Skip to content

ratzenboe/diffractive-event-selection

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Diffractive background studies

This collection of c++ and python 3+ programs is used to (1) study the background component in simulated (Pythia-8) diffractive events at ALICE and (2) to reject the background component in the measured data.

  1. The background study (1) builds upon and uses c++ classes stored in ./lib/. These classes range from base classes necessary to execute tasks to plotting classes. In oder to be able to use these classes, the rootlogon-file has to be modified. See rootlogon-example.C for the necessary lines which have to be added.
  2. In order to study the background component ALICE tasks are available in ./tasks/. These tasks require an additional folder containing the Offline Analysis DataBase - an OADB folder - to be placed into the ./tasks/ folder. A short description on how to run the tasks is presented in the main folder ./tasks/README.md.
  3. If the EventDef class has been used to create a precise list of the decay modes with their respective sub-decays then a decaymodes.tex file is created (located in the respective task folder where the .go script has been evoked) which is a table written in latex format. This table can be transferred into a .pdf format by copying the decaymodes.tex file into the ./latex/ folder and invoking ./latex/compile.sh. The pdf file is stored in ./latex/output/doc.pdf.
  4. Plotting is usually done via a special class saved in ./lib called the PlotTask class. It can be used to make a wide variety of plots (e.g. ratio plots, significance plots, etc.). It can be used to plot the task-output histograms as well standarad histograms saved in a .root format. The aim of this class is to plot histograms in a uniform style. With multiple implemented functions (see ./lib/PlotTask.h) a plot can be made more quickly and simply without having to deal with individual root funtions for individual hisotgrams. In the folder ./plottingscripts/ some macros can be found which make use of this class.
  5. Additional smaller c++ macros which are not crucial to the background study but may become useful in the study of background events are saved in ./misc

The background rejection is done with machine learning methods with python 3+.

  1. In oder to use the data stored in the CEP-buffers (i.e. CEPEventBuffer, CEPTrackBuffer,and the raw buffers) a few steps have to be taken. The necessary programs to do so are stored in the folder ./root2pyt/ and the procedure is described there.
  2. After the data is converted into the special format (refered to as the event-dictionary) machine learning algorithms (neural networks using the Keras software framework) can be trained using the programs (and instructions) provided in the ./ml/ folder.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published