Analytical and experimental investigation of sidelobe suppression techniques for reflector type spacecraft antenna Final technical report

Near axis sidelobe suppression techniques for circularly polarized reflector type spacecraft antenna

Longitudinal elastic velocities in MgO to 360 kbar

Numerical descriptions of shock wave induced flows obtained with a two-dimensional Lagrangian finite difference code are compared in detail with experimental data obtained via the lateral relaxation method for polycrystalline magnesium oxide (MgO) to a pressure of 360 kbar. The equation of state used for MgO was assumed to be of the Mie-Grüneisen form, and detailed comparison of experimental and calculated data was used to obtain refined values of the shear strength and shear modulus of MgO at high pressures. The best fitting rheological model for MgO was characterized by a shear strength which decreased from a value of 26 kbar at 16.5-kbar mean stress to 13.5 kbar at 360-kbar mean stress along the principal Hugoniot curve. The first and second pressure derivatives of the shear modulus, when the shear modulus is evaluated as a quadratic function of pressure, yield (∂μ/∂P) = 2.44 and μ(∂^2μ/∂P^2) = 1.7±3.0. The uncertainties in the determination of μ(∂^2μ/∂P^2) have been reduced by a factor of 5 over previous estimates

Off-diagonal disorder in the Anderson model of localization

We examine the localization properties of the Anderson Hamiltonian with additional off-diagonal disorder using the transfer-matrix method and finite-size scaling. We compute the localization lengths and study the metal-insulator transition (MIT) as a function of diagonal disorder, as well as its energy dependence. Furthermore we investigate the different influence of odd and even system sizes on the localization properties in quasi one-dimensional systems. Applying the finite-size scaling approach in conjunction with a nonlinear fitting procedure yields the critical parameters of the MIT. In three dimensions, we find that the resulting critical exponent of the localization length agrees with the exponent for the Anderson model with pure diagonal disorder.Comment: 12 pages including 4 EPS figures, accepted for publication in phys. stat. sol. (b

The Geophysical Model Generator: a tool to unify and interpret geophysical datasets

Geophysical datasets and their interpretations form the basis of geodynamic simulations of the Earth’s mantle and lithosphere. Yet, going from data to models is often non-trivial, particularly in complex regions such as the Alps. This is because creating consistent three-dimensional models from these datasets is often challenging due to technical discrepancies such as different data set formats, different spatial resolutions or discrepancies between different data sets. At the same time, the different datasets obtained through initiatives such as AlpArray contain a wealth of data that can help to constrain subsurface models to an unprecedented extent. Yet interpreting these different data still involves subjective steps and ideally different datasets are combined in the process. To facilitate the joint interpretation of these datasets and the generation of geodynamic model setups, we therefore developed an open-source package - the Geophysical Model Generator (GMG) - to assist with unifying these datasets in a common data format that can then be further used to visualize, compare and interpret data. Within this package, we provide a set of routines to import different datasets, convert them to a common data format and to process them further (e.g., to create vote maps from different tomographies). These unified datasets can then be exported as vtk-files for further 3D visualization (e.g., Paraview). Moreover, with the Geophysical Model Generator it is also possible to create model setups for numerical models (such as the 3D geodynamic code LaMEM). This package thus covers the entire workflow from data import to numerical model generation. Key features of the Geophysical Model Generator include 1) the creation of 3D volumes from seismic tomography models, 2) the import of 2D data (e.g., surface or Moho topography or screenshots from published papers) and 3) the incorporation of point data such as earthquake locations or GPS measurements. Both scalar and vector data can be handled. With these tools, one can then create a consistent overview of the entire data available for a given region. The package is written in Julia and hosted as a public open-source repository on GitHub (https://github.com/JuliaGeodynamics/GeophysicalModelGenerator.jl). To assist the joint interpretation of different geophysical datasets, we furthermore provide a graphical user interface that allows to view and compare them (https://github.com/JuliaGeodynamics/DataPicker). The GUI works provides an interactive webpage, allows loading different datasets and facilitates the manual interpretation of different structures (such as subducting slabs) along profiles and visualize them in 3D while taking different data into account. An example of the current version is given in Figure 1

Assessing factors that may predispose Minnesota farms to wolf depredations on cattle

Wolf (Canis lupus) depredations on livestock cause considerable conflict and expense in Minnesota. Furthermore, claims are made that such depredations are fostered by the type of animal husbandry practiced. Thus, we tried to detect factors that might predispose farms in Minnesota to wolf depredations. We compared results of interviews with 41 cattle farmers experiencing chronic cattle losses to wolves (chronic farms) with results from 41 nearby matched farms with no wolf losses to determine farm characteristics or husbandry practices that differed and that therefore might have affected wolf depredations. We also used a Geographic Information System (GIS) to detect any habitat differences between the 2 types of farms. We found no differences between chronic and matched farms in the 11 farm characteristics and management practices that we surveyed, except that farms with chronic losses were larger, had more cattle, and had herds farther from human dwellings. Habitat types were the same around farms with and without losses. The role of proper carcass disposal as a possible factor predisposing farms to wolf depredations remains unclear

Carburisation of ferritic Fe–Cr alloys by low carbon activity gases

Model Fe–Cr alloys were exposed to Ar–CO2–H2O gas mixtures at 650 and 800 °C. At equilibrium, these atmospheres are oxidising to the alloys, but decarburising (aC ≈ 10−15 to 10−13). In addition to developing external oxide scales, however, the alloys also carburised. Carbon supersaturation at the scale/alloy interface relative to the gas reflects local equilibrium: a low oxygen potential corresponds to a high pCO/pCO2 ratio, and hence to a high carbon activity. Interfacial carbon activities calculated on the basis of scale–alloy equilibrium are shown to be in good agreement with measured carburisation rates and precipitate volume fractions, providing support for the validity of the thermodynamic model

Model Checking CTL is Almost Always Inherently Sequential

The model checking problem for CTL is known to be P-complete (Clarke, Emerson, and Sistla (1986), see Schnoebelen (2002)). We consider fragments of CTL obtained by restricting the use of temporal modalities or the use of negations---restrictions already studied for LTL by Sistla and Clarke (1985) and Markey (2004). For all these fragments, except for the trivial case without any temporal operator, we systematically prove model checking to be either inherently sequential (P-complete) or very efficiently parallelizable (LOGCFL-complete). For most fragments, however, model checking for CTL is already P-complete. Hence our results indicate that, in cases where the combined complexity is of relevance, approaching CTL model checking by parallelism cannot be expected to result in any significant speedup. We also completely determine the complexity of the model checking problem for all fragments of the extensions ECTL, CTL+, and ECTL+

Towards integrated superconducting detectors on lithium niobate waveguides

Superconducting detectors are now well-established tools for low-light optics, and in particular quantum optics, boasting high-efficiency, fast response and low noise. Similarly, lithium niobate is an important platform for integrated optics given its high second-order nonlinearity, used for high-speed electro-optic modulation and polarization conversion, as well as frequency conversion and sources of quantum light. Combining these technologies addresses the requirements for a single platform capable of generating, manipulating and measuring quantum light in many degrees of freedom, in a compact and potentially scalable manner. We will report on progress integrating tungsten transition-edge sensors (TESs) and amorphous tungsten silicide superconducting nanowire single-photon detectors (SNSPDs) on titanium in-diffused lithium niobate waveguides. The travelling-wave design couples the evanescent field from the waveguides into the superconducting absorber. We will report on simulations and measurements of the absorption, which we can characterize at room temperature prior to cooling down the devices. Independently, we show how the detectors respond to flood illumination, normally incident on the devices, demonstrating their functionality.Comment: 7 pages, 4 figure