# 2016-12-15-tracker-efficiency¶

Chris- 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

s-z cut- 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?