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CU calorimeter study

CU calorimeter study. Toshinori Abe Uriel Nauenberg Joseph Proulx University of Colorado Jan. 9, 2003. Introduction. CU group is interested in developing tile sampling calorimeter for a future linear collider. We propose a new design of the tile calorimeter for energy flow.

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CU calorimeter study

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  1. CU calorimeter study Toshinori Abe Uriel Nauenberg Joseph Proulx University of Colorado Jan. 9, 2003

  2. Introduction • CU group is interested in developing tile sampling calorimeter for a future linear collider. • We propose a new design of the tile calorimeter for energy flow. • In this talk, I will pick up some results from our recent studies of the calorimeter.

  3. Topics of Discussion • Brief description of Energy flow analysis • Effects of position resolution • Design of a tile calorimeter • Position resolution • Summary

  4. Energy flow analysis • Typical idea of energy flow. charged particles  tracker neutral particles  calorimeter • What information can calorimeters provide? Energy important! (jet energy, etc) positionimportant! (jet direction, etc) (direction and longitudinal shower shape) for sampling calorimeter

  5. Energy flow (cont.) • Experience by ALEPH says photon reconstruction is important because: Typical multi-jet event charged particles carry 64% E tracker photons carry 25% EEM cal. neutral hadrons carry 11% EHAD cal. • Excellent position resolution helps to distinguish between charged and neutral clusters.

  6. Effects from position resolution • The position resolution resolution affects the following two parts: (1) Jet direction (p0 separation) (2) Separation between neutral and charged clusters. • In the following slides, I will show how these affects mass reconstruction by reconstructing W mass.

  7. W mass reconstruction (ideal) • I reconstruct W mass using eett events at 500GeV using Fast MC.

  8. W mass reconstruction (cont.) • To check p0 separation effect, I merge neutral clusters concerning the position resolution.

  9. Track cluster matching • Track-cluster association has been done by extrapolating the track to the cluster. The performace is determined by the cluster position resolution.

  10. W mass reconstruction • Track-cluster matching affects mass reconstruction more than jet direction. Ideal case=4.0GeV

  11. Position resolution importance • You see more effect from track-cluster matching than p0 separation. • Hence, current our activities are focused on improving the position resolution more than p0 separation.

  12. Design of calorimeter • W + scintillator • There are half size offsets layer by layer to improve position resolution. • The tile size is about 4×4cm2 at the inner radius (~200cm).

  13. Energy linearity

  14. Energy resolution

  15. Position resolution • Sampling calorimeter gives two measurements. • Simple energy weight + line fitting

  16. sf vs. sj • f gives better resolution than j. So we will use f. (But j is important to GMSB)

  17. Shower starting or max.? • Which defined position gives better resolution, shower starting point or max. point? • It looks shower starting point gives better resolution for hadron particles…

  18. Position resolution • For EM showers, the position at shower max. gives better position resolution.

  19. Benefit of CU geometry • CU design gives better resolution than normal design.

  20. More improvement • We could get more precise position resolution as follows: • Correct the systematic from energy weight method. • Assume particles come from IP (i.e. IP constraint) • These works are done by Joseph Proulx.

  21. Systematic from energy weight

  22. After the correction • No offset geometry shows strong position dependence in the resolution. CU geometry also helps to reduce the systematic further.

  23. Current best achievement 0.7mm resolution!

  24. Summary • We have studied CU designed calorimeter. • CU calorimeter shows better position resolution performance than ordinal tower calorimeter and 0.7mm at high energy is current best achieved value. • More studies • cosmic ray test • KS0p0p0reconstruction • clustering, p0 separation?…

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