A Survey of Computational High Frequency Wave Propagation II. Olof Runborg NADA, KTH

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A Survey of Computational High Frequency Wave Propagation II Olof Runborg NADA, KTH High Frequency Wave Propagation CSCAMM, September 19-22, 2005

Numerical methods Direct methods Wave equation (time domain) Integral equation methods (frequency domain) Asymptotic methods Physical optics Geometrical optics (Gaussian beams) Hybrid methods

Direct numerical methods for the wave equation Scalar wave equation u tt c(x) 2 Δu =0, (t, x) R + Ω, Ω R d + boundary and initial data. Discretize Ω, time and u. Many methods: FD (explicit, uniform staggered grids), FV, FEM (implicit or DG). Complexity O(ω (1/p+1)(d+1) ) (including time). Issues: First/second order system. Treatment of boundaries/interfaces. Phase errors.

Direct integral equation methods for Helmholtz Scattering problem for Helmholtz equation: u = u s + u inc, c 1 Δu s + ω 2 u s =0, x R d \ Ω, u s = u inc, x Ω + radiation condition Rewrite as integral equation, e.g. u inc (x) = G(ω x x ) u(x ) n dx, x Ω. Ω Discretize Ω and u n O(ωd 1 ) unknowns. Finite element/collocation methods, method of moments. Full matrix equation, direct solution, complexity O(ω 3(d 1) ). Fast multipole methods, iterative solver, complexity O(ω (d 1) ). Issues: 1 st /2 nd kind Fredholm equations. Conditioning. Corners.

Physical optics Integral formulation of scattering problem u s (x) = G(ω x x ) u(x ) n dx, x R d \ Ω, Ω Approximate u n by geometrical optics solution. E.g. if u inc =exp(iωα x) is a plane wave, Ω convex, then u n (u inc + u GO s ) 2iωα ˆn(x)e iωα x, x illuminated, = n 0, x in shadow. Cost of computing solution still depends on ω. Exact PO u n = A(x,ω)eiωα x /ω then A(x,ω) smooth, uniformly in ω, except at shadow boundaries. Discretize and solve A(x,ω) at cost independent of ω. [Bruno]

Geometrical optics models and numerical methods u tt c(x) 2 Δu =0 Rays Kinetic Eikonal dx dt = c2 p, dp dt Ray tracing = c c Wavefront methods f t + c 2 p x f 1 c c pf =0 Moment methods, Full phase space methods φ t + c φ =0 Hamilton Jacobi methods

Time-dependent version. Eikonal equation Wave equation plus ansatz u(t, x) A(t, x)e iωφ(t,x) give φ t + c(x) φ =0. Upwind, high-resolution (ENO, WENO) finite difference methods [Osher, Shu, et al] Stationary version. Helmholtz equation plus ansatz u(x) A(x)e iωϕ(x) give ϕ = c(x) 1. Fast marching [Sethian] or fast sweeping methods [Zhao, Tsai, et al]. (Note, if IC and BC match, φ = ϕ t.)

Eikonal equation Ansatz only treats one wave. In general crossing waves u(x) A 1 (x)e iωϕ1(x) + A 2 (x)e iωϕ2(x) + Nonlinear equation, no superposition principle Viscosity solution, kinks First arrival property: ϕ visc (x) =min n ϕ n (x)

Example: Eikonal solution

Geometrical optics models and numerical methods u tt c(x) 2 Δu =0 Rays Kinetic Eikonal dx dt = c2 p, dp dt Ray tracing = c c Wavefront methods f t + c 2 p x f 1 c c pf =0 Moment methods, Full phase space methods φ t + c φ =0 Hamilton Jacobi methods

Ray tracing Rays are the (bi)characteristics (x(t), p(t)) of the eikonal equation, given by ODEs dx dt = c(x)2 p, dp dt = c(x) c(x), Hamiltonian system with H = c(x) p and H 1. Solve with numerical ODE methods, e.g. Runge Kutta. Note, if valid at t = 0, then for all t>0: ϕ(x(t)) = t, ϕ(x(t)) = p(t), (phase traveltime) (local ray direction) p(t) =1/c(x(t)), (H = 1 conserved, can reduce to p S d 1 ) There are also ODEs for the amplitude along rays. Issues: Diverging rays. Interpolation onto regular grid.

Example: Ray/Wavefront solutions

Ray tracing boundary value problem Start and endpoint of ray given. - Piecewise constant c(x) Rays piecewise straight lines. Find refraction/reflection points at interfaces by Newton s method. - Smoothly varying c(x) Ray tracing eq is a nonlinear elliptic boundary value problem ( ) d 2 dx c(x) = c(x) dt dt c(x), x(0) = x 0, x(t )=x 1. t additional unknown. Solve by shooting method or discretize PDE + Newton. Multiple solutions difficult.

Wavefront tracking Directly solve for wavefront given by ϕ(x) =const. Suppose γ(α) is the initial wavefront, ϕ(γ(α)) = 0. Follow ensemble of rays x(t, α) t p(t, α) t = c 2 p, x(0,α)=γ(α), = c c, p(0,α)= γ (α) c γ (α). Note: Moving front in normal direction a possibility x t = c x α x α (since 0 = α ϕ(x(t, α)) = x α φ = x α p) But not good since wavefront non-smooth!

Phase space Phase space (x, p), where p S d 1 is local ray direction Observation: Wavefront is a smooth curve in phase space. 2D problems: 1D curve in 3D phase space (x, y, θ). 3D problems: 2D surface in 5D phase space (x, y, z, θ, α). θ θ θ x y x y x y

Wavefront construction Propagate Lagrangian markers on the wavefront in phase space. Insert new markers adaptively by interpolation when front resolution deteriorates. Interpolate traveltime/phase/amplitude onto regular grid. [Vinje, Iversen, Gjöystdal, Lambaré,...]

Geometrical optics models and numerical methods u tt c(x) 2 Δu =0 Rays Kinetic Eikonal dx dt = c2 p, dp dt Ray tracing = c c Wavefront methods f t + c 2 p x f 1 c c pf =0 Moment methods, Full phase space methods φ t + c φ =0 Hamilton Jacobi methods

Kinetic formulation Let f(t, x, p) be the particle (photon) density in phase space. Bicharacteristic equations f t + c 2 p x f c c pf =0. f supported on p = c(x) 1,(H 1). Can also be derived directly from wave eq. through e.g. Wigner measures [Tartar, Lions, Paul, Gerard, Mauser, Markowich, Poupaud,... ] Relationship to wave equation solution: u = Ae iωφ f = A 2 δ (p φ). Note: Loss of phase information.

Moment equations Derived from transport equation in phase space + closure assumption for a system of equations representing the moments. (C.f. hydrodynamic limit from Boltzmann eq.) PDE description in the small (t, x)-space. Arbitrary good superposition. N crossing waves allowed. (But larger N means a larger system of PDEs must be solved.) [Brenier,Corrias,Engquist,OR](waveequation), [Gosse, Jin, Li, Markowich, Sparber] (Schrödinger)

Derivations, homogenous case (c 1) Starting point is f t + p x f =0. Let p =(p 1,p 2 ). Define the moments, m ij = p i 1p j 2 fdp. R 2 From R 2 p i 1p j 2 (f t + p x f)dp =0, we get the infinite (valid i, j 0) system of moment equations (m ij ) t +(m i+1,j ) x +(m i,j+1 ) y =0.

Derivations, homogenous case, cont. Make the closure assumption f(x, p,t)= N A 2 k δ( p 1, arg p θ k ). k=1 The moments take the form m ij = N A 2 k cos i θ k sin j θ k. k=1 Corresponds to a maximum of N waves at each point. Choose equations for moments m 2k 1,0 and m 0,2k 1, k =1,...,N. Gives closed system of 2N equations with 2N unknowns (the A k s and θ k s).

Moment equations, examples Ex. N =1 u 1 u 2 t + u 2 1 u 2 1 +u 2 2 u 1 u 2 u 2 1 +u 2 2 x + u 1 u 2 u 2 1 +u 2 2 u 2 2 u 2 1 +u 2 2 y =0. where u 1 = m 10 = A 2 cos θ and u 2 = m 01 = A 2 sin θ. For N 2, F 0 (u) t + F 1 (u) x + F 2 (u) y =0. where F 0 (u), F 1 (u) andf 2 (u) are complicated non-linear functions. PDE = weakly hyperbolic system of conservation laws, (with source terms when c varies) Flux functions in conservation law can be difficult to evaluate.

Wedge example 2 2 1.8 1.8 1.6 1.6 1.4 1.4 1.2 1.2 1 1 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 N =1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 N =2 15 7 6 10 5 4 3 5 2 1 0 0 0 0 0.5 0.5 1 x 1.5 2 0 0.5 N =1 y 1 1.5 2 1 x 1.5 0.5 2 0 y N =2 1 1.5 2

Hybrid methods Full Helmholtz or wave equation where variations in c(x) and/or geometry on same scale as wavelength. Ω 1 x i Ω 2 GO elsewhere, typically for long range interactions. Ex. antenna + aircraft. Coupling of models.

Other methods Hamilton Jacobi methods [Vidale, van Trier, Symes, Engquist, Fatemi, Osher, Benamou,...] Wavefront tracking using level sets in phase space [Osher, Tsai, Cheng, Liu, Jin, Qian,... ] Wavefront tracking using segment projection [Engquist, OR, Tornberg] Full phase space methods [Sethian, Fomel, Symes, Qian]