An Investigation into the Radiation Damage of the Silicon Detectors of the H1-PLUG Calorimeter within the HERA environment

The silicon detectors used in the H1-PLUG calorimeter have shown increasing aging effects during the '94 run period of the electron proton storage ring HERA. These effects were particularly manifest as degradation of the signal to noise level and the calibration stability. The reasons for this behaviour have been found to be correlated with radiation damage to the silicon oxide passivation edges of the detectors in strong and fluctuating increases of the leakage currents and in severe changes of the flat band voltages. Depletion voltages however are found to be stable and therefore bulk damage of the silicon can be excluded. A comparison with measurements made by thermoluminescence dosimeters as well as related laboratory experiments suggest that the aging is due to very low energetic electrons and photons.Comment: 17 pages, latex, 21 figures, eps-format, appende

Arcfinder: An algorithm for the automatic detection of gravitational arcs

We present an efficient algorithm designed for and capable of detecting elongated, thin features such as lines and curves in astronomical images, and its application to the automatic detection of gravitational arcs. The algorithm is sufficiently robust to detect such features even if their surface brightness is near the pixel noise in the image, yet the amount of spurious detections is low. The algorithm subdivides the image into a grid of overlapping cells which are iteratively shifted towards a local centre of brightness in their immediate neighbourhood. It then computes the ellipticity for each cell, and combines cells with correlated ellipticities into objects. These are combined to graphs in a next step, which are then further processed to determine properties of the detected objects. We demonstrate the operation and the efficiency of the algorithm applying it to HST images of galaxy clusters known to contain gravitational arcs. The algorithm completes the analysis of an image with 3000x3000 pixels in about 4 seconds on an ordinary desktop PC. We discuss further applications, the method's remaining problems and possible approaches to their solution.Comment: 12 pages, 12 figure

THz-range free-electron laser ESR spectroscopy: techniques and applications in high magnetic fields

The successful use of picosecond-pulse free-electron-laser (FEL) radiation for the continuous-wave THz-range electron spin resonance (ESR) spectroscopy has been demonstrated. The combination of two linac-based FELs (covering the wavelength range of 4 - 250 $\mu$m) with pulsed magnetic fields up to 70 T allows for multi-frequency ESR spectroscopy in a frequency range of 1.2 - 75 THz with a spectral resolution better than 1%. The performance of the spectrometer is illustrated with ESR spectra obtained in the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the low-dimensional organic material (C$_6$H$_9$N$_2$)CuCl$_3$.Comment: 9 pages, 9 figures. Rev. Sci. Instrum., accepte

Neural View-Interpolation for Sparse Light Field Video

We suggest representing light field (LF) videos as "one-off" neural networks (NN), i.e., a learned mapping from view-plus-time coordinates to high-resolution color values, trained on sparse views. Initially, this sounds like a bad idea for three main reasons: First, a NN LF will likely have less quality than a same-sized pixel basis representation. Second, only few training data, e.g., 9 exemplars per frame are available for sparse LF videos. Third, there is no generalization across LFs, but across view and time instead. Consequently, a network needs to be trained for each LF video. Surprisingly, these problems can turn into substantial advantages: Other than the linear pixel basis, a NN has to come up with a compact, non-linear i.e., more intelligent, explanation of color, conditioned on the sparse view and time coordinates. As observed for many NN however, this representation now is interpolatable: if the image output for sparse view coordinates is plausible, it is for all intermediate, continuous coordinates as well. Our specific network architecture involves a differentiable occlusion-aware warping step, which leads to a compact set of trainable parameters and consequently fast learning and fast execution

A Bayesian Approach to Manifold Topology Reconstruction

In this paper, we investigate the problem of statistical reconstruction of piecewise linear manifold topology. Given a noisy, probably undersampled point cloud from a one- or two-manifold, the algorithm reconstructs an approximated most likely mesh in a Bayesian sense from which the sample might have been taken. We incorporate statistical priors on the object geometry to improve the reconstruction quality if additional knowledge about the class of original shapes is available. The priors can be formulated analytically or learned from example geometry with known manifold tessellation. The statistical objective function is approximated by a linear programming / integer programming problem, for which a globally optimal solution is found. We apply the algorithm to a set of 2D and 3D reconstruction examples, demon-strating that a statistics-based manifold reconstruction is feasible, and still yields plausible results in situations where sampling conditions are violated

8-MW wind turbine tower computational shell buckling benchmark. Part 2: detailed reference solution

An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design. This paper presents a detailed reference solution to the computational buckling analysis of a standardised benchmark problem of an 8-MW multi-strake wind turbine support tower. Both linear and nonlinear analyses are performed, including advanced GMNIA with several different models of geometric imperfections. The crucial issue of interpreting the imperfection amplitude in a way that is compliant with the new prEN 1993-1-6 is discussed in detail. The solution presented herein is intended for use by analysts in both industry and academia for training, verification and calibration of finite element models and is intended to initiate a public repository of such computational solutions for metal civil engineering shell structures. This paper is the second of a pair. The first paper presents a synthesis of 29 submissions to an international round-robin exercise performed on the same benchmark problem

Development of a High-Resolution, Single-Photon X-Ray Detector

Research on the development of a low-temperature, magnetic bolometer for x-ray detection is reported. The principal accomplishments during the first phase of this research are as follows. (1) We have constructed SQUID magnetometers and detected both 122 keV and 6 keV x-rays in relatively larger metallic samples with high quantum efficiency. (2) The magnetic properties of a metal sample with localized paramagnetic spins have been measured and found to agree with theoretical expectations. (3) The size of the magnetic response of the sample to x-rays is in agreement with predictions based on the properties of the sample and sensitivity of the magnetometer, supporting the prediction that a resolution of 1 eV at 10 keV should be achievable