Status of Flavour tagging tools for CLIC_SiD

1. Status of Flavour tagging tools for CLIC_SiD Tomas Lastovicka (FZU AV CZ, Prague) LCD software readiness meeting CERN 26/09/2010

2. Outlook • LCFI Package • Updates and Recent Work • Future Plans

3. LCFI Jet Flavour Tag Package • Used for jet flavour tagging and secondary vertex reconstruction. • Topological vertex finder ZVRES. • Standard LCIO input/output • Marlin environment (used for both ILD/SiD) • Flavour tagging based on Neural Nets. • Combine several variables… Probability Tubes Vertex Function

4. NN Input Flavour Discriminating Variables • Currently, there are 14 flavour discriminating variables R- and Rz- significancefor 2 tracks with the highest impact parameter significance in R (“leading tracks”) Relative momenta of the leading tracks (relative to jet energy) Joint Probability in R and Rz Decay length and decay length significance (relative to jet energy) Pt-corrected vertex mass Secondary vertex probability Relative total momentum of non-primary vertex tracks and their number • These inputs are re-normalised and transformed by tanh() - except joint and secondary vertex probabilities. • Tracks/vertices have to pass some minimal selection cuts.

5. NN Input Flavour Discriminating Variables • Inputs are sent to 3 neural networks (8 inputs each) according to the number of secondary vertices found in a given jet • 0 vertices: R-, Rz- significance and momenta for 2 leading tracks Joint Probability (R, Rz) • 1 vertex and >1 vertices: Decay length, decay length significance, pt-corrected vertex mass, Total momentum of non-primary vertex tracks and their number, Joint Probability (R, Rz), Secondary vertex probability • This is not a dogma, inputs can be added/removed • Not that trivial inside the package, requires some coding. • Studies better done outside the package (I fancy FANN package for this purpose).

6. Studies so far • SiD related: • There is a lot of experience with running LCFI from SiD LoI. • LCFI package exists within Marlin environment only • It was not re-written nor wrapped to Java. • LCIO (Linear Collider I/O) turned out to be a very useful framework. • I’ve looked at FastMC Z{uds},c,bevents @ various TeV : light-mistag c-mistag 3 TeV 3 TeV 500 GeV 500 GeV (b-tag efficiency vsmistageff)

7. Studies so far • On ILD HA events from Marco • Fully simulated and reconstructed events (not the latest geometry though) • LCFI tagging variables plots for b-jets. • Not enough statistics for various jet tags to train NN.

8. Recent Software Updates • FANN package interfaced to LCFI directly • Enables faster turn-around. • Great for playing around with various input variables. • FANN nets do not need to be “translated” to LCFI nets. • work on a NN configuration convertor in progress • not a part of the official LCFI release… FANN = Fast Artificial Neural Network - Used for SiD LoI analyses in Oxford

9. Future Plans • There will be h{bB,cC} samples (10k each) available soon (Ch. Grefe) • full simulation and reconstruction • not with the final geometry • to check if all works as supposed with the LCFI package • to optimise/improve the package • to prepare for the light Higgs analysis e+e- eeh  eebB