Title :
Developments in MC event generator tuning and systematics
fDate :
Oct. 30 2010-Nov. 6 2010
Abstract :
Activity in tuning of Monte Carlo event generator models to experimental data has been revitalised by the approach and arrival of data in a new energy regime, from the Large Hadron Collider experiments. The state of the art in MC tuning technology is the Professor toolkit, which is fundamentally based on bin-wise parameterisation of computationally intensive MC observables as a function of generator parameters: the parameterisation then acts as a CPU-efficient model of the generator, making tuning amenable to numerical minimisation. In this talk I summarise the Professor method and some of the tuning results obtained in response to LHC data, with an outlook upon the potential of the MC parameterisation method for improved estimation of uncertainties in MC tunes and predictions.
Keywords :
Monte Carlo methods; data analysis; high energy physics instrumentation computing; minimisation; CPU-efficient model; LHC data analysis; Large Hadron Collider experiment; Monte Carlo event generator model; Monte Carlo parameterisation method; Monte Carlo tuning technology; Professor toolkit method; bin-wise parameterisation analysis; energy regime; numerical minimisation; Covariance matrix; Data models; Generators; Large Hadron Collider; Physics; Systematics; Tuning;
Conference_Titel :
Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE
Conference_Location :
Knoxville, TN
Print_ISBN :
978-1-4244-9106-3
DOI :
10.1109/NSSMIC.2010.5873737
