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| | 3 | === Definition === |
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| | 5 | In general, the probability that an event is accepted depends on the characteristics of the measured event, and not on the process that produced it. The measured probability density %$\bar{P}(x,\alpha)$% can be related to the produced probability density %$P(x,\alpha)$%: %\[\bar{P}(x,\alpha)=Acc(x) P(x,\alpha)\]% where %$ Acc(x)$% is the detector acceptance, which depends only on %$ x $% |
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| | 7 | In the computation of the likelihood of the MatrixElement, this acceptance term induce the following term: %\[\int Acc(x) P(x,\alpha)dx\]% |
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| | 9 | This could be estimated easily, by MC, as the number of accepted events on the number of generated events. %\[\frac{N_{accepted}}{N_{generated}}\]% |
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| | 11 | === How to compute Acceptance term with pythia/PGS. === |
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| | 13 | WARNING: This module is in devellopment. This module is (not yet) on any official distribution. |
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| | 15 | 1. In order to have the computation of the acceptance term in MW you have to put in the MadWeight_card.dat the following option |
| | 16 | {{{ |
| | 17 | Block MW_Run |
| | 18 | 4. T # normalizes weight (1/sigma prefactor) |
| | 19 | acceptance_run T # computes the acceptance term}}} |
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| | 21 | -- Main.OlivierMattelaer - 22 May 2009 |
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