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Simulation of Z->jets in CMS Outline –Introduction –Technique –Results –Conclusion.

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Presentation on theme: "Simulation of Z->jets in CMS Outline –Introduction –Technique –Results –Conclusion."— Presentation transcript:

1 Simulation of Z->jets in CMS Outline –Introduction –Technique –Results –Conclusion

2 Analysis Processes Use Pythia to generate particles Use GEANT4 to simulate the response of Ecal and Hcal Digitization to ADC counts Convert ADC counts to energy in one calorimeter cell Combine ECAL and HCAL cells into projective towers Convert CaloTowers into standard objects Run clustering algorithm to produce jets

3 Source of the simulation Single particle: π + –Flat pt: 10 <pt< 70 GeV/c –Flat eta: -4.5<eta<4.5 –Flat phi: -π<phi< π –Fixed vertex: (vx,vy,vz)=(0,0,0) Single particle: Z0 –Pt=0; –Fixed vertex: (vx,vy,vz)=(0,0,0) –Decay in Pythia (Z->Q+Qbar) The MC data are big ~ 3MBytes/event Only the user defined tree is saved to disk. 2000 events are analyzed in both cases.

4 Z->QQbar event in Pythia Event listing (summary) I particle/jet KS KF orig p_x p_y p_z E m 1 (Z0) 11 23 0 0.000 0.000 0.000 94.759 94.759 2 (d) 14 1 1 -41.344 -16.277 16.444 47.380 0.330 3 (dbar) 14 -1 1 41.344 16.277 -16.444 47.380 0.330 4 (CMshower) 11 94 2 0.000 0.000 0.000 94.759 94.759 5 (d) 14 1 4 -34.971 -13.768 13.909 53.375 35.255 6 (dbar) 14 -1 4 34.971 13.768 -13.909 41.384 10.325 7 (d) 14 1 5 -36.812 -18.053 14.235 47.507 19.321 8 (g) 14 21 5 1.841 4.284 -0.326 5.868 3.547 9 (dbar) 14 -1 6 35.106 13.670 -13.929 41.216 9.242 10 (g) 13 21 6 -0.135 0.098 0.020 0.168 0.000 11 (d) 14 1 7 -38.560 -17.634 11.607 44.323 5.653 12 (g) 13 21 7 1.748 -0.419 2.629 3.184 0.000 13 (d) 13 1 8 1.099 1.950 1.569 2.753 0.330 14 (dbar) 13 -1 8 0.742 2.334 -1.895 3.115 0.330 15 (dbar) 14 -1 9 19.381 10.556 -4.419 22.577 1.767 16 (g) 13 21 9 15.725 3.114 -9.509 18.639 0.000 17 (d) 14 1 11 -38.324 -17.520 11.016 43.677 3.259 18 (g) 13 21 11 -0.236 -0.114 0.590 0.646 0.000 19 (dbar) 13 -1 15 15.328 9.122 -3.632 18.206 0.330 20 (g) 13 21 15 4.054 1.435 -0.787 4.372 0.000 21 (d) 14 1 17 -37.248 -16.830 10.378 42.248 2.556 22 (g) 13 21 17 -1.076 -0.690 0.638 1.429 0.000 23 (d) 13 1 21 -34.693 -15.550 8.977 39.065 0.330 24 (g) 13 21 21 -2.555 -1.280 1.402 3.183 0.000 25 (d) A 12 1 13 1.099 1.950 1.569 2.753 0.330 26 (g) I 12 21 10 -0.135 0.098 0.020 0.168 0.000 27 (g) I 12 21 16 15.725 3.114 -9.509 18.639 0.000 28 (g) I 12 21 20 4.054 1.435 -0.787 4.372 0.000 29 (dbar) V 11 -1 19 15.328 9.122 -3.632 18.206 0.330 30 (dbar) A 12 -1 14 0.742 2.334 -1.895 3.115 0.330 31 (g) I 12 21 12 1.748 -0.419 2.629 3.184 0.000 32 (g) I 12 21 18 -0.236 -0.114 0.590 0.646 0.000 33 (g) I 12 21 22 -1.076 -0.690 0.638 1.429 0.000 34 (g) I 12 21 24 -2.555 -1.280 1.402 3.183 0.000 35 (d) V 11 1 23 -34.693 -15.550 8.977 39.065 0.330 36 (string) 11 92 25 36.070 15.718 -12.340 44.137 15.739 37 (K*0) 11 313 36 1.035 1.934 1.398 2.773 0.961 38 (Kbar0) 11 -311 36 1.383 0.483 -0.764 1.725 0.498 39 (rho-) 11 -213 36 1.006 0.193 -0.886 1.501 0.647 40 pi+ 1 211 36 5.658 1.011 -2.978 6.475 0.140 41 pi- 1 -211 36 5.864 1.585 -3.776 7.154 0.140 42 pi+ 1 211 36 0.614 0.141 0.062 0.648 0.140 43 (eta') 11 331 36 4.172 1.342 -1.223 4.649 0.958 44 (rho0) 11 113 36 13.972 7.834 -3.758 16.473 0.806 45 (eta) 11 221 36 2.367 1.195 -0.415 2.739 0.547 46 (string) 11 92 30 -36.070 -15.718 12.340 50.622 29.364 47 (rho0) 11 113 46 0.366 0.536 -0.760 1.304 0.838 48 pi+ 1 211 46 0.385 0.669 0.674 1.034 0.140 49 (rho-) 11 -213 46 0.261 0.669 -0.468 1.167 0.792 50 (rho+) 11 213 46 0.758 0.132 0.558 1.118 0.588 51 (pi0) 11 111 46 0.694 0.260 0.367 0.838 0.135 52 (pi0) 11 111 46 -0.699 -0.636 0.444 1.052 0.135 53 (rho-) 11 -213 46 -0.330 -0.237 0.536 1.003 0.745 54 (rho0) 11 113 46 -4.272 -1.804 1.622 4.973 0.776 55 (rho0) 11 113 46 -1.185 -0.323 0.629 1.538 0.678 56 (rho0) 11 113 46 -6.825 -3.675 1.546 7.951 0.858 57 (eta) 11 221 46 -10.489 -5.042 2.928 12.013 0.547 58 (Kbar0) 11 -311 46 -5.708 -2.300 1.741 6.415 0.498 59 (K*0) 11 313 46 -9.026 -3.968 2.524 10.216 0.877 60 (K0) 11 311 37 0.784 0.823 0.831 1.493 0.498 61 (pi0) 11 111 37 0.251 1.112 0.567 1.280 0.135 62 K_L0 1 130 38 1.383 0.483 -0.764 1.725 0.498 63 pi- 1 -211 39 0.716 0.190 -0.259 0.797 0.140 64 (pi0) 11 111 39 0.290 0.003 -0.627 0.704 0.135 65 gamma 1 22 43 0.858 0.041 -0.298 0.909 0.000 66 (rho0) 11 113 43 3.314 1.302 -0.925 3.740 0.678 67 pi+ 1 211 44 4.561 2.368 -1.523 5.362 0.140 68 pi- 1 -211 44 9.411 5.467 -2.235 11.112 0.140 ………

5 Jet reconstruction Input: towers (reco) or stable particles (MC) Output: Jets list, Jet direction, Jets energy Algorithms: Iterative Cone Midpoint Cone -- this analysis K T Seedless Infrared Safe cone

6 Jet reconstruction algorithms Iterative cone 1.Make an E T -ordered list for the inputs 2.Pick up the largest E T input (above a specified threshold) and create a cone (cone size is given R) 3.Use the objects in that cone to calculate the proto-jet direction and energy 4.The computed direction is used to seed a new proto-jet 5.Repeat step 3&4 until the energy of the proto-jet changes by less than 1% and the direction of the proto-jet changes by ΔR<0.01 between iterations 6.Put this stable proto-jet to the jet list. Remove all the objects in the stable proto-jet cone from the input list 7.Start from step 2 to find another jet until no more object has an E T above the threshold

7 Jet reconstruction algorithms Midpoint cone 1.Use all E T >threshold inputs to find stable proto-jets. In this procedure, no object is removed from the input list. 2.For every pair of proto-jets that are closer than R, a midpoint is calculated as the direction of the combined momentum. These midpoints are then used as additional seeds to find more proto-jets. 3.Starting with the highest E T proto-jet, if the proto-jet does not share objects with other proto-jets, it is defined as a jet and removed from the proto-jet list. 4.If there is shared part of two proto-jets, calculate factor f= E T _shared/ E T _neighbor 1.f>0.5, merge the 2 proto-jets to one 2.f<0.5, assign the shared part to the proto-jet that is closest 5.Repeat step 3&4 until no proto-jet left

8 Single π + jet events

9 Between Reco jets and Gen jets Match condition: ΔR<0.2

10 Jets from Z decay

11 Conclusions and todo list Code can run smoothly The first look of Z->QQbar events reco jets have spikes in a few certain eta and phi directions, need to figure out why move further to a more complicated case -- embed Z decay to real events Optimize the algorithm

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