## Mathematik

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- Euclidean decompositions of hyperbolic manifolds and their duals (1998)
- Epstein and Penner constructed in [EP88] the Euclidean decomposition of a non-compact hyperbolic n-manifold of finite volume for a choice of cusps, n >= 2. The manifold is cut along geodesic hyperplanes into hyperbolic ideal convex polyhedra. The intersection of the cusps with the Euclidean decomposition determined by them turns out to be rather simple as stated in Theorem 2.2. A dual decomposition resulting from the expansion of the cusps was already mentioned in [EP88]. These two dual hyperbolic decompositions of the manifold induce two dual decompositions in the Euclidean structure of the cusp sections. This observation leads in Theorems 5.1 and 5.2 to easily computable, necessary conditions for an arbitrary ideal polyhedral decomposition of the manifold to be a Euclidean decomposition.

- Homfly skeins and the Hopf link (2001)
- This thesis exhibits skeins based on the Homfly polynomial and their relations to Schur functions. The closures of skein-theoretic idempotents of the Hecke algebra are shown to be specializations of Schur functions. This result is applied to the calculation of the Homfly polynomial of the decorated Hopf link. A closed formula for these Homfly polynomials is given. Furthermore, the specialization of the variables to roots of unity is considered. The techniques are skein theory on the one side, and the theory of symmetric functions in the formulation of Schur functions on the other side. Many previously known results have been proved here by only using skein theory and without using knowledge about quantum groups.

- Approximating Perpetuities (2006)
- A perpetuity is a real valued random variable which is characterised by a distributional fixed-point equation of the form X=AX+b, where (A,b) is a vector of random variables independent of X, whereas dependencies between A and b are allowed. Conditions for existence and uniqueness of solutions of such fixed-point equations are known, as is the tail behaviour for most cases. In this work, we look at the central area and develop an algorithm to approximate the distribution function and possibly density of a large class of such perpetuities. For one specific example from the probabilistic analysis of algorithms, the algorithm is implemented and explicit error bounds for this approximation are given. At last, we look at some examples, where the densities or at least some properties are known to compare the theoretical error bounds to the actual error of the approximation. The algorithm used here is based on a method which was developed for another class of fixed-point equations. While adapting to this case, a considerable improvement was found, which can be translated to the original method.

- Lyapunov functions for linear nonautonomous dynamical equations on time scales (2006)
- The existence of a Lyapunov function is established following a method of Yoshizawa for the uniform exponential asymptotic stability of the zero solution of a nonautonomous linear dynamical equation on a time scale with uniformly bounded graininess.

- Concentration of multivariate random recursive sequences arising in the analysis of algorithms (2006)
- Stochastic analysis of algorithms can be motivated by the analysis of randomized algorithms or by postulating on the sets of inputs of the same length some probability distributions. In both cases implied random quantities are analyzed. Here, the running time is of great concern. Characteristics like expectation, variance, limit law, rates of convergence and tail bounds are studied. For the running time, beside the expectation, upper bounds on the right tail are particularly important, since one wants to know large values of the running time not taking place with possibly high probability. In the first chapter game trees are analyzed. The worst case runnig time of Snir's randomized algorithm is specified and its expectation, asymptotic behavior of the variance, a limit law with uniquely characterized limit and tail bounds are identified. Furthermore, a limit law for the value of the game tree under Pearl's probabilistic modell is proved. In the second chapter upper and lower bounds for the Wiener Index of random binary search trees are identified. In the third chapter tail bounds for the generation size of multitype Galton-Watson processes (with immigration) are derived, depending on their offspring distribution. Therefore, the method used to prove the tail bounds in the first chapter is generalized.

- Stochastic models for near-synchronous neuronal firing activity (2006)
- It is commonly agreed that cortical information processing is based on the electric discharges (spikes') of nerve cells. Evidence is accumulating which suggests that the temporal interaction among a large number of neurons can take place with high precision, indicating that the efficiency of cortical processing may depend crucially on the precise spike timing of many cells. This work focuses on two temporal properties of parallel spike trains that attracted growing interest in the recent years: In the first place, specific delays (phase offsets') between the firing times of two spike trains are investigated. In particular, it is studied whether small phase offsets can be identified with confidence between two spike trains that have the tendency to fire almost simultaneously. Second, the temporal relations between multiple spike trains are investigated on the basis of such small offsets between pairs of processes. Since the analysis of all delays among the firing activity of n neurons is extremely complex, a method is required with which this highly dimensional information can be collapsed in a straightforward manner such that the temporal interaction among a large number of neurons can be represented consistently in a single temporal map. Finally, a stochastic model is presented that provides a framework to integrate and explain the observed temporal relations that result from the previous analyses.

- A note on strong solutions of stochastic differential equations with a discontinuous drift coefficient (2006)
- The existence of a mean-square continuous strong solution is established for vector-valued Itö stochastic differential equations with a discontinuous drift coefficient, which is an increasing function, and with a Lipschitz continuous diffusion coefficient. A scalar stochastic differential equation with the Heaviside function as its drift coefficient is considered as an example. Upper and lower solutions are used in the proof.