Changes between Version 2 and Version 3 of AcceptanceTerm


Ignore:
Timestamp:
04/12/12 09:30:42 (8 years ago)
Author:
md987
Comment:

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  • AcceptanceTerm

    v2 v3  
    33=== 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 $
     5In 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: %\[\int Acc(x) P(x,\alpha)dx\]%
     7In 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. %\[\frac{N_{accepted}}{N_{generated}}\]%
     9This 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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    1111=== How to compute Acceptance term with pythia/PGS. ===
     
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