Antiblockade in Rydberg excitation of an ultracold lattice gas

It is shown that the two-step excitation scheme typically used to create an ultracold Rydberg gas can be described with an effective two-level rate equation, greatly reducing the complexity of the optical Bloch equations. This allows us to solve the many-body problem of interacting cold atoms with a Monte Carlo technique. Our results reproduce the Rydberg blockade effect. However, we demonstrate that an Autler-Townes double peak structure in the two-step excitation scheme, which occurs for moderate pulse lengths as used in the experiment, can give rise to an antiblockade effect. It is observable in a lattice gas with regularly spaced atoms. Since the antiblockade effect is robust against a large number of lattice defects it should be experimentally realizable with an optical lattice created by CO$_{2}$ lasers.Comment: 4 pages, 6 figure

Modelling Pattern Recognition in Cricket Phonotaxis

A spiking neuron implementation of pattern recognition of the calling songs in Gryllus bimaculatus is proposed. A simplified model of the auditory interneuron AN1 has been fitted to extracellular physiological data. The model captures the aspects of AN1’s rate-response to acoustic stimulation which are believed to be sufficient for pattern recognition. Stimulation patterns can be induced into the model via current injecton of the signals envelope-shapes. The model was used as the input stage to the pattern recognition mechanisms. A biologically plausible filter mechanism for pulse-pause patterns is proposed which is based on short term synaptic plasticity. Three simple filter mechanism are described, based on either isolated synaptic depression or synaptic facilitation. These filters are able to reproduce physiological findings from the cricket’s auditory brain neurons. Further, it is argued that more complex filters can be produced by using combinations of depression and facilitation, and that a complete model of the cricket’s pattern recognition apparatus may be implemented in this way. This however is left as a subject of further studies

Determination of measurement uncertainty by Monte Carlo simulation

Modern coordinate measurement machines (CMM) are universal tools to measure geometric features of complex three-dimensional workpieces. To use them as reliable means of quality control, the suitability of the device for the specific measurement task has to be proven. Therefore, the ISO 14253 standard requires, knowledge of the measurement uncertainty and, that it is in reasonable relation with the specified tolerances. Hence, the determination of the measurement uncertainty, which is a complex and also costly task, is of utmost importance. The measurement uncertainty is usually influenced by several contributions of various sources. Among those of the machine itself, e.g., guideway errors and the influence of the probe and styli play an important role. Furthermore, several properties of the workpiece, such as its form deviations and surface roughness, have to be considered. Also the environmental conditions, i.e., temperature and its gradients, pressure, relative humidity and others contribute to the overall measurement uncertainty. Currently, there are different approaches to determine task-specific measurement uncertainties. This work reports on recent advancements extending the well-established method of PTB's Virtual Coordinate Measuring Machine (VCMM) to suit present-day needs in industrial applications. The VCMM utilizes numerical simulations to determine the task-specific measurement uncertainty incorporating broad knowledge about the contributions of, e.g., the used CMM, the environment and the workpiece

Listen, You are Writing! Speeding up Online Spelling with a Dynamic Auditory BCI

Representing an intuitive spelling interface for brain–computer interfaces (BCI) in the auditory domain is not straight-forward. In consequence, all existing approaches based on event-related potentials (ERP) rely at least partially on a visual representation of the interface. This online study introduces an auditory spelling interface that eliminates the necessity for such a visualization. In up to two sessions, a group of healthy subjects (N = 21) was asked to use a text entry application, utilizing the spatial cues of the AMUSE paradigm (Auditory Multi-class Spatial ERP). The speller relies on the auditory sense both for stimulation and the core feedback. Without prior BCI experience, 76% of the participants were able to write a full sentence during the first session. By exploiting the advantages of a newly introduced dynamic stopping method, a maximum writing speed of 1.41 char/min (7.55 bits/min) could be reached during the second session (average: 0.94 char/min, 5.26 bits/min). For the first time, the presented work shows that an auditory BCI can reach performances similar to state-of-the-art visual BCIs based on covert attention. These results represent an important step toward a purely auditory BCI

Skyline Query Processing

This thesis deals with a special subset of multi-dimensional set of points, called the Skyline. These points are the maxima or minima of the complete set and are of special interest for the field of decision support. Coming from basic algorithms for computing the Skyline we will develop ideas and algorithms for "on-the-fly" or online computation of the Skyline. We will also extend the concept of Skyline with new application domains leading us to user profiling with the help of Skyline

FreeContact: fast and free software for protein contact prediction from residue co-evolution

Background: 20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Results: Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library “libfreecontact”, complete with command line tool “freecontact”, as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. Conclusions: FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud)