Abstract
One of the main components of the CMS experiment is the Silicon Tracker. This device, designed to measure the trajectories of charged particles, is composed of approximately 16,000 planar silicon detector modules, which makes it the biggest of its kind. However, systematic measurement errors, caused by unavoidable inaccuracies in the construction and assembly phase, reduce the precision of the measurements significantly. The geometrical corrections that are therefore required have to be known to an accuracy that is better than the intrinsic resolution of the detector modules. The Kalman Alignment Algorithm is a novel approach to extract a set of alignment constants from a large collection of recorded particle tracks, and is applicable for a system even as big as the CMS Tracker. To show that the method is functional and well understood, and thus suitable for the data-taking period of the CMS experiment, two case studies are presented and discussed here.
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