1. E. Devetak – CERN CLIC1 LCFI: vertexing and flavour-tagging Erik Devetak Oxford University CERN-CLIC Meeting 14/05/09 Vertexing Flavour Tagging Charge ID Physics examples Integration into ILD/SiD

2. E. Devetak – CERN CLIC 2 LCFI 1998-2008 ???  Universities participating (2005-2008): Bristol, Edinburgh,Glasgow, Liverpool, Nijmegen, Oxford, RAL AIMS  Develop Vertex detector for ILC: point resolution of 3.5 μm  Develop tools that will exploit the vertex detector (vertexing of secondary, tertiary + flavour tagging)  Perform relevant physics analysis

3. E. Devetak – CERN CLIC 3 The Algorithm 2 different vertexing algorithms implemented (ZVRES, ZVKIN) 14 discriminatory variables 2 different neural networks with different topologies (built in and FANN)  Vertexing of Tracks  Calculation of Discriminating variables  Neural Network using discriminating variables  All Modular  Part of the ILC-Soft Reconstruction Software  Used in both the SiD and ILD detector concepts NIM paper in the process of internal review, package available: http://ilcsoft.desy.de/portal/software_packages/lcfivertex/

4. E. Devetak – CERN CLIC 4 Vertex Finding D. Jackson, NIM A 388 (1997) 247 Implemented by B. Jeffery and LCFI collaboration Probability Tubes Vertex Function  LCFI implemented general ZVRES algorithm:  Represent tracks with Gaussian ´probability tubes´  Calculate vertex function  Search 3D-space for maxima of this function  Combine close-by vertices - resolve ambiguities

5. E. Devetak – CERN CLIC 5 Vertexing - Results  Used sample with CoM = 91.2GeV  Good performance  Also for finding tertiary vertices!  Two Main issues:  One prong Vertices ( one charge track in each vertex!)  Resolving Vertices close to IP

6. E. Devetak – CERN CLIC 6 Tagging Inputs  Really have three set of inputs:  No secondary vertex found (6 inputs)  At least one secondary vertex found (6 inputs)  Always used Joint Probability (2 Inputs)  Joint Probability = Probability all tracks from primary vertex!  For distribution of tracks from IP, use tracks with negative impact parameters.  Calculate probability track has impact parameter significance larger that what reconstructed  Recombine probabilities of all tracks into single value

7. E. Devetak – CERN CLIC 7 Tagging Inputs – no sec. vertex  No secondary vertex found → impact parameters significances  Use two tracks with highest significances in z 0 and d 0 !  But also use momentum of these tracks!

8. E. Devetak – CERN CLIC 8 Tagging Inputs – sec. vertex  Use Vertex information.  Decay length and its significance, momentum of vertex, number of non primary tracks and probability all from same secondary…

9. E. Devetak – CERN CLIC 9 P t Corrected Vertex Mass  Most important parameter (particularly for b tagging)  Calculate vertex mass from charged tracks  Use error matrix of vertices to correct for neutrals

10. E. Devetak – CERN CLIC 10 Combining the Inputs  Data mining problem → many possible techniques  LCFI implemented ad hoc neural network approach.  Trained 9 different networks:  Dependence on number of vertices (1,2,3+)  Definition of signal (b, c, c with b only background)  SiD also tried using FANN package networks  Simpler Method train only 3 networks (b, c, c with b only background)  Always use all Inputs (when available else set to default)  Add 2 Inputs Number of Vertices, Energy of Jet.

11. E. Devetak – CERN CLIC 11 Performance  Performance tested on di-jet events CoM 500 GeV and CoM 91.2GeV  Tested on LDC/ILD and SiD (also with alternative ANN) LDC/ILD 91.2GeV and 500 GeV (SM dijet sample) b c (b-bkgr)‏ c SiD FANN 500 GeV (SM dijet sample)

12. E. Devetak – CERN CLIC 12 Performance -2 c NN output for 1,2,3+ vertex case b tag NN output for 6 jet t-tbar sample  Can look at results for each neural network  Test results for different samples

13. E. Devetak – CERN CLIC 13 Vertex Charge  Package contains also two vertex charge calculation.  Assumption B meson (use all secondary vertices)  Assumption D meson (use only furthest secondary vertex!)  Also tested extension by using more sophisticated reconstructions of many variables; for now  Momentum weighted vertex charge  Momentum weighted jet charge combined in one parameter Combined Charge

14. E. Devetak – CERN CLIC 14 Physics Example – hadronic ttbar  Often used in the SiD and ILD LOIs  In the Hadronic ttbar example used to:  Reject background  Reduce jet combinatorics  B-bbar quark fb assymetry  But also used in:  H→cc  Additional SiD sbottom analysis  Additional ILD ZHH…

15. E. Devetak – CERN CLIC 15 Integration in ILD/SiD framework  LCFIVertex has been fully coded in the Marlin ILD/framework.  Makes use of LCIO data structure  Inherits its dependencies.  But works also with SiD:  Detector geometry independent (well almost need fake file to make the framework happy and change one line of code)  Hence can do Sid Reconstruction up to jet finding and then move to LCFI  But you need to install the whole ILD framework! (many dependencies!)  Analysis done in such way are just as valid!

16. E. Devetak – CERN CLIC 16 Conclusion  Presented the LCFI Vertex package. Capabilities:  Vertexing  Flavour Tagging  Charge reconstruction  Showed performance and usage in ILD and SiD Detector!  Flexible and easy to use!  LCIO allows for easy usage of software of both detector concepts!  Gave examples of why it can be a very useful tool!  Physics studies! (very varied) Ready to be used… should also be easy! NIM paper has been submitted for review.

17. E. Devetak – CERN CLIC 17 LINKS on How-To presentations: http://ilcagenda.linearcollider.org/materialDisplay.py?contribId=53&sessi onId=20&materialId=slides&confId=1446 Class Structure -Vertexing Flavour Tagging Discriminants http://ilcagenda.linearcollider.org/materialDisplay.py?contribId=56&sessi onId=20&materialId=slides&confId=1446 Flavour Tagging http://ilcagenda.linearcollider.org/materialDisplay.py?contribId=57&sessi onId=20&materialId=slides&confId=1446

18. E. Devetak – CERN CLIC 18 Other LINKS: Manual (most up to date really) Download (here find also information on other ILD packages LCFI Depends on. Note ilcinstall this should install everything for you) http://ilcsoft.desy.de/portal/software_packages/ http://ilcsoft.desy.de/portal/e14/e17/e18/infoboxContent324/LCFIVertex-v00- 03-refman.pdf

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