In English

Method development and pilot experiments for the R3B micro-vertex tracker

Julius Hagdahl
Göteborg : Chalmers tekniska högskola, 2011. 53 s.
[Examensarbete på avancerad nivå]

Radioactive beam experiments allow physicists to study nuclei at the limits of stability. Knowledge about the properties of such exotic nuclei is essential for under-standing the processes of stellar nucleosynthesis through which all elements heavier than hydrogen are formed. The LAND experimental setup at the GSI facility outside Darmstadt, Germany, can measure properties of highly unstable nuclei using invariant mass reconstruction. One of the key detector systems of this setup is the micro-vertex tracker; an array of double-sided silicon strip detectors used for energy loss and position measurements. This thesis aims to give an introduction to the properties of these detectors and the methods used for calibrating and analysing the measurement data they produce. Further-more, an alternative approach to analysing the measurement data is described and evaluated. This approach aims to extract physical quantities from the detector signals by matching them to sets of characteristic templates for different types of events. Such templates have been calculated from data acquired during the S393 experiment which was carried out in the fall of 2010. An attempt to reconstruct properties of these events based on these clusters was then performed. It was found to be difficult to calculate templates for the different event characte-ristics with small enough errors to be able to success-fully reconstruct events using this method. Although the overall performance of this alternative method was found to be disappointing, the results presented can hopefully provide a basis for further development. Also included is a brief description of an alternative unpacker software which implements a reduced data format for the micro-vertex tracker. This format aims to reduce the amount of data produced by the detector system through a non-feature removal algorithm, allowing it to identify and discard all non-significant signals from the tracker.



Publikationen registrerades 2013-06-24. Den ändrades senast 2013-09-11

CPL ID: 179103

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