Speaker
Mr
Edmund Widl
(Institut für Hochenergiephysik (HEPHY Vienna))
Description
The Kalman alignment algorithm (KAA) has been specifically developed to cope with the
demands that arise from the specifications of the CMS Tracker. The algorithmic
concept is based on the Kalman filter formalism and is designed to avoid the
inversion of large matrices.
Most notably, the KAA strikes a balance between conventional global and local
track-based alignment algorithms, by restricting the computation of alignment
parameters not only to alignable objects hit by the same track, but also to all other
alignable objects that are significantly correlated. Nevertheless, this feature also
comes with various trade-offs: Mechanisms are needed that affect which alignable
objects are significantly correlated and keep track of these correlations. Due to the
large amount of alignable objects involved at each update (at least compared to local
alignment algorithms), the time spent for retrieving and writing alignment parameters
as well as the required user memory (RAM) becomes a significant factor.
The full-scale test presented here, i.e., the employment of the KAA to the
(misaligned) CMS Tracker, demonstrates the feasability of the algorithm in a
realistic scenario. It is shown that both the computation time and the amount of
required user memory are within reasonable bounds, given the available computing
resources, and that the obtained results are satisfactory.
| Submitted on behalf of Collaboration (ex, BaBar, ATLAS) | CMS |
|---|
Primary author
Mr
Edmund Widl
(Institut für Hochenergiephysik (HEPHY Vienna))
Co-author
Dr
Rudolf Frühwirth
(Institut für Hochenergiephysik (HEPHY Vienna))
