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TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 0 LCFI Vertex Package: Parameter Optimisation Sonja Hillert (Oxford) on behalf of the.

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Presentation on theme: "TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 0 LCFI Vertex Package: Parameter Optimisation Sonja Hillert (Oxford) on behalf of the."— Presentation transcript:

1 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 0 LCFI Vertex Package: Parameter Optimisation Sonja Hillert (Oxford) on behalf of the LCFI collaboration TILC08 Joint ACFA Physics and Detector Workshop and GDE meeting on the International Linear Collider 3 – 7 March 2008  Introduction  Track selection for full MC and reconstruction  Status of parameter tuning  Quark charge quality indicator

2 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 1 interface SGV to internal format interface LCIO to internal format input to LCFI Vertex Package output of LCFI Vertex Package interface internal format to SGV interface internal format to LCIO ZVRESZVKIN ZVTOP: vertex information track attachment assuming c jet track attachment assuming b jet track attachment for flavour tag find vertex- dependent flavour tag inputs find vertex charge find vertex- independent flavour tag inputs neural net flavour tag

3 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 2 Preparation for mass reconstruction - overview  ensure compatibility of LDCtracking, PandoraPFA, LCFIVertex  check LCFI code runs without problems with the new detector models (VXD03, VXD04, new SiLC detectors when available)  implementation of correction procedures based on reconstructed information: photon conversions K S and  decay tracks hadronic interactions  parameter tuning with full MC and reconstruction: optimise track selection for ZVRES and IP-fit based tune ZVRES parameters optimise track selection for flavour tag tune flavour tag parameters, in particular: parameters for joint probability calculation  training of new neural nets using full MC, reconstruction and optimised code parameters DONE ONGOING FIRST RESULTS IN PREPARATION Clare Lynch (Bristol) Roberval Walsh (Edinburgh) Kristian Harder (RAL) Roberval Walsh (Edinburgh) K Harder et al. (RAL)

4 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 3 b c (b-bkgr) c FullLDCTracking, LDC01_05Sc open: Wolf PFA full: PandoraPFA, different steering c c (b-bkgr) b open: Wolf PFA full: PandoraPFA FullLDCTracking, LDC01_05Sc Compatibility with other packages  The initial result (left, ILD optimisation meeting 30 th January) seemed to indicate worse flavour tag performance with PandoraPFA input than with Wolf input  This was traced back to differences in the FullLDCTracking steering  Using same tracking settings, performance is in excellent agreement  Mark Thomson has checked that PFA performance is not affected (ILD mtg 13 th Feb) Kristian Harder, Talini Pinto Jayawardena (RAL)

5 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 4 Correction procedures (conversions, K S,  ) open: photon conversions, uncorrected full: photon conversions off c c (b-bkgr) b track cheater, Wolf  during validation of LCFI code, photon conversions switched off at GEANT-level  Central switch that also affects CAL showers  NOT VIABLE FOR MASS PRODUCTION  so far, K S and  decay tracks removed using MC information  2 new Marlin processors in preparation (Kristian Harder, RAL): standalone conversion / V0 tagger performance analysis for standalone tagger

6 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 5 Conversion tagger performance analysis : first results New processor to monitor performance  scans all MCParticle collections for actual conversions/V0  scans all Track collections for matching reconstructed tracks  scans all ReconstructedParticle collections for matching objects: either individual track objects or composite objects involving conversion/V0 tracks  output mostly in the form of tables + a few histograms: looks reasonable radius of MC V0 (pure 5GeV K S 0 sample) (Kristian Harder, RAL)

7 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 6 Parameter tuning: approach  A lot of progress has been made preparing this complex study (Roberval Walsh): ensured MarlinReco runs on Edinburgh cluster (1400 nodes, 64-bit machines) and gives reasonable results (runs 3 times faster than on local machine) main criterion for optimisation of parameters: flavour tag performance in terms of purity vs efficiency; parameters varied one at a time & performance evaluated scripts written and checked to automatically vary parameters under study in steering files First results obtained for track selection for IP fit Production of a training sample for flavour tag NN’s underway on the GRID: Many thanks to the DESY-group!

8 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 7 Example: effect of varying track  2 /ndf cut for IPfit snapshot of current status – very preliminary! b c c (b-bkgr)

9 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 8  improvement to calculation of one of the inputs for the flavour tag-NN:  probability that a track from primary vertex has impact parameter significance > b/  b is  the symmetric function needs to be obtained from a fit of the negative side of the impact parameter distribution (done separately for R-  and z);  current version of LCFI Vertex uses hard coded parameterisation obtained from fast MC  Erik Devetak implemented and tested a module to obtain parameters properly from a fit Flavour tag: parameters for joint probability

10 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 9 Fit macro for joint probability calculation: results parameters for R  joint probability previousnew 1.0131.015 0.0250.280 0.1020.561 0.0410.006 0.0160.048 parameters for Z joint probability previousnew 1.0161.043 0.0270.271 0.0950.468 0.0410.006 0.0150.048 open: previous joint probability parameters full: new parameters using FullLDCTracking, LDC01_05Sc c c (b-bkgr) b Obtained new values with full MC & reconstruction (left): values change as expected, flavour tag performance stable. Erik Devetak, Talini Pinto Jayawardena, Kristian Harder

11 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 10 Quark charge quality indicator: motivation  Idea: find a quality indicator for the quark charge – similar to the flavour tag: The higher the value of the quality indicator, the more likely the quark charge has been correctly reconstructed  In analyses, this could be used as a kind of “quark charge tag”: to resolve ambiguities in events with 2 or more b-jets where results are ambiguous (e.g. events with 2 b-jets both with same reconstructed quark charge, or for events with 4 b-jets, where one knows quark charge is wrong for >= 1 jet(s) ) to improve the event selection, yielding a sample with better quark charge purity  I had a first look at the possibilities for this with SGV (need a lot of statistics!): simple quality indicator defined studied resulting improvement in quark charge selection for 2-jet events (Z-peak)

12 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 11 Approach  For initial study, obtain quark charge purity as function of a number of sensitive variables (histogram correctly & wrongly found quark charge, calculate bin-wise correct/total)  Distributions look considerably different for two- and three (or more) vertex jets  Need to do this separately for the two categories (as for flavour tag)  For each jet within jet-selection cuts, calculate a quality estimator as follows: multiply individual purities  (v i ) for each of the input variables v i : Q quark -tag =  i = 1..n  (v i )  For sample of two-jet events at the Z-peak, find quark charge leakage rate, q = N(Q q wrong) / N(jets in sample) for the usual quark charge reconstruction and an improved procedure (details later)

13 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 12 Input variables used  As input variables used some of the flavour tag variables, namely: decay length and decay length significance of most significant vertex, M Pt seed vertex momentum sum of number of tracks in all non-primary vertices  Further variables included (should be specifically sensitive to vertex & quark charge quality) : : average of L/D value for all tracks assigned to decay chain (L/D) max, (L/D) min : maximum and minimum values of L/D of assigned tracks (L/D) max – (L/D) min : average T variable (measure of transverse distance of track from seed axis) T max, T min : maximum and minimum values of T for assigned tracks T max – T min

14 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 13 Example input: average L/D  shown are the distributions and resulting quark charge purity for the 2 vertex case Q q correctQ q wrong

15 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 14 Improved quark charge determination for 2-jet events  Example how this can be used to improve quark charge in 2-jet events: for jets with vertex charge 0, can use information from other jet, if good quality (see cut above) if same reconstructed quark charge is found for both jets, use the one with higher quality estimate, after subtracting an offset taking into account that the 2-vertex and the 3-vertex distribution peak at different values 2 vertex jets Q q wrong Q q correct 3 vertex jets Q q correct Q q wrong

16 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 15 Results from improved correction procedure raw Q q correctraw Q q wrongmodified Q q correct modified Q q wrong opposite sign~ 1237002674~ 1237002674 this jet 00~180500~ 1120007861 other jet 0~ 210300~ 23100~ 210300~ 23100 clash~25300 ~34400~16100  For clash category: before comparing quality estimators, subtract 0.35 for jets with 2-vertices, 0.28 for jets with 3 or more vertices raw Q q modified Q q opposite sign2.1 % this jet 0100 %6.6 % other jet 09.9 % clash38.0 %25.3 % ~ 60600 “this jet 0” jets discarded increase in efficiency by 30% resulting quark leakage for entire (new selection) sample: 8.2% Next step: train NN with SGV, implement NN-based Marlin processor using this net

17 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 16 Summary  LCFI Vertex package works reliably with both Wolf and PandoraPFA;  Performance with new vertex detector geometries VXD03, VXD04 being checked  Correction procedures for photon conversions, K S and  decay tracks and hadronic interactions being implemented, first results look promising  Preparation for code parameter tuning making good progress: semi-automatic scripts written, samples generated for retraining of neural networks with full MC & reconstruction  Quark charge “tag” permits improvement of quark charge sign selection: Simple quark charge quality indicator implemented and tested using 2-jet events at the Z-peak At a b-tag efficiency of 70%, by combining information from both jets in the event can increase efficiency by 30% and achieve quark charge leakage of 8.2% (i.e. 1.6 % less than with standard procedure); neural net-based approach to be implemented in Marlin shortly

18 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 17 Additional Material

19 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 18 Diagnostic features Purity of reconstructed track-vertex association (%) MC track Reconstructed track-vertex association origin Two-vertex case Three-vertex case Pri. Sec. Iso. Pri. Sec. Ter. Iso. Primary 90.5 1.61 27.7 97.2 4.66 2.43 46.5 B decay 7.2 48.6 35.1 1.91 74.9 9.99 24.5 D decay 2.28 49.8 37.2 0.935 20.5 87.6 29 All above 47.3 41 11.7 36.8 32.2 24.9 6.07 Diagnostic plots and tables will permit us to choose package parameters that are tuned to full MC and reconstruction and will be used in the “central reconstruction” of MC samples for ILD optimisation.

20 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 19 Vertex charge reconstruction  b-jets contain a complex decay chain, from which the charge has to be found  in the 40% of cases where b quark hadronises to charged B-hadron, quark sign can be determined by vertex charge  need to find all stable tracks from B decay chain: define seed axis cut on L/D (normalised distance between IP and projection of track POCA onto seed axis) tracks that form vertices other than IP are assigned regardless of their L/D  need vertex finding as prerequisite (definition of seed axis)  in most analyses, only calculate charge for jet of specific flavour: need flavour tagging  probability of mis-reconstructing vertex charge is small for both charged and neutral cases

21 TILC08 workshop, Sendai 4 th March 2008Sonja Hillert (Oxford) p. 20 D. Jackson, ZVTOP seminar talk 2004 TwoTrackCut TrackTrimCut ResolverCut

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