Erlangen 2026 – wissenschaftliches Programm
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HK: Fachverband Physik der Hadronen und Kerne
HK 36: Instrumentation VII
HK 36.3: Vortrag
Donnerstag, 19. März 2026, 14:30–14:45, PHIL B 302
Update on the Developments in Optimization and Characterization for the ToASt-based Silicon-Strip-Detectors of the PANDA MVD — •Raphael Ratz1, Kai-Thomas Brinkmann1, Marvin Peter1, Hans-Georg Zaunick1, Giovanni Mazza2, Michele Caselle3, and Daniela Calvo2 for the PANDA collaboration — 12nd Physics Institute, Justus Liebig University, Giessen — 2Istituto Nazionale di Fisica Nucleare - Sezione di Torino, Turin — 3Karlsruhe Institute of Technology, Karlsruhe
The Micro Vertex Detector (MVD) of the PANDA experiment consists of silicon strip detectors, read out by the Torino Amplifier for silicon Strip detectors (ToASt) ASIC. Each ToASt employs a multitude of parameters, some of which affect the Signal-to-Noise Ratio (SNR) of the Time-over-Threshold (ToT) measurement. Thus, an optimization and an energy calibration for the measured ToTs is favorable.
After establishing the parameters that most affect SNR, they were optimized pairwise using a grid search method with the integrated testpulser of the ToASt. As the analysis of the correlation matrix suggests multiparameter effects on the SNR, a Bayesian optimization algorithm was investigated. While covering more than two parameters simultaneously, this approach also decreases the time needed compared to a grid search, allowing each sensor channel to be optimized individually.
In addition, a calibration between the measured ToT and the deposited charge, and subsequently the deposited energy, was achieved. Lastly, a web-based user interface for configuring sensors and online analysis of measurements was developed. Supported by BMFTR.
Keywords: Signal-to-Noise Ratio; Bayesian Optimization; Silicon Strip Detectors; ToASt; Particle Tracker