Direct observation of the influence of the As-Fe-As angle on the Tc of superconducting SmFeAsO1−x_{1-x}Fx_{x}

The electrical resistivity, crystalline structure and electronic properties calculated from the experimentally measured atomic positions of the compound SmFeAsO$_{0.81}$F$_{0.19}$ have been studied up to pressures ~20GPa. The correlation between the pressure dependence of the superconducting transition temperature (Tc) and crystallographic parameters on the same sample shows clearly that a regular FeAs$_{4}$ tetrahedron maximizes Tc, through optimization of carrier transfer to the FeAs planes as indicated by the evolution of the electronic band structures.Comment: 15pages, 4 figure

Large lianas as hyperdynamic elements of the tropical forest canopy

Lianas (woody vines) are an important component of lowland tropical forests. We report large liana and tree inventory and dynamics data from Amazonia over periods of up to 24 years, making this the longest geographically extensive study of liana ecology to date. We use these results to address basic questions about the ecology of large lianas in mature forests and their interactions with trees. In one intensively studied site we find that large lianas (≥10 cm diameter) represent ,5% of liana stems, but 80% of biomass of well-lit upper canopy lianas. Across sites, large lianas and large trees are both most successful in terms of structural importance in richer soil forests, but large liana success may be controlled more by the availability of large tree supports rather than directly by soil conditions. Long-term annual turnover rates of large lianas are 5–8%, three times those of trees. Lianas are implicated in large tree mortality: liana-infested large trees are three times more likely to die than liana-free large trees, and large lianas are involved in the death of at least 30% of tree basal area. Thus large lianas are a much more dynamic component of Amazon forests than are canopy trees, and they play a much more significant functional role than their structural contribution suggests

Two approaches for effective modelling of rain-rate time-series for radiocommunication system simulations

The paper presents a model which allows to synthetically generate rain rate time-series for a fixed location. Rain rate time-series are very much correlated with signal attenuation in Ka band and above and, thus, enable to realistically simulate propagation effects on Earth-satellite links. The model presented are based on Markov chains

Current Induced Order Parameter Dynamics: Microscopic Theory Applied to Co/Cu/Co spin valves

Transport currents can alter alter order parameter dynamics and change steady states in superconductors, in ferromagnets, and in hybrid systems. In this article we present a scheme for fully microscopic evaluation of order parameter dynamics that is intended for application to nanoscale systems. The approach relies on time-dependent mean-field-theory, on an adiabatic approximation, and on the use of non-equilibrium Greens function (NEGF) theory to calculate the influence of a bias voltage across a system on its steady-state density matrix. We apply this scheme to examine the spin-transfer torques which drive magnetization dynamics in Co/Cu/Co spin-valve structures. Our microscopic torques are peaked near Co/Cu interfaces, in agreement with most previous pictures, but suprisingly act mainly on Co transition metal $d$-orbitals rather than on $s$-orbitals as generally supposed.Comment: 9 pages, 5 figure

Ab-initio GMR and current-induced torques in Au/Cr multilayers

We report on an {\em ab-initio} study of giant magnetoresistance (GMR) and current-induced-torques (CITs) in Cr/Au multilayers that is based on non-equilibrium Green's functions and spin density functional theory. We find substantial GMR due primarily to a spin-dependent resonance centered at the Cr/Au interface and predict that the CITs are strong enough to switch the antiferromagnetic order parameter at current-densities $\sim 100$ times smaller than typical ferromagnetic metal circuit switching densities.Comment: 8 pages, 6 figure

Strong, Weak and Branching Bisimulation for Transition Systems and Markov Reward Chains: A Unifying Matrix Approach

We first study labeled transition systems with explicit successful termination. We establish the notions of strong, weak, and branching bisimulation in terms of boolean matrix theory, introducing thus a novel and powerful algebraic apparatus. Next we consider Markov reward chains which are standardly presented in real matrix theory. By interpreting the obtained matrix conditions for bisimulations in this setting, we automatically obtain the definitions of strong, weak, and branching bisimulation for Markov reward chains. The obtained strong and weak bisimulations are shown to coincide with some existing notions, while the obtained branching bisimulation is new, but its usefulness is questionable

Limitations on the superposition principle: superselection rules in non-relativistic quantum mechanics

The superposition principle is a very basic ingredient of quantum theory. What may come as a surprise to many students, and even to many practitioners of the quantum craft, is tha superposition has limitations imposed by certain requirements of the theory. The discussion of such limitations arising from the so-called superselection rules is the main purpose of this paper. Some of their principal consequences are also discussed. The univalence, mass and particle number superselection rules of non-relativistic quantum mechanics are also derived using rather simple methods.Comment: 22 pages, no figure

Using genetic algorithms to generate test sequences for complex timed systems

The generation of test data for state based specifications is a computationally expensive process. This problem is magnified if we consider that time con- straints have to be taken into account to govern the transitions of the studied system. The main goal of this paper is to introduce a complete methodology, sup- ported by tools, that addresses this issue by represent- ing the test data generation problem as an optimisa- tion problem. We use heuristics to generate test cases. In order to assess the suitability of our approach we consider two different case studies: a communication protocol and the scientific application BIPS3D. We give details concerning how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs outperform random search and seem to scale well as the problem size increases. It is worth to mention that we use a very simple fitness function that can be eas- ily adapted to be used with other evolutionary search techniques