We report on the observation of quantized surface spin waves in periodic arrays of magnetic Ni81Fe19 wires by means of Brillouin light scattering spectroscopy. At small wavevectors (q_1 = 0 - 0.9*100000 cm^-1 ) several discrete, dispersionless modes with a frequency splitting of up to 0.9 GHz were observed for the wavevector oriented perpendicular to the wires. From the frequencies of the modes and the wavevector interval, where each mode is observed, the modes are identified as dipole-exchange surface spin wave modes of the film with quantized wavevector values determined by the boundary conditions at the lateral edges of the wires. With increasing wavevector the separation of the modes becomes smaller, and the frequencies of the discrete modes converge to the dispersion of the dipole-exchange surface mode of a continuous film.
The Fock space of bosons and fermions and its underlying superalgebra are represented by algebras of functions on a superspace. We define Gaussian integration on infinite dimensional superspaces, and construct superanalogs of the classical function spaces with a reproducing kernel - including the Bargmann-Fock representation - and of the Wiener-Segal representation. The latter representation requires the investigation of Wick ordering on Z 2 -graded algebras. As application we derive a Mehler formula for the Ornstein-Uhlenbeck semigroup on the Fock space.
An asymptotic-induced scheme for nonstationary transport equations with thediffusion scaling is developed. The scheme works uniformly for all ranges ofmean free paths. It is based on the asymptotic analysis of the diffusion limit ofthe transport equation. A theoretical investigation of the behaviour of thescheme in the diffusion limit is given and an approximation property is proven.Moreover, numerical results for different physical situations are shown and atheuniform convergence of the scheme is established numerically.
We investigate in how far interpolation mechanisms based on the nearest-neighbor rule (NNR) can support cancer research. The main objective is to usethe NNR to predict the likelihood of tumorigenesis based on given risk factors.By using a genetic algorithm to optimize the parameters of the nearest-neighbourprediction, the performance of this interpolation method can be improved sub-stantially. Furthermore, it is possible to detect risk factors which are hardly ornot relevant to tumorigenesis. Our preliminary studies demonstrate that NNR-based interpolation is a simple tool that nevertheless has enough potential to beseriously considered for cancer research or related research.
We present a general framework for developing search heuristics for au-tomated theorem provers. This framework allows for the construction ofheuristics that are on the one hand able to replay (parts of) a given prooffound in the past but are on the other hand flexible enough to deviate fromthe given proof path in order to solve similar proof problems. We substanti-ate the abstract framework by the presentation of three distinct techniquesfor learning appropriate search heuristics based on soADcalled features. Wedemonstrate the usefulness of these techniques in the area of equational de-duction. Comparisons with the renowned theorem prover Otter validatethe applicability and strength of our approach.
Retrieving multiple cases is supposed to be an adequate retrieval strategy for guiding partial-order planners because of the recognized flexibility of these planners to interleave steps in the plans. Cases are combined by merging them. In this paper, we will examine two different kinds of merging cases in the context of partial-order planning. We will see that merging cases can be very difficult if the cases are merged eagerly. On the other hand, if cases are merged by avoiding redundant steps, the guidance of the additional cases tends to decrease with the number of covered goals and retrieved cases in domains having a certain kind of interactions. Thus, to retrieve a single case covering many of the goals of the problem or to retrieve fewer cases covering many of the goals is at least equally effective as to retrieve several cases covering all goals in these domains.
This paper shows an approach to profit from type information about planning objects in a partial-order planner. The approach turns out to combine representational and computational advantages. On the one hand, type hierarchies allow better structuring of domain specifications. On the other hand, operators contain type constraints which reduce the search space of the planner as they partially achieve the functionality of filter conditions.
Viele Entwicklungsprozesse, wie sie z.B. beim Entwurf von grossen Softwaresystemen benötigt werden, basieren in erster Linie auf dem Wissen der mit der Entwicklung betrauten Mitarbeiter. Mit wachsender Komplexität der Entwurfsaufgaben und mit wachsender Anzahl der Mitarbeiter in einem Projekt wird die Koordination und Verteilung dieses Wissens immer problematischer. Aus diesem Grund versucht man zunehmend, das Wissen der Mitarbeiter in elektronischer Form, d.h. in Rechnern zu speichern und zu verwalten. Dadurch, dass der Entwurf eines komplexen Systems ebenfalls am Rechner modelliert wird, steht benötigtes Wissen sofort zur Verfügung und kann zur Entscheidungsunterstützung herangezogen werden. Gerade bei der Planung grosser Projekte stehen jedoch oft Entscheidungen aus, die erst später, während der Abwicklung getroffen werden können. Da gängige Workflow-Management-System zumeist eine komplette Modellierung verlangen, bevor die Abwicklung eines Projektmodells beginnen kann, habt sich dieser Ansatz gerade für umfangreiche Projekte als eher ungeeignet herausgestellt.