# INSTR'20

24-28 February 2020
Budker Institute of Nuclear Physics
Asia/Novosibirsk timezone

## FPGA-based algorithms for feature extraction in the PANDA shashlyk calorimeter

28 Feb 2020, 15:30
20m
Contributed Oral Calorimetry

### Speaker

Mr Markus Preston (Stockholm University)

### Description

PANDA is one of the four experimental pillars of the upcoming FAIR facility in Darmstadt, Germany. In PANDA, an antiproton beam with an energy between 1.5 and 15 GeV/$c$ will interact in a hydrogen or nuclear target, allowing for studies of various aspects of non-perturbative QCD. Motivated by the high interaction rates and the diverse physics goals of the experiment, a triggerless readout approach will be employed. In this approach, each detector subsystem will be equipped with intelligent front-end electronics that independently identify signals of interest in real time. In order to detect the most forward-directed photons, electrons and positrons in PANDA, a shashlyk- type calorimeter is being constructed. This detector consists of 1512 individual cells of interleaved plastic scintillators and lead plates, and has been optimised to have a relative energy resolution of approximately 3%/$\sqrt{\text{GeV}}$ and a time resolution of approximately 100 ps/$\sqrt{\text{GeV}}$. The signals from this detector will be digitised by sampling ADCs and processed in real time by FPGAs. As part of the triggerless approach, these FPGAs will perform so-called feature extraction on the digitised signals, where the pulse-height and time of incoming pulses are extracted in real time. A substantial pileup rate is expected, and it is foreseen that the chosen algorithm should enable reconstruction of such events. The work presented here has consisted of developing a detailed Geant4-based model of the shashlyk calorimeter and readout system, calibrating this model against testbeam data, and using it to evaluate potential feature-extraction algorithms for the PANDA shashlyk calorimeter.

### Primary author

Mr Markus Preston (Stockholm University)

### Co-author

Prof. Per-Erik Tegnér (Stockholm University)

 Slides