1. Presentation of new Kraków Group
Krzysztof Korcyl
(Cracow University of Technology, IFJ - PAN)

2. The group
4 (6) persons (lecturers at the Cracow University of Technology Institute of Teleinformatics
Faculty of Physics, Mathematics and Informatics)
two have phd in informatics
two have phd in physics ( + habilitation + 1 prof.)
good chance to get students (masters only – for small well defined projects – the CUT does not have phd studies)

3. The expertise Recent interests and expertise of the group members:
Image processing - algorithms (medical images)
technologies (GPU with CUDA)
Parallel processing – OpenMP, MPI
large scale architectures
Real time processing – modeling real time systems, architectures
Large scale configuration management (co-author of CERN Quattor)
Software engineering and project management (Agile/SCRUM) (experience in business (Motorola) and scientific (CERN) projects)

4. Possible areas of collaboration
Polish contribution to the FAIR project
(the group can count on some financial support):
in direct cooperation with the Jagiellonian University:
Forward Tracker – real time track recognition – studies on algorithms with different technologies (FPGA, GPUs)
related to activities in AGH (FEE for STT)
central tracker - STT - real time track recognition
same FEE as for the Forward Tracker
fast sampling ADC (in place of TDC with TOT)
Not related to the polish FAIR (i.e. no financial suport – hobby):
modeling of the real time DAQT system for PANDA

5. Tracks Generation and Reconstruction

6. Track Generator Simple Track Generator for any STT Geometry Features:
(For the moment) based on math equation of circle-arcs and straight-lines
Adding noise (radius of drift circles, bogus ST hits)
To do:
Tracks generation based on physics

7. Track Reconstructor Prototype – proof of concept, architected with:
good parallelisation properties,
computational stability
in mind, towards RT
Reconstruction of circle-arcs and straight-lines

8. Track Reconstructor - Aproach
hybrid graph/histogramming for better accuracy when introducing noise (still good parallelisation and concurency) - for some class of events one method will be OK (room for speedup)
STT graph used for noise reduction / calcualtion speedup
calculation in legendre space after conformal transformations (for arcs)
geometrical pair-wise tangent lines fitting (pairs determination may impact accuracy)
graph representation of whole STT (actually we can generate graphs for any STT geometry)

9. Track Reconstruction – To Do
Parallelisation (GPU, MPP CPU),
Graph vs Histogram tunning,
ST hits pairs determination tunning
Evaluation (and adding?) Kalman/Wiener filters
Adding physics (circle arcs vs spirals)
Accuracy evaluation and tunning
other geometrical fitting (analitical solution to tangent non-pair-wise problem?)