Abstract
In this article we describe Professor, a new program for tuning model
parameters of Monte Carlo event generators to experimental data by
parameterising the per-bin generator response to parameter variations and
numerically optimising the parameterised behaviour. Simulated experimental
analysis data is obtained using the Rivet analysis toolkit. This paper presents
the Professor procedure and implementation, illustrated with the application of
the method to tunes of the Pythia 6 event generator to data from the LEP/SLD
and Tevatron experiments. These tunes are substantial improvements on existing
standard choices, and are recommended as base tunes for LHC experiments, to be
themselves systematically improved upon when early LHC data is available.
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