2016-12-15-tracker-efficiency¶

• looking at geometry issues
• performed cycloidal track fit - results uploaded to the wiki page; no obvious misalignment (few mrad which is probably compatible with bias in calculation)
• looked at space point residuals - results uploaded to the wiki page; no big residual which might indicate a misalignment
• no evidence of a misalignment

Ed

• nturns algorithm assesses the number of turns; gives "real phi"
• s is the "real phi"*radius
• then fit straight line to s
• Apply chi2 cut to determine if it is a good track
• for each station, plot residual between fitted s and measured s
• plot that against s length (which is helix radius times azimuthal change in angle for entire radius)
• expect mean of 0 with 1 mm RMS
• getting RMS ~ 10s mm
• Proposed actions:
  • check vs MC; if we see it in MC it is algorithmic; if we see it in data, it is some combination of algorithm and data
  • Check for correlations between circle fit errors and s-z fit errors (are errors in circle fit pulling the s-z fit out?)
  • put a series of counters in to see where the fit fails

• n_turns algorithm; there is a std::vector<>::push_back() and a std::vector<>[index] before the push_back(); so attempt to dereference an unallocated vector element.
• Proposed action: keep digging and writing unit tests

• TKU, TKD is okay(ish) in MC
• TKU is okay(ish) in data
• TKD is bad in data
• Either:
  • Uncorrelated Noise/dead channels
  • Alignment
  • Correlated noise
• Discussion of how noise can create inefficiency
  • Assertion that uncorrelated noise should not create sufficient inefficiency
  • Circle fit has too generous road cut, includes noise and pulls off radius; which effects the s-z fit?