gTau
results at D0h
Anne-Catherine
Le Bihan
Abstract:
Efficient and discriminating identification of tau lepton
is essential
for many measurements and searches of the D0 analysis
program.
A set of neural networks has been developed in order
to identify taus
in their
hadronic modes. The neutral network
technique uses
as input variables describing the narrowness, isolation
and transverse energy deposit of tau jets in comparison
to QCD jets,
and the fact that tau decay products have less associated
charged tracks
and a small number of neutral particles. This identification method has been
used in the measurement of Z -> ΡΡ -> ΡhadrΚ cross
section
as well as in searches for supersymmetric particles,
leading to e + e + tau final states.
These topologies are expected to arise if R-parity is
violated
and the lightest neutralino is allowed to decay through
Ι133 coupling.
Preliminary limits have been set on this susy scenario.