Abstract
LHCb will commence data taking as the first dedicated heavy flavour experiment at a hadron collider in 2008. A very high hit precision from its vertex detector (vertex locator, VELO) is essential to meet the tight requirements of vertex reconstruction in B-physics. The single hit precision of the VELO is better than 10 μ m . However, the VELO is operated only 8 mm from the beam and must be retracted and reinserted each LHC fill. Hence, the detector places unique demands on its alignment algorithm. The partially assembled VELO system has already been tested in a beam test. The novel software alignment methods are presented together with their interplay with the metrology measurements. Results from Monte Carlo simulation studies are discussed and recent beam test results are shown that prove the method's precision at the micron level.
Highlights
Residuals tell the difference between an ideal world and reality Alignment should bring the two worlds as close together as possible ⇒ Minimise residuals!
Conclusion y x φ=−90 o φ=90 o positive residual positive residual negative residual unbiased track fit hit on sensor φ=−90 o φ=90 o negative residual positive residual negative residual unbiased track fit hit on sensor
VELO software alignment is fully implemented and tested 3 stages to align the VELO system ⇒ using residual distributions/ Millepede Precision at micron level ⇒ well below detector resolution Excellent agreement with metrology Ready for first beam
Summary
While detectors are becoming ever bigger the first hits have to have a resolution on the micron level!. A knowledge of the position of these detectors to a precision better than their resolution is vital. This information can come from: Metrology (only before data taking) Hardware alignment (e.g. optical systems) Track based software alignment. For a vertex detector only software alignment provides necessary precision during operation. Tracker misalignment deteriorates track resolution with impact on measurements of Lifetime Impact parameter Momentum, and mass Impact on tracking itself, on trigger and event yield. Residuals tell the difference between an ideal world (track fit) and reality (hit on a misaligned detector) Alignment should bring the two worlds as close together as possible ⇒ Minimise residuals!
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