Last update:
Apr 1, 2000
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New Kinematic Fitting Algorithms and Lessons Learned from KWFIT
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Paul Avery
University of Florida
Presented by:
Paul Avery
I discuss new algorithms encoded in the kinematic fitting program KWFIT
and some general lessons learned in applying kinematic fitting to
particle physics data. Though originally written for CLEO use, KWFIT is
a general standalone program.
KWFIT encodes standard constraints involving vertexing, mass, energy,
4-momentum and back-to-back tracks. A powerful capability is its ability
to build "virtual particles" from a set of daughters under a vertex
constraint, taking advantage of an interesting theorem that allows
well-measured tracks, poor tracks and neutrals such as pizeros and
gammas to participate without biasing the resultant track parameters. I
have recently added algorithms to optimally fit for lifetimes using all
track and vertex information and a new algorithm that allows the
lifetime of decays such as $D^0 \to K_s \pi^0$ to be determined.
I also discuss additional information available from kinematic fitting
that, although currently not used, could be used to improve signal to
noise ratios. In addition, the large amount accumulated experience with
KWFIT points to certain lessons about track representation, storage
precision and sensitivity to failures.
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