Monitoring of L1Calo EM Trigger Items: Overview & Midterm Results Hardeep Bansil University of Birmingham Birmingham ATLAS Weekly Meeting 11/11/2010

Contents Trigger and L1Calo Analysis Efficiencies – Bump at Low Transverse Energies – Missing Trigger Events 2

ATLAS Trigger Divided into three levels (L1 hardware based, L2 & EF software based) Reduces 40 MHz bunch- crossing rate to ≈200 Hz for recording while keeping events containing physics processes of interest Level-1 has three sub-systems: – Calorimeter Trigger – Muon Trigger – Central Trigger (CTP) L1 identifies Regions of Interest (RoIs) to send to L2 L2 looks around RoI with full detector info, EF looks at whole event in detail using same algorithms as used in offline reconstruction 3

Level-1 Calorimeter Trigger (L1Calo) Summed analogue signals sent to USA15 in Trigger Towers (0.1x0.1) Signals digitised and sent to specific modules to identify electrons, photons, taus and jets as well as total and missing energy Event level result sent to L1 CTP, if passed get L1A and data readout to DAQ 4

Cluster Processor Birmingham responsibility 4-crate system, each crate covers one quadrant with 14 modules in each crate Receives trigger tower info up to |η| < 2.5 to identify e/γ/τ/h Uses 4x4 sliding window algorithm – The EM cluster (e/γ) or HAD cluster (τ/hadron) must have E T greater than the electromagnetic or hadronic threshold under consideration. – The E T in the EM isolation ring must be less than the electromagnetic isolation threshold. – The E T in the HAD isolation ring must be less than the hadronic isolation threshold. – For EM clusters, the total E T in the hadronic inner core must be less than a threshold. 5

data10 Analysis Used AthenaProduction with ESDs on grid with TrigT1CaloAnalysisExamples package Using MinBias stream  events pass L1_MBTS_1 || L1_MBTS_2 items Using JetTauEtmiss stream  events pass L1_J*, EM cluster under study must have ΔR > 0.4 from jet ROI which triggered event (tag & probe) eγ Good Runs Lists / Lumi block selection Require ≥ 1 vertex with ≥ 3 associated tracks Remove photon conversions based on eγ code Remove crack region between barrel and end-cap & OTX cuts ΔR < 0.15 for matching RoIs to clusters of offline electrons / photons Started from calibrated eγ candidates from egClusterCollection (reconstructed using sliding window algorithm) … recalculate raw cluster E T, η, φ using energy weighting of CaloCells that make up CaloCluster Done with period E data () for electron and photon candidates with no isEm requirement  better statistics but poor jet rejection 6

Efficiencies EM2, EM3, EM5 Combined Efficiency Plot (MinBias stream) – Generally agrees well with public results – Dips in efficiencies in plateau more noticeable for public results – Bump present at low E T in efficiencies, significant for EM2 and less conspicuous for higher energy thresholds – In my results there is a contribution to bump in Monte Carlo for EM2 but very little for EM3 and EM5 7

Efficiencies EM10, EM14 Combined Efficiency Plot (MinBias stream) – No bump at these energies – Relative to EM2, EM3, EM5 turn on starts a little earlier – General shape features for EMx thresholds in terms of cluster E T raw : x+1.0 : ε ≈ 0.2 – 0.4 (L1Calo just able to see energy to trigger) x+2.5 : ε > 0.9 (Getting there!) x+5.0 : ε = 1 (Plateau of turn-on curve takes a little while to reach) Fit Fermi function to curves as better way to describe this in future? 8

Efficiencies EM5 Turn On Curve – MBTS to JET trigger comparison – To show that it does not matter which independent trigger is used – MBTS uses MinBias stream, JET uses JetTauEtmiss stream – Plotted without Monte Carlo – Overall shapes look very similar – JET tag and probe estimates slightly higher efficiencies at low E T but in plateau results are similar  important for physics analyses 9

Bump See a bump at low E T (also in public results) Causes for bump were studied originally by looking at all objects within an event (text dump) and trying to classify them One cluster matched to one RoI – Noise and miscalibration (dominant effect) Raw cluster has E T < 3 GeV than this but this is enough to make a 3 GeV RoI (Energies in L1Calo are normally rounded down but with slight miscalibrations in trigger, noise, … it is possible) Signals from LAr to L1Calo could add up to 500 MeV in noise but would not explain some raw clusters triggering with less than 2 GeV  some other effect present? Dodgy offline reconstruction? – Offline cluster calibration The offline calibration produces a big difference between the raw and calibrated energies of the cluster with calibrated energy much less than the raw energy. 10

Bump Two or more clusters matched to one RoI – Bad matching to RoI (thought to be dominant) One cluster with low energy matches to another one nearby with a much higher energy  artefact of trigger tower granularity and ΔR 3 GeV – Offline reconstruction of clusters One cluster from an electron and one cluster from a photon with energy less than 3 GeV. Energies and positions are almost identical or at least very close – both objects were reconstructed from the same cluster so RoI sees enough energy to make a 3 GeV RoI  Subset of Noise and miscalibration effect – Two or more clusters combined to make RoI 2 clusters nearby each other with very different energies add up together so that the trigger tower sees enough energy for a 3+ GeV RoI Based on common features of objects in these events, an algorithm was developed to automatically classify them 11

Bump Why is there a difference between the data and Monte Carlo for EM3 and EM5? For Monte Carlo, noise effect dominates which contributes to a bump in EM2 Cluster combination and bad matching only have small effects so nothing for EM3 & EM5 Monte Carlo (MC09) has not got an ideal response in this case, need to see if MC10 will be better 12 EffectDataMC Noise & Miscal ± ± 1.34 Bad Matching20.65 ± ± 0.11 Off. Recon.3.39 ± ± 0.05 Cl. Calibration0.13 ± ± 0.05 Cl. Combination16.00 ± ± 0.08

Bump Contributions as a function of E T raw Noise effect dominates in all E T bins Comparable results for cluster combination and bad matching Any good ideas for y-axis title? 13 EffectData Noise & Miscal ± 0.35 Bad Matching20.65 ± 0.18 Off. Recon.3.39 ± 0.07 Cl. Calibration0.13 ± 0.01 Cl. Combination16.00 ± 0.15

Bump Asked why we see a ‘bump’ and not a ‘shoulder’ Mainly due to electron and photon reconstruction Based on sliding window algorithm which searches for seed clusters with at least 2.5 GeV in second layer Fraction that trigger is higher around 1-2 GeV than 0-1 and 2- 3 GeV giving a bump 14 Why should reconstruction produce clusters with raw E T less than 2.5 GeV then? – Will need to understand this – Papers only give details above 2.5 GeV

Missing Trigger Events The turn-on curves calculated for the energy thresholds indicate that there are some candidates for which no EmTau RoI was produced If no energy produced then there was a lack of energy seen in the PPr  many stages lead up to this so many reasons for it Killed trigger tower (for being too noisy/faulty electronics) Dead trigger tower (signal lost before receivers) BCID calculates that object out of time with LHC beam Shower spread over many trigger towers so no single trigger tower sees enough energy (either from early shower in Inner Detector or actually part of a jet) In the transition region, the summation of trigger towers was difficult so either the barrel or endcap towers were deliberately masked (again causing a lack of energy seen) 15

Missing Trigger Events η-φ efficiency map for EM3 (JET triggers) with OTX cuts for offline clusters with raw E T > 5 GeV – Done in offline coordinates, φ shift from L1Calo coordinates – Areas with reduced efficiency are identified and problems (attempted to be) understood  many understood to some level, many not – Need to do with respect to RoI coordinates  problems clearer 16 Transition Region

Missing Trigger Events η-φ efficiency map for EM3 (JET triggers) with OTX cuts for offline clusters with raw E T > 5 GeV – Done in offline coordinates, φ shift from L1Calo coordinates – Areas with reduced efficiency are identified and problems (attempted to be) understood  many understood to some level, many not – Need to do with respect to RoI coordinates  problems clearer 17 Transition Region HV Problem Loose cable LAr miscabling Know L1Calo sees less energy, not sure why Dead tower Killed tower

Results η-φ efficiency map for EM3 (JET triggers) with/without OTX cuts for clusters with raw E T > 5 GeV – Where OTX problem is in second layer, eγ reconstruction poor and trigger tower efficiency drops – In other places, OTX cuts are conservative – Would prefer not to use OTX cuts  what is best way to adjust this without reducing the areas where efficiency will be very bad? 18 Without OTX CutsWith OTX cuts

Next steps FOR L1CALO MONITORING Submit midterm today! Migrate code to latest version of TrigT1CaloAnalysisExamples package Run over more recent data (period F-H/I) Improve understanding of offline reconstruction Work out the best way to get statistics in the future Look at bump on TT level? Clever things with fits of Fermi functions? Dead material corrections Algorithm to identify cause of missing trigger events FOR OTHER TOPICS Start diffractive charm physics 19