Developments of the PWG3 muon analysis code

Developments of the PWG3 muon analysis code Analysis Train for the standard AOD generation from the ESD  Analysis task to fill the standard AOD with the muon information Preparation of AOD replication for muon tagged events Other developments in the PWG3 muon analysis code:  Analysis tasks for the determination of the efficiency of the • Tracking chambers • Trigger chambers Alice Offline Week, July 10th 2008

ESD AliAnalysisTask ESDfilter AOD ESD AliAnalysisTask ESDfilter AliAnalysisTask ESDMuonFilter AOD From the ESD to the standard AOD Up to now the AOD generation from ESD was done using only one analysis task ANALYSIS/AliAnalysisTaskESDfilter.cxx for all the tracks, including muons Now there is a new analysis task which takes care of filling in the AOD the muon tracks to allow a better modularity PWG3/muon/AliAnalysisTaskESDMuonFilter.cxx

Analysis Train The AOD creation from the ESD will now be done calling the two analysis tasks: 1)ANALYSIS/AliAnalysisTaskESDfilter.cxx • which writes in the AOD: • the header of the event • all the tracks apart from muons • other infos AliAnalysisTaskESDfilter *esdfilter = new AliAnalysisTaskESDfilter("ESD Filter"); 2)PWG3/muon/AliAnalysisTaskESDMuonFilter.cxx • which updates • the tracks branch in the AOD, adding the muons • the header of the event AliAnalysisTaskESDMuonFilter *esdmuonfilter = new AliAnalysisTaskESDMuonFilter("ESDs"); Muon information are copied from AliESDMuonTrackAliAODTrack

New methods in AliAODTrack Philippe Pillot New methods added to the AliAODTrack Track parameters at DCA have been added to the AliAODTrack: • Double32_t fMomentumAtDCA[3]; // momentum (px,py,pz) at DCA • Double32_t fPositionAtDCA[2]; // trasverse position (x,y) at DCA • void SetXYAtDCA(Double_t x, Double_t y); • void SetPxPyPzAtDCA(Double_t pX, Double_t pY, Double_t pZ); • Double_t XAtDCA(); • Double_t YAtDCA(); • Double_t ZAtDCA(); • Bool_t XYZAtDCA(Double_t x[3]); • Double_t DCA(); • Double_t PxAtDCA(); • Double_t PyAtDCA(); • Double_t PzAtDCA(); • Double_t PAtDCA(); • Bool_t PxPyPzAtDCA(Double_t p[3]); Corrected methods dealing with fITSMuonClusterMap in AliAODTrack  with the method AliAODTrack::IsMuonTrack() it is possible to correctly select muons in the muon arm In AliAnalysisTaskESDMuonFilter.cxx the AODTracks are now filled with these new infos

Test of the analysis train The analysis train has been tested • Locally • CAF • GRID  by Mihaela Gheata The macro to run the analysis train on the CAF is PWG3/muon/AnalysisTrainMuonCAF.C The macro has been tested on the CAF using some files from the PDC08/LHC08t  minimum bias pp@14TeV PDC07/LHC07g  dimuons pp@14TeV

Cuts on muon tracks ESD AliAnalysisTask ESDfilter AliAnalysisTask ESDMuonFilter AOD AliESDMuonTrackCuts New class implemented to provide the possibility to apply some selection cuts on the muon tracks before filling the AOD: PWG3/muon/AliESDMuonTrackCuts (based on a similar class already existing for the AliESDtrack: AliESDtrackCuts) AliESDMuonTrackCuts* esdMuonTrackCut = new AliESDMuonTrackCuts("AliESDMuonTrackCuts", ""); esdMuonTrackCut->SetPtRange(0.,0.5); // examples of kinematic cuts that can be applied esdMuonTrackCut->SetHistogramsOn(kTRUE); // methods to draw control histos esdMuonTrackCut->DefineHistograms(); esdMuonTrackCut->DrawHistograms(); AliAnalysisFilter* trackMuonFilter = new AliAnalysisFilter("trackMuonFilter"); trackMuonFilter->AddCuts(esdMuonTrackCuts); AliAnalysisTaskESDMuonFilter *esdmuonfilter = new AliAnalysisTaskESDMuonFilter("Muon”); esdmuonfilter->SetTrackFilter(trackMuonFilter);

AliESDMuonTrackCuts (2) For the moment only kinematic cuts are implemented Number of muon tracks Number of rejected tracks Number of tracks not surviving the pT cut Number of tracks not surviving the p cut

ESD • This step is ready and tested Standard AOD Need to select events containing only muons MUON AOD replication Muon-AOD replication • AOD containing only events where muons in the dimuon spectrometer are present.

Selection of muon events Several possibilities to select events containing only muons: 1) Loop on the events and select only those containing muons  time consuming 2)Read the AliAODHeader and read the event only if it contains muons  but in the AliAODHeader the number of muons is not stored. 3)Use the AliAODTags Applying cuts on the Event level AliTagAnalysis *TagAna = new AliTagAnalysis("AOD"); AliEventTagCuts *evCuts = new AliEventTagCuts(); evCuts->SetNMuonRange(1,1); TChain* chain1 = 0x0; TagAna->ChainLocalTags("/n60raid3/alice/roberta/ESDMuon/TagAODTest"); chain1 = TagAna->QueryTags(runCuts,lhcCuts,detCuts,evCuts);

AliAODTags to filter muons AOD Replica of track branch Replica of the events Header Replica of other branches Muon AOD AliAODTags The AliAODTags can be the approach to follow in order to select events containing muons Once we have tagged events containing at least one muon, the next step is the creation of a Muon-AOD replica containing: • the header of the event • the full event which contains the muon

Muon-AOD replica The idea is to create a replica of the standard AOD containing events where at least one muon is present • Method to automatically copy (from standard AOD to user-AOD) the header of the interesting events is already implemented AliAODHandler::SetNeedsHeaderReplication() • Methods to automatically copy other branches from the standard AOD to the user AOD not yet available Generalizing the code for AOD header replication, we have implemented, as a test, the replica of the TRACK branch for the interesting events AliAODHandler::NeedsTracksBranchReplication()

Muon-AOD (2) The replica is done in AliAnalysisTaskSE AliAnalysisTaskSE::CreateOutputObject() If(handler->NeedsTracksBranchReplication(){ fAODTracks = new TClonesArray("AliAODTrack",500); handler->AddBranch("TClonesArray", &fAODTracks); } AliAnalysisTaskSE::Exec() If(handler->NeedsTracksBranchReplication(){ AliAODInputHandler* aodH =dynamic_cast<AliAODInputHandler*>(fInputHandler); for(int i=0;i<InputEvent()->GetNumberOfTracks();i++){ AliAODTrack *track = dynamic_cast<AliAODTrack*>(InputEvent()->GetTrack(i)); new((*fAODTracks)[i]) AliAODTrack(*track);} } Code not yet committed Is this a suitable way to proceed in order to produce a replica of the AOD? Should we foresee other methods to replicate all other useful branches?

Creation of Muon-AOD Our proposal: In p-p@ 14TeVwe expect 1 muon track out of ~200 min. bias collisions: • MUON-AOD replication could be done in the official analysis train •  small data size of the MUON AOD replica • Several AODs files could be merged • ~106 muon tracks in a 3 hours run in p-p @ 14TeV at nominal luminosity

Muon AOD Add dimuon branch Dimuon AOD Macros for analysis Histos Adding dimuon information Once the MUON-AOD replica will be available, it will be possible, maybe as a further step, to add a dimuon branch, to include dimuon information Method to add new branches (as the dimuon branch) to the standard AOD exists: AliAnalysisTaskSE:AddAODBranch() Classes to compute dimuon information already existing PWG3/MUON/AliAODDimuon.cxx

Link between AODs and MC Julien Faivre Requirement from the last PWG3 meeting: Important to keep track of the link between the MC information and the AOD. What happens if the AOD granularity is different from the ESDs one?

Number of muons detected by the chamber εintrinsic= Number of muons which have passed through the chamber Intrinsic efficiency of the tracking chambers Nicolas LeBris The intrinsic efficiency of the tracking chambers represents the “quality” of the wires chambers of the dimuon arm. This efficiency is given by: This efficiency must be calculated with the real data. This is the goal of the Analysis task: AliAnalysisTaskMuonTrackingEff & AliCheckMuonDetEltResponse Those classes depend on MUON packages  our proposal is to create a new library PWG3muonMUON for the PWG3 classes that depend on MUON packages 1. intrinsic efficiency as a function of the position in each detection element of each chamber. 2. total intrinsic efficiency of each chamber (one plane of detection elements) 3. number of tracks used for the efficiency calculation (for errors calculation).

Intrinsic efficiency of the tracking chambers (2) ( local or batch mode) RunAnalysisTaskMuonTrackingEff.C geometry.root AnalysisTaskMuonTrackingEff.C AliAnalysisTaskMuonTrackingEff.cxx AliCheckMuonDetEltResponse.cxx AliESDs.root Input files Output histograms Efficiency as function of the position for each detection element Total efficiency of each chamber (10 chambers in the spectrometer ) AliMuonTrackingCh amberEffHisto.root Output file Results from a simulation of 10000 J/Ψ (20000 muon tracks)

Number of muons detected by the chamber εintrinsic= Number of muons which have passed through the chamber Intrinsic efficiency of the trigger chambers Diego Stocco The intrinsic efficiency of the trigger chambers is provided for the local boards Trigger tracks are created when 3 out of 4 chambers are hit both on the bending and in the non-bending plane Efficiency will be calculated separately for bending and not bending plane Efficiency will be calculated with the real data. Method already tested in the cosmic run

Intrinsic efficiency of the trigger chambers (2) ( local or batch mode) PWG3/muon/AnalysTrigChEff.C AliESDs.root AliAnalysisTaskTrigChEff.cxx Input files Output MUON.TriggerEfficiencyMaps.root which contains the ingredients for the eff. calculation

Conclusions Analysis Train (with separated filling of the muon tracks) has been tested locally/CAF/Grid Possibility of applying cuts on the muon tracks before filling the standard AOD has been implemented • Production of muon AOD under discussion: • The use of metadata information could help selecting events containing only muons. • Need to replicate useful branches from the standard to the Muon AOD  code to be completed and committed AnalysisTasks for tracking/trigger chamber efficiency is ready

Developments of the PWG3 muon analysis code