1. the ATLAS detector

2. High energy particle physics Typical detector layout Tracking chamber ElectroMagnetic calorimeter Hadronic calorimeter Muon chamber Innermost Layer....... Outermost Layer photons electrons muons pions,protons neutrons

3. ATLAS TEST BEAM SETUP Calorimeter TRT muon stations

5. tracking stations (SCT)

6. TRT

7. Test Beam data : used to test performances of design of various ATLAS detector components. We want to use these data to play around with particle identification. In particular we want to see how well we can distinguish electrons from pions with ATLAS. We have various informations available (in parenthesis name of variables as in ROOT code): 1) The fraction of energy deposited in the first sampling layer of the Electromagnetic calorimeter (EMF1) 2) The fraction of energy deposited in the whole Electromagnetic calorimeter (LArF) 3) The fraction of energy deposited in the whole Hadronic calorimeter (HadF) 4) Number of cherenkov counts (Cher2) 5) Muon tag from the muon system (MuTag) 6) Number of High threshold and Low threshold hits in the TRT (nHT, nLT) 7) Sum of Time spent over Threshold divided by Sum of length crossed in the straw, for all straws in the TRT crossed by a particle (SumToT, SumL)

8. This is no MC simulation, so we have no way to know the true identity of a particle (track) observed in the detector. So we use variables 1-5) to make a preselection, a division of particles in two sample: electrons and pions. Then we try to find the best cuts for variables 6) and 7) to improve separation. preselection: obtain the cut values for making a electron(e) and pion(pi) sample by iterative process, where each variable is considered in turn. 1.1) First, apply some reasonable cuts on all other variables but one. 1.2) plot the variable in question for e and pi selected by the cuts on all other variables. 1.3) choose a value cut from the plot for this variable. 1.4) do the same for all other variables. 1.5) Repeat a few times, until you seem to converge. To quantify how good separation for this preselection you are achieving by using a cut value on a variable, you want to check for that variable what is the efficiency and purity achieved e.g. I am studying variable 5 to select e and pi, and used 1-4) to split sample in e and pi. cut_5_e: efficiency_5,e = Number of e selected by the cut on 5/ Number of e before the cut on 5 rejection_5,pi= Number of pi selected by the cut on 5/Number of pi before the cut on 5 cut_5_pi: efficiency_5,pi = Number of pi selected by the cut on 5/ Number of pi before the cut on 5 rejection_5,e= Number of e selected by the cut on 5/Number of e before the cut on 5 usually, you would stop on a value for cut_5_e and cut_5_pi when you get about <0.01 rejection, and still have some statistics (~few 100 particles in sample)

9. e.g. start with cut on LarF cut_LarF_e : LarF>0.5 cut_LarF_pi : LarF <0.4 and throw away muons with cut MuTag<460. In general electrons will have low values for HadF, and high values for EMF1 and LarF and Cher2. Pions will have the opposite. Plot the other variables, try to fix some value for all but one, and then start tuning last one. and so on.... Q: the beams of pions and electrons are of different energies for different runs (code recognizes this from file read in automatically) => do you see the need for different cuts for different energies? Now to TRT: 0) at a given energy, for one of the variables (fixing cuts on the others), try to plot efficiency vs rejection curve obtained when varying cut value for selecting electrons e.g. 1) the beams of pions and electrons are of different energies for different runs (code recognizes this form file read in automatically) => do you see the need for different cuts for different energies? 2) try to plot for each energy, the rejection factor obtained with TRT for pions for the cut for selecting electrons which provide roughly 90% efficiency for electron identification. What do you observe?

10. 3) try to calculate for the variables 1-7) the correlation between the variables. correlation(x,y) = [N* ∑ (x * y) – ∑ x* ∑ y ] sqrt [N* ∑ x^2 - ( ∑ x)^2] * sqrt [N* ∑ y^2 - ( ∑ y)^2] 0=uncorrelated, 1=fully correlated. Are they all equally important for particle identification? can one of them, or more, be skipped ? see also https://twiki.cern.ch/twiki/bin/view/Atlas/PidTrtCtbhttps://twiki.cern.ch/twiki/bin/view/Atlas/PidTrtCtb and http://hep.nbi.dk/resources/atlas_trt-pid/TrtPidCtb.pdf

11. Practicalities: copy from ekspfys0 account the files ~/root/pid/CTBanalysis.cxx ~/root/pid/CTBanalysis.h ~/root/pid/Makefile ~/root/pid/StrawQualityRef.txt make a link like this ln -s /scr/hep/xella/ TRTdata then try to do: gmake and then run./CTBanalysis Take a look at the first plots. Then edit CTBanalysis.cxx further, to do the study suggested