A few important PDEs constant coefficients = 1 variable coefficients = c(x) ∇ ⋅ ( c∇u ) = f ∇ 2u = f Poisson’s equation: example: f = charge density, u = –electric potential example: f = heat source/sink rate u = steady-state temperature example: f = solute source/sink rate, u = steady-state concentration example: f ~ force on stretched string/drum u = steady-state displacement c = thermal conductivity c = diffusion coefficient c ~ “springy-ness” ∇ ⋅ ( c∇u ) = 0 ∇ 2u = 0 Laplace’s equation: c = permittivity ε examples: as for Poisson, but no sources ∂u = ∇ 2u ∂t Heat/diffusion equation: ∂u = ∇ ⋅ (c∇u) ∂t examples: u = temperature u = solute concentration c = thermal conductivity c = diffusion coefficient ∂ 2u = ∇ ⋅ (c∇u) ∂t 2 ∂ 2u = ∇ 2u ∂t 2 Scalar wave equation: examples: u = displacement of stretched string/drum u = density of gas/fluid c2 = 1 / wave speed + many, many others… Maxwell (electromagnetism) Schrödinger (quantum mechanics) Navier–Stokes / Stokes / Euler (fluids) Black-Scholes (options pricing) Lamé–Navier (linear elastic solids) beam equation (bending thin solid strips) advection-diffusion (diffusion in flows) reaction-diffusion (diffusion+chemistry) minimal-surface equation (soap films) nonlinear wave equation (e.g. solitary ocean waves) unknowns: 18.06 18.303 finite-dimensional linear algebra linear algebra w/ functions & derivatives Ω vector space of column vectors x (or x ) in n (or n), or possibly x(t) [time-dependent] vector space of real-valued (or complex) functions u(x) [for x in some domain Ω], or possibly u(x,t) [time-dependent], … possibly restricted by some boundary conditions at the boundary ∂Ω [e.g. u(x) = 0 on ∂Ω] … possibly with vector-valued u(x) [vector fields] vector space: we can add, subtract, & multiply by constants without leaving the space linear operators: ∂Ω matrices A linear operators on functions Â, [ Âu = function ] using partial derivatives. examples: Â1u = ∇2u [ Laplacian operator ] Â2u = 3u [ mult. by constant ] Â3u |x = a(x) u(x) [ mult. by function ]  = 4Â1 + Â2 + 7Â3 [ linear comb. of ops. ] linearity: A(αx+βy) = αAx + βAy Â(αu+βv) = αÂu + βÂv dot product and transpose: complex x: x ⋅ y = xTy = Σi xiyi xT → xT = x* T T x ⋅ Ay = x Ay = (Ax) y ⇔ (A)Tij = Aji [swap rows/cols] basis: set of vectors bi with span = whole space ⇔ any x = Σi ci bi for some coefficients ci … if orthonormal basis, then ci = biTx ⎛ ∂ ⎞T ⎜ ⎟ = ??? ⎝ ∂x ⎠ [ e.g. Fourier series! ] u(x) ⋅ v(x) = 〈u,v〉 = ???????? [inner product] [= some integral] 〈u,Âv〉 = 〈Â*u,v〉 ⇒ Â* = ???????? (= † in physics) [adjoint] ∞ set of functions bi(x) with span = whole space ⇔ any u(x) = Σi ci bi(x) for some coefficients ci … if orthonormal basis, then ci = 〈bi, u〉 linear equations: solve Ax = b for x solve Âu = f for u(x) existence & uniqueness: Ax = b solvable if b in column space of A. Solution unique if null space of A = {0}, or equivalently if eigenvalues of A are ≠ 0. Âu = f solvable if f(x) in col. space (image) of Â. Solution unique if null space (kernel) of  = {0}, or equivalently if eigenvalues of  are ≠ 0. eigenvalues/vectors: solve Ax = λx for x and λ. For this x, A acts just like a number (λ). [e.g. Anx = λnx, eAx = eλx.] solve Âu = λu for u(x) [eigenfunction] and λ. For this u,  acts just like a number (λ). example: [e.g. Ânu = λnu, eÂu = eλu.] ∂ 2 2 ∂x 2 sin(kx) = (−k ) sin(kx) time-evolution initial-value problem: solve dx/dt = Ax for x(0)=b [system of ODEs] ⇒ x = eAt b [ if A constant ] … expand b in eigenvectors, mult. each by eλt solve ∂u/∂t = Âu for u(x,0)=f(x) ⇒ u(x,t) = eÂt f(x) [ if  constant ] … expand f in eigenfunctions, mult. each by eλt symmetric: A = AT ⇒ real λ, orthogonal eigenvectors, diagonalizable  = ÂT [??????] ⇒ real λ, orthogonal eigenvectors (???) diagonalizable (???) positive definite / semi-definite: A = AT, xTAx > 0 for any x ≠ 0 / xTAx ≥ 0 ⇔ real λ>0/≥0, A=BTB for some B  = Â*, 〈u,Âu〉>0 / ≥0 for u ≠ 0 (???) ˆ ˆ ˆ ⇔ real λ>0/≥0, Â=B*B for some B (???) important fact: –∇2 is symmetric positive definite or semi-definite! inverses: orthogonal / unitary: A-1 A = A A-1 = 1 [if it exists] ⇒ Ax=b solved by x = A-1b ⎛ ∂ ⎞−1 ⎜ ⎟ = ??? ⎝ ∂x ⎠ … some kind of integral? A-1 = AT ⇔ (Ax) ⋅ (Ax) = x ⋅ x for any x ⇒ |λ|=1, orthogonal eigenvectors, diagonalizable Â-1 = ?????? ⇒ Âu = f solved by f = –1u ??? […delta functions & Green’s functions] Â-1 = Â* ⇔ 〈Âu,Âu〉 = 〈u,u〉 for any u ⇒ |λ|=1, orthogonal eigenvectors (???) diagonalizable (???)