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A. Bischoff

Publications and source records attributed to A. Bischoff.

3 recordsLinked to original sources

Ejby -- A new H5/6 ordinary chondrite fall in Copenhagen, Denmark

On February 6, 2016 at 21:07:19 UT, a very bright fireball was seen over the eastern part of Denmark. The weather was cloudy over eastern Denmark, but many people saw the sky light up-even in the heavily illuminated Copenhagen. Two hundred and thirty three reports of the associated sound and light phenomena were received by the Danish fireball network. We have formed a consortium to describe the meteorite and the circumstances of the fall and the results are presented in this paper. The first fragment of the meteorite was found the day after the fall, and in the following weeks, a total of 11 fragments with a total weight of 8982 g were found. The meteorite is an unbrecciated, weakly shocked (S2), ordinary H chondrite of petrologic type 5/6 (Bouvier et al. 2017). The concentration of the cosmogenic radionuclides suggests that the preatmospheric radius was rather small ~20 cm. The cosmic ray exposure age of Ejby (83 +/- 11 Ma) is the highest of an H chondrite and the second highest age for an ordinary chondrite. Using the preatmospheric orbit of the Ejby meteoroid (Spurny et al. 2017) locations of the recovered fragments, and wind data from the date of the fall, we have modeled the dark flight (below 18 km) of the fragments. The recovery location of the largest fragment can only be explained if aerodynamic effects during the dark flight phase are included. The recovery location of all other fragments are consistent with the dark flight modeling.

astro-ph.EP

The D0 Silicon Microstrip Tracker

This paper describes the mechanical design, the readout chain, the production, testing and the installation of the Silicon Microstrip Tracker of the D0 experiment at the Fermilab Tevatron collider. In addition, description of the performance of the detector during the experiment data collection between 2001 and 2010 is provided.

physics.ins-det

Neural Networks for Impact Parameter Determination

An accurate impact parameter determination in a heavy ion collision is crucial for almost all further analysis. The capabilities of an artificial neural network are investigated to that respect. A novel input generation for the network is proposed, namely the transverse and longitudinal momentum distribution of all outgoing (or actually detectable) particles. The neural network approach yields an improvement in performance of a factor of two as compared to classical techniques. To achieve this improvement simple network architectures and a 5 by 5 input grid in (p_t,p_z) space are sufficient.

nucl-th