Alignment of the CLAS12 central hybrid tracker with a Kalman Filter

CLAS Collaboration

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Several factors can contribute to the difficulty of aligning the sensors of tracking detectors, including a large number of modules, multiple types of detector technologies, and non-linear strip patterns on the sensors. The latter two of these three factors apply to the CLAS12 CVT, which is a hybrid detector consisting of planar silicon sensors with non-parallel strips, and cylindrical micromegas sensors with longitudinal and arc-shaped strips located within a 5 T superconducting solenoid. To align this detector, we used the Kalman Alignment Algorithm, which accounts for correlations between the alignment parameters without requiring the time-consuming inversion of large matrices. This is the first time that this algorithm has been adapted for use with hybrid technologies, non-parallel strips, and curved sensors. We present the results for the first alignment of the CLAS12 CVT using straight tracks from cosmic rays and from a target with the magnetic field turned off. After running this procedure, we achieved alignment at the level of 10μm, and the widths of the residual spectra were greatly reduced. These results attest to the flexibility of this algorithm and its applicability to future use in the CLAS12 CVT and other hybrid or curved trackers, such as those proposed for the future Electron-Ion Collider.

Original languageEnglish
Article number168032
JournalNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Early online date1 Feb 2023
Publication statusPublished - Apr 2023

Bibliographical note

Funding Information:
We acknowledge the outstanding efforts of the staff of the Accelerator, the Nuclear Physics Division, Hall B, and the Detector Support Group at JLab that have contributed to the design, construction, installation, and operation of the CLAS12 detector. We thank Maurizio Ungaro for his contributions in the CLAS12 simulations. We also thank the CLAS Collaboration for staffing shifts and taking high quality data. This work was supported by the United States Department of Energy under JSA/DOE Contract DE-AC05-06OR23177 . This work was also supported in part by the U.S. National Science Foundation , the State Committee of Science of the Republic of Armenia , the Chilean Agencia Nacional de Investigación y Desarrollo , the Italian Istituto Nazionale di Fisica Nucleare , the French Centre National de la Recherche Scientifique , the French Commissariat a l’Energie Atomique , the Scottish Universities Physics Alliance (SUPA) , the United Kingdom Science and Technology Facilities Council (STFC) , the National Research Foundation of Korea , the Deutsche Forschungsgemeinschaft (DFG) , and the Russian Science Foundation . This research was funded in part by the French Agence Nationale de la Recherche contract no. 37 . This work was supported as well by the EU Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement No. 101003460 .

Publisher Copyright:
© 2023


  • Alignment
  • Detector
  • Kalman filter

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