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Elastic Data Analysis

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Elastic Data Analysis. Jorge Molina. CBPF. PID Meeting 06/Feb/2003. EVENT SELECTION ... Must exist 3 reconstructed segments per. detector, ie all 6 segments ... – PowerPoint PPT presentation

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Title: Elastic Data Analysis


1
Elastic Data Analysis
Jorge Molina
CBPF
PID Meeting 06/Feb/2003
2
EVENT SELECTION
  • Cuts in multiplicity are made requiring
  • One or zero hits in each of 12 planes
  • (6 x detector)
  • Must exist 3 reconstructed segments per

  • detector, ie all 6 segments must be nonzero
  • The values of x and y are calculated with ideal
  • positions of the segments (J. Barreto method)
  • Values of x accepted if the difference between
  • x_uv and x_seg is less than 0.5 mm (tough
  • condition)

3
Hitmap of events for runs at Operational position
Beam position
17.1 mm (9 sigmas)
P1D Detector
Beam position
13.8 mm (9 sigmas)
P2D Detector
4
Hitmap of events for runs at 4 mm off from
Operational position
Beam position
21.1 mm
P1D Detector
Beam position
17.8 mm
P2D Detector
5
RECONSTRUCTED xi VALUES
The reconstructed xi values for runs 132-188 at
operational positions
PRELIMINARY!
6
RECONSTRUCTED t VALUES
Data behaves according to theory in the t range
covered by the FPD detector.
PRELIMINARY!
For elastic events we expect a behavior like
7
MONTE CARLO
Simulation of elastic events for pots at
operational positions
8
Another view of MC elastic events (13k), taking
as reference the beam line
Beam position
17.1 mm (8.98 sigmas)
Beam position
13.8 mm (8.70 sigmas)
9
Nexts Steps
1. Resolution studies 2. Acceptance
studies 3. Efficiency of fibers 4. MC of
elastic events --gt In progress 5. dN/dt
Plots --gt estimated for march
Need the mapping file
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