arXiv subjects

Laurent Demanet

Publications and source records attributed to Laurent Demanet.

41 records · Page 3Linked to original sources

arXiv2008

Discrete Symbol Calculus

This paper deals with efficient numerical representation and manipulation of differential and integral operators as symbols in phase-space, i.e., functions of space $x$ and frequency $ξ$. The symbol smoothness conditions obeyed by many operators in connection to smooth linear partial differential equations allow to write fast-converging, non-asymptotic expansions in adequate systems of rational Chebyshev functions or hierarchical splines. The classical results of closedness of such symbol classes under multiplication, inversion and taking the square root translate into practical iterative algorithms for realizing these operations directly in the proposed expansions. Because symbol-based numerical methods handle operators and not functions, their complexity depends on the desired resolution $N$ very weakly, typically only through $\log N$ factors. We present three applications to computational problems related to wave propagation: 1) preconditioning the Helmholtz equation, 2) decomposing wavefields into one-way components and 3) depth-stepping in reflection seismology.

math.NA↗

arXiv2008

Scattering in flatland: Efficient representations via wave atoms

This paper presents a numerical compression strategy for the boundary integral equation of acoustic scattering in two dimensions. These equations have oscillatory kernels that we represent in a basis of wave atoms, and compress by thresholding the small coefficients to zero. This phenomenon was perhaps first observed in 1993 by Bradie, Coifman, and Grossman, in the context of local Fourier bases \cite{BCG}. Their results have since then been extended in various ways. The purpose of this paper is to bridge a theoretical gap and prove that a well-chosen fixed expansion, the nonstandard wave atom form, provides a compression of the acoustic single and double layer potentials with wave number $k$ as $O(k)$-by-$O(k)$ matrices with $O(k^{1+1/\infty})$ nonnegligible entries, with a constant that depends on the relative $\ell_2$ accuracy $\eps$ in an acceptable way. The argument assumes smooth, separated, and not necessarily convex scatterers in two dimensions. The essential features of wave atoms that enable to write this result as a theorem is a sharp time-frequency localization that wavelet packets do not obey, and a parabolic scaling wavelength $\sim$ (essential diameter)${}^2$. Numerical experiments support the estimate and show that this wave atom representation may be of interest for applications where the same scattering problem needs to be solved for many boundary conditions, for example, the computation of radar cross sections.

math.NA↗

arXiv2006

Fast Computation of Fourier Integral Operators

We introduce a general purpose algorithm for rapidly computing certain types of oscillatory integrals which frequently arise in problems connected to wave propagation and general hyperbolic equations. The problem is to evaluate numerically a so-called Fourier integral operator (FIO) of the form $\int e^{2πi Φ(x,ξ)} a(x,ξ) \hat{f}(ξ) \mathrm{d}ξ$ at points given on a Cartesian grid. Here, $ξ$ is a frequency variable, $\hat f(ξ)$ is the Fourier transform of the input $f$, $a(x,ξ)$ is an amplitude and $Φ(x,ξ)$ is a phase function, which is typically as large as $|ξ|$; hence the integral is highly oscillatory at high frequencies. Because an FIO is a dense matrix, a naive matrix vector product with an input given on a Cartesian grid of size $N$ by $N$ would require $O(N^4)$ operations. This paper develops a new numerical algorithm which requires $O(N^{2.5} \log N)$ operations, and as low as $O(\sqrt{N})$ in storage space. It operates by localizing the integral over polar wedges with small angular aperture in the frequency plane. On each wedge, the algorithm factorizes the kernel $e^{2 πi Φ(x,ξ)} a(x,ξ)$ into two components: 1) a diffeomorphism which is handled by means of a nonuniform FFT and 2) a residual factor which is handled by numerical separation of the spatial and frequency variables. The key to the complexity and accuracy estimates is that the separation rank of the residual kernel is \emph{provably independent of the problem size}. Several numerical examples demonstrate the efficiency and accuracy of the proposed methodology. We also discuss the potential of our ideas for various applications such as reflection seismology.

math.NA↗

arXiv2005

Numerical verification of a gap condition for linearized NLS

We make a detailed numerical study of the spectrum of two Schroedinger operators L_- and L_+ arising in the linearization of the supercritical nonlinear Schroedinger equation (NLS) about the standing wave, in three dimensions. This study was motivated by a recent result of the second author on conditional asymptotic stability of solitary waves in the case of a cubic nonlinearity. Underlying the validity of this result is a spectral condition on the operators L_- and L_+, namely that they have no eigenvalues nor resonances in the gap (a region of the positive real axis between zero and the continuous spectrum,) which we call the gap property. The present numerical study verifies this spectral condition, and further shows that the gap property holds for NLS exponents of the form 2*beta + 1, as long as beta_* < beta <= 1, where beta_* = 0.913958905 +- 1e-8. Our strategy consists of rewriting the original eigenvalue problem via the Birman-Schwinger method. From a numerical analysis viewpoint, our main contribution is an efficient quadrature rule for the kernel 1/|x-y| in R^3, i.e., provably spectrally accurate. As a result, we are able to give similar accuracy estimates for all our eigenvalue computations. We also propose an improvement of the Petviashvili's iteration for the computation of standing wave profiles which automatically chooses the radial solution.

math.AP↗

arXiv2004

The Curvelet Representation of Wave Propagators is Optimally Sparse

This paper argues that curvelets provide a powerful tool for representing very general linear symmetric systems of hyperbolic differential equations. Curvelets are a recently developed multiscale system in which the elements are highly anisotropic at fine scales, with effective support shaped according to the parabolic scaling principle width ~ length^2 at fine scales. We prove that for a wide class of linear hyperbolic differential equations, the curvelet representation of the solution operator is both optimally sparse and well organized. It is sparse in the sense that the matrix entries decay nearly exponentially fast (i.e. faster than any negative polynomial), and well-organized in the sense that the very few nonnegligible entries occur near a shifted diagonal. Indeed, we actually show that the action of the wave-group on a curvelet is well-approximated by simply translating the center of the curvelet along the Hamiltonian flow--hence the diagonal shift in the curvelet epresentation. A physical interpretation of this result is that curvelets may be viewed as coherent waveforms with enough frequency localization so that they behave like waves but at the same time, with enough spatial localization so that they simultaneously behave like particles.

math.AP↗