Tools for optimising and assessing the performance of the vertex detector

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

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

3. 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 q)

4. 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. Current status cont’d • LCFI proposed independent development of full GEANT4-based description • of processes in vertex detector sensors and readout chain to UK funding agencies • (see also 59th DESY-PRC, May 05) • while such an approach is in principle appreciated, the currentfunding 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

6. 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-rightforward-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. 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. 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. 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 • http://www.phy.bris.ac.uk/research/pppages/DaveB/NeuralNet.tar.gz

10. Vertex charge reconstruction studied in using SGV framework Vertex charge reconstruction 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 ECM = 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. performance for c-tag 0.2 b-jet mis-tag probability 0.1 0 0.30 0.44 c-tag efficiency 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% blue: use only secondary vertex parameters magenta: also use primary vertex momentum

12. Plans for Snowmass • presentation of results onvertex charge reconstruction over range of ECM 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. Additional Material

14. 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 Qsum (charge), PTvtx (transverse momentum), Mvtx (mass) • vertex charge • Pt-corrected massused as b-tag parameter Vertex charge reconstruction Additional Material ~ Additional Material ~ Additional Material Additional Material ~ Additional Material ~ Additional Material

15. Lmin ~ 6mm for D ~ 30 mm Changes since LCWS 2004 • between LCWS04 and ECFA workshop (Durham) : • optimised cut on L/D, masked KS and L • 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) Additional Material ~ Additional Material ~ Additional Material Additional Material ~ Additional Material ~ Additional Material an atypical event with a large distance of the seed vertex from the IP

16. Improvement of reconstructed vertex charge Additional Material ~ Additional Material ~ Additional Material Additional Material ~ Additional Material ~ Additional Material