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I am working on a track finding module specialized for low momentum
tracks in the Silicon Vertex Detector (a double-sided strip detector) of
the Belle II experiment (Tsukuba, Japan). Transverse momenta (pT) down
to 50 MeV/c (high deviations due to material effects) shall be
reconstructed and only a small number of layers are available (3-4
layers depending on pT), while facing considerable background, mainly
Bhabha-Scattering and Touschek effect. We plan to deal with it by
combining 3 different techniques: a Cellular Automaton produces track
candidates (TCs) which are filtered by a Kalman filter which calculates
quality indicators for each TC. These quality indicators are used by a
neuronal network of Hopfield type to determine a reasonable set of TCs
which do not share hits. I am currently working using linux (ubuntu) and
am familiar with Microsoft Windows too. C++ and Python are the languages
I use most. Basic knowledge for C and Octave (Matlab) does exist too. |