L1Calo EM Efficiencies Hardeep Bansil University of Birmingham L1Calo Joint Meeting, Stockholm 29/06/2011

Contents EM efficiencies Dealing with 2011 data Turn-on Curves Efficiency maps Next steps 2

Calculating Efficiencies Efficiencies calculated for L1 electromagnetic trigger items as to determine L1Calo (CPM) performance Calculated by using raw offline clusters of electrons and photons and matching them to EmTau RoIs (using recommendations of egamma group) Done two different ways – Function of E T – turn on curve – Function of η and φ – efficiency map Also as a function of each data taking period (similar to most offline analyses) LAr OTX cuts can be applied Transition region between EM barrel and endcap excluded (1.37 < |η| < 1.52) 3

Method Using AthenaProduction Using JetTauEtmiss stream DESD_CALJET (processed) Sample obtained with Jet Tag and Probe method – EM objects also reconstructed as jets so need to find another L1_J* RoI in the event (Δr > 0.4 away) so that they can be studied Raw cluster E T, η, φ using energy weighting of CaloCells that make up CaloCluster 4 Event studiedEvent ignored

2010 Results Plans from Cambridge 2010 – Plots looked good (E T curves sharp going to 100%, high efficiency in maps, clearly identified regions with poor performance) 2011 – Get efficiencies to support existing tools in terms of identifying towers with reduced performance and making information available to those are interested in it Run on Tier 0 for every run + offline for every period – Looked into this with Juraj and Pete Faulkner – Trimmed code to get info just for maps (10, 20, 30 GeV) and turn-on curves Adjust databases retrospectively if poor performance regions 5 10 GeV clusters, EM5 EM14, 2010 Period E-I

2010 Results Plans from Cambridge 2010 – Plots looked good (E T curves sharp, high efficiency in maps, clearly identified regions with poor performance) 2011 – Get efficiencies to support existing tools in terms of identifying towers with reduced performance and making information available to those are interested in it Run on Tier 0 for every run + offline for every period – Looked into this with Juraj and Pete Faulkner Adjust databases retrospectively if poor performance regions 6 NOT ACHIEVED THIS YET 10 GeV clusters, EM5 EM14, 2010 Period E-I

Prompt processing and reprocessing The RAW data of triggered events are written to disk/tape This data is processed to produce outputs for physics analysis – Detector ‘hits’  track and cluster finding  Physics object reconstruction (combining information from different detectors)  applying calibrations and alignment Often the data is processed promptly at Tier‐0 and then reprocessed at a later time (with improved software and/or calibrations) around 1-2 times a year (usually targeting a major conference). 7

Turn-on Curves EM10 and EM14 as a function of offline raw cluster E T With prompt processed data, the efficiency is significantly affected by IsEm quality of candidates – Lower IsEm quality, more candidates trying to match with RoIs – Really not an issue with reprocessed data as better calibration IsEm loose and tight show sharp rises, plateau not quite at 100% (IsEm none definitely not to be used) 8 EM14, 2011 Period D-E EM10, 2011 Period D-E

Turn-on Curves EM14 as a function of offline raw cluster E T (IsEm Tight) Updated calibrations (timing update from first 2011 collision data, overlap endcap fix) have improved efficiencies with time 9 EM14, 2011 Period D-E EM14, 2011 Period B-C

Efficiency Maps 2011 Comparison Looking at previous page’s plots in terms on efficiency maps now EM14 as a function of offline raw cluster E T (IsEm Tight) with 20 GeV raw clusters Overall improvement in efficiency – Although area affected by calo non-HV has no tight clusters In 2011 data, not enough stats for the furthest out towers (especially when applying cuts to account for clusters falling half out of calorimeter) Period D-E 2011 Period B-C

Efficiency Maps 2010/11 Comparison Looking at previous page’s plots in terms on efficiency maps now EM5 using IsEm loose clusters with 10 GeV raw E T Big reduction in efficiency due to prompt/reprocessed data – Unfair comparison? In 2011 data, not enough stats for the furthest out towers (especially when applying cuts to account for clusters falling half out of calorimeter) Period D-E 2010 Period I

Efficiency Maps IsEm Going back to how IsEm can affect an efficiency map… IsEm None – plenty of statistics, after certain energy cut energy get pretty uniform but picks up very unusual behaviour in certain areas (are these really problematic regions or due to fakes localised to a particular area), get candidates in dead OTX region IsEm Tight – fewer stats but less affected by large structures reducing efficiencies GeV ‘tight’ clusters - EM14 20 GeV ‘none’ clusters - EM14

Efficiency Maps Comparison with DBs Comparing the Trigger Tower Bad Calo / Dead Channel databases with the efficiency maps (applied a cut afterwards to exclude these in plots) Clearly databases need to be updated 13 EM Dead Channel EM Bad Calo Looks like miscabling region - Are these dead channels now? No issue in other plots The region of calo with no HV does not show up as bad (unless it shows up in dead channel in wrong place)

Efficiency Maps Noisy towers? Sensitive to some sort of noise spike affecting number of candidates in tower (not that it could be easily seen in efficiency map) Tight clusters 20 GeV EM14, 2011 Period B-C 14 Hit map for all candidates Efficiency map

Running on single runs only If at Tier 0, run on full ESD not skimmed DESD_CALJET but just to get idea Run , approx events – larger than most runs Turn-on curves look reasonable but clearly not enough clusters at IsEm tight level for efficiency maps – Still necessary to produce maps for every run period? Two places where efficiency drops in plateau and one reduced efficiency tower – Could be related but would need to look at other plots as well – May need to adjust z-axis palette to distinguish between 100% and slightly lower 15 EM14 Single Run 20 GeV tight clusters - EM14

If at Tier 0, run on full ESD not skimmed DESD_CALJET but just to get idea Run , approx events – larger than most runs Turn-on curves look reasonable but clearly not enough clusters at IsEm tight level for efficiency maps Loose clusters: more statistics but plateau not at 100% so harder to distinguish which towers have poor performance Running on single runs only 16 EM14 Single Run 20 GeV loose clusters - EM14

Next steps Determine appropriate IsEm cuts to use as a balance between efficiency and statistics – Investigate observation of unusual structures Use the conditions database or improve electron / photon candidate selection some other way? Push on with running on Tier 0 – Important for getting regions of poor performance updated in databases and for physics studies – Can you use GRLs or at least identify bad/good lumi blocks? Any suggestions welcome! 17