We start from some preexisting hepmc2 input files, and the code runs
- fastjet clustering with anti-kt R = 0.4
- for each jet we take all the constitents and connect shower history with generalized kt p = 0.0, 0.5, 1.0
- for each setting, integrate some pre-existing dE/dx on the lines
- we report the outputs in the test.out text file
If you want to try different new scenarios yourself, we typically only need to change the functions (T profile & dEdx) in the EvaluateEnergyLoss.cpp. The rest are helper functions.
Clone this repository and do make. You will need fastjet installed (if fastjet-config is in the path it is ok)
8 columns: event weight, jet PT, jet eta, jet phi, constituents, eloss p = 0, eloss p = 0.5, eloss p = 1 each row is a jet
Here there are a few relevant functions
- BuildCATree(vector<>, double): builds the parton shower tree. Second parameter is the p in the generalized kt
- AssignTime(...): go through the tree and assign time. New function for this exercise. In principle if things look good we don't need to touch this anymore.
- AssignQG(...): go through the tree and assign q/g type. If the two children are qq or gg, assign g. If qg or gq, assign q.
The main program that does the energy loss calculation. Functions...
- main(...): the main function that reads hepmc2 file and calls RunAnalysis(...)
- RunAnalysis(...): cluster jet with anti-kt, then for each clustered jet integrate energy loss
- dEdx(...): calculates dE/dx given some parameters
- ParticleELoss(...): integrate over one internal particle line
- GetT(...): gets the temperature given some time. Change medium assumptions here
- GetTotalEnergyLoss(...): calls ParticleELoss(...) recursively and adds up everything