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Monte Carlo Tuning for $e^+e^-to$ Hadrons and Comparison with Unfolded LEP Data

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 نشر من قبل Jennifer Kile
 تاريخ النشر 2017
  مجال البحث
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We perform two tunes of the SHERPA Monte Carlo generator for the generation of $e^+e^-rightarrowmbox{hadrons}$ using the publicly-available LEP analyses in Rivet. In each of these tunes, we generate events at $sqrt{s}=91.25mbox{ GeV}$ using matrix elements for final states containing up to six partons. In the first, LO tune, matrix elements for all final states are generated at leading order; in the second, NLO tune, matrix elements for final states with up to four partons are generated at next-to-leading order using BlackHat, while those for states with five and six partons are generated at leading order. The tunes are accomplished using Professor, and comparisons with unfolded LEP1 and LEP2 data are produced with Rivet. We also compare the data with events generated with KK2f interfaced to PYTHIA using the standard ALEPH tune. We find that both SHERPA samples show improvement relative to KK2f for observables related to four-jet final states, while all three samples produce comparable results for event-shape variables. Overall, the agreement with data is best for the LO tune. We provide our tuning parameters and many data-Monte Carlo comparisons.



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We use the SHERPA Monte Carlo generator to simulate the process $e^+e^-rightarrowmbox{hadrons}$ using matrix elements with up to six partons in the final state. Two samples of SHERPA events are generated. In the LO sample, all final states are genera ted with leading order matrix elements; in the NLO sample, matrix elements for final states with up to four partons are generated at next-to-leading order, while matrix elements for final states with five or six partons are generated at leading order. The resulting samples are then passed through the ALEPH detector simulation. We compare the Monte Carlo samples to each other, to samples generated using the KK2f generator interfaced with PYTHIA, and to the archived ALEPH data at both LEP1 and LEP2 energies. We focus on four-jet observables with particular attention given to dijet masses. The LO and NLO SHERPA samples show significant improvement over the KK2f generation for observables directly related to clustering events into four jets, while maintaining similar performance to KK2f for event-shape variables. We additionally reweight the dijet masses using LEP1 data and find that this greatly improves the agreement between the three Monte Carlo samples at LEP2 energies for these observables.
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