Georg Brandes and the Jewish question

Georg Brandes (1842­­­­­­–1927) was a famous European literary and cultural critic who is one of the most controversial personalities to be found in Danish intellectual life. His position as the leading figure in the so-called modern breakthrough is, of course, beyond dispute. The controversy has been and still is centered around the significance of his efforts. In this connection reference has often been made to his Jewish heritage as something “non-Danish” or “foreign”. To be sure, anti-Semitism at its worst never really acquired a foothold in Denmark, but it did, however, come to play a decisive role in the disqualification of Brandes and in the discrediation of the name he left to posterity. No matter how things were worded, they always had to do with Brandes’ Jewish ancestry. Quite understandably, serious scholarly research, has until recently on the whole avoided this controversial aspect of such an already extremely controversial person. There are obviously things having to do with Brandes’ life and works which cannot be explained unless we take into account his Jewish ancestry, a subject which, quite against his will, became one of the central themes in his life

Infrainguinal inflow assessment and endovenous stent placement in iliofemoral post-thrombotic obstructions

Purpose To assess the technical success, patency, and clinical outcome, following assessment of inflow and infrainguinal endovenous stent placement in patients with iliofemoral post-thrombotic obstruction with infrainguinal involvement. Methods A retrospective analysis of 39 patients with iliofemoral post-thrombotic venous obstruction accepted for infrainguinal stent placement in the period November 2009–December 2016. The clinical status was categorized according to the Clinical Etiological Anatomical Pathophysiological (CEAP) classification and symptom severity was assessed using Venous Clinical Severity Score (VCSS). The inflow was categorized as “good”, “fair”, or “poor” depending on vein caliber and extent of post-thrombotic changes in the inflow vessel(s). Stent patency was assessed by duplex ultrasound. Median follow-up was 44 months (range 2–90 months). Results Stent placement was successful in all 39 patients. Primary patency after 24 months was 78%. Thirty of 39 patients (77%) had open stents at final follow-up. Re-interventions were performed in four patients and included catheter-directed thrombolysis (CDT) in all and adjunctive stenting in two. Twenty-eight of 39 patients (72%) reported a sustained clinical improvement. Patients with “good” inflow had better patency compared to those with “fair”/“poor” (p = 0.01). One patient experienced acute contralateral iliofemoral thrombosis; this segment was successfully treated with CDT and stenting. No other complications required intervention. Conclusion Infrainguinal endovenous stent placement was a feasible and safe treatment with good patency and clinical results, and should be considered in patients with substantial symptoms from post-thrombotic obstructions with infrainguinal involvement. Stents with good inflow have better patency and inflow assessment is essential in deciding the optimal stent landing zone

The DUNE Far Detector Vertical Drift Technology, Technical Design Report

International audienceDUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype