The Complexity of Linear Tensor Product Problems in (Anti-) Symmetric Hilbert Spaces

We study linear problems defined on tensor products of Hilbert spaces with an additional (anti-) symmetry property. We construct a linear algorithm that uses finitely many continuous linear functionals and show an explicit formula for its worst case error in terms of the singular values of the univariate problem. Moreover, we show that this algorithm is optimal with respect to a wide class of algorithms and investigate its complexity. We clarify the influence of different (anti-) symmetry conditions on the complexity, compared to the classical unrestricted problem. In particular, for symmetric problems we give characterizations for polynomial tractability and strong polynomial tractability in terms of the amount of the assumed symmetry. Finally, we apply our results to the approximation problem of solutions of the electronic Schr\"odinger equation.Comment: Extended version (53 pages); corrected typos, added journal referenc

Segre maps and entanglement for multipartite systems of indistinguishable particles

We elaborate the concept of entanglement for multipartite system with bosonic and fermionic constituents and its generalization to systems with arbitrary parastatistics. The entanglement is characterized in terms of generalized Segre maps, supplementing thus an algebraic approach to the problem by a more geometric point of view.Comment: 16 pages, the version to appear in J. Phys. A. arXiv admin note: text overlap with arXiv:1012.075

Several Approaches to Break the Curse of Dimensionality

In modern science the efficient numerical treatment of high-dimensional problems becomes more and more important. A fundamental insight of the theory of information-based complexity (IBC for short) is that the computational hardness of a problem can not be described properly only by the rate of convergence. There exist problems for which an exponential number of information operations is needed in order to reduce the initial error, although there are algorithms which provide an arbitrary large rate of convergence. Problems that yield this exponential dependence are said to suffer from the curse of dimensionality. While analyzing numerical problems it turns out that we can often vanquish this curse by exploiting additional structural properties. The aim of this thesis is to present several approaches of this type. Moreover, a detailed introduction to the field of IBC is given.Comment: 133 pages, my Ph.D. thesis for becoming Dr. rer. nat. at Friedrich-Schiller-University Jen