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 discrimination with converted photons

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Presentation on theme: " discrimination with converted photons"— Presentation transcript:

1  discrimination with converted photons
Nicolas Chanon, Zhang Zhen Guoming Chen, Suzanne Gascon-Shotkin, Morgan Lethuillier 08/05/2009 – IHEP CMS weekly meeting I – Converted photons selection II – Input variables III – TMVA results

2  discrimination with converted photons
I – Converted photons selection Samples : mH=120GeV H->gg, QCD Preselection at generator level : Et1>37.5 GeV, Et2>22.5 GeV (background only)‏ Selection at reconstructed level : - Use of converted photon collection in CMSSW_1_6_12 and ask isConverted=1. - ||<2.5. - Et threeshold has been increased. Now events are selected if there is at least one photon with Et>40 GeV. TMVA is then applied to all photons which have Et>25 GeV - Tracker ISO : No tracks with pt>1.5 GeV inside ΔR<0.3 around the direction of the photon candidate. We consider tracks with hits in at least two layers of the silicon pixel detector. - Ecal ISO : Sum of Et of the ECAL basic clusters within 0.06<ΔR<0.35 around the direction of the photon candidate <6 GeV in barrel, <3 GeV in endcap. If one of the candidates is in endcap the other has to satisfy : Sum of Et of the ECAL<3 - Hcal ISO : Sum of Et of the HCAL towers within ΔR<0.3 around the direction of the photon candidate<6 GeV (5 GeV) in barrel (endcap)‏

3  discrimination with converted photons
I – Converted photons selection Contents of the converted photon collection : Event N, converted photon collection : - convphot 1 : SC 1 : track 1 - convphot 2 : SC 1 : track 2 - convphot 3 : SC 1 : track 3 - convphot 4 : SC 2 : track 4 and track 5 - convphot 5 : SC 2 : track 4 and track 6 - convphot 6 : SC 2 : track 5 and track 6 - convphot 7 : SC 3 : nTracks=0, isConverted=0 => For each converted photon supercluster, how to select the best tracks ?

4  discrimination with converted photons
I – Converted photons selection Isolation study of converted tracks. Goal : select the best tracks associated to each SC. 2 ideas : - Include the converted photon tracks when applying the track isolation to the photon. - In order to be sure that selected tracks are not charged hadrons or Pi+/Pi-, try to apply the hcal isolation to the converted tracks themselves.

5  discrimination with converted photons
I – Converted photons selection HCAL iso of converted tracks signal, 1trk background, 1trk signal, 2trk background, 2trk

6  discrimination with converted photons
I – Converted photons selection Track iso included converted photon tracks signal, 1trk background, 1trk signal, 2trk background, 2trk

7  discrimination with converted photons
I – Converted photons selection Conclusion of these isolation studies : - HCAL with Et<5 iso below dR<0.3 applied to converted photon tracks seems to be the best choice. - Including converted tracks to Photon TrkIsolation kills too much photons... Selection of the best tracks among all converted photon tracks candidates : - Previously, Zhen was selecting tracks having (EoverP+pairSep) the closest to 1. - But EoverP closest to 1 gives almost the same results. All the TMVA results shown later are obtained with this criteria. - I tried also two different things : - Apply this EoverP closest to 1 criteria only to photons having tracks passing the HCAL isolation => No improvement. (Later, try different Et threshold...)‏ - Select the photons that have the HCAL energy in the cone dR=0.3 closest to 0. If this energy is 0 for several candidates, select the one with EoverP closest to 1. => Seems to give a little improvement in bkgd rejection (2-3%) in the 2 track case.

8  discrimination with converted photons
II – Input variables cEP cEP (correlation eta-phi) is a basic cluster shape variable. It is the non-diagonal element of the correlation matrix. This is the correlation between eta_i and phi_j on each cristals inside the seed cluster. 1trk case 2trk case

9  discrimination with converted photons
II – Input variables cPP cPP (correlation phi-phi) is a basic cluster shape variable. It is the bottom diagonal element of the correlation matrix. This is the correlation between phi_i and phi_j on each cristals inside the seed cluster. For photons that are indeed converted, cPP is higher because of the magnetic field which move electrons in the phi direction. 1trk case 2trk case

10  discrimination with converted photons
II – Input variables s9/(s9-s1-s2)‏ This variable is an « home made » basic cluster shape variable. This variable is E3x3 over (E3x3 minus the first and the second crystal energy in the BC)‏. If energy is very centered in the SC, s9(s9-s1-s2) will be small. 1trk case 2trk case

11  discrimination with converted photons
II – Input variables R9 This variable is the usual cluster shape variable, equal to E3x3 divided by the energy of the supercluster. If R9 increases, most of the energy will be concentrated in 3x3 crystals instead of 5x5 or more, so that usually, photons with R9>0.93 are considered as unconverted photons... used in 1trk case only

12  discrimination with converted photons
II – Input variables EoverP This variable is the energy of the supercluster divided by the norm of the momentum of the tracks. EoverP is used to see if tracks and supercluster have the same energy. EoverP close to 1 means the converted photon is well reconstructed. For the 1 trk case, there is no reason for EoverP to be close to 1, because one of the electrons is lost... Indeed removing this variable from the TMVA increase the rejection by 2-3%. Previously used in 1trk and 2trk case. Now used in 2trk case only

13  discrimination with converted photons
II – Input variables ptoverjetpt This variable is the pt of the photon divided by the pt of the closest jet (with pt_jet>15 GeV). I guess for the signal, the jet is always a fake jet including the photon (that's why the shape is centered in 1). For the background, this can be real jet including the Pi0 and some other particles than just one photon, so that the tails are bigger. 1trk case 2trk case

14  discrimination with converted photons
II – Input variables closest_SC_dR This is the DR between the converted photon supercluster and the closest jet supercluster in the ECAL (DR = 10 is the chosen value if there is no other supercluster in ECAL.)‏ For the signal, most of the matched SC are signal photons, whereas for the background jets are more smeared. If the photon come from a Pi0 this variable gives information about jet activity around it.

15  discrimination with converted photons
II – Input variables dR_SC_trckclosest This is the DR between the converted photon supercluster and the closest track (with pt_trk>5 GeV). (DR = 10 if there is no track with pt>5 GeV)‏ This variable gives information about jet activity in the tracker. 1trk case only

16  discrimination with converted photons
III – TMVA results Root version Zhen's last presentation 1trk Case, Root v.5.19 Same code, Root v.5.22 => All the following results have been made with the last Root version (v.5.22)‏

17  discrimination with converted photons
III – TMVA results 1 track case

18  discrimination with converted photons
III – TMVA results 1 track case Bkgd rejection is now 63% Whas has changed ? - Root v.5.22 instead of (for all but BDT, same results)‏ - New Et cut on photons : 1st phot Et>40, others >25 (~1% decrease)‏ - Remove EoverP from the input variables (2-3% increase)‏ - Add dR_SC_trckclosest (I had already it in my last talk, with a bkd rejection of 60%)‏

19  discrimination with converted photons
III – TMVA results 1 track case BDT slightly overtrained, not MLP.

20  discrimination with converted photons
III – TMVA results 2 tracks case

21  discrimination with converted photons
III – TMVA results 2 tracks case Select the convphot with tracks the most hcal isolated. If no hcal energy around photons, select the one with EoverP closest to 1 Conv phot selected with EoverP closest to 1 Almost the same results as last time.

22  discrimination with converted photons
III – TMVA results 2 tracks case No overtraining -> so why BDT so low ?

23  discrimination with converted photons
Conclusions : - New cuts on photon pt has been established to respect generator level cut - Started to study the isolation of converted photon tracks . - For 1 trk case, keep dR_SC_trkclosest proposed last time, and discard EoverP. 1trak case rejection is now 63% and 2tracks 50%. The 2 tracks could be improved with a careful study of isloation. - BDT results depends on root version ! Perspectives : - Apply the MVA to the Gamma+Jet samples. - Instead of EoverP criterion, use Ted's likelihood to select the best converted photon. - Check with MC truth info the proportion of real Pi0 in the background samples (later, with Nancy's implementation of conversion MC truth). - Check the relative importance of all the variables. - Investigate the asymmetry variable pointed out by Anagnostou - Divide samples in different pt bin


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