Technical University of Dortmund

About: Technical University of Dortmund is a education organization based out in Dortmund, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 13028 authors who have published 27666 publications receiving 615557 citations. The organization is also known as: Dortmund University & University of Dortmund.

Spin Noise of Electrons and Holes in Self-Assembled Quantum Dots

Abstract: We measure the frequency spectra of random spin fluctuations, or ``spin noise,'' in ensembles of $(\mathrm{In},\mathrm{Ga})\mathrm{As}/\mathrm{GaAs}$ quantum dots (QDs) at low temperatures. We employ a spin noise spectrometer based on a sensitive optical Faraday rotation magnetometer that is coupled to a digitizer and field-programmable gate array, to measure and average noise spectra from 0--1 GHz continuously in real time with $\mathrm{\text{subnanoradian}}/\sqrt{\mathrm{Hz}}$ sensitivity. Both electron and hole spin fluctuations generate distinct noise peaks, whose shift and broadening with magnetic field directly reveal their $g$ factors and dephasing rates within the ensemble. A large, energy-dependent anisotropy of the in-plane hole $g$ factor is clearly exposed, reflecting systematic variations in the average QD confinement potential.

Effective Hamiltonians and bindings energies of Wannier excitons in polar semiconductors

Abstract: The interaction of Wannier excitons with an LO-phonon field is investigated in detail. We derive effective local Hamiltonians which may be used to calculate the whole exciton spectrum in a polarizable medium. The constituents of the exciton are no longer treated as two independent polarons. The coupling of the polarons is described by new displacement amplitudes. The ground-state energy is evaluated variationally as an example and the analytic expression for the exciton's self-energy is discussed as a function of the binding-strength. We do not reproduce numerical results for various materials which have been given in previous letters and have been found to compare satisfactorily with experimental data. Meanwhile our results have been used with great success in a variety of more complex problems due to its formal simplicity and its quantitative accuracy.

Duration of sleep depending on the type of shift work

Abstract: Time budget studies were performed in eight groups of shift workers. The 9,480 diary records of altogether 1,230 shift workers were analyzed and related to corresponding shift types. The shortest night sleep was found before the morning shift (mean 7.0 h). There were large differences in the duration of day sleep when classifying this sleep into specific types, as day sleep before 1st night shift (mean 2.1 h), between two night shifts (mean 6.1 h), or after last night shift (mean 4.2 h). Average sleep durations of five kinds of day sleep and 12 kinds of night sleep are presented together with 14 frequency distributions of durations of sleep. It is concluded that there should not be many night shifts in succession and that morning shifts should not begin too early to avoid an accumulation of sleep deficits.

Crossover is provably essential for the Ising model on trees

Abstract: Due to experimental evidence it is incontestable that crossover is essential for some fitness functions. However, theoretical results without assumptions are difficult. So-called real royal road functions are known where crossover is proved to be essential, i.e., mutation-based algorithms have an exponential expected runtime while the expected runtime of a genetic algorithm is polynomially bounded. However, these functions are artificial and have been designed in such a way that crossover is essential only at the very end (or at other well-specified points) of the optimization process.Here, a more natural fitness function based on a generalized Ising model is presented where crossover is essential throughout the whole optimization process. Mutation-based algorithms such as (μ+λ) EAs with constant population size are proved to have an exponential expected runtime while the expected runtime of a simple genetic algorithm with population size 2 and fitness sharing is polynomially bounded.