Scaling property of the critical hopping parameters for the Bose-Hubbard model

Recently precise results for the boundary between the Mott insulator phase and the superfluid phase of the homogeneous Bose-Hubbard model have become available for arbitrary integer filling factor g and any lattice dimension d > 1. We use these data for demonstrating that the critical hopping parameters obey a scaling relationship which allows one to map results for different g onto each other. Unexpectedly, the mean-field result captures the dependence of the exact critical parameters on the filling factor almost fully. We also present an approximation formula which describes the critical parameters for d > 1 and any g with high accuracy.Comment: 5 pages, 5 figures. to appear in EPJ

Molecular Fine Structure from Water Window X-rays

Postprint (published version

Convolutional CRFs for semantic segmentation

For the challenging semantic image segmentation task the best performing models have traditionally combined the structured modelling capabilities of Conditional Random Fields (CRFs) with the feature extraction power of CNNs. In more recent works however, CRF post-processing has fallen out of favour. We argue that this is mainly due to the slow training and inference speeds of CRFs, as well as the difficulty of learning the internal CRF parameters. To overcome both issues we propose to add the assumption of conditional independence to the framework of fully-connected CRFs. This allows us to reformulate the inference in terms of convolutions, which can be implemented highly efficiently on GPUs. Doing so speeds up inference and training by two orders of magnitude. All parameters of the convolutional CRFs can easily be optimized using backpropagation. Towards the goal of facilitating further CRF research we have made our implementations publicly available

Coherently controlled entanglement generation in a binary Bose-Einstein condensate

Considering a two-component Bose-Einstein condensate in a double-well potential, a method to generate a Bell state consisting of two spatially separated condensates is suggested. For repulsive interactions, the required tunnelling control is achieved numerically by varying the amplitude of a sinusoidal potential difference between the wells. Both numerical and analytical calculations reveal the emergence of a highly entangled mesoscopic state.Comment: 6 pages, 6 figures, epl2.cl

Money laundering through consulting firms

The aim of this article is to illustrate potential conduits for money laundering in the consulting sector in Austria, Germany, Liechtenstein, and Switzerland. A qualitative content analysis of 100 semi-standardized expert interviews with both criminals and prevention experts was conducted, along with a quantitative survey of 200 compliance officers, allowing for the identification of concrete methods of money laundering in the consulting sector. Due to their excellent reputation, consulting companies in German-speaking countries in Europe continue to be extraordinarily attractive to money launderers. Most notably, they can be used for layering and integration, as well as for working around various issues with tax codes. As the qualitative findings are based on semi-standardized interviews, they are limited to only the 100 interviewees’ perspectives. The identification of loopholes and weaknesses in the current anti-money laundering mechanisms is meant to provide compliance officers, law enforcement agencies, and legislators with valuable insights into how criminals operate, with the aim of helping them to more effectively combat money laundering. While the previous literature focuses on organizations fighting money laundering and on the improvement of anti-money laundering measures, this article illustrates how money launderers operate to avoid arrest. Prevention methods and criminal perspectives are equally taken into account

The Evolutionarily Dynamics of Aposematism: a Numerical Analysis of Co-Evolution in Finite Populations

The majority of species are under predatory risk in their natural habitat and targeted by predators as part of the food web. During the evolution of ecosystems, manifold mechanisms have emerged to avoid predation. So called secondary defences, which are used after a predator has initiated prey-catching behaviour, commonly involve the expression of toxins or deterrent substances which are not observable by the predator. Hence, the possession of such secondary defence in many prey species comes with a specific signal of that defence (aposematism). This paper builds on the ideas of existing models of such signalling behaviour, using a model of co-evolution and generalisation of aversive information and introduces a new methodology of numerical analysis for finite populations. This new methodology significantly improves the accessibility of previous models. In finite populations, investigating the co-evolution of defence and signalling requires an understanding of natural selection as well as an assessment of the effects of drift as an additional force acting on stability. The new methodology is able to reproduce the predicted solutions of preceding models and finds additional solutions involving negative correlation between signal strength and the extent of secondary defence. In addition, genetic drift extends the range of stable aposematic solutions through the introduction of a new pseudo-stability and gives new insights into the diversification of aposematic displays