EtMiss and Tau updates Meeting di gruppo ATLAS D. Cavalli, C. Pizio, S. Resconi

NEW Jet/MET organization 2 NEW task forces have been created inside the Jet/MET group, since October 08: (1) Data Preparation for Missing Et and Jet Measurements (S.R., R. Teuscher ) (2) Jet Reconstruction and Calibration (E. Fullana, A. Schwartzman) • The scope of task force (1) is focused on data preparation for Missing Et and jet measurements in early data  main items related to noise studies, study of cleaning variables to reject cosmics and beam gas events, strategies to deal with detector faults, like missing modules, bad channels…  study in details single beam/cosmics data  develop common tools (package) inside Athena for cleaning cuts/variables  use/study DPDs (Derived Physics Data) format from single beam/cosmics  close connection with calo experts (LAr and Tile) • more details in the wiki and in meetings: https://twiki.cern.ch/twiki/bin/view/AtlasProtected/JetEtmissDataPreparation

MissingET processing on real data  work in the context of the Task Force In first prompt processing of single beam data (Sept 08) highest level of descoping:  MissingET was one of the few combined algo that was ready to run (no egamma, no tau…)  Only METAlg with a minimal set of MET Tools to calculate: MET_Base = EtMiss from all CaloCells (Ecell2 noise)  etx(), ety(), sumet(),  exCalo(CaloReg), eyCalo(CaloReg), etSumCalo(CaloReg),ncellCalo(CaloReg) CaloReg = PEMB, EMB, PEMEC, EME, TILE, HEC, FCAL  exReg(EtaReg), etReg(EtaReg), etSumReg(EtaReg) EtaReg = Central (||1.5), EndCap (1.5||  3.2), Forward (3.2||5)  Since rel 14.2.23.2 added quantity for basic performance/noise studies with first data: MET_Base0 = EtMiss from all CaloCells WITHOUT any noise cuts  Available in “data08_cosmag*recon*f75*”  In second reprocessing (Xmas 08) no more need to descope MET:  All combined reco algo (egamma, tau, jets…) have run, all needed input objects to MET were available  Full MissingET reconstruction successful

MissingET on reprocessed data  work in the context of the Task Force • First look to MET quantities on reprocessed single beam data: data08_1beammag.00087764.physics_L1Calo.merge.AOD.o4_r605_p17_tid034969 (~ 35000 evts) data08_1beammag.00087764.physics_L1Calo.merge.DPD_CALOCOMM.o4_r605_p17_tid034969 (~ 7000 evts) SUMET distributions AOD DPD Used same ARA code to analyse AOD and DPD data Good agreement between AOD and DPD distributions of main MET quantities

MissingET on reprocessed data  work in the context of the Task Force SUMET Ref terms AOD DPD Checking all contributions to MET from all reco objects (ele/gamma/tau/jets…): • MET_RefEle and MET_RefTau terms are zero both in AOD and DPD due to problems with the tracking  MissingET is a powerfull tool also for debugging all reco objects

Masking bad channels in MET Reconstruction  work in the context of the Task Force • To mask bad channels both in LAr and Tile calos different bad channel tools are available: LArBadChanTool/Masker, TileBadChanTool CaloBadChanTool combines LAr+Tile but less detailed info • To allow the possibility to use them in MissingET package a new MET tool has been implemented  METCellMaskTool • at the moment it allows two possibilities that can be configured in METGetter.py: • (1) use CaloBadChanTool for all cells (LAr + Tile) setting: WhichBadChanTool = “OnlyCalo“ SelectBadChan = “Dead”, “Noisy”, “Affected“, “All” ,“Dead+Noisy”, “Noisy+Affected” • (2) use LArBadChannelMasker for LAr cells + CaloBadChannelTool for Tile cells setting: WhichBadChanTool = “Calo+LAr“ SelectBadChan = “Dead”, “Noisy”, “Affected“, “All” theLArMasker.ProblemsToMask=["deadReadout","deadPhys","almostDead","short", "lowNoiseHG", "highNoiseHG","unstableNoiseHG","lowNoiseMG","highNoiseMG","unstableNoiseMG","lowNoiseLG", "highNoiseLG","unstableNoiseLG","deadCalib","distorted","peculiarCalibrationLine", "sporadicBurstNoise","problematicForUnknownReason","shortProblem","missingFEB"]  in contact with LAr and Tile experts to understand which level of masking should be applied for Tile cells  for LAr cells 

EM fraction of SUMET_Base  work in the context of the Task Force EM fraction of SumET = SumET in EM calos / SumET_Base SUMET_BASE_EM =(SumET_EMB+ SumET_PEMB+SumET_EMEC+ SumET_PEMEC) / SumET_Base  those info are already available in ESD / AOD / CBNT cosmics J4 Ztautau Ztautau J4 cosmics cosmics: data08_cosmag.00092099.physics_L1Calo Ztautau sample: trig1_misal1_csc11.005188.A3_Ztautau_filter J4 sample: trig1_misal1_csc11.005013.J4_pythia_jetjet Cosmics or beam halo muons leave most of their energy in Tile cal, so this will lead to very low EM fraction. SUMET_BASE_EM is a good candidate for Cleaning cuts  Under study in cosmics analysis

Other MET deliverables for rel 15.0.0 • MET reconstruction from Calo / TopoTowers (in view of first data):  a new tool that loops on Towers and calculate MET to be implemented • Towards the best MET Refined Calibration: for each reconstructed object apply the best calibration weights to its constituent CaloCells test CalibHits based e/gamma calib in progress to improve electron contribution to MET (METRefEleTool) tests by Caterina in contact with Leonardo • Merging with ObjMissingET (by Wisconsin group): Calibration of cells outside reconstructed objects provided by ObjMET now integrated in MissingET package  plan to close ObjMissingET package in rel 15.0.0. • MET reconstruction on AOD: On AOD NOT possible to re-calculate EtMiss at Cell level. New method to remove overlap among reco objects developped in collaboration with Peter Loch Peter will come to Milan next week to finalize the implementation • METPerformance package:  NEW package to provide official tools and macros for measuring the MET algorithm performance, first version already in CVS  Donatella will provide macros used for EtMiss CSC note

Z    lepton-hadron in first data (1-100pb-1) detector understanding (instrumental effects on EtMiss!) validation of SW for Tau and EtMiss reconstruction select a high purity sample determine the absolute energy scale of Tau (from reco visible mass) and EtMiss (from reco invariant mass) determination of t-jet efficiency from data s(Z   ) measurement  overall consistency/universality prepare the A/H   analysis

Analysis for CSC Notes:  (D. Cavalli/C. Pizio) Tau CSC Note EtMiss CSC Note Z to tau-tau in first ATLAS data ATL-PHYS-INT-2009-005 (D. Cavalli/C. Pizio) Approved (ref. K. Jackobs) Baseline analysis for Z tt lh - All details about analysis method and results in CSC notes - new: W background estimation from data ATL-PHYS-INT-2009-005

EtMiss and Tau scales determination cross section measurement Updates: Now: 10 TeV analysis Our main goal: EtMiss and Tau scales determination cross section measurement Updates: trigger study (now in progress for Beatenberg…) first results from 10 TeV analysis signal+backgds (ATLAS week) cuts tuning (from 14 TeV to 10 TeV) Many ATLAS groups now interested in t channels (Ztt, Wtn) with first data In contact with Italian groups working on Zmm Strong collaboration with Freiburg group CROSS SECTION

Long term plans for tt channels A  tt  lh analysis: Ztt is a background, parallel analysis, same tools P.h.D. thesis of Will Davey  Melbourne-Milano PhD (Cotutela)  17 Feb – 15 Aug in Milan (6 mesi di borsa di studio per stare a Milano)

BACKUP SLIDES

First tests of METCellMaskTool • re-reconstructed single beam data run 87764, physics_L1Calo, with rel 14.5.0.5 • in METGetter.py set: “OnlyCalo” = use CaloBadChannelTool for all cells (LAr+Tile) “All” = “Dead” + “Noisy” + “Affected “ = mask all bad channels MET_BASE MET_BASE_MASK SUMET_BASE SUMET_BASE_MASK 200 400 200 400 For most of evts ( MET/SUMET – MET/SUMET_MASK) < 10 GeV In few evts large effect of bad channels  can cause high fake MET

First tests of METCellMaskTool • Check which calos give the main contribution from bad channels to MET_Base and SUMET_Base PEMB EMB PEMEC EMEC TILE HEC FCAL Tile calo and EMB give the main contribution