If you are unfamiliar with non-perturbative physics or anything that is mentioned here (minimum bias, underlying event, ...), go and grab a tutor. They will explain everything to you in detail.
In this exercise, we are going to simulate minimum bias events, and compare with minimum bias and underlying event measurements. Also, we will switch off parts of the event generator, use different parameters for the hadronization model and study the effects on the observables (playing around with the event generator in order to improve the description of some observables).
The simulation of minimum bias events heavily relies on the accurate modeling of:
- Multi-parton interactions,
- Colour reconnection
Minimum bias and underlying event analyses are therefore excellent assets to study these aspects of
the event simulation.
Use what you have learned so far and simulate 10000 Events using the prepared LHC-MB.in file, then change the name of the created .yoda file to something else (default.yoda for example) and look at the plots.
You can download the input file via
In the next step, switch off colour reconnection and simulate again 10000 events.
The switch is already included in the input file. You just need to find and remove the comment.
Now plot the two yoda files with the following command
rivet-mkhtml default.yoda LHC-MB.yoda
and look at the observables.
Which observables are heavily affected by colour reconnection?
Now we are going to switch off diffraction (remember to include colour reconnection again). Just comment out the following line in the input file
and run LHC-MB.in again for 10000 events.
Have a look at the plots from ATLAS_2012_I1084540 and try to explain what happens.
Before we go on, set everything to the default settings (include diffraction and colour reconnection).
While the underlying event/minimum bias model does a relatively good job in describing general properties of
the measurements, such as rapidity distributions or pT spectra of charged particles, it becomes more difficult once the observables get more inclusive.
Have a look at the flavor observables from CMS_2011_S8978280.
In two steps we are going to change several parameters in the Hadronization model in order to improve the description of strangeness observables like the Kaon pT distribution.
1: Increase the value of PwtSquark (default is 0.3)
The parameter PwtSquark is the weight to produce a strange-antistrange quark pair during cluster fission.
Increasing it will increase to probability to produce strangeness during the cluster fissioning stage.
Run Herwig again for 10000 events and compare with the default.yoda file you created in the beginning.
In the next step we are going to allow the non-perturbative gluons which are left after the Parton Shower evolution has terminated to split into strange-antistrange quark pairs.
Fot this we have to make several changes to the input file.
2: Remove the comments from Change 3 (see input file) and assign a value between 0 and 1 to SplitPwtSquark
Run Herwig again for 10000 events and compare with the other .yoda files.
Do the observables favor strangeness from the cluster fissioning stage or from the gluon splitting stage? What is the difference? (Low PwtSquark and high SplitPwtSquark value and vice versa)