Biasing the generation of unweighted partonic events at LO

Since v2.5.0, MadGraph5_aMC@NLO can bias the generation of LO unweighted partonic events, using existing or customized biasing weights. This wiki page will cover the details of how to setup and write your own bias function.

The motivation for using a bias function typically falls in one of the following two categories:

• a) Producing smoother distributions for the tail of a particular observable. This means that physical results obtained in presence of the bias will be identical but sampled differently.
• b) One wants to modify the integrand so as to really impact the physical results. This can be useful for a plethora of applications: ad-hoc unitarisation of the matrix elements, merging weights, inclusion of higher order contributions, etc..

Before going into the detail of the usage of the bias module and the instructions for building your customized bias, we present here an example of their use for the case a) above to smoothen the distribution of the jet transverse momentum for the process 'p p > e+ e- j'.

These two plots were both obtained from 10k events, but for the right-hand side one, the matrix element have been biased by the quantity $(\;{p_t(j_1)}/{1000.0}\;)^4$.

These plots can be straight-forwardly reproduced with (you will need to have install MadAnalysis for the plots to be automatically generated)

./bin/mg5_aMC
MG5_aMC> generate p p > e+ e- j
MG5_aMC> launch
MG5_aMC> set bias_module ptj_bias
MG5_aMC> done

Usage of a bias module