# Changes between Version 3 and Version 4 of IntroMatching

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Timestamp:
02/28/13 02:17:22 (7 years ago)
Comment:

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Unmodified
 v3 The dependence to the parton-shower evolution variable is here important. The MLM schemes can be used with both "old" virtuality-ordered showers ( '''MSTP(81)=0 or 1''' in Pythia) and "new" $P_{T}$-ordered showers (( '''MSTP(81)=20 or 21''' in Pythia)), whereas the Shower-$K_{T}$ has been designed only for the latter. * Cone- or $K_{T}$-jet MLM: The final-state partons in an MG/ME event are clustered according to the $K_{T}$-jet algorithm to find the "equivalent parton shower history'' of the event. The Feynman diagram information from !MadGraph is used to allow only clusterings that correspond to diagrams existing in the generated matrix element. For the cone jet algorithm, a minimum $P_T$ and $\Delta R$ must be defined for all partons. For the $K_T$ scheme, the smallest $K_{T}$ value is restricted to be above the cutoff scale "xqcut". In order to closely mimic the behaviour of the parton shower, the $K_{T}$ value for each clustering vertex corresponding to a QCD emission is used as renormalization scale for $\alpha_{s}$ in that vertex. As factorization scale, as well as renormalization scale for the central hard $2\to1$ or $2\to2$ process, the transverse mass $m_{T}^2 = P_{T}^2 + m^2$ of the particle(s) produced in the central process is used. This event is then passed to Pythia for parton showering. After showering, but before hadronization and decays, the final-state partons are clustered into jets; for the cone jet MLM scheme using cone jets, with minimum $P_T > P_T^{ME}$ and $\Delta R=\Delta R^{ME}$, and for the $K_{T}$-jet scheme using $K_{T}$ jets with a cutoff scale $Qcut > xqcut$. These jets are then compared to the original partons from the matrix element event. A jet is considered to be matched to the closest parton if, for the cone jet scheme, the jet is within 1.5$\Delta R$ from the parton, and for the $K_{T}$-jet scheme, if the jet measure $K_{T}(parton,jet)$ is smaller than the cutoff $Qcut$. The event is rejected unless each jet is matched to a parton, except for the highest multiplicity sample, where extra jets are allowed below the $P_T$ or $K_{T}$ scale (for the respective schemes) of the softest matrix element parton in the event. These matching schemes can be used with both the old (vituality-ordered) and the new ($\pt$-ordered) shower implementations of \pythia. * Cone- or $K_{T}$-jet MLM: The final-state partons in an MG/ME event are clustered according to the $K_{T}$-jet algorithm to find the "equivalent parton shower history'' of the event. The Feynman diagram information from !MadGraph is used to allow only clusterings that correspond to diagrams existing in the generated matrix element. For the cone jet algorithm, a minimum $P_T$ and $\Delta R$ must be defined for all partons. For the $K_T$ scheme, the smallest $K_{T}$ value is restricted to be above the cutoff scale "xqcut". In order to closely mimic the behaviour of the parton shower, the $K_{T}$ value for each clustering vertex corresponding to a QCD emission is used as renormalization scale for $\alpha_{s}$ in that vertex. As factorization scale, as well as renormalization scale for the central hard $2\to1$ or $2\to2$ process, the transverse mass $m_{T}^2 = P_{T}^2 + m^2$ of the particle(s) produced in the central process is used. This event is then passed to Pythia for parton showering. After showering, but before hadronization and decays, the final-state partons are clustered into jets; for the cone jet MLM scheme using cone jets, with minimum $P_T > P_T^{ME}$ and $\Delta R=\Delta R^{ME}$, and for the $K_{T}$-jet scheme using $K_{T}$ jets with a cutoff scale $Qcut > xqcut$. These jets are then compared to the original partons from the matrix element event. A jet is considered to be matched to the closest parton if, for the cone jet scheme, the jet is within 1.5$\Delta R$ from the parton, and for the $K_{T}$-jet scheme, if the jet measure $K_{T}(parton,jet)$ is smaller than the cutoff $Qcut$. The event is rejected unless each jet is matched to a parton, except for the highest multiplicity sample, where extra jets are allowed below the $P_T$ or $K_{T}$ scale (for the respective schemes) of the softest matrix element parton in the event. These matching schemes can be used with both the old (vituality-ordered) and the new ($P_T$-ordered) shower implementations of \pythia. * Shower-$K_{T}$: In this scheme, events are generated by MG/ME as described above, including the reweighting of $\alpha_{s}$. The event is then passed to Pythia and showered using the $P_{T}$-ordered showers. In this case, Pythia reports the scale of the first (hardest) emission in the shower, $Q_{hard}$. For events from lower-multiplicity samples, the event is rejected if $Q_{hard}$ is above the matching scale $Qcut$, while events from the highest multiplicity sample are rejected if $Q_{hard} > Q^{ME}''{low}$, the scale of the softest matrix element parton in the event. This matching scheme is simpler and yet effectively mimics the workings of the $K''{T}$-jet MLM scheme. However, it allows for the matching scale $Qcut$ to be set equal to the matrix element cutoff scale $xqcut$, and it more directly samples the Sudakov form factor used in the shower. Furthermore, the treatment of the highest multiplicity sample more closely mimics that used in the CKKW matching scheme. * Shower-$K_{T}$: In this scheme, events are generated by MG/ME as described above, including the reweighting of $\alpha_{s}$. The event is then passed to Pythia and showered using the $P_{T}$-ordered showers. In this case, Pythia reports the scale of the first (hardest) emission in the shower, $Q_{hard}$. For events from lower-multiplicity samples, the event is rejected if $Q_{hard}$ is above the matching scale $Qcut$, while events from the highest multiplicity sample are rejected if $Q_{hard} > Q^{ME}_{low}$, the scale of the softest matrix element parton in the event. This matching scheme is simpler and yet effectively mimics the workings of the $K''{T}$-jet MLM scheme. However, it allows for the matching scale $Qcut$ to be set equal to the matrix element cutoff scale $xqcut$, and it more directly samples the Sudakov form factor used in the shower. Furthermore, the treatment of the highest multiplicity sample more closely mimics that used in the CKKW matching scheme. === Practical aspects ===