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Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 0 Tools for optimising and assessing the performance of the vertex.

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Presentation on theme: "Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 0 Tools for optimising and assessing the performance of the vertex."— Presentation transcript:

1 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 0 Tools for optimising and assessing the performance of the vertex detector Sonja Hillert (Oxford) on behalf of the LCFI collaboration Simulation Software Meeting DESY, 27 / 28 June 2005 from MIPS to physics high-level reconstruction tools outlook: plans for Snowmass

2 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 1 Typical event processing at the ILC reconstruction of tracks, CAL-cells energy flow objects first order jet finding b-jets c-jets uds-jets gluon-jets tune track-jet association for tracks from SV or TV contained in neighbouring jet associate with parent jet in some cases; tag some as c-cbar or b-bbar classify B as charged or neutral classify D as charged or neutral charged B charged D neutral B neutral D charge dipole, protons, charged kaons or leptons from SV, TV charged kaons or leptons b bbar b c cbar c bbar flavour identification

3 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 2 From MIPS to physics To optimise design of vertex detector and evaluate its physics performance need: 1) sufficiently accurate reconstruction (from MIPS to tracks) 2) high-level reconstruction tools, e.g. flavour tagging, vertex charge reconstruction, … (see previous page) 3) study of benchmark physics channels based on these tools Step 1 comprises, e.g., simulation of : signals from the sensors: charge generation/collection, multiple scattering data sparsification: signal & background hit densities, edge of acceptance Other parameters to be determined from the results obtained with the entire chain: overall detector design: radial positions (inner radius!) and length of detector layers, arrangement of sensors in layers, overlap of barrel staves (alignment), strength of B-field material budget: beam pipe, sensors, electronics, support structure (material at large cos )

4 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 3 Current status so far focused on high-level reconstruction tools (in particular flavour-tag, vertex charge) using mainly fast MC simulation SGV and (for part of the studies) JAS3; SGV: core of the program well tested ( DELPHI), allows fast change of geometry lacks: accurate description of processes in sensors & readout chain, and of multiple scattering JAS3: full MC under development, but not ready / robust for the time being; tracking used in the fast MC available under JAS3 less precise than SGV (SGV: Billoir algorithm)

5 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 4 LCFI proposed independent development of full GEANT4-based description of processes in vertex detector sensors and readout chain to UK funding agencies (see also 59 th DESY-PRC, May 05) while such an approach is in principle appreciated, the current funding situation in the UK does not allow an effort in this field at the level needed to implement the full MIPS to physics programme looking for ideas how to form international effort to develop the essential simulation and reconstruction tools Current status contd

6 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 5 Future plans future programme will depend on further negotiations – outline of plans preliminary! envisage top-down approach: select physics channels requiring variety of higher level reconstruction tools; develop/improve and assess those in parallel processes to be studied (both requiring flavour tagging, vertex charge reconstruction): Higgs self-coupling: might profit from improving track-jet association using vertex information Left-right forward-backward asymmetry in e+e- b bbar, c cbar: sensitive to polar angle dependence, decays outside the vertex detector (at high energy), could be used to assess performance of charge dipole reconstruction (yielding quark charge measurement for neutral hadrons) use these processes as benchmarks to determine sensitivity to detector design parameters on a timescale of ~ 2-3 years

7 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 6 Visualisation tools Purpose: flavour tagging & vertex charge reconstruction can be improved by looking at cases, where the reconstruction fails, on an event by event basis top: written in Python with Coin/HEPVis wrappers; input read from XML file (D. Bailey) right: root-based tool; so far MC tracks only; reconstruction level to be added (B Jeffery)

8 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 7 OO reference version of ZVTOP ZVTOP in use for ~10 years, several versions (SLD LEP ILC … variable transformations; differences in what is included in the different versions) LCFI therefore decided to develop an object oriented (C++) version of ZVTOP, and to check it against the SLD code (a Java-based version is being developed at SLAC) latest version of ZVTOP (ZVTOP3) comprises two branches: ´ZVRES´ and ´ZVKIN´ (also known as the ´ghost track algorithm´) ghost track algorithm should: cope with cases with a 1-prong B decay followed by a 1-prong D decay allow reconstruction of the charge dipole (information on neutral B´s) at the ILC: improve flavour tagging capabilities development of the class structure in progress; estimated timescale for development and verification: ~ 1 year

9 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 8 Neural Network Tool neural nets used for flavour tagging, vertex charge reconstruction, … C++ based code developed in Bristol allows implementation of feed-forward nets of arbitrary topologies: 3 response functions available: sigmoid, tansigmoid, linear, can be combined (i.e. different neurons in same net can have different response functions) 4 training algorithms: 3 based on back-propagation, 1 genetic algorithm networks generated with this tool can be serialised as plain text or in XML format for retrieval from a web server tar-file available at

10 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 9 Vertex charge reconstruction Vertex charge reconstruction studied in using SGV framework Procedure: find vertices and vertex axis (ZVTOP) assign tracks to B decay chain & sum their charge: can either use a neural net or assign all tracks found in inner vertices (methods work equally well at E CM = 200 GeV) Status: extending study to range of centre of mass energies: larger fraction of B hadrons decay outside vertex detector find steep drop in 2D seed vertex decay length at the vertex detector edge drop of efficiency indications that this is due to faulty track selection Plans: extend study to ccbar events, combine with flavour tagging

11 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 10 Flavour tagging Study e + e - qqbar events (all flavours except for ttbar), so far using JAS3 framework neural net used for flavour tagging: including the primary vertex momentum (left) as input variable, in addition to secondary vertex parameters, improves b/c jet separation by 10% performance for c-tag c-tag efficiency b-jet mis-tag probability blue: use only secondary vertex parameters magenta: also use primary vertex momentum

12 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 11 Plans for Snowmass presentation of results on vertex charge reconstruction over range of E CM values comparison of SiD detector concept and formerly European concept in terms of vertex charge reconstruction using SGV ; in particular look at performance at edge of polar angle range, where difference between the detectors is expected (SiD vertex detector includes forward disks, LCFI-detector does not)

13 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 12 Additional Material

14 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 13 Vertex charge reconstruction Vertex charge reconstruction studied in at, select two-jet events with jets back-to-back, contained in detector acceptance need to find all stable B decay chain tracks – procedure: run vertex finder ZVTOP: the vertex furthest away from the IP (seed) allows to define a vertex axis reduce number of degrees of freedom cut on L/D, optimised for detector configuration under study, used to assign tracks to the B decay chain by summing over these tracks obtain Q sum (charge), P T vtx (transverse momentum), M vtx (mass) vertex charge Pt-corrected mass used as b-tag parameter Additional Material ~ Additional Material ~ Additional Material

15 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 14 Additional Material ~ Additional Material ~ Additional Material Changes since LCWS 2004 between LCWS04 and ECFA workshop (Durham) : optimised cut on L/D, masked K S and dropped ISR while studying vertex charge reconstruction for fixed jet energy (otherwise lose ~ 85% of generated events through back-to-back cut on jets) include information from inner vertices: seed vertex is ZVTOP vertex furthest from IP; assigning tracks contained in inner vertices to B decay chain regardless of their L/D value improves vertex charge reconstruction (for large distances of seed vertex from IP, L/D cut is much larger than required to remove IP tracks) L min ~ 6mm for D ~ 30 mm an atypical event with a large distance of the seed vertex from the IP

16 Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 15 Improvement of reconstructed vertex charge Additional Material ~ Additional Material ~ Additional Material


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