High performance algorithms based on a new wawelet expansion for time dependent acoustics obstale scattering

This paper presents a highly parallelizable numerical method to solve time dependent acoustic obstacle scattering problems. The method proposed is a generalization of the ``operator expansion method" developed by Recchioni and Zirilli [SIAM J.~Sci.~Comput., 25 (2003), 1158-1186]. The numerical method proposed reduces, via a perturbative approach, the solution of the scattering problem to the solution of a sequence of systems of first kind integral equations. The numerical solution of these systems of integral equations is challenging when scattering problems involving realistic obstacles and small wavelengths are solved. A computational method has been developed to solve these challenging problems with affordable computing resources. To this aim a new way of using the wavelet transform and new bases of wavelets are introduced, and a version of the operator expansion method is developed that constructs directly element by element in a fully parallelizable way. Several numerical experiments involving realistic obstacles and ``small" wavelengths are proposed and high dimensional vector spaces are used in the numerical experiments. To evaluate the performance of the proposed algorithm on parallel computing facilities, appropriate speed up factors are introduced and evaluated

Rapid computation of far-field statistics for random obstacle scattering

In this article, we consider the numerical approximation of far-field statistics for acoustic scattering problems in the case of random obstacles. In particular, we consider the computation of the expected far-field pattern and the expected scattered wave away from the scatterer as well as the computation of the corresponding variances. To that end, we introduce an artificial interface, which almost surely contains all realizations of the random scatterer. At this interface, we directly approximate the second order statistics, i.e., the expectation and the variance, of the Cauchy data by means of boundary integral equations. From these quantities, we are able to rapidly evaluate statistics of the scattered wave everywhere in the exterior domain, including the expectation and the variance of the far-field. By employing a low-rank approximation of the Cauchy data's two-point correlation function, we drastically reduce the cost of the computation of the scattered wave's variance. Numerical results are provided in order to demonstrate the feasibility of the proposed approach

Wave-number-explicit bounds in time-harmonic scattering

In this paper we consider the problem of scattering of time-harmonic acoustic waves by a bounded sound soft obstacle in two and three dimensions, studying dependence on the wave number in two classical formulations of this problem. The first is the standard variational/weak formulation in the part of the exterior domain contained in a large sphere, with an exact Dirichletto-Neumann map applied on the boundary. The second formulation is as a second kind boundary integral equation in which the solution is sought as a combined single- and double-layer potential. For the variational formulation we obtain, in the case when the obstacle is starlike, explicit upper and lower bounds which show that the inf-sup constant decreases like k −1 as the wave number k increases. We also give an example where the obstacle is not starlike and the inf-sup constant decreases at least as fast as k −2. For the boundary integral equation formulation, if the boundary is also Lipschitz and piecewise smooth, we show that the norm of the inverse boundary integral operator is bounded independently of k if the coupling parameter is chosen correctly. The methods we use also lead to explicit bounds on the solution of the scattering problem in the energy norm when the obstacle is starlike in which the dependence of the norm of the solution on the wave number and on the geometry are made explicit

Probing Solar Convection

In the solar convection zone acoustic waves are scattered by turbulent sound speed fluctuations. In this paper the scattering of waves by convective cells is treated using Rytov's technique. Particular care is taken to include diffraction effects which are important especially for high-degree modes that are confined to the surface layers of the Sun. The scattering leads to damping of the waves and causes a phase shift. Damping manifests itself in the width of the spectral peak of p-mode eigenfrequencies. The contribution of scattering to the line widths is estimated and the sensitivity of the results on the assumed spectrum of the turbulence is studied. Finally the theoretical predictions are compared with recently measured line widths of high-degree modes.Comment: 26 pages, 7 figures, accepted by MNRA

Wave Propagation

A wave is one of the basic physics phenomena observed by mankind since ancient time. The wave is also one of the most-studied physics phenomena that can be well described by mathematics. The study may be the best illustration of what is “science”, which approximates the laws of nature by using human defined symbols, operators, and languages. Having a good understanding of waves and wave propagation can help us to improve the quality of life and provide a pathway for future explorations of the nature and universe. This book introduces some exciting applications and theories to those who have general interests in waves and wave propagations, and provides insights and references to those who are specialized in the areas presented in the book

Financial cycles, credit networks and macroeconomic fluctuations: multi-scale stochastic models and wavelet analysis

This project focuses on the macroeconomics of financial cycles. Usually defined in terms of self-reinforcing interactions between perceptions of value and risk, attitudes towards risk and financing constraints, which translate into booms followed by bust, the recent empirical literature has recurred to two approaches \u2013 turning point analysis and frequency-based filters - applied to measures of credit and asset prices to pose a number of stylized facts. First, financial cycles tend to display a greater amplitude and a lower frequency in comparison to business cycles, with peaks associated with systemic crises. Second, financial cycles depend on policy regimes and on the pace of financial innovations, leading to a wide cross-country heterogeneity and a time-varying degree of global synchronization. The latter point is clearly related to the structural transformations occurred in financial systems over the last three decades, like the cumulative integration of traditional banking with capital market developments and the increasing degree of interconnections among financial institutions. However, to date very little is known about determinants and mechanisms behind financial cycles, and on how they interact with business cycles and medium-to-long-run macroeconomic performance. In this project we plan to research along three dimensions: i) measurement issues, in order to provide a comprehensive assessment of the evolution of co-movements between financial and real variables across a sample of financial developed countries, both over time and at different frequencies; ii) theoretical issues, aimed at exploring under what circumstances the network of interconnections among financial intermediaries and between intermediaries and non-financial borrowers might evolve cyclically, contributing this way to regulate the incentives agents have in taking risks, and to set the importance of credit and financial frictions in accounting for time-varying misallocations of resources; iii) policy issues, given the role assigned by international supervisory bodies to a proper characterization and knowledge of the financial cycle as a prerequisite for the macro-prudential regulation of banks, and the scope of monetary policy in promoting financial stability in addition to the typical mandate of price stability. Our task requires the employment of a new approach to macroeconomic analysis, diverse analytical tools and one unifying economic principle. As regards the latter, our focal point is the notion of risk externalities, across financial institutions and between the financial sector and the real economy. The set of tools we plan to employ spans from wavelets methods to multi-scale models in continuous time, and from strategic network formation to agent-based computational techniques. All these tools are instrumental in building and estimating macroeconomic models characterized by interrelated markets operating at different time scales

Rapid computation of far-field statistics for random obstacle scattering

In this article, we consider the numerical approximation of far-field statistics for acoustic scattering problems in the case of random obstacles. In particular, we consider the computation of the expected far-field pattern and the expected scattered wave away from the scatterer as well as the computation of the corresponding variances. To that end, we introduce an artificial interface, which almost surely contains all realizations of the random scatterer. At this interface, we directly approximate the second order statistics, i.e., the expectation and the variance, of the Cauchy data by means of boundary integral equations. From these quantities, we are able to rapidly evaluate statistics of the scattered wave everywhere in the exterior domain, including the expectation and the variance of the far-field. By employing a low-rank approximation of the Cauchy data's two-point correlation function, we drastically reduce the cost of the computation of the scattered wave's variance. Numerical results are provided in order to demonstrate the feasibility of the proposed approach

An adaptive wavelet method for the solution of boundary integral equations in three dimensions

In science and engineering one often comes across partial differential equations in three dimensions, some of which can be formulated as boundary integral equations on the boundary of the three-dimensional domain of interest. With this approach the dimensionality of the problem can be reduced by one dimension and the interior as well as the exterior problem can be solved. However, this advantage does not come entirely without cost, as the involved matrices are dense. By using a wavelet scheme many matrix entries become sufficiently small such that they can be neglected without compromising the convergence rate of the underlying Galerkin scheme. In this thesis we go a step further and use an adaptive wavelet approach, meaning that specific parts of the geometry will be resolved with much detail, while other parts can stay coarse. After we have introduced the necessary theoretical foundation on boundary integral equations, wavelets and adaptive wavelet schemes, we present the details on the implementation followed by several numerical results. In the final chapter of this thesis we present the concept of goal-oriented error estimation, again followed by numerical results