The Heat Kernel Dexter Chua
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Laplace's Equation, the Wave Equation and More
Lecture Notes on PDEs, part II: Laplace's equation, the wave equation and more Fall 2018 Contents 1 The wave equation (introduction)2 1.1 Solution (separation of variables)........................3 1.2 Standing waves..................................4 1.3 Solution (eigenfunction expansion).......................6 2 Laplace's equation8 2.1 Solution in a rectangle..............................9 2.2 Rectangle, with more boundary conditions................... 11 2.2.1 Remarks on separation of variables for Laplace's equation....... 13 3 More solution techniques 14 3.1 Steady states................................... 14 3.2 Moving inhomogeneous BCs into a source................... 17 4 Inhomogeneous boundary conditions 20 4.1 A useful lemma.................................. 20 4.2 PDE with Inhomogeneous BCs: example.................... 21 4.2.1 The new part: equations for the coefficients.............. 21 4.2.2 The rest of the solution.......................... 22 4.3 Theoretical note: What does it mean to be a solution?............ 23 5 Robin boundary conditions 24 5.1 Eigenvalues in nasty cases, graphically..................... 24 5.2 Solving the PDE................................. 26 6 Equations in other geometries 29 6.1 Laplace's equation in a disk........................... 29 7 Appendix 31 7.1 PDEs with source terms; example........................ 31 7.2 Good basis functions for Laplace's equation.................. 33 7.3 Compatibility conditions............................. 34 1 1 The wave equation (introduction) The wave equation is the third of the essential linear PDEs in applied mathematics. In one dimension, it has the form 2 utt = c uxx for u(x; t): As the name suggests, the wave equation describes the propagation of waves, so it is of fundamental importance to many fields. -
THE ONE-DIMENSIONAL HEAT EQUATION. 1. Derivation. Imagine a Dilute Material Species Free to Diffuse Along One Dimension
THE ONE-DIMENSIONAL HEAT EQUATION. 1. Derivation. Imagine a dilute material species free to diffuse along one dimension; a gas in a cylindrical cavity, for example. To model this mathematically, we consider the concentration of the given species as a function of the linear dimension and time: u(x; t), defined so that the total amount Q of diffusing material contained in a given interval [a; b] is equal to (or at least proportional to) the integral of u: Z b Q[a; b](t) = u(x; t)dx: a Then the conservation law of the species in question says the rate of change of Q[a; b] in time equals the net amount of the species flowing into [a; b] through its boundary points; that is, there exists a function d(x; t), the ‘diffusion rate from right to left', so that: dQ[a; b] = d(b; t) − d(a; t): dt It is an experimental fact about diffusion phenomena (which can be under- stood in terms of collisions of large numbers of particles) that the diffusion rate at any point is proportional to the gradient of concentration, with the right-to-left flow rate being positive if the concentration is increasing from left to right at (x; t), that is: d(x; t) > 0 when ux(x; t) > 0. So as a first approximation, it is natural to set: d(x; t) = kux(x; t); k > 0 (`Fick's law of diffusion’ ): Combining these two assumptions we have, for any bounded interval [a; b]: d Z b u(x; t)dx = k(ux(b; t) − ux(a; t)): dt a Since b is arbitrary, differentiating both sides as a function of b we find: ut(x; t) = kuxx(x; t); the diffusion (or heat) equation in one dimension. -
Notes on the Atiyah-Singer Index Theorem Liviu I. Nicolaescu
Notes on the Atiyah-Singer Index Theorem Liviu I. Nicolaescu Notes for a topics in topology course, University of Notre Dame, Spring 2004, Spring 2013. Last revision: November 15, 2013 i The Atiyah-Singer Index Theorem This is arguably one of the deepest and most beautiful results in modern geometry, and in my view is a must know for any geometer/topologist. It has to do with elliptic partial differential opera- tors on a compact manifold, namely those operators P with the property that dim ker P; dim coker P < 1. In general these integers are very difficult to compute without some very precise information about P . Remarkably, their difference, called the index of P , is a “soft” quantity in the sense that its determination can be carried out relying only on topological tools. You should compare this with the following elementary situation. m n Suppose we are given a linear operator A : C ! C . From this information alone we cannot compute the dimension of its kernel or of its cokernel. We can however compute their difference which, according to the rank-nullity theorem for n×m matrices must be dim ker A−dim coker A = m − n. Michael Atiyah and Isadore Singer have shown in the 1960s that the index of an elliptic operator is determined by certain cohomology classes on the background manifold. These cohomology classes are in turn topological invariants of the vector bundles on which the differential operator acts and the homotopy class of the principal symbol of the operator. Moreover, they proved that in order to understand the index problem for an arbitrary elliptic operator it suffices to understand the index problem for a very special class of first order elliptic operators, namely the Dirac type elliptic operators. -
Heat Kernels and Function Theory on Metric Measure Spaces
Heat kernels and function theory on metric measure spaces Alexander Grigor’yan Imperial College London SW7 2AZ United Kingdom and Institute of Control Sciences of RAS Moscow, Russia email: [email protected] Contents 1 Introduction 2 2 Definition of a heat kernel and examples 5 3 Volume of balls 8 4 Energy form 10 5 Besov spaces and energy domain 13 5.1 Besov spaces in Rn ............................ 13 5.2 Besov spaces in a metric measure space . 14 5.3 Identification of energy domains and Besov spaces . 15 5.4 Subordinated heat kernel ......................... 19 6 Intrinsic characterization of walk dimension 22 7 Inequalities for walk dimension 23 8 Embedding of Besov spaces into H¨olderspaces 29 9 Bessel potential spaces 30 1 1 Introduction The classical heat kernel in Rn is the fundamental solution to the heat equation, which is given by the following formula 1 x y 2 pt (x, y) = exp | − | . (1.1) n/2 t (4πt) − 4 ! x y 2 It is worth observing that the Gaussian term exp | − | does not depend in n, − 4t n/2 whereas the other term (4πt)− reflects the dependence of the heat kernel on the underlying space via its dimension. The notion of heat kernel extends to any Riemannian manifold M. In this case, the heat kernel pt (x, y) is the minimal positive fundamental solution to the heat ∂u equation ∂t = ∆u where ∆ is the Laplace-Beltrami operator on M, and it always exists (see [11], [13], [16]). Under certain assumptions about M, the heat kernel can be estimated similarly to (1.1). -
LECTURE 7: HEAT EQUATION and ENERGY METHODS Readings
LECTURE 7: HEAT EQUATION AND ENERGY METHODS Readings: • Section 2.3.4: Energy Methods • Convexity (see notes) • Section 2.3.3a: Strong Maximum Principle (pages 57-59) This week we'll discuss more properties of the heat equation, in partic- ular how to apply energy methods to the heat equation. In fact, let's start with energy methods, since they are more fun! Recall the definition of parabolic boundary and parabolic cylinder from last time: Notation: UT = U × (0;T ] ΓT = UT nUT Note: Think of ΓT like a cup: It contains the sides and bottoms, but not the top. And think of UT as water: It contains the inside and the top. Date: Monday, May 11, 2020. 1 2 LECTURE 7: HEAT EQUATION AND ENERGY METHODS Weak Maximum Principle: max u = max u UT ΓT 1. Uniqueness Reading: Section 2.3.4: Energy Methods Fact: There is at most one solution of: ( ut − ∆u = f in UT u = g on ΓT LECTURE 7: HEAT EQUATION AND ENERGY METHODS 3 We will present two proofs of this fact: One using energy methods, and the other one using the maximum principle above Proof: Suppose u and v are solutions, and let w = u − v, then w solves ( wt − ∆w = 0 in UT u = 0 on ΓT Proof using Energy Methods: Now for fixed t, consider the following energy: Z E(t) = (w(x; t))2 dx U Then: Z Z Z 0 IBP 2 E (t) = 2w (wt) = 2w∆w = −2 jDwj ≤ 0 U U U 4 LECTURE 7: HEAT EQUATION AND ENERGY METHODS Therefore E0(t) ≤ 0, so the energy is decreasing, and hence: Z Z (0 ≤)E(t) ≤ E(0) = (w(x; 0))2 dx = 0 = 0 U And hence E(t) = R w2 ≡ 0, which implies w ≡ 0, so u − v ≡ 0, and hence u = v . -
Lecture 24: Laplace's Equation
Introductory lecture notes on Partial Differential Equations - ⃝c Anthony Peirce. 1 Not to be copied, used, or revised without explicit written permission from the copyright owner. Lecture 24: Laplace's Equation (Compiled 26 April 2019) In this lecture we start our study of Laplace's equation, which represents the steady state of a field that depends on two or more independent variables, which are typically spatial. We demonstrate the decomposition of the inhomogeneous Dirichlet Boundary value problem for the Laplacian on a rectangular domain into a sequence of four boundary value problems each having only one boundary segment that has inhomogeneous boundary conditions and the remainder of the boundary is subject to homogeneous boundary conditions. These latter problems can then be solved by separation of variables. Key Concepts: Laplace's equation; Steady State boundary value problems in two or more dimensions; Linearity; Decomposition of a complex boundary value problem into subproblems Reference Section: Boyce and Di Prima Section 10.8 24 Laplace's Equation 24.1 Summary of the equations we have studied thus far In this course we have studied the solution of the second order linear PDE. @u = α2∆u Heat equation: Parabolic T = α2X2 Dispersion Relation σ = −α2k2 @t @2u (24.1) = c2∆u Wave equation: Hyperbolic T 2 − c2X2 = A Dispersion Relation σ = ick @t2 ∆u = 0 Laplace's equation: Elliptic X2 + Y 2 = A Dispersion Relation σ = k Important: (1) These equations are second order because they have at most 2nd partial derivatives. (2) These equations are all linear so that a linear combination of solutions is again a solution. -
Heat Kernel Analysis on Graphs
Heat Kernel Analysis On Graphs Xiao Bai Submitted for the degree of Doctor of Philosophy Department of Computer Science June 7, 2007 Abstract In this thesis we aim to develop a framework for graph characterization by com- bining the methods from spectral graph theory and manifold learning theory. The algorithms are applied to graph clustering, graph matching and object recogni- tion. Spectral graph theory has been widely applied in areas such as image recog- nition, image segmentation, motion tracking, image matching and etc. The heat kernel is an important component of spectral graph theory since it can be viewed as describing the flow of information across the edges of the graph with time. Our first contribution is to investigate how to extract useful and stable invari- ants from the graph heat kernel as a means of clustering graphs. The best set of invariants are the heat kernel trace, the zeta function and its derivative at the origin. We also study heat content invariants. The polynomial co-efficients can be computed from the Laplacian eigensystem. Graph clustering is performed by applying principal components analysis to vectors constructed from the invari- ants or simply based on the unitary features extracted from the graph heat kernel. We experiment with the algorithms on the COIL and Oxford-Caltech databases. We further investigate the heat kernel as a means of graph embedding. The second contribution of the thesis is the introduction of two graph embedding methods. The first of these uses the Euclidean distance between graph nodes. To do this we equate the spectral and parametric forms of the heat kernel to com- i pute an approximate Euclidean distance between nodes. -
Greens' Function and Dual Integral Equations Method to Solve Heat Equation for Unbounded Plate
Gen. Math. Notes, Vol. 23, No. 2, August 2014, pp. 108-115 ISSN 2219-7184; Copyright © ICSRS Publication, 2014 www.i-csrs.org Available free online at http://www.geman.in Greens' Function and Dual Integral Equations Method to Solve Heat Equation for Unbounded Plate N.A. Hoshan Tafila Technical University, Tafila, Jordan E-mail: [email protected] (Received: 16-3-13 / Accepted: 14-5-14) Abstract In this paper we present Greens function for solving non-homogeneous two dimensional non-stationary heat equation in axially symmetrical cylindrical coordinates for unbounded plate high with discontinuous boundary conditions. The solution of the given mixed boundary value problem is obtained with the aid of the dual integral equations (DIE), Greens function, Laplace transform (L-transform) , separation of variables and given in form of functional series. Keywords: Greens function, dual integral equations, mixed boundary conditions. 1 Introduction Several problems involving homogeneous mixed boundary value problems of a non- stationary heat equation and Helmholtz equation were discussed with details in monographs [1, 4-7]. In this paper we present the use of Greens function and DIE for solving non- homogeneous and non-stationary heat equation in axially symmetrical cylindrical coordinates for unbounded plate of a high h. The goal of this paper is to extend the applications DIE which is widely used for solving mathematical physics equations of the 109 N.A. Hoshan elliptic and parabolic types in different coordinate systems subject to mixed boundary conditions, to solve non-homogeneous heat conduction equation, related to both first and second mixed boundary conditions acted on the surface of unbounded cylindrical plate. -
Chapter H1: 1.1–1.2 – Introduction, Heat Equation
Name Math 3150 Problems Haberman Chapter H1 Due Date: Problems are collected on Wednesday. Submitted work. Please submit one stapled package per problem set. Label each problem with its corresponding problem number, e.g., Problem H3.1-4 . Labels like Problem XC-H1.2-4 are extra credit problems. Attach this printed sheet to simplify your work. Labels Explained. The label Problem Hx.y-z means the problem is for Haberman 4E or 5E, chapter x , section y , problem z . Label Problem H2.0-3 is background problem 3 in Chapter 2 (take y = 0 in label Problem Hx.y-z ). If not a background problem, then the problem number should match a corresponding problem in the textbook. The chapters corresponding to 1,2,3,4,10 in Haberman 4E or 5E appear in the hybrid textbook Edwards-Penney-Haberman as chapters 12,13,14,15,16. Required Background. Only calculus I and II plus engineering differential equations are assumed. If you cannot understand a problem, then read the references and return to the problem afterwards. Your job is to understand the Heat Equation. Chapter H1: 1.1{1.2 { Introduction, Heat Equation Problem H1.0-1. (Partial Derivatives) Compute the partial derivatives. @ @ @ (1 + t + x2) (1 + xt + (tx)2) (sin xt + t2 + tx2) @x @x @x @ @ @ (sinh t sin 2x) (e2t+x sin(t + x)) (e3t+2x(et sin x + ex cos t)) @t @t @t Problem H1.0-2. (Jacobian) f1 Find the Jacobian matrix J and the Jacobian determinant jJj for the transformation F(x; y) = , where f1(x; y) = f2 y cos(2y) sin(3x), f2(x; y) = e sin(y + x). -
10 Heat Equation: Interpretation of the Solution
Math 124A { October 26, 2011 «Viktor Grigoryan 10 Heat equation: interpretation of the solution Last time we considered the IVP for the heat equation on the whole line u − ku = 0 (−∞ < x < 1; 0 < t < 1); t xx (1) u(x; 0) = φ(x); and derived the solution formula Z 1 u(x; t) = S(x − y; t)φ(y) dy; for t > 0; (2) −∞ where S(x; t) is the heat kernel, 1 2 S(x; t) = p e−x =4kt: (3) 4πkt Substituting this expression into (2), we can rewrite the solution as 1 1 Z 2 u(x; t) = p e−(x−y) =4ktφ(y) dy; for t > 0: (4) 4πkt −∞ Recall that to derive the solution formula we first considered the heat IVP with the following particular initial data 1; x > 0; Q(x; 0) = H(x) = (5) 0; x < 0: Then using dilation invariance of the Heaviside step function H(x), and the uniquenessp of solutions to the heat IVP on the whole line, we deduced that Q depends only on the ratio x= t, which lead to a reduction of the heat equation to an ODE. Solving the ODE and checking the initial condition (5), we arrived at the following explicit solution p x= 4kt 1 1 Z 2 Q(x; t) = + p e−p dp; for t > 0: (6) 2 π 0 The heat kernel S(x; t) was then defined as the spatial derivative of this particular solution Q(x; t), i.e. @Q S(x; t) = (x; t); (7) @x and hence it also solves the heat equation by the differentiation property. -
Inverse Spectral Problems in Riemannian Geometry
Inverse Spectral Problems in Riemannian Geometry Peter A. Perry Department of Mathematics, University of Kentucky, Lexington, Kentucky 40506-0027, U.S.A. 1 Introduction Over twenty years ago, Marc Kac posed what is arguably one of the simplest inverse problems in pure mathematics: "Can one hear the shape of a drum?" [19]. Mathematically, the question is formulated as follows. Let /2 be a simply connected, plane domain (the drumhead) bounded by a smooth curve 7, and consider the wave equation on /2 with Dirichlet boundary condition on 7 (the drumhead is clamped at the boundary): Au(z,t) = ~utt(x,t) in/2, u(z, t) = 0 on 7. The function u(z,t) is the displacement of the drumhead, as it vibrates, at position z and time t. Looking for solutions of the form u(z, t) = Re ei~tv(z) (normal modes) leads to an eigenvalue problem for the Dirichlet Laplacian on B: v(x) = 0 on 7 (1) where A = ~2/c2. We write the infinite sequence of Dirichlet eigenvalues for this problem as {A,(/2)}n=l,c¢ or simply { A-},~=1 co it" the choice of domain/2 is clear in context. Kac's question means the following: is it possible to distinguish "drums" /21 and/22 with distinct (modulo isometrics) bounding curves 71 and 72, simply by "hearing" all of the eigenvalues of the Dirichlet Laplacian? Another way of asking the question is this. What is the geometric content of the eigenvalues of the Laplacian? Is there sufficient geometric information to determine the bounding curve 7 uniquely? In what follows we will call two domains isospectral if all of their Dirichlet eigenvalues are the same. -
An Introduction to Pseudo-Differential Operators
An introduction to pseudo-differential operators Jean-Marc Bouclet1 Universit´ede Toulouse 3 Institut de Math´ematiquesde Toulouse [email protected] 2 Contents 1 Background on analysis on manifolds 7 2 The Weyl law: statement of the problem 13 3 Pseudodifferential calculus 19 3.1 The Fourier transform . 19 3.2 Definition of pseudo-differential operators . 21 3.3 Symbolic calculus . 24 3.4 Proofs . 27 4 Some tools of spectral theory 41 4.1 Hilbert-Schmidt operators . 41 4.2 Trace class operators . 44 4.3 Functional calculus via the Helffer-Sj¨ostrandformula . 50 5 L2 bounds for pseudo-differential operators 55 5.1 L2 estimates . 55 5.2 Hilbert-Schmidt estimates . 60 5.3 Trace class estimates . 61 6 Elliptic parametrix and applications 65 n 6.1 Parametrix on R ................................ 65 6.2 Localization of the parametrix . 71 7 Proof of the Weyl law 75 7.1 The resolvent of the Laplacian on a compact manifold . 75 7.2 Diagonalization of ∆g .............................. 78 7.3 Proof of the Weyl law . 81 A Proof of the Peetre Theorem 85 3 4 CONTENTS Introduction The spirit of these notes is to use the famous Weyl law (on the asymptotic distribution of eigenvalues of the Laplace operator on a compact manifold) as a case study to introduce and illustrate one of the many applications of the pseudo-differential calculus. The material presented here corresponds to a 24 hours course taught in Toulouse in 2012 and 2013. We introduce all tools required to give a complete proof of the Weyl law, mainly the semiclassical pseudo-differential calculus, and then of course prove it! The price to pay is that we avoid presenting many classical concepts or results which are not necessary for our purpose (such as Borel summations, principal symbols, invariance by diffeomorphism or the G˚ardinginequality).