This topic is under construction....

About The Package

This package enables the user to properly calibrate the DLL distributions of their signal mode, and thus calculate the efficiency of a given cut accurately.

It is assumed that the DLL of a particular track depends on small set of kinematic or event variables. The set of these variables has changed during development of the package, at the time of writing track momentum, pseudorapidity and number of tracks in the event are the most commonly used.

Through "golden modes" that can be reconstructed without the use of the RICH detectors, it is possible to acquire pure calibration samples of pions and kaons. The DLL distributions of these tracks shows the true response of the RICH detectors to tracks with the same kinematics.

The calibration and signal samples under study (acquired by some sort of fit, and appropriate background subtraction) are then binned in the chosen variables. In the limit where the bins are infinitely fine and the assumption of DLL depending on only the kinematic and event variables used being correct, then the DLL distribution of tracks in a particular bin of the calibration sample should be single-valued (this is important, make sure you understand this). The population of each bin in the calibration and signal samples is compared, the ratio of these is assigned as the weight to that particular bin. The true DLL distribution of the signal tracks is then given by the DLL distribution of the calibration sample weighted bin by bin.

The weighting process is repeated for each track in the final state of the signal mode, to obtain the DLL distributions for all tracks.

Getting the Code

How to get and compile the code and some more technical info can be found here.

Usage

Test_Data.cpp

Test_Data.cpp is the script provided with the package to do the weighting with data. You give it input of your signal sample kinematics from data, and it weights the data calibration samples using just momentum and pseudorapidity as the weighting variables. I have attached a heavily annotated version of Test_Data.cpp, which hopefully leaves any usage questions beyond doubt.

Other scripts to do the weighting procedure that are provided are Test_MC.cpp, Test_EvtMC.cpp and Test_EvtData.cpp. Test_MC.cpp performs the same as Test_Data.cpp on Monte Carlo, and is used primarily for validation of the procedure and systematic calculations. Test_EvtData.cpp does the same as Test_Data.cpp but number of tracks in the event is used as a weighting variable in addition to track momentum and pseudorapidity. You can guess what Test_EvtMC.cpp does...

Example Results

Here are some example plots that should be the result of Test_Data.cpp. These are drawn by running the PlotWeightedDLLs.cpp script located in PIDPerfScripts/scripts/ in the package.

I will put the plots here at a later date.

Analysis Specific Details

This section contains details of how this package was used for this analysis.

The binning scheme used is 32 bins in p in the range (0,150)GeV=c and 4 bins in in the range (1.5,5). This provides a way of knowing what the true ?LL distributions of the tracks in both our signal and normalisation modes are, and therefore what the e ciency of a given PID cut is, with systematic uncertainties associated with the procedure. However, the observed numbers of events in these two modes are too small (35 in B0s ! D0K0 and 154 in B0d ! D00) to perform this weighting procedure with data. Therefore, p and distributions from higher statistics Monte Carlo samples 4 are used to weight the calibration sample, which however introduces an additional systematic from any dierences that exist between these distributions in data and Monte Carlo.

-- EdmundSmith - 2011-08-10

• Test_Data.cpp: Heavily annotated version of Test_Data.cpp