This page details my studies of the effects of applying cuts on outgoing parton pseudorapidities at pythia level.

I have been preparing a filtered dijet simulation focused on the Endcap-Endcap and Barrel-Endcap regions and have found that using pt cuts appropriate to the physics I want to explore, the time to run the simulation would be impractically large, even utilizing cloud computing. See here for more details.

One suggestion which was raised was to make cuts on the allowed phase space for outgoing particles at pythia level. In pythia, this is done using the CKIN flags. The most familiar are CKIN3 and CKIN4 which set the lower and upper bounds on outgoing particle pt. Other quantites important to 2->2 hard scattering can be restricted using CKIN flags as well, these include rapidity, cos(theta*), invariant mass, and outgoing particle pseudorapidity among others. It looks to me that restricting the ranges of the outgoing particle pseudorapidity (CKIN13-CKIN16) would be the most effective cuts for my purpose, but questions were raised as to what frame these pseudorapidities were defined in. The study below is an attempt to answer this question as well as get an idea for how these cuts would affect a simulation. (Further details about the CKIN flags can be found in sec 9.2 of the Pythia manual which can be downloaded from here).

For this study, I have thrown 40000 filtered pythia events in the 7-9 pt bin. The pythia filter was set to accept Barrel-Barrel events where Pt_hi > 10Gev and Pt_lo > 7, Barrel-Endcap events where Pt_hi > 6 and Pt_lo > 5, and Endcap-Endcap events where Pt_hi > 4 and Pt_lo > 3. In addition, there was a trigger filter requirement in the BFC such that any event would need to have satisfied the JP1, AJP, or BHT3 triggers. Finally, the pythia phase space cuts I applied were that the pseudorapidities of the outgoing particles from the hard scattering process where between 0.90 and 4.0. (CKIN13 = 0.9, CKIN14 = 4.0, CKIN15 = 0.9, and CKIN16 = 4.0). I have also disabled vertex smearing, so all events should be thrown at a Z vertex of 0.

Fig 1: This figure shows the pseudorapidity for one outgoing particle vs the pseudorapidity of the other outgoing particle as contained in the pythia.root file. It is clear that the proper region is populated given the phase space cuts made above.

Further plots from the pythia record can be found here.

In addition to the pythia record, we are interested in how things look at the very end, ie, what would the jet finder see. The following plots show quantities obtained from the jet trees created from the simulation.

Fig 2: This figure shows the eta of one jet vs the eta of the other jet for event in which two jets were found.

Fig 3: As can be see in the above figure, there are a considerable number of events in which at least one jet is outside the eta range I had specified in pythia. To see if jets were really from hard scattering or if they were 'soft' jets which resulted from initial/final state radiation or some other soft process, I plotted the phi of one jet vs the phi of the other jet for events in which at least one jet had an eta below 0.0. The idea here was that if the jets with eta below 0 were from soft processes, there phi's should not be back to back.

As can be seen in the above plot, there is a decent amount of scatter, but there is a slight enhancement where the back to back bands should be. In the following plots, I have imposed a delta phi cut such that only dijets with delta phi = 180 +/- 30 degrees will pass.

Fig 4: This plot shows the phi of one jet vs the phi of the other jet after the delta phi cut of 180 +/- 30 degrees was applied.

Fig 5: This plot shows the eta of one jet vs the eta of the other jet after the same delta phi cut used in Fig 4 was applied.

Conclusions So Far: When I suggested cutting on outgoing particle pseudorapidity at pythia level questions were raised about wether eta was defined in the partonic COM frame or the proton-proton COM frame (lab frame). If the pseudorapidity I was cutting on was defined in the partonic COM frame for example the sharp cutoffs would be highly smeared in the lab frame due to the boost between the two frames, severily reducing the effectiveness of pythia eta cuts. But I believe that the pythia level pseudorapidities I'm cutting on are defined in the lab frame for the simple fact that the cuts I made above are not symmetric about zero, and if pseudorapidity was defined in the partonic COM frame, all outgoing particle pseudorapidities would have to be symmetric around zero, so no event would pass the cuts.

As can be seen in Figs 2 and 5, there are a good number of events where one of the jets has moved quite far out of the pseudorapidity region I defined in pythia. One cause of these wayward jets could be soft processes applied by pythia after the hard scattering kinematics have been set such as initial/final state radiation and hadronization among others. If soft processes are the cause, there effect is much larger than I would have expected.

Removing Initial/Final State Radiation Effects

At the jet phone on 7/27/2010, Carl suggested that I just turn off the initial state and final state radiation effects in pythia and see how that affects my eta vs eta plots. The plots below were run under identical conditions as those above except that I have turned off initial / final state radiation at pythia level. This is done with the commands: MSTP 61=0 and MSTP 71=0.

Fig 6: This figure shows the eta of one jet vs the eta of the other jet where two jets were found by the jet finder and the Is/Fs radiation was turned off.

Fig 7: This figure shows the eta of one jet vs the eta of the other jet with the condition that the jets be within +/- 30 degrees of back to back to eachother and with Is/Fs radiation turned off.

Figures 6 and 7 clearly show a reduction in the tails indicating that a substantial portion of the tails seen in figures 2 and 5 can be explained as Initial state and Final state radiation effects. In addition to reducing the counts in the tails, removing Is and Fs effects also reduces the total number of dijets seen. In the case of dijets with the phi cut, about 22% of events are lost (1092 -> 856). To get a better idea of where in eta we are losing events I have created plots showing the eta distribution of jet1 (jet2) when jet2 (jet1) has an eta of 0.7 or greater and superimposed the distribution with no Is or Fs onto the distribution where all processes are enabled.

Fig 8: This plot shows the eta distribution of jet1 for all events that have jet2 eta >= 0.7. The black curve is for the data set with all processes turned on and the red curve is for the data set with Is and Fs radiation turned off. Note that the integrals of the two curves are not equal, the black curve contains 910 events and the red curve contains 826 events.

Fig 9: This plot shows the eta distribution of jet2 for all events that have jet1 eta >= 0.7. The black and red curves are defined the same way as in figure 8. The black curve contains 922 events and the red curve contains 825 events.