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 generation, use different parameters for the hadronization model and study the effects on the observables. (Playing around with event generators 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, * Diffraction * Colour reconnection * Hadronization If you are unfamiliar with non-perturbative physics or anything that was mentioned here, go and grab a tutor. He/She will explaineverthing to you detail. Minimum bias and underlying event analyses are therefore excellent in order 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. Colour Reconnection ------------------------- 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 rivet-mkhtml default.yoda LHC-MB.yoda and look at the observables. Which observables are heavily affected by colour reconnection? Diffraction ------------- Now we are going to switch off diffraction (remember to include colour reconnection again). Just comment out the following line in the input file read snippets/Diffraction.in 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. Hadronization parameters ------------------------------- Before we go on, set everything to the default settings (include diffraction and colour reconnection). While the underlying event/minimum bias model does a relative good job in describing general properties of the measurements, such as rapidity distributions or number of charged particles. It gets more difficult to have a good description once the observables become 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 on the cluster fission stage. Run Herwig again for 10000 events and compare with the default.yoda file you created in the beginning. 2: Remove the comments from Change 3 (see input file) and assign a value between 0 and 1 to SplitPwtSquark With these changes the non-perturbative gluons which are left after the Parton Shower evolution has finished are allowed to split into strange-antistrange quark pairs, giving also an increase in strange particles. Run Herwig again for 10000 event 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)

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, * Diffraction * Colour reconnection * Hadronization 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. {F1090291} You can download the input file via wget https://phab-files.hepforge.org/file/download/3fx5ccp6qkd5bnztpya5/PHID-FILE-llgb6slr2623oxfg6cx5/LHC-MB.in Colour Reconnection ------------------------- 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? Diffraction ------------- Now we are going to switch off diffraction (remember to include colour reconnection again). Just comment out the following line in the input file read snippets/Diffraction.in 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. Hadronization parameters ------------------------------- For a realistic simulation of minimum bias events we need to include colour reconnection and diffraction. While the 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 become 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 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 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 (default is ~0.8) 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)

In this exercise we are going to simulate minimum bias events 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 generation, use different parameters for the hadronization model and studywe will switch off parts of the effects on the observables.vent generator, (Playing around with event generatorsuse 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, * Diffraction * Colour reconnection * Hadronization If you are unfamiliar with non-perturbative physics or anything that was mentioned here, go and grab a tutor. He/She will explaineverthing to you detail. Minimum bias and underlying event analyses are therefore excellent in orderassets 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. {F1090291} You can download the input file via wget https://phab-files.hepforge.org/file/download/3fx5ccp6qkd5bnztpya5/PHID-FILE-llgb6slr2623oxfg6cx5/LHC-MB.in Colour Reconnection ------------------------- 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? Diffraction ------------- Now we are going to switch off diffraction (remember to include colour reconnection again). Just comment out the following line in the input file read snippets/Diffraction.in 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. Hadronization parameters ------------------------------- Before we go on, set everything to the default settings (include diffraction andFor a realistic simulation of minimum bias events we need to include colour reconnection)n and diffraction. While the underlying event/minimum bias model does a relatively good job in describing general properties of the measurements, such as rapidity distributions or numberpT spectra of charged particles., It getit becomes more difficult to have a good descriptiont once the observables become 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 onduring the cluster fissionning stage. Run Herwig again for 10000 events and compare with the default.yoda file you created in the beginning. 2: Remove the comments from Change 3 (see input file) and assign a value between 0 and 1 to SplitPwtSquarkIn the next step we 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. With these changes the non-perturbative gluons which are left after the Parton Shower evolution has finished are allowed to split into strange-antistrange quark pairs, giving also an increase in strange particles. 2: Remove the comments from Change 3 (see input file) and assign a value between 0 and 1 to SplitPwtSquark (default is ~0.8) 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)