e4nu Analysis code

This repository contains the e4nu analysis code and utils to plot the relevant information. The following are brief descriptions of the code structure and various classes. Additional information on the analysis can be found on the e4nu Wiki.

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Compile and run e4nu analyses

To configure the software:

1. Setup the environmental variables according to the farm you're in. For the FNAL gpvm, source e4nu_gpvm_env.sh;. For the ifarm, source e4nu_ifarm_env.sh;.
2. Compile the code "make" from the E4NUANALYSIS directory: cd $E4NUANALYSIS; make;
3. If a previous installation exists, cd $E4NUANALYSIS; make clean ; make;
4. Run the main application, ./e4nuanalysis. You can pass a different configuration file by passing the name to ./e4nuanalysis my_config.txt. The configuration file must live in ConfigFiles.
5. There's some configurable options that can be passed to the main analysis app. This enables the user to write a simple bash script that runs the whole analysis. For instance, you can run the 1p1pim analysis at 2 GeV on carbon using ConfFiles/mc_conf/run_clas6mc_1pimanalysis_eC12_2GeV.sh.

After each run, you will get a new root file containing information from the valid analysed events. The information stored in this file, as well as it's name, can be configured from a configuration file (see Configuration guide Wiki).

The user might want to obtain the cross section from the output files. src/apps/plote4nuanalysis.cxx is responsible to plot the cross section for a given list of observables. This app takes into account the acceptance correction. The input options are:

• monte carlo files location
• data files location. This is optional in case you only want to see the mc predictions.
• output location is the directory where all plots will be stored
• name of input mc files, without the extension (_true.reco or _truereco.root). It will be used to compute the distributions for the true distribution, and the true+reconstructed distributions. These are used for the acceptance calculation. The user can specify a list of MC files in case they want to compare against more than one model. The acceptance correction in that case is the average of all models.
• input data file, without the _class6data.root extension
• Comma separated list of observables. I.e ECal,proton_mom,...,HadAlphaT
• Optional list for the models name. Its size must be the same as the number of mc files
• Optional title for the plots
• Name for the data legend
• No FSI root file. This file is separate because it should not be used to compute the acceptance.
• Bool to decide where to compute additional systematics (sector by sector, fiducial systematics, etc.) [To Be Added]
• Add Systematics list of name and percentage corresponding to overall normalization systematics It is useful to store all the commands in a bash script. An example can be found in Documentation/run_1p1pi_plotting.sh

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Directory Structure

The code can be found in different subdirectories, with the following structure:

• src : source directory. Further described below.
• data : contains data files used to run analyses. There's two sub-directories, AcceptanceMaps and FiducialsCorrections, containing acceptance maps and fiducial corrections. As of now, only CLAS6 information is available.
• ConfigFiles : it contains examples of configuration files. For instance, see example_configuration.txt
• PlottingScripts : it contains examples of plotting scripts that can be used to plot the output of e4nu analysis.

The structure of the src directory is as follows:

• conf : it contains most of the constants and configurables. Most of the constants depend on the configuration. It provides with the corresponding getter functions to access those.
• utils : it provides with utils which can be used for any analysis. Some examples are Fiducial.h, KinematicUtils.h (with event kinematics definitions), and so on.
• physics : it contains the implementation of EventI, and the corresponding specializations for data and MC, CLAS6Event and MCEvent. It also contains the EventHolder class and it's specializations. These are used to load the data from the input root files.
• analysis : this directory contains the main classes used for analysis. The structure it's explained in the next section.
• apps : contains the main executable, e4nuanalysis.cxx
• make : it contains some make files needed for compilation

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E4nu Analysis Code

The analysis app e4nuanalysis.cxx is the main executable. It's content is simple: it instiantates an E4NuAnalysis object (see below details on inheritance chain), configured with ConfigFiles/example_configuration. This object is then used to load the data from an input root file (analysis -> LoadData()), run the analysis and background subtraction methods, and finally, store the analized information in a TTree as well as Histograms.

The main analysis flow is as follows:

The e4nu analysis code is highly factorized into different classes, which inherit from each other. ConfigureI is the base class, E4NuAnalyisis is the top derived class. The main structure is depicted in the diagram below: The (...) boxes indicate that new classes might be added to accomodate new analysis cuts, specific to a new analysis (see user gide section below).

Each class has a specific role within the e4nu analysis:

• ConfigueI: it is responsible for the analysis configuration. The configuration is setup with an input txt file (see ConfigFiles/example_configuration.txt). All aspects of the analysis are configurable. It can be used to change the signal Topology definition, or turn off/on analysis cuts/requirements.
• BackgroundI: it deals with all background subtraction methods. More information on the available configuration setups can be found in Configuration Guide.
• AnalysisI: it deals with analysis features common between data and MC. In particular:
  1. Requires valid event weights
  2. Electron kinematic cuts
  3. Cuts on Q2, W
  4. Applies a minimum momentum cut on hadrons
  5. Cooks the event - it removes all particles not specified in topology definition. For instance, in the case of a 1p0pi analysis, it would remove neutrons, kaons, or other particles from the event. This simplifies the loops later in the analysis.
• MCCLAS6AnalysisI: it deals with analysis features specific to MC data for CLAS6 analysis:
  1. Smears hadrons kinematics
  2. Fiducials are taken care for
  3. Acceptance weights are computed
• CLAS6AnalysisI: it deals with analysis features specific to CLAS6 data.
• MCCLAS6StandardAnalysis and CLAS6StandardAnalysis: they inherit from the MCCLAS6AnalysisI and CLAS6AnalysisI interfaces. The standard classes are templates to facilitate the integration of new analysis by new users. For this reason, the standard classes simply call the MCCLAS6AnalysisI::GetValidEvent(id) or CLAS6AnalysisI::GetValidEvent(id) functions. For analysis that differ from the standard one, a new class should be added with a new implementation of GetValidEvent(id), using these classes as templates. The analysis is configured with the AnalysisID keyword. For now, only the standard analysis is available (analysis id of 0). New analysis would require a new analysis ID.
• E4NuAnalysis: this is the main class used for analysis. It is responsible to call either the MC or data objects according to the Configuration. It also deals with the signal/bkg selection. An E4NuAnalysis object is defined in e4nuanalysis.cxx using a configuration file.