequence x 1, x 2, x 3,... converges towars x M if any open set U such that x U contains all the points x n except a finite set. The basic example of a topological space is R n equippe with the Eucliean norm x 2 = x x x 2 n for x = (x 1,..., x n ). A set U R n is open if for any x U there is a positive number ɛ = ɛ(x) such that y U if x y < ɛ. The convergence is then the usual one: x (n) x if for any ɛ > 0 there is an integer n ɛ such that x x (n) < ɛ for n > n ɛ. Actually, all the spaces we stuy in (finite imensional) ifferential geometry are locally homeomorphic to R n. Definition. A topological space M is calle a smooth manifol of imension n if 1) there is a family of open sets U α (with α Λ) such that the union of all U α s is equal to M, 2) for each α there is a homeomorphism φ α : U α V α R n such that 3) the coorinate transformations φ α φ 1 β smooth functions in R n. on their omains of efinition are Example 1 R n is a smooth manifol. We nee only one coorinate chart U = M with φ : U R n the ientity mapping. Example 2 The same as above, but take M R n any open set. Example 3 Take M = S 1, the unit circle. Set U equal to the subset parametrize by the polar angle 0.1 < φ < π+0.1 an V equal to the set π < φ < 2π. Then U V consists of two intervals π < φ < π an 0.1 < φ < 0 2π 0.1 < φ < 2π. 1

2 2 The coorinate transformation is the ientity map φ φ on the former an the translation φ φ + 2π on the latter interval. Exercise Define a manifol structure on the unit sphere S 2. Example 4 The group GL(n, R) of invertible real n n matrices is a smooth manifol as an open subset of R n2. It is an open subset since it is a complement of the close surface etermine by the polynomial equation eta = Differentiable maps Let M, N be a pair of smooth manifols (of imensions m, n) an f : M N a continuous map. If (U, φ) is a local coorinate chart on M an (V, ψ) a coorinate chart on N then we have a map ψ f φ 1 from some open subset of R m to an open subset of R n. If the composite map is smooth for any pair of coorinate charts we say that f is smooth. The reaer shoul convince himself that the conition of smoothness for f oes not epen on the choice of coorinate charts. From elementary results in ifferential calculus it follows that if g : N P is another smooth map then also g f : M P is smooth. Note that we can write the map ψ f φ 1 as y = (y 1,..., y n ) = (y 1 (x 1,..., x m ),......, y n (x 1,..., x m )) in terms of the Cartesian coorinates. Smoothness of f simply means that the coorinate functions y i (x 1, x 2,..., x m ) are smooth functions. Remark In a given topological space M one can often construct ifferent inequivalent smooth structures. That is, one might be able to construct atlases {(U α, φ α )} an {(V α, ψ α )} such that both efine a structure of smooth manifol, say M U an M V, but the ientity map i : M U M V woul not be smooth. A famous example of this phenomen are the spheres S 7, S 11 (John Milnor, 1956). On the sphere S 7 there are exactly 28 inequivalent ifferentiable structures! On the Eucliean space R 4 there is an infinite number of ifferentiable structures (S.K. Donalson, 1983). A iffeomorphism is a one-to-one smooth map f : M N such that its inverse f 1 : N M is also smooth. The set of iffeomorphisms M M forms a group Diff(M). A smooth map f : M N is an immersion if at each point p M the rank of the erivative h x is equal to the imension of M. Here h = ψ f φ 1 with

3 the notation as before. Finally f : M N is an embeing if f is injective an it is an immersion; in that case f(m) N is an embee submanifol. A smooth curve on a manifol M is a smooth map γ from an open interval of the real axes to M. Let p M an (U, φ) a coorinate chart with p U. Assume that curves γ 1, γ 2 go through p, let us say p = γ i (0). We say that the curves are equivalent at p, γ 1 γ 2, if t φ(γ 1(t)) t=0 = t φ(γ 2(t)) t=0. This relation oes not epen on the choice of (U, φ) as is easily seen by the help of the chain rule: t ψ(γ 1(t)) t ψ(γ 2(t)) = (ψ φ 1 ) ( t φ(γ 1(t)) ) t φ(γ 2(t)) = 0 at the point t = 0. Clearly if γ 1 γ 2 an γ 2 γ 3 at the point p then also γ 1 γ 3 an γ 2 γ 1. Trivially γ γ for any curve γ through p so that is an equivalence relation. A tangent vector v at a point p is an equivalence class of smooth curves [γ] through p. For a given chart (U, φ) at p the equivalence classes are parametrize by the vector t φ(γ(t)) t=0 R n. Thus the space T p M of tangent vectors v = [γ] inherits the natural linear structure of R n. Again, it is a simple exercise using the chain rule that the linear structure oes not epen on the choice of the coorinate chart. We enote by T M the isjoint union of all the tangent spaces T p M. This is calle the tangent bunle of M. We shall efine a smooth structure on T M. Let p M an (U, φ) a coorinate chart at p. Let π : T M M the natural projection, (p, v) p. Define φ : π 1 (U) R n R n as φ(p, [γ]) = (φ(p), t φ(γ(t)) t=0). 3 If now (V, ψ) is another coorinate chart at p then ( φ ψ 1 )(x, v) = (φ(ψ 1 (x)), (φ ψ 1 ) (x)v), by the chain rule. It follows that φ ψ 1 is smooth in its omain of efinition an thus the pairs (π 1 (U), φ) form an atlas on T M, giving T M a smooth structure.

4 4 Example 1 If M is an open set in R n then T M = M R n. Example 2 Let M = S 1. Writing z S 1 as a complex number of unit moulus, consier curves through z written as γ(t) = ze ivt with v R. This gives in fact a parametrization for the equivalence classes [γ] as vectors in R. The tangent spaces at ifferent points z 1, z 2 are relate by the phase shift z 1 z 1 2 an it follows that T M is simply the prouct S 1 R. Example 3 In general, T M M R n. The simplest example for this is the unit sphere M = S 2. Using the spherical coorinates, for example, one can ientify the tangent space at a given point (θ, φ) as the plane R 2. However, there is no natural way to ientify the tangent spaces at ifferent points on the sphere; the sphere is not parallelizable. This is the content of the famous hairy ball theorem. Any smooth vector fiel on the sphere has zeros. (If there were a globally nonzero vector fiel on S 2 we woul obtain a basis in all the tangent spaces by taking a (oriente) unit normal vector fiel to the given vector fiel. Together they woul form a basis in the tangent spaces an coul be use for ientifying the tangent spaces as a stanar R 2.) Exercise The unit 3-sphere S 3 can be thought of complex unitary 2 2 matrices with eterminant =1. T S 3 = S 3 R 3. Use this fact to show that the tangent bunle is trivial, Let f : M N be a smooth map. We efine a linear map T p f : T p M T f(p) N, as T p f [γ] = [f γ], where γ is a curve through the point p. This map is expresse in terms of local coorinates as follows. Let (U, φ) be a coorinate chart at p an (V, ψ) a chart at f(p) N. Then the coorinates for [γ] T p M are v = t φ(γ(t)) t=0 an the coorinates for [f γ] T f(p) N are w = t ψ(f(γ(t))) t=0. But by the chain rule, w = (ψ f φ 1 ) (x) t φ(γ(t)) t=0 = (ψ f φ 1 ) (x) v with x = φ(p). Thus in local coorinates the linear map T p f is the erivative of ψ f φ 1 at the point x. Putting together all the maps T p f we obtain a map T f : T M T N.

5 5 Proposition. The map T f : T M T N is smooth. Proof. Recall that the coorinate charts (U, φ), (V, ψ) on M, N, respectivly, lea to coorinate charts (π 1 (U), φ) an (π 1 (V ), ψ) on T M, T N. Now ( ψ T f φ 1 )(x, v) = ((ψ f φ 1 )(x), (ψ f φ 1 ) (x)v) for (x, v) φ(π 1 (U)) R m R m. Both component functions are smooth an thus T f is smooth by efinition. If f : M N an g : N P are smooth maps then g f : M P is smooth an T (g f) = T g T f. To see this, the curve γ through p M is first mappe to f γ through f(p) N an further, by T g, to the curve g f γ through g(f(p)) P. In terms of local coorinates x i at p, y i at f(p) an z i at g(f(p)) the chain rule becomes the stanar formula, z i x j = k z i y k y k x j. 1.3 Vector fiels We enote by C (M) the algebra of smooth real value functions on M. A erivation of the algebra C (M) is a linear map : C (M) C (M) such that (fg) = (f)g + f(g) for all f, g. Let v T p M an f C (M). Choose a curve γ through p representing v. Set v f = t f(γ(t)) t=0. Clearly v : C (M) R is linear. Furthermore, v (fg) = t f(γ(t)) t=0g(γ(0)) + f(γ(0)) t g(γ(t)) t=0 = (v f)g(p) + f(p)(v g). A vector fiel on a manifol M is a smooth istribution of tangent vectors on M, that is, a smooth map X : M T M such that X(p) T p M. From the

6 6 previous formula follows that a vector fiel efines a erivation of C (M); take above v = X(p) at each point p M an the right- han-sie efines a smooth function on M an the operation satisfies the Leibnitz rule. We enote by D 1 (M) the space of vector fiels on M. As we have seen, a vector fiel gives a linear map X : C (M) C (M) obeying the Leibnitz rule. Conversely, one can prove that any erivation of the algebra C (M) is represente by a vector fiel. One can evelope an algebraic approach to manifol theory. In that the commutative algebra A = C (M) plays a central role. Points in M correspon to maximal ieals in the algebra A. Namely, any point p efines the ieal I p A consisting of all functions which vanish at the point p. The action of a vector fiel on functions is given in terms of local coorinates x 1,..., x n as follows. If v = X(p) is represente by a curve γ then (X f)(p) = t f(γ(t)) t=0 = k f x k x k t (t = 0) k X k (x) f x k. Thus a vector fiel is locally represente by the vector value function (X 1 (x),..., X n (x)). In aition of being a real vector space, D 1 (M) is a left moule for the algebra C (M). This means that we have a linear left multiplication (f, X) fx. The value of fx at a point p is simply the vector f(p)x(p) T p M. As we have seen, in a coorinate system x i a vector fiel efines a erivation with local representation X = k X k x k. In a secon coorinate system x k we have a representation X = X k x k obtain the coorinate transformation rule. Using the chain rule for ifferentiation we X k(x ) = j x k x j X j (x), for x k = x k (x 1,..., x n ). We shall enote k = x k repeate inices, an we use Einstein s summation convention over Let X, Y D 1 (M). We efine a new erivation of C (M), the commutator [X, Y ] D 1 (M), by [X, Y ]f = X(Y f) Y (Xf).

7 7 We prove that this is inee a erivation of C (M). [X, Y ](fg) = X(Y (fg)) Y (X(fg)) = X(fY g + gy f) Y (fxg + gxf) = (Xf)(Y g) + fx(y g) + (Xg)(Y f) + gx(y f) (Y f)(xg) fy (Xg) (Y g)(xf) gy (Xf) = f[x, Y ]g + g[x, Y ]f. Writing X = X k k an Y = Y k k we obtain the coorinate expression [X, Y ] k = X j j Y k Y j j X k. Thus we may view D 1 (M) simply as the space of first orer linear partial ifferential operators on M with the orinary commutator of ifferential operators. The commutator [X, Y ] is also calle the Lie bracket on D 1 (M). It has the basic properties (1) [X, Y ] is linear in both arguments (2) [X, Y ] = [Y, X] (3) [X, [Y, Z]] + [Y, [Z, X]] + [Z, [X, Y ]] = 0. The last property is calle the Jacobi ientity. A vector space equippe with a Lie bracket satisfying the properties above is calle a Lie algebra. Other examples of Lie algebras: Example 1 Any vector space with the bracket [X, Y ] = 0. Example 2 The angular momentum Lie algebra with basis L 1, L 2, L 3 an nonzero commutators [L 1, L 2 ] = L 3 + cyclically permute relations. Example 3 The space of n n matrices with the usual commutator of matrices, [X, Y ] = XY Y X. Exercise Check the relations [X, fy ] = f[x, Y ] + (Xf)Y, an [fx, Y ] = f[x, Y ] (Y f)x for X, Y D 1 (M) an f C (M). Let f : M N be a iffeomorphism an X D 1 (M). We can efine a vector fiel Y = f X on N by setting Y (q) = T p f X(p) for q = f(p). In terms of local coorinates, y k Y = Y k = X j. y k x j y k

8 8 In the case M = N this gives back the coorinate transformation rule for vector fiels. Let X D 1 (M). Consier the ifferential equation X(γ(t)) = t γ(t) for a smooth curve γ. In terms of local coorinates this equation is written as X k (x(t)) = t x k(t), k = 1, 2,..., n. By the theory of orinary ifferential equations this system has locally, at a neighborhoo of an initial point p = γ(0), a unique solution. However, in general the solution oes not nee to exten to < t < + except in the case when M is a compact manifol. The (local) solution γ is calle an integral curve of X through the point p. The integral curves for a vector fiel X efine a (local) flow on the manifol M. This is a (local) map f : R M M given by f(t, p) = γ(t) where γ is the integral curve through p. We have the ientity (1) f(t + s, p) = f(t, f(s, p)), which follows from the uniqueness of the local solution to the first orer orinary ifferential equation. In coorinates, an t f k(t, f(s, x)) = X k (f(t, f(s, x))) t f k(t + s, x) = X k (f(t + s, x)). Thus both sies of (1) obey the same ifferential equation. Since the initial conitions are the same, at t = 0 both sies are equal to f(0, f(s, x)) = f(s, x), the solutions must agree. Denoting f t (p) = f(t, p), observe that the map R Diff loc (M), t f t, is a homomorphism, f t f s = f t+s.

9 Thus we have a one parameter group of (local) transformations f t on M. In the case when M is compact we actually have globally globally efine transformations on M. Example Let X(r, φ) = ( r sin φ, r cos φ) be a vector fiel on M = R 2. The integral curves are solutions of the equations 9 x (t) = r(t) sin φ(t) y (t) = r(t) cos φ(t) an the solutions are easily seen to be given by (x(t), y(t)) = (r 0 cos(φ+φ 0 ), r 0 sin(φ+ φ 0 )), where the initial conition is specifie by the constants φ 0, r 0. The one parameter group of tranformations generate by the vector fiel X is then the group of rotations in the plane. Further reaing: M. Nakahara: Geometry, Topology an Physics, Institute of Physics Publ. (1990), sections S. S. Chern, W.H. Chen, K.S. Lam: Lectures on Differential Geometry, Worl Scientific Publ. (1999), Chapter 1.

Darboux s theorem and symplectic geometry

Darboux s theorem and symplectic geometry Darboux s theorem an symplectic geometry Liang, Feng May 9, 2014 Abstract Symplectic geometry is a very important branch of ifferential geometry, it is a special case of poisson geometry, an coul also

More information

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

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

More information

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

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

More information

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

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

More information

PDE Notes, Lecture #11

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

More information

Euler equations for multiple integrals

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

More information

DIFFERENTIAL GEOMETRY, LECTURE 15, JULY 10

DIFFERENTIAL GEOMETRY, LECTURE 15, JULY 10 DIFFERENTIAL GEOMETRY, LECTURE 15, JULY 10 5. Levi-Civita connection From now on we are intereste in connections on the tangent bunle T X of a Riemanninam manifol (X, g). Out main result will be a construction

More information

SYMPLECTIC GEOMETRY: LECTURE 3

SYMPLECTIC GEOMETRY: LECTURE 3 SYMPLECTIC GEOMETRY: LECTURE 3 LIAT KESSLER 1. Local forms Vector fiels an the Lie erivative. A vector fiel on a manifol M is a smooth assignment of a vector tangent to M at each point. We think of M as

More information

fy (X(g)) Y (f)x(g) gy (X(f)) Y (g)x(f)) = fx(y (g)) + gx(y (f)) fy (X(g)) gy (X(f))

fy (X(g)) Y (f)x(g) gy (X(f)) Y (g)x(f)) = fx(y (g)) + gx(y (f)) fy (X(g)) gy (X(f)) 1. Basic algebra of vector fields Let V be a finite dimensional vector space over R. Recall that V = {L : V R} is defined to be the set of all linear maps to R. V is isomorphic to V, but there is no canonical

More information

LECTURE 1: BASIC CONCEPTS, PROBLEMS, AND EXAMPLES

LECTURE 1: BASIC CONCEPTS, PROBLEMS, AND EXAMPLES LECTURE 1: BASIC CONCEPTS, PROBLEMS, AND EXAMPLES WEIMIN CHEN, UMASS, SPRING 07 In this lecture we give a general introuction to the basic concepts an some of the funamental problems in symplectic geometry/topology,

More information

Quantum Mechanics in Three Dimensions

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

More information

Physics 5153 Classical Mechanics. The Virial Theorem and The Poisson Bracket-1

Physics 5153 Classical Mechanics. The Virial Theorem and The Poisson Bracket-1 Physics 5153 Classical Mechanics The Virial Theorem an The Poisson Bracket 1 Introuction In this lecture we will consier two applications of the Hamiltonian. The first, the Virial Theorem, applies to systems

More information

Final Exam Study Guide and Practice Problems Solutions

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

More information

7. Localization. (d 1, m 1 ) (d 2, m 2 ) d 3 D : d 3 d 1 m 2 = d 3 d 2 m 1. (ii) If (d 1, m 1 ) (d 1, m 1 ) and (d 2, m 2 ) (d 2, m 2 ) then

7. Localization. (d 1, m 1 ) (d 2, m 2 ) d 3 D : d 3 d 1 m 2 = d 3 d 2 m 1. (ii) If (d 1, m 1 ) (d 1, m 1 ) and (d 2, m 2 ) (d 2, m 2 ) then 7. Localization To prove Theorem 6.1 it becomes necessary to be able to a enominators to rings (an to moules), even when the rings have zero-ivisors. It is a tool use all the time in commutative algebra,

More information

Schrödinger s equation.

Schrödinger s equation. Physics 342 Lecture 5 Schröinger s Equation Lecture 5 Physics 342 Quantum Mechanics I Wenesay, February 3r, 2010 Toay we iscuss Schröinger s equation an show that it supports the basic interpretation of

More information

Math 115 Section 018 Course Note

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

More information

23 Implicit differentiation

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

More information

Tensors, Fields Pt. 1 and the Lie Bracket Pt. 1

Tensors, Fields Pt. 1 and the Lie Bracket Pt. 1 Tensors, Fiels Pt. 1 an the Lie Bracket Pt. 1 PHYS 500 - Southern Illinois University September 8, 2016 PHYS 500 - Southern Illinois University Tensors, Fiels Pt. 1 an the Lie Bracket Pt. 1 September 8,

More information

Table of Common Derivatives By David Abraham

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

More information

6 General properties of an autonomous system of two first order ODE

6 General properties of an autonomous system of two first order ODE 6 General properties of an autonomous system of two first orer ODE Here we embark on stuying the autonomous system of two first orer ifferential equations of the form ẋ 1 = f 1 (, x 2 ), ẋ 2 = f 2 (, x

More information

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

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

More information

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

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

More information

Lagrangian and Hamiltonian Mechanics

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

More information

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

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

More information

1 Lecture 20: Implicit differentiation

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

More information

Differentiability, Computing Derivatives, Trig Review. Goals:

Differentiability, Computing Derivatives, Trig Review. Goals: Secants vs. Derivatives - Unit #3 : Goals: Differentiability, Computing Derivatives, Trig Review Determine when a function is ifferentiable at a point Relate the erivative graph to the the graph of an

More information

ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS

ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS MARK SCHACHNER Abstract. When consiere as an algebraic space, the set of arithmetic functions equippe with the operations of pointwise aition an

More information

Diagonalization of Matrices Dr. E. Jacobs

Diagonalization of Matrices Dr. E. Jacobs Diagonalization of Matrices Dr. E. Jacobs One of the very interesting lessons in this course is how certain algebraic techniques can be use to solve ifferential equations. The purpose of these notes is

More information

Implicit Differentiation

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

More information

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

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

More information

Further Differentiation and Applications

Further Differentiation and Applications Avance Higher Notes (Unit ) Prerequisites: Inverse function property; prouct, quotient an chain rules; inflexion points. Maths Applications: Concavity; ifferentiability. Real-Worl Applications: Particle

More information

Exam 2 Review Solutions

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

More information

Sturm-Liouville Theory

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

More information

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

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

More information

1 Second Facts About Spaces of Modular Forms

1 Second Facts About Spaces of Modular Forms April 30, :00 pm 1 Secon Facts About Spaces of Moular Forms We have repeately use facts about the imensions of the space of moular forms, mostly to give specific examples of an relations between moular

More information

13.1: Vector-Valued Functions and Motion in Space, 14.1: Functions of Several Variables, and 14.2: Limits and Continuity in Higher Dimensions

13.1: Vector-Valued Functions and Motion in Space, 14.1: Functions of Several Variables, and 14.2: Limits and Continuity in Higher Dimensions 13.1: Vector-Value Functions an Motion in Space, 14.1: Functions of Several Variables, an 14.2: Limits an Continuity in Higher Dimensions TA: Sam Fleischer November 3 Section 13.1: Vector-Value Functions

More information

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control 19 Eigenvalues, Eigenvectors, Orinary Differential Equations, an Control This section introuces eigenvalues an eigenvectors of a matrix, an iscusses the role of the eigenvalues in etermining the behavior

More information

Introduction to the Vlasov-Poisson system

Introduction to the Vlasov-Poisson system Introuction to the Vlasov-Poisson system Simone Calogero 1 The Vlasov equation Consier a particle with mass m > 0. Let x(t) R 3 enote the position of the particle at time t R an v(t) = ẋ(t) = x(t)/t its

More information

Differentiability, Computing Derivatives, Trig Review

Differentiability, Computing Derivatives, Trig Review Unit #3 : Differentiability, Computing Derivatives, Trig Review Goals: Determine when a function is ifferentiable at a point Relate the erivative graph to the the graph of an original function Compute

More information

1 Definition of the derivative

1 Definition of the derivative Math 20A - Calculus by Jon Rogawski Chapter 3 - Differentiation Prepare by Jason Gais Definition of the erivative Remark.. Recall our iscussion of tangent lines from way back. We now rephrase this in terms

More information

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

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

More information

Differentiation ( , 9.5)

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

More information

Ordinary Differential Equations: Homework 2

Ordinary Differential Equations: Homework 2 Orinary Differential Equations: Homework 2 M. Gameiro, J.-P. Lessar, J.D. Mireles James, K. Mischaikow January 30, 2017 2 0.1 Eercises Eercise 0.1.1. Let (X, ) be a metric space. function (in the metric

More information

Characteristic classes of vector bundles

Characteristic classes of vector bundles Characteristic classes of vector bunles Yoshinori Hashimoto 1 Introuction Let be a smooth, connecte, compact manifol of imension n without bounary, an p : E be a real or complex vector bunle of rank k

More information

Zachary Scherr Math 503 HW 5 Due Friday, Feb 26

Zachary Scherr Math 503 HW 5 Due Friday, Feb 26 Zachary Scherr Math 503 HW 5 Due Friay, Feb 26 1 Reaing 1. Rea Chapter 9 of Dummit an Foote 2 Problems 1. 9.1.13 Solution: We alreay know that if R is any commutative ring, then R[x]/(x r = R for any r

More information

1 Heisenberg Representation

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

More information

model considered before, but the prey obey logistic growth in the absence of predators. In

model considered before, but the prey obey logistic growth in the absence of predators. In 5.2. First Orer Systems of Differential Equations. Phase Portraits an Linearity. Section Objective(s): Moifie Preator-Prey Moel. Graphical Representations of Solutions. Phase Portraits. Vector Fiels an

More information

BLOW-UP FORMULAS FOR ( 2)-SPHERES

BLOW-UP FORMULAS FOR ( 2)-SPHERES BLOW-UP FORMULAS FOR 2)-SPHERES ROGIER BRUSSEE In this note we give a universal formula for the evaluation of the Donalson polynomials on 2)-spheres, i.e. smooth spheres of selfintersection 2. Note that

More information

Algebra IV. Contents. Alexei Skorobogatov. December 12, 2017

Algebra IV. Contents. Alexei Skorobogatov. December 12, 2017 Algebra IV Alexei Skorobogatov December 12, 2017 Abstract This course is an introuction to homological algebra an group cohomology. Contents 1 Moules over a ring 2 1.1 Definitions an examples.........................

More information

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes Fin these erivatives of these functions: y.7 Implicit Differentiation -- A Brief Introuction -- Stuent Notes tan y sin tan = sin y e = e = Write the inverses of these functions: y tan y sin How woul we

More information

G4003 Advanced Mechanics 1. We already saw that if q is a cyclic variable, the associated conjugate momentum is conserved, L = const.

G4003 Advanced Mechanics 1. We already saw that if q is a cyclic variable, the associated conjugate momentum is conserved, L = const. G4003 Avance Mechanics 1 The Noether theorem We alreay saw that if q is a cyclic variable, the associate conjugate momentum is conserve, q = 0 p q = const. (1) This is the simplest incarnation of Noether

More information

Pure Further Mathematics 1. Revision Notes

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

More information

Math 342 Partial Differential Equations «Viktor Grigoryan

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

More information

Separation of Variables

Separation of Variables Physics 342 Lecture 1 Separation of Variables Lecture 1 Physics 342 Quantum Mechanics I Monay, January 25th, 2010 There are three basic mathematical tools we nee, an then we can begin working on the physical

More information

The Non-abelian Hodge Correspondence for Non-Compact Curves

The Non-abelian Hodge Correspondence for Non-Compact Curves 1 Section 1 Setup The Non-abelian Hoge Corresponence for Non-Compact Curves Chris Elliott May 8, 2011 1 Setup In this talk I will escribe the non-abelian Hoge theory of a non-compact curve. This was worke

More information

Euler Equations: derivation, basic invariants and formulae

Euler Equations: derivation, basic invariants and formulae Euler Equations: erivation, basic invariants an formulae Mat 529, Lesson 1. 1 Derivation The incompressible Euler equations are couple with t u + u u + p = 0, (1) u = 0. (2) The unknown variable is the

More information

Function Spaces. 1 Hilbert Spaces

Function Spaces. 1 Hilbert Spaces Function Spaces A function space is a set of functions F that has some structure. Often a nonparametric regression function or classifier is chosen to lie in some function space, where the assume structure

More information

Implicit Differentiation

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

More information

Manifolds and tangent bundles. Vector fields and flows. 1 Differential manifolds, smooth maps, submanifolds

Manifolds and tangent bundles. Vector fields and flows. 1 Differential manifolds, smooth maps, submanifolds MA 755 Fall 05. Notes #1. I. Kogan. Manifolds and tangent bundles. Vector fields and flows. 1 Differential manifolds, smooth maps, submanifolds Definition 1 An n-dimensional C k -differentiable manifold

More information

INTERSECTION HOMOLOGY OF LINKAGE SPACES IN ODD DIMENSIONAL EUCLIDEAN SPACE

INTERSECTION HOMOLOGY OF LINKAGE SPACES IN ODD DIMENSIONAL EUCLIDEAN SPACE INTERSECTION HOMOLOGY OF LINKAGE SPACES IN ODD DIMENSIONAL EUCLIDEAN SPACE DIRK SCHÜTZ Abstract. We consier the mouli spaces M (l) of a close linkage with n links an prescribe lengths l R n in -imensional

More information

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

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

More information

Convergence of Random Walks

Convergence of Random Walks Chapter 16 Convergence of Ranom Walks This lecture examines the convergence of ranom walks to the Wiener process. This is very important both physically an statistically, an illustrates the utility of

More information

Linear First-Order Equations

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

More information

Differentiation Rules Derivatives of Polynomials and Exponential Functions

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

More information

Fall 2016: Calculus I Final

Fall 2016: Calculus I Final Answer the questions in the spaces provie on the question sheets. If you run out of room for an answer, continue on the back of the page. NO calculators or other electronic evices, books or notes are allowe

More information

1 Lecture 13: The derivative as a function.

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

More information

Nöether s Theorem Under the Legendre Transform by Jonathan Herman

Nöether s Theorem Under the Legendre Transform by Jonathan Herman Nöether s Theorem Uner the Legenre Transform by Jonathan Herman A research paper presente to the University of Waterloo in fulfilment of the research paper requirement for the egree of Master of Mathematics

More information

0.1 Diffeomorphisms. 0.2 The differential

0.1 Diffeomorphisms. 0.2 The differential Lectures 6 and 7, October 10 and 12 Easy fact: An open subset of a differentiable manifold is a differentiable manifold of the same dimension the ambient space differentiable structure induces a differentiable

More information

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

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

More information

February 21 Math 1190 sec. 63 Spring 2017

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

More information

Zachary Scherr Math 503 HW 3 Due Friday, Feb 12

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

More information

Section 7.2. The Calculus of Complex Functions

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

More information

Partial Differential Equations

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

More information

Characterizing Real-Valued Multivariate Complex Polynomials and Their Symmetric Tensor Representations

Characterizing Real-Valued Multivariate Complex Polynomials and Their Symmetric Tensor Representations Characterizing Real-Value Multivariate Complex Polynomials an Their Symmetric Tensor Representations Bo JIANG Zhening LI Shuzhong ZHANG December 31, 2014 Abstract In this paper we stuy multivariate polynomial

More information

arxiv: v1 [math.dg] 1 Nov 2015

arxiv: v1 [math.dg] 1 Nov 2015 DARBOUX-WEINSTEIN THEOREM FOR LOCALLY CONFORMALLY SYMPLECTIC MANIFOLDS arxiv:1511.00227v1 [math.dg] 1 Nov 2015 ALEXANDRA OTIMAN AND MIRON STANCIU Abstract. A locally conformally symplectic (LCS) form is

More information

Math 1272 Solutions for Spring 2005 Final Exam. asked to find the limit of the sequence. This is equivalent to evaluating lim. lim.

Math 1272 Solutions for Spring 2005 Final Exam. asked to find the limit of the sequence. This is equivalent to evaluating lim. lim. Math 7 Solutions for Spring 5 Final Exam ) We are gien an infinite sequence for which the general term is a n 3 + 5n n + n an are 3 + 5n aske to fin the limit of the sequence. This is equialent to ealuating

More information

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

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

More information

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy,

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy, NOTES ON EULER-BOOLE SUMMATION JONATHAN M BORWEIN, NEIL J CALKIN, AND DANTE MANNA Abstract We stuy a connection between Euler-MacLaurin Summation an Boole Summation suggeste in an AMM note from 196, which

More information

Lecture 1b. Differential operators and orthogonal coordinates. Partial derivatives. Divergence and divergence theorem. Gradient. A y. + A y y dy. 1b.

Lecture 1b. Differential operators and orthogonal coordinates. Partial derivatives. Divergence and divergence theorem. Gradient. A y. + A y y dy. 1b. b. Partial erivatives Lecture b Differential operators an orthogonal coorinates Recall from our calculus courses that the erivative of a function can be efine as f ()=lim 0 or using the central ifference

More information

INTRODUCTION TO SYMPLECTIC MECHANICS: LECTURE IV. Maurice de Gosson

INTRODUCTION TO SYMPLECTIC MECHANICS: LECTURE IV. Maurice de Gosson INTRODUCTION TO SYMPLECTIC MECHANICS: LECTURE IV Maurice e Gosson ii 4 Hamiltonian Mechanics Physically speaking, Hamiltonian mechanics is a paraphrase (an generalization!) of Newton s secon law, popularly

More information

Chapter 2 Lagrangian Modeling

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

More information

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

Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling. Chapter 8 Analytic Functions Stuents nee encouragement. So if a stuent gets an answer right, tell them it was a lucky guess. That way, they evelop a goo, lucky feeling. 1 8.1 Complex Derivatives -Jack

More information

MAT 545: Complex Geometry Fall 2008

MAT 545: Complex Geometry Fall 2008 MAT 545: Complex Geometry Fall 2008 Notes on Lefschetz Decomposition 1 Statement Let (M, J, ω) be a Kahler manifol. Since ω is a close 2-form, it inuces a well-efine homomorphism L: H k (M) H k+2 (M),

More information

12.11 Laplace s Equation in Cylindrical and

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

More information

The Exact Form and General Integrating Factors

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

More information

From Local to Global Control

From Local to Global Control Proceeings of the 47th IEEE Conference on Decision an Control Cancun, Mexico, Dec. 9-, 8 ThB. From Local to Global Control Stephen P. Banks, M. Tomás-Roríguez. Automatic Control Engineering Department,

More information

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) 2t 1 + t 2 cos x = 1 t2 sin x =

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) 2t 1 + t 2 cos x = 1 t2 sin x = 6.4 Integration using tan/ We will revisit the ouble angle ientities: sin = sin/ cos/ = tan/ sec / = tan/ + tan / cos = cos / sin / tan = = tan / sec / tan/ tan /. = tan / + tan / So writing t = tan/ we

More information

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

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

More information

REAL ANALYSIS I HOMEWORK 5

REAL ANALYSIS I HOMEWORK 5 REAL ANALYSIS I HOMEWORK 5 CİHAN BAHRAN The questions are from Stein an Shakarchi s text, Chapter 3. 1. Suppose ϕ is an integrable function on R with R ϕ(x)x = 1. Let K δ(x) = δ ϕ(x/δ), δ > 0. (a) Prove

More information

CAUCHY INTEGRAL THEOREM

CAUCHY INTEGRAL THEOREM CAUCHY INTEGRAL THEOREM XI CHEN 1. Differential Forms, Integration an Stokes Theorem Let X be an open set in R n an C (X) be the set of complex value C functions on X. A ifferential 1-form is (1.1) ω =

More information

ON THE GEOMETRIC APPROACH TO THE MOTION OF INERTIAL MECHANICAL SYSTEMS

ON THE GEOMETRIC APPROACH TO THE MOTION OF INERTIAL MECHANICAL SYSTEMS ON THE GEOMETRIC APPROACH TO THE MOTION OF INERTIAL MECHANICAL SYSTEMS ADRIAN CONSTANTIN AND BORIS KOLEV Abstract. Accoring to the principle of least action, the spatially perioic motions of one-imensional

More information

Survival Facts from Quantum Mechanics

Survival Facts from Quantum Mechanics Survival Facts from Quantum Mechanics Operators, Eigenvalues an Eigenfunctions An operator O may be thought as something that operates on a function to prouce another function. We enote operators with

More information

Mathematical Review Problems

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

More information

u!i = a T u = 0. Then S satisfies

u!i = a T u = 0. Then S satisfies Deterministic Conitions for Subspace Ientifiability from Incomplete Sampling Daniel L Pimentel-Alarcón, Nigel Boston, Robert D Nowak University of Wisconsin-Maison Abstract Consier an r-imensional subspace

More information

Integration Review. May 11, 2013

Integration Review. May 11, 2013 Integration Review May 11, 2013 Goals: Review the funamental theorem of calculus. Review u-substitution. Review integration by parts. Do lots of integration eamples. 1 Funamental Theorem of Calculus In

More information

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) = 2 2t 1 + t 2 cos x = 1 t2 We will revisit the double angle identities:

cosh x sinh x So writing t = tan(x/2) we have 6.4 Integration using tan(x/2) = 2 2t 1 + t 2 cos x = 1 t2 We will revisit the double angle identities: 6.4 Integration using tanx/) We will revisit the ouble angle ientities: sin x = sinx/) cosx/) = tanx/) sec x/) = tanx/) + tan x/) cos x = cos x/) sin x/) tan x = = tan x/) sec x/) tanx/) tan x/). = tan

More information

Section 7.1: Integration by Parts

Section 7.1: Integration by Parts Section 7.1: Integration by Parts 1. Introuction to Integration Techniques Unlike ifferentiation where there are a large number of rules which allow you (in principle) to ifferentiate any function, the

More information

Introduction to variational calculus: Lecture notes 1

Introduction to variational calculus: Lecture notes 1 October 10, 2006 Introuction to variational calculus: Lecture notes 1 Ewin Langmann Mathematical Physics, KTH Physics, AlbaNova, SE-106 91 Stockholm, Sween Abstract I give an informal summary of variational

More information

SYDE 112, LECTURE 1: Review & Antidifferentiation

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

More information