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{\Large\bf
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Optimal jet clustering algorithms for the measurement of the top quark mass
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J.~D'Hondt and {\underline{J.~Heyninck}} \\

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Vrije Universiteit Brussel,Pleinlaan 2, B-1050 Brussels, Belgium \\

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{\bf   Abstract}
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The top quark occupies not only a peculiar place within the Standard Model,
but also in models beyond the Standard Model. The measurements of its properties
will therefore reveal information about new physics in every possible discovery
scenario. If no new phenomena are observed with the LHC experiment, the
top sector will be the most sensitive domain to look for unexpected deviations from the 
Standard Model predictions. 

To test the correctness of the predictions of the Standard Model 
it is crucial to obtain well estimated predictions, hence to obtain
precise measurements of its free parameters. One of these parameters is the
mass of the top quark, which is currently measured to be 174.3 $\pm$ 5.1 GeV/c$^2$
by the Tevatron Collaborations. The CMS experiment at the Large Hadron Collider aims to
measure the top quark mass with a precision of about 1 GeV/c$^2$ by using the
process $pp \rightarrow t{\bar t} \rightarrow bl\nu {\bar b}q{\bar q'}$.

A key issue to measure the kinematics of this multi-particle final state is to
decide which particles originate from which primary partons. 
An optimal clustering algorithm should cluster the correct particles
into jets aiming for the smallest residual polution of secundary particles which
do not originate from the same primary parton. In practice one aims for an
algorithm which results in the smallest bias on the reconstruced jet energy and 
momentum and the best resolution on these quantities. With Monte Carlo simulation
of the physics process we studied these quantities for several well-known and some
new jet clustering algorithms. A method was designed to identify the optimal algorithm.


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{\em (Contribution for the BPS International Scientific Meeting 2004)}
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