Items on agenda:

• Started writing the thesis: https://www.overleaf.com/read/hcvqgpxnjqnz#2cd750
• Simulations for different IRs done, always 50 Events. Using this to evaluate NN performance for different IRs: 
  • PbPb: 10, 30, 50 kHz
  • pp: 100, 500, 1000, 1500 kHz
• Current developments:
  • dE/dx tuning:
    • Obtained workflow by Jens. Calibration object being produced and loaded, but no effect on tpcptracks.root observed yet. Investigating.
  • Lambda / K0S reconstruction efficiency:
    • Obtained workflow from Ruben
    • Asked Sandro if it is possible to inject K0S and Lambda into FST simulation (basically add the digits on-top == merge the two simulations): Technically possible, only needs minor development on simulations framework

 Study of NN input size:

• Used currently exisiting training data to extract different "input-grids" (row x pad x time): (1x5x5), (1x7x7), (3x7x7), (5x7x7) and current reference case (7x7x7)
• Used 7x7x7 for classification and only compared effect for changing input to regression network
•  Observations:
  • Smooth behaviour for 2D cases (i.e. 1x5x5 and 1x7x7) at sector boundaries, as expected
  • No reliable momentum vector estimate for 2D, as expected (since 3D charge information is needed)
  • 3x7x7 vs 7x7x7: Phi estimate (= width of Phi distribution) worsens by around 10% across pT, Theta estimate by around 20%. But both distributions well centered across pT for both cases.
  • qTot and dE/dx performance is basically equally as good for 2D as for 3D input. Sigma estimation actually slightly improves for 2D case
  • 1x5x5 vs 1x7x7 (and also 3D): Width of CoG-time estimate at inner radii improves with larger pad-time window (left 1x5x5, right 5x7x7). CoG-pad estimate stays the very similar.

• • Tracking efficiency at very low pT improves for 3D input, but is overall almost identical between both 2D and 3D case

Next steps:

• Small things: Update macro with axis label plotting and add comparison macro for all plots (to plot TGraphs of two QA outputs into one plot)
• Giulio: Get the alidist recipe working fully
• Repeat studies on all interaction rates
• Above mentioned: dE/dx calibration + Lambda-K0S analysis