tools for optimising and assessing the performance of the vertex detector

Sonja Hillert, University of Oxford Simulation Software Meeting ~ DESY 28 June 2005 p. 1

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


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

cbar

bbar

flavour

identification


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 )


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)


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 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 cont’d


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


Visualisation toolsPurpose: 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)


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


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


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 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


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-j

et

mis

-ta

g p

rob

ab

ilit

y

0

0.1

0.2

0.440.30

blue: use only secondary vertex parameters

magenta: also use primary vertex momentum


Plans for Snowmass

presentation of results on vertex 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)


Additional Material


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 Qsum (charge), PTvtx (transverse momentum), Mvtx (mass)

vertex charge

Pt-corrected mass used as b-tag parameter

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Changes since LCWS 2004

between LCWS04 and ECFA workshop (Durham) :

optimised cut on L/D, masked KS 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)

Lmin ~ 6mm for D ~ 30 mm

an atypical event

with a large distance of

the seed vertex from the IP


Improvement of reconstructed vertex chargeA

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tools for optimising and assessing the performance of the vertex detector

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