J/Ψ event selection algorithm - status

1. J/Ψevent selection algorithm - status Maciej KrauzeInstitute of Physics University of Silesia, Katowice M.Krauze, J/Ψ event selection algorithm - status

2. Motivations • there are many background events due to very low J/Ψ multiplicity • reduction of the number of events • in order to make it possible to store the data • to make the online analysis feasible Requirements of the method • fast  because we measure at the full beam luminosity • using as less detector information as possible (currently: 3 stations of the Transition Radiation Detector) • efficient  to reduce the bulk of data passed to the next level analysis system M.Krauze, J/Ψ event selection algorithm - status

3. Software tools • UrQMD, Pluto, Geant & ROOT • as a software base, CBM framework package was used; this package incorporates TRD detectors layout The detector layout used in our studies M.Krauze, J/Ψ event selection algorithm - status

4. Why TRD can be usefull for background event reduction • it can provide information about the particle’s trajectory and momentum (estimation!) • it can distinguish between e+e- and hadrons (Π, p) • 95-99% of hadron rejection (depends on the particle’s momentum) • the detector has large material budget so the the multiple scattering process has an influence on obtained results • not very high resolution M.Krauze, J/Ψ event selection algorithm - status

5. Event selection – methods & ideas • to supress as many background events as possible • to preserve the signal How? • the main selection critterion is the invariant mass value • we take every 2 particles of unlike charge within the same event and calculate the invariant mass of the pair • for the J/Ψ particles, the invariant mass of the decay pair is 3.1 GeV/c2 • if the event does not contain any pairs of invariant mass greater than 2 GeV/c2, it is REJECTED M.Krauze, J/Ψ event selection algorithm - status

6. TRD1 TRD2 Y Target Z Transversal momentum cut • removes low-energy particles from background • removes some fraction of signal (depends on the threshold value) • to perform it we need a magnetic field and a method of momentum reconstruction Further reduction of the number of particles taken to the combinatorics (speed!) • non-bending plane cut (Y): M.Krauze, J/Ψ event selection algorithm - status

7. Further reduction of the number of particles taken to the combinatorics (continued) • bending plane cut (X): X Target Z these two geometric cuts combined reject 75% of secondaries while only 3% of signal is lost TRD1 TRD2 1 m M.Krauze, J/Ψ event selection algorithm - status

8. Requirements of the method • fast track finder (at present we consider ideal tracks) • precise track fitter (Kalman Filter) • momentum determination method (fast and precise) Summary and next steps • the algorithm has roughly 90% efficiency or more (depends on the parameters used) • we have to consider realistic track finder • one can use some additional cuts (Pt angle, opening angle, momentum value etc.) • to achieve greater efficiency, it may be necessary to use information from additional detector(s) M.Krauze, J/Ψ event selection algorithm - status