Mattione Update 10312011

Procedure

• Reconstruct π(1600) -> b1π events with t-slope = 2.0 (was 5.0 for X(2000)) using both the 334 and 1234 segmentations
• Plot Δβ vs p for π⁺ candidates to see proton, π⁺ separation.

Details

• The 1234 segmentation is not available in the HDGEANT simulation, so the BCAL shower time for the 1234 segmentation was smeared manually during reconstruction
  • 1234: The BCAL hit-time smear was disabled in mc_smear
  • 1234: The shower time was smeared by: σ_smear = sqrt(σ²_{t_334} - σ²_{t_334_NoSmear}) * σ_{t_1234} / σ_{t_334}
• Fit David's γ σ_t Improvement: Make dE, θ map
• Fit the π^- & proton BCAL shower σ_t vs θ distributions in dE bins:
  • Both the non-smeared and smeared

will apply improvement % to these resolutions.

• Generate, simulate, smear, and reconstruct π(1600) -> b1π events with t-slope = 2.0 (was 5.0 for X(2000))
  • For 1234 Segmentation, disabled BCAL hit t-smear in mc_smear, smeared reconstructed shower time as a function of dE & &theta during reconstruction to reach improved resolution.
    • Proton, π⁺'s, π^-'s all smeared the same.

David's BCAL Photon Time Resolution Studies

• γ BCAL σ_t vs. dE (GeV):

Time Resolution Segmentation Ratio

• γ BCAL σ_{t_1234} / σ_{t_334} vs. dE (GeV):

• Fits to γ BCAL σ_{t_1234} / σ_{t_334} vs. θ in dE bins:
• Don't trust fits at low-θ, so linearly-interpolate between 12 and 16 degrees.

BCAL π^- 334 Segmentation σ_t Fits

• BCAL π^- 334 Segmentation σ_t Fits vs. θ in dE bins:

X(2000) -> b1pi Events, π⁺ BCAL Δβ vs p

Δβ = β_p - β_t = p/sqrt(p*p + m*m) - path/(c*TOF)

• X(2000) -> b1pi Events, π⁺ BCAL Δβ vs p, 334 Segmentation:

• X(2000) -> b1pi Events, π⁺ BCAL Δβ vs p, 1234 Segmentation: