Application to VELO |
1. VELO Residuals |
2. Problem & Strategy |
3. Internal Alignment |
4. Box Alignment |
5. Software Description |
6. How To Create Misaligned Events ? |
7. How To Use The Software ? |
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Application to the VELO
2. VELO algorithm (Part III)
D. Global Alignment (STEP 2)
D1. Introduction
At the end of Step 1, the VELO halves are internally aligned. Boxes offsets and tilts are still to be determined. Classic tracks become useless to perform this task, as we now need parameters involving both parts of the VELO.D2. Using the primary vertex: definitions
The idea is to use again Millepede, so a generalized least square minimization, we will just fit primary vertices instead of track parameters. During Step 1, we use the coordinates (Xi,Yi,Zi) in order to fit global and local parameters. In Step 2, we use the tracks parameters as the coordinates, in order to determine the primary vertex corrdinates (Vx,Vy,Vz): The track parameters are corrected from the individual misalignments di', and the remaining global parameters are just the one we are looking for (ie the global offsets and tilts).D3. Using the overlap tracks: definitions
Once again we will try to use Millepede here, but it's even more simpler than with primary vertices. Idea is to fit overlaping tracks as we are fitting the classic ones. The only difference is that those tracks are corrected from internal misalignments, and the only misalignment are the one between the two boxes. So at the end of the day, we measure the offsets and tilts of one box w.r.t.the other one, i.e. only 6 constants.D4. Step 2 results with minimum bias and particle gun events
Results presented here have been obtained via the same code and datasets than the ones used for internal alignment studies. To only difference is the adjunction of 20000 ParticleGun events to each datasets: charged pions (1.0<P<30GeV/c) shooted over the whole VELO sensitive area.D4.1 Primary vertices only
The primary vertex selection prior to the Millepede fit is largely based on LHCb PrimVtxFinder.cpp method. We first look for vertex seeds on the Z axis, then a vertex candidate is fitted, outlying tracks are rejected if necessary, and if the candidate satisfies the selection criteria, it is feed into Millepede. This is a constrained fit, as we expect all the primary vertices to come from the same (X,Y) position. However, it should be noticed that this (X,Y) position hasn't to be known.D4.2 Overlapping tracks
Using the overlapping tracks, one didn't get the boxes position w.r.t. the beam, but the position of one box w.r.t. the other. Indeed left box is fixed and we move only the right one. The results obtained via this process are shown on Fig.2, once again for both tilts and offsets.D4.3 Improvment of the PV method
In order to suppress the bias seen on Fig.1, the idea is to run in parallel PV and overlap techniques, and applying some very simple constraint equations linking the two method. Results obtained in this case are shown on Fig.3. In particular, the resolution plots show that using the constraints not only improves the resolution of the absolute box positions w.r.t. the beam (O(10%) improvment), but also provides a good correction for all the parameters (chi-square of the distributions is much better), thus removing the outliers.