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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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