1,227 research outputs found
Besov regularity for operator equations on patchwise smooth manifolds
We study regularity properties of solutions to operator equations on
patchwise smooth manifolds such as, e.g., boundaries of
polyhedral domains . Using suitable biorthogonal
wavelet bases , we introduce a new class of Besov-type spaces
of functions
. Special attention is paid on the
rate of convergence for best -term wavelet approximation to functions in
these scales since this determines the performance of adaptive numerical
schemes. We show embeddings of (weighted) Sobolev spaces on
into , ,
which lead us to regularity assertions for the equations under consideration.
Finally, we apply our results to a boundary integral equation of the second
kind which arises from the double layer ansatz for Dirichlet problems for
Laplace's equation in .Comment: 42 pages, 3 figures, updated after peer review. Preprint: Bericht
Mathematik Nr. 2013-03 des Fachbereichs Mathematik und Informatik,
Universit\"at Marburg. To appear in J. Found. Comput. Mat
Inertial manifolds and finite-dimensional reduction for dissipative PDEs
These notes are devoted to the problem of finite-dimensional reduction for
parabolic PDEs. We give a detailed exposition of the classical theory of
inertial manifolds as well as various attempts to generalize it based on the
so-called Man\'e projection theorems. The recent counterexamples which show
that the underlying dynamics may be in a sense infinite-dimensional if the
spectral gap condition is violated as well as the discussion on the most
important open problems are also included.Comment: This manuscript is an extended version of the lecture notes taught by
the author as a part of the crash course in the Analysis of Nonlinear PDEs at
Maxwell Center for Analysis and Nonlinear PDEs (Edinburgh, November, 8-9,
2012
Tensor-Sparsity of Solutions to High-Dimensional Elliptic Partial Differential Equations
A recurring theme in attempts to break the curse of dimensionality in the
numerical approximations of solutions to high-dimensional partial differential
equations (PDEs) is to employ some form of sparse tensor approximation.
Unfortunately, there are only a few results that quantify the possible
advantages of such an approach. This paper introduces a class of
functions, which can be written as a sum of rank-one tensors using a total of
at most parameters and then uses this notion of sparsity to prove a
regularity theorem for certain high-dimensional elliptic PDEs. It is shown,
among other results, that whenever the right-hand side of the elliptic PDE
can be approximated with a certain rate in the norm of
by elements of , then the solution can be
approximated in from to accuracy
for any . Since these results require
knowledge of the eigenbasis of the elliptic operator considered, we propose a
second "basis-free" model of tensor sparsity and prove a regularity theorem for
this second sparsity model as well. We then proceed to address the important
question of the extent such regularity theorems translate into results on
computational complexity. It is shown how this second model can be used to
derive computational algorithms with performance that breaks the curse of
dimensionality on certain model high-dimensional elliptic PDEs with
tensor-sparse data.Comment: 41 pages, 1 figur
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