Data-driven extraction of jet energy loss distributions in heavy-ion collisions
Project description
Data driven extraction of jet energy loss distributions in heavy ion collisions
Introduction
This python package is a simple tool to extract mean pt loss $P(\Delta p_T)$, and the mean pt loss as a function of jet pt -- $\langle\Delta p_T\rangle(p_T)$, from the experimental single jet RAA for AA collisions at a specific beam energy (with pt spectra in proton+proton collisions at the same beam energy) or the single hadron/gamma hadron pt spectra (without pt spectra in proton+proton collisions).
Example: >>> from jeteloss import PythiaPP, RAA2Eloss >>> pp_x, pp_y = PythiaPP(sqrts_in_gev = 2760) >>> raa_fname = "RAA_2760.txt" >>> eloss = RAA2Eloss(raa_fname, pp_x, pp_y) >>> eloss.train() >>> eloss.save_results() >>> eloss.plot_mean_ptloss() >>> eloss.plot_pt_loss_dist()
Citation
If you have used this package to produce results for presentation/publications, please cite the following two papers, from where one can find the detailed information of the underlying physics.
Installation
Method 1: using pip
Step 1:
pip install jeteloss
Step 2:
git clone git@github.com:lgpang/jeteloss.git
Step 3:
cd jeteloss/examples
python example1.py
Method 2: install from local directory
Step 1: download the code from github
git clone git@github.com:lgpang/jeteloss.git
Step 2: install jeteloss and dependences
cd jeteloss
python setup.py install
Step 3: run example code
cd examples
python example1.py
Method 3: using anaconda
Step 1: To create one clean python virtual environment
conda create -n test_jeteloss python=3.6
Step 2: To activate this environment, use:
source activate test_jeteloss
Step 3: Install jeteloss module and its dependences
pip install jeteloss
Step 4: Run the example code downloaded using:
git clone git@github.com:lgpang/jeteloss.git
cd jeteloss/examples
python example1.py
Step 5: To deactivate an active environment, use:
source deactivate
Step 6: Clean up To see how many environments do you have, use:
conda env list
To remove one environment, use:
conda remove --name test_jeteloss --all
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