Efficiencies are shown for an unprescaled single-jet trigger with two different calibrations applied to jets in the ATLAS high-level trigger (HLT), for 2017 (closed markers) and 2018 data (open markers). Offline jets are selected with ABS(η) < 2.8. The red circles show a calibration using only calorimeter information, while the blue squares show a calibration that also includes track information. Both calibrations include the Global Sequential Calibration (GSC) [1]. The GSC corrects jets according to their longitudinal shower shape and associated track characteristics without changing the overall energy scale. It can be split into parts involving calorimeter-based variables, and parts involving track-based variables. Since tracking is not guaranteed to be available for all jet thresholds, options are provided with and without the track-based corrections. The additional track-based corrections allow for improved agreement between the scale of trigger and offline jets as a function of pT, and thus the trigger efficiency rises more rapidly. Statistical uncertainties only are shown. |
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Efficiencies are shown for an unprescaled six-jet trigger with two different calibrations applied to jets in the ATLAS high-level trigger (HLT), for 2017 (closed markers) and 2018 data (open markers). Offline jets are selected with ABS(η) < 2.8. The red circles show a calibration using only calorimeter information, while the blue squares show a calibration that also includes track information. Both calibrations include the Global Sequential Calibration (GSC) [1]. The GSC corrects jets according to their longitudinal shower shape and associated track characteristics without changing the overall energy scale. It can be split into parts involving calorimeter-based variables, and parts involving track-based variables. Since tracking is not guaranteed to be available for all jet thresholds, options are provided with and without the track-based corrections. The additional track-based corrections allow for improved agreement between the scale of trigger and offline jets as a function of pT, and thus the trigger efficiency rises more rapidly. Statistical uncertainties only are shown. |
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Efficiencies for two unprescaled single large-R jet triggers are shown as a function of the leading offline trimmed [1] jet pT, with trimming parameters fcut = 0.05 and Rsub = 0.2, for 2017 data. Offline jets are selected with ABS(η) < 2.2. In red (circles) is a trigger with an ET threshold of 460 GeV, while in blue (squares) is a trigger with an ET threshold of 420 GeV and also a cut of 35 GeV on the mass of the selected trimmed trigger jet. The mass cut significantly suppresses the QCD di-jet background, allowing a lower ET threshold, while retaining nearly all signal-like jets with a mass of above 50 GeV (for this trigger, the offline jets in the plot are required to have a mass above 50 GeV). A slight inefficiency due to the application of the trimming procedure is mitigated by using fcut = 0.04 for trigger jets, while the standard offline selection uses fcut = 0.05. Statistical uncertainties only are shown. |
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Efficiencies for three unprescaled single large-R jet triggers are shown as a function of the leading offline trimmed [1] R=1.0 jet pT, with trimming parameters fcut=0.05 and Rsub=0.2, for 2017 data. Offline jets are selected with ABS(η) < 2.2. In red (closed circles) is a trigger using R=1.0 jets with area-based pileup subtraction applied, while in blue (open circles) is a trigger using R=0.4 jets, calibrated using calorimeter information as for standard 2017 small-R jet triggers, reclustered to form R=1.0 jets. In green (squares) is a trigger that applies trimming, with improved performance with respect to trimmed offline jets. A slight inefficiency due to the application of the trimming procedure is mitigated by using fcut=0.04 for trigger jets, while the standard offline selection uses fcut=0.05. Statistical uncertainties only are shown. |
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Efficiencies for two different Level-1 triggers are shown as a function of the leading offline trimmed [1] jet pT for large-radius jets with different numbers of subjets, using 2017 data. The first Level-1 trigger requires ET > 100 GeV in a Δη × Δφ window of 0.8×0.8. The second is a Level-1 topological trigger requiring Σ ET > 111 GeV within a cone. The cone algorithm evaluates, for each jet region-of-interest (ROI, Δη × Δφ window of 0.8×0.8) i satisfying ETi > 15 GeV, Σjin i ETj for all jet ROIs j within a radius 1.0. The threshold of 111 GeV was chosen to give equal rate to the 0.8×0.8 square window. For jets with large numbers of subjets, this topological Level-1 trigger recovers efficiency with respect to the sliding-window algorithm. Statistical uncertainties only are shown. |
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Efficiencies for a Level-1 trigger requiring [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies for a Level-1 topological trigger requiring [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies are shown for a single-jet trigger with three different calibrations applied to jets in the ATLAS high-level trigger (HLT). Offline jets are selected with [1] ATLAS-CONF-2015-002, [2] ATLAS-CONF-2015-017. |
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Efficiencies are shown for an unprescaled 6-jet trigger with two different calibrations applied to jets in the ATLAS high-level trigger (HLT). Offline jets are selected with [1] ATLAS-CONF-2015-002, [2] ATLAS-CONF-2015-017. |
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This plot is superseded by the more recent one above ("Jet Trigger Efficiency Plots, Trimming and Mass Cuts in Large-R Jets (June 27, 2018)"). Efficiencies for HLT large-R single-jet triggers are shown as a function of the leading offline trimmed [1] jet [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies for HLT large-R triggers are shown as a function of the second leading offline trimmed [1] jet [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies for an HLT large-R trigger is shown as a function of the second leading offline trimmed [1] jet mass for jets with [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies are shown for an unprescaled single-jet trigger with three different calibrations applied to jets in the ATLAS high-level trigger (HLT). Offline jets are selected with [1] ATLAS-CONF-2015-002, [2] ATLAS-CONF-2015-017. |
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Efficiencies are shown for an unprescaled 6-jet trigger with two different calibrations applied to jets in the ATLAS high-level trigger (HLT). Offline jets are selected with [1] ATLAS-CONF-2015-002, [2] ATLAS-CONF-2015-017. |
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Efficiencies for HLT large-R single-jet triggers are shown as a function of the leading offline trimmed [1] jet [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies for HLT large-R di-jet triggers are shown as a function of the second leading offline trimmed [1] jet [1] D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming, JHEP 02 (2010) 084, [arXiv:0912.1342]. |
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Efficiencies are shown for the lowest un-prescaled single-jet trigger with (red, closed circules) and without (blue, open circles) the updated calibration applied to jets in the ATLAS high-level trigger (HLT), selecting jets with |
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Efficiency of the HLT_5j65_0eta240_L14J15 trigger as a function of the transverse momentum of the 5th leading offline jet. The trigger selection requires 5 jets with ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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Efficiency of the HLT_6j45_0eta240 trigger as a function of the transverse momentum of the 6th leading offline jet. The trigger selection requires 6 jets with ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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Efficiencies for L1 single-jet triggers are shown as a function of leading offline jet ![]() ![]() ![]() ![]() |
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Efficiencies for HLT single-jet triggers are shown as a function of leading offline jet ![]() ![]() ![]() ![]() |
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Efficiencies for forward L1 single-jet triggers are shown as a function of leading offline jet ![]() ![]() ![]() ![]() ![]() ![]() |
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Efficiencies for HLT single-jet triggers are shown as a function of leading offline jet ![]() ![]() ![]() ![]() |
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Efficiencies are shown for L1 n-jet triggers as a function of the ![]() ![]() ![]() ![]() ![]() |
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Efficiencies are shown for HLT N-jet triggers as a function of the ![]() ![]() ![]() ![]() ![]() |
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Relative jet response as a function of the jet pseudorapidity for anti-![]() ![]() ![]() ![]() |
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Comparison of central (![]() |
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Comparison of forward (![]() |
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Comparison of per-event isolated multi-jet trigger efficiency turn-on curves between data and MC simulation of dijet events using Pythia 8 for four typical threshold-multiplicity combinations from the full 2015 dataset. High level trigger (HLT) jets are formed from topo-clusters at the electromagnetic energy scale. The HLT jets are then calibrated to the hadronic scale by first applying a jet-by-jet area subtraction procedure followed by a jet energy scale weighting that is dependent on the HLT jet pt and eta. N is the number of jets above the specified threshold required to fire the trigger: 4 for HLT_4j45 and HLT_4j85 or 5 for HLT_5j45 and HLT_5j85. Isolation is enforced by requiring each of the N leading jets to be isolated by ![]() ![]() |
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Comparison of per-event ![]() ![]() ![]() |
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Comparison of central (![]() ![]() ![]() |
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Comparison of forward (![]() ![]() ![]() |
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Comparison of per-event isolated multi-jet trigger efficiency turn-on curves for three typical threshold-multiplicity combinations from the full 2015 dataset. Level-1 trigger (L1) jets are formed from Regions of Interest (RoIs), of size ![]() ![]() ![]() ![]() |
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Transverse momentum of HLT jets compared to offline jets, after correcting HLT jets for pile-up and applying dedicated MC-based jet energy scale correction factors. No data-MC in-situ correction is applied to offline jets. Events are selected using the HLT_j60 single jet triggers. HLT and offline jets are matched using ![]() ![]() |
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Transverse momentum of HLT jets compared to truth particle jets in Monte Carlo simulation, after correcting HLT jets for pile-up and applying dedicated MC-based jet energy scale correction factors. Events are selected using any of the HLT single jet triggers. HLT and truth jets are matched using ![]() ![]() |
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Distribution of the transverse momentum of leading HLT jets recorded in the data scouting stream (triggered by the unprescaled L1_J75 trigger), marked as Data Scouting jets, compared to the distribution of all leading HLT recorded by any of the single jet high level triggers in the main physics stream in a single run. Jets are required to have and ![]() ![]() |
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Trigger rate for the data scouting chain seeded by the Level-1 trigger J75 compared to the lowest unprescaled single jet trigger j360, which selects events where a trigger jet with ![]() |
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Trigger rate for the data scouting chain seeded by the Level-1 trigger J75 compared to the sum of the rates of all prescaled and unprescaled central single jet triggers, during a time range of a single run. Overlaps in the rate of the single jet triggers are considered negligible. | ![]() png eps
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Trigger rate for the data scouting chain seeded by the Level-1 trigger J75 compared to the sum of rates of all prescaled and unprescaled single jet triggers, of the jet trigger seeded by the same Level-1 trigger, and to the rate of the lowest unprescaled single jet trigger, during the time range of a single run. Overlaps in the rate of the single jet triggers are considered negligible. | ![]() png eps
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Transverse momentum of HLT jets compared to offline jets. Events are selected using the HLT_j100 trigger. HLT and offline jets are matched using ![]() ![]() ![]() ![]() ![]() |
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Transverse momentum response of HLT jets relative to offline jets. Events are selected using the HLT_j100 trigger. HLT and offline jets are matched using ![]() ![]() ![]() ![]() ![]() |
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Example of plots used in the jet trigger monitoring. The energy and azimuthal angle is shown for all HLT jets reconstructed in events retained by any jet trigger, which is useful to understand energy spikes in the calorimeter and are used in data-quality assessment. The HLT jets are corrected for pileup and have MC-based jet energy scale correction factors applied. The jets are recorded if they are above a minimal threshold in transverse momentum. The plot extends beyond φ=π due to the choice of binning in the monitoring histograms. | ![]() png pdf eps |
Example of jet trigger monitoring. The pseudo-rapidity and azimuthal angle is shown for all HLT jets reconstructed in events retained by any jet trigger, which is useful to understand energy spikes in the calorimeter and are used in data-quality assessment. The HLT jets are corrected for pileup and have MC-based jet energy scale correction factors applied. | ![]() png pdf eps |
Comparison of per-event trigger efficiency turn-on curves between data and MC simulation using Pythia 8 for three typical thresholds from June 2015. High level trigger (HLT) jets are formed from topo-clusters at the electromagnetic energy scale. The HLT jets are then calibrated to the hadronic scale by first applying a jet-by-jet area subtraction procedure followed by a jet energy scale weighting that is dependent on the HLT jet pt and eta. Each efficiency is determined using events retained with a lower threshold trigger that is found to be fully efficient in the phase space of interest. | ![]() png pdf |
Assessment of the spatial dependence of the per-jet trigger efficiency for a single high level trigger (HLT) jet threshold of 25 GeV in the central region of the ATLAS calorimeters ( ABS(eta) < 3.2) using data collected in June 2015. The HLT jets are formed from topo-clusters at the electromagnetic energy scale. The jets are then calibrated to the hadronic scale by first applying a jet-by-jet area subtraction procedure followed by a jet energy scale weighting that is dependent on the HLT jet pt and eta. The efficiency is evaluated for an offline jet pT selection of 30 GeV. | ![]() png pdf |
Assessment of the spatial dependence of the per-jet trigger efficiency for a single high level trigger (HLT) jet threshold of 25 GeV in the forward region of the ATLAS calorimeters (3.2 < ABS(eta) < 4.4) using data collected in June 2015. The HLT jets are formed from topo-clusters at the electromagnetic energy scale. The jets are then calibrated to the hadronic scale by first applying a jet-by-jet area subtraction procedure followed by a jet energy scale weighting that is dependent on the HLT jet pt and eta. The efficiency is evaluated for an offline jet pT selection of 30 GeV. | ![]() png pdf |
Calorimeter Partial Scan data readout scheme: blue dots represent the Level-1 jet positions in a particular simulated event. In the Partial Scan scheme, the ATLAS data acquisition system reads out only the calorimeter data from regions around the Level-1 jet positions, corresponding to the green rectangles in the figure, and prepares three-dimensional clusters (topological clusters) from these data alone. This is followed by a jet finding step using topological clusters as input. Thus the jet finding in the Partial Scan scheme runs as if in a single-pass scan over the full calorimeter, but with the detector data suppressed outside the regions defined by Level-1 jet positions. Contrary to previous Region-by-Region Scan the Partial Scan also removes any overlap between regions. In this example the green boxes have a size of eta x phi = 1x1. | ![]() png pdf eps |
Number of calorimeter cells read out in the Partial Scan and Full Scan readout schemes used by the jet trigger. The black line represents the Full Scan readout scheme, where the full calorimeter data is read out by the ATLAS data acquisition system. Calorimeter cells read out by the Partial Scan scheme are represented for two alternative settings: the red dotted line corresponds to reading out regions of eta x phi = 1x1 around the Level-1 jet positions and the blue dashed line corresponds to geometrical regions of eta x phi = 1.5x1.5. The data sample used consist of QCD di-jet events with leading-jet transverse momentum above 20 GeV and 40 simultaneous interactions per bunch-crossing. | ![]() png pdf eps |
Comparison of the time taken to retrieve the calorimeter cells in the Full Scan and the Partial Scan readout schemes used in the jet trigger. The black line represents the full calorimeter readout (Full Scan). The partial calorimeter readout (Partial Scan) is represented for two alternative settings: the red dotted line corresponds to reading out regions of eta x phi = 1x1 around the Level-1 jet positions and the blue dashed line corresponds to geometrical regions of eta x phi = 1.5x1.5 around the Level-1 jets. The data sample used consist of QCD di-jet events with leading-jet transverse momentum above 20 GeV and 40 simultaneous interactions per bunch-crossing. As the Partial Scan has to select the cells to retrieve, the readout may take longer than in Full Scan when the number of cells to retrieve increase, as can be seen in the Partial Scan with regions of 1.5x1.5. | ![]() png pdf eps |
Processing time for cluster reconstruction using the ATLAS Topological Cluster algorithm, from calorimeter cells read out using the Partial Scan and the Full Scan schemes employed by the jet trigger. The measured times include the clustering, splitting, cluster correction and moments calculation steps. The black line represents the full calorimeter readout (Full Scan), the partial calorimeter readout (Partial Scan) is represented for two alternative settings: the red dotted line corresponds to reading out regions of eta x phi = 1x1 around the Level-1 jet positions and the blue dashed line corresponds to reading out geometrical regions of eta x phi = 1.5x1.5 around the Level-1 jets. The data sample used consist of QCD di-jet events with leading-jet transverse momentum above 20 GeV and a mean of 40 simultaneous interactions per bunch-crossing. | ![]() png pdf eps |
Jet transverse energy spectrum transposed to the full calorimeter readout (Full Scan) transverse energy scale, E_{T}^{FS}, for High Level Trigger jets matching jets identified by Level-1 (within a radius 1 around the Level-1 jet in the eta x phi plane). The black line represents the Full Scan readout scheme, where all calorimeter cells contribute to jet finding. For the partial calorimeter readout scheme (Partial Scan) the transverse energy of the closest Full Scan jet was used. Partial Scan histograms are represented for two alternative settings: the red dotted line corresponds to reading out regions of eta x phi = 1x1 around the Level-1 jet positions and the blue dashed line corresponds to reading out geometrical regions of eta x phi = 1.5x1.5 around the Level-1 jets. The data sample used consist of QCD di-jet events with leading-jet transverse momentum above 20 GeV and 40 simultaneous interactions per bunch-crossing. | ![]() png pdf eps |
Ratio between the Partial Scan (PS) and Full Scan (FS) jets, for High Level Trigger jets most closely matching jets identified at Level-1 (within a radius 1 around the Level-1 jet in the eta x phi plane), represented versus the jet transverse energy for Full Scan jets, E_{T}^{FS}. For Partial Scan jets, the transverse energy of the closest Full Scan jet was used to calculate the efficiency. Partial Scan efficiencies are represented for two alternative settings: the red dotted line corresponds to reading out regions of eta x phi = 1x1 around the Level-1 jet positions and the blue dashed line corresponds to reading out geometrical regions of eta x phi = 1.5x1.5 around the Level-1 jets. The statistical error bars represent the square root of the sum of squares of weights. The error bars variation reflects the combination of the three data sets used, each data set represents a different energy region and have different weights. The data sample used consist of QCD di-jet events with leading-jet transverse momentum above 20 GeV and 40 simultaneous interactions per bunch-crossing. | ![]() png pdf eps |
Relative transverse energy difference between jets reconstructed using the Partial Scan (PS) and Full Scan (FS) calorimeter readout schemes, represented versus the Full Scan jet transverse energy, E_{T}^{FS}, for High Level Trigger jets matching jets identified at Level-1 (within a radius 1 around the Level-1 jet in the eta x phi plane). Partial Scan jets are displayed for two alternative settings: the red dotted line corresponds to reading out regions of eta x phi = 1x1 around the Level-1 jet positions and the blue dashed line corresponds to reading out geometrical regions of eta x phi = 1.5x1.5 around the Level-1 jets. The error bars represent the standard error on the mean. The data sample used consist of QCD di-jet events with leading-jet transverse momentum above 20 GeV and 40 simultaneous interactions per bunch-crossing. | ![]() png pdf eps |
Per-jet efficiency turn-on curves in Monte Carlo (MC) simulation for multiple Phase I upgrade Level-1 jet trigger options. A global feature extraction (gFEX) reconstruction algorithm (closed red markers, left) from the TDAQ Phase I Upgrade Technical Design Report (TDR) CERN-LHCC-2013-018, ATLAS-TDR-023] with a 140 GeV threshold is compared to full simulation of the Run I Level-1 calorimeter jet trigger (open blue markers, left and right) with a 100 GeV threshold. The gFEX reconstruction implements a simple seeded cone algorithm with a nominal radius of R=1.0 and with a seed selection of 15 GeV applied to calorimeter towers with area 0.2x0.2 in eta-phi. The 140 GeV gFEX trigger threshold is chosen to match the L1_J100 single subjet turn-on curve. Pair-produced top quark MC simulation samples are simulated with a pile-up level equivalent to an average number of interactions per bunch-crossing, or |
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Event-level Level-1 trigger efficiency turn-on curves as a function of the offline trimmed jet pT for (left) ttbar events and (right) WH -> lnu+bbbar events. Both processes are simulated with a pile-up level equivalent to an average number of interactions per bunch-crossing, or |
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Correlation between the offline event energy density (rho) ATLAS-CONF-2013-083] on the horizontal axis and a simplified calculation of the event energy density in the Level-1 calorimeter trigger using the gFEX. (left) The correlation for ttbar events and (right) ZH -> nunu+bbbar events events. Both Monte Carlo simulation samples are simulated with a pile-up level equivalent to an average number of interactions per bunch-crossing ( |
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The efficiency for L2 full scan at electromagnetic (EM) calibration scale and hadronic (EM+JES) calibration scale scale. The efficiency is plotted as a function of the leading offline jet pT. The minimum jet ET thresholds are 15 GeV for the EM-scale trigger, and 35 GeV for the EM+JES-scale trigger, so that both curves attain 99% efficiency point for same offline jet pT of 60 GeV. The rate for this EM+JES trigger is 18% smaller than the one for the EM trigger. | The efficiency for L1 (0.8x0.8 sliding window) and L2 full scan (anti-kT R=0.4 with trigger towers as inputs) jets to satisfy a six jet trigger (trigger run offline) in events where at least six anti-kT R=0.4 jets have been identified offline with ABS(eta) < 2.8, ET > 30 GeV (these events were pre-selected using a four jet trigger). The efficiency is plotted as a function of the sixth offline jet ET. The L2 full scan uses as input to the anti-kT algorithm all trigger towers read-out at L1, no only the ones that were accepted by the L1 selection, allowing for a reduction of the L1 inefficiency, which is mostly due to the sliding window algorithm. | The efficiency for L2 full scan and L2 partial scan (anti-kT R=0.4) jets to satisfy a six jet trigger (trigger run offline) in events where at least six anti-kT R=0.4 jets have been identified offline with ABS(eta) < 2.8, ET > 30 GeV (these events were pre-selected using a four jet trigger). The efficiency is plotted as a function of the sixth offline jet ET. The L2 full scan uses as input to the anti-kT algorithm the trigger towers from the complete detector. The L2 partial scan used as input to the anti-kT algorithm the calorimeter cells only from those regions of the detector in which significant jet activity was found by the L2 full scan. |
Efficiency of the primary HLT jet trigger used for the 2011 heavy ion run. The efficiency was evaluated using the data from the PbPb collisions at \sqrt{s_{NN}}=2.76 TeV corresponding to an integrated luminosity of 2.4 ub-1. The HLT trigger algorithm is anti-kt R=0.2 with a threshold of ET=20 GeV. The HLT trigger algorithm is seeded by events with total transverse energy greater than 10 GeV identified by the Level 1 trigger. Efficiency is evaluated with respect to offline anti-kt R=0.2 jets. Both the offline and HLT jets are at the electromagnetic scale. | ![]() |
Jet position resolution (in pseudorapidity) of the primary HLT jet trigger used for the 2011 heavy ion run. The jet position was evaluated using the data from the PbPb collisions at \sqrt{s_{NN}}=2.76 TeV corresponding to an integrated luminosity of 2.4 ub-1. The HLT trigger algorithm is anti-kt R=0.2 with a threshold of ET=20 GeV. The HLT trigger algorithm is seeded by events with total transverse energy greater than 10 GeV identified by the Level 1 trigger. The jet position resolution is evaluated with respect to offline anti-kt R=0.2 jets. | ![]() [eps] |
Figure 1: Efficiency for various Level-1 trigger chains in data and Pythia and Herwig Monte Carlo, calculated using the bootstrap method. For data, the efficiency is computed with respect to events taken by an independent trigger 100% efficient in the relevant region. | ![]() [pdf] |
Figure 2: Efficiency for various Level-2 trigger chains in data and Pythia and Herwig Monte Carlo, calculated using the bootstrap method. For data, the efficiency is computed with respect to events taken by a Level-1 trigger 100% efficient in the relevant region. | ![]() [pdf] |
Figure 3: Efficiency for various Event Filter trigger chains in data and Pythia and Herwig Monte Carlo, calculated using the bootstrap method. For data, the efficiency is computed with respect to events taken by a Level-2 trigger 100% efficient in the relevant region. | ![]() [pdf] |
Figure 4: Efficiency for low-pT Event Filter trigger chains in data and Pythia and Herwig Monte Carlo, calculated using the bootstrap method. For data, the efficiency is computed with respect to events taken by a Level-2 trigger 100% efficient in the relevant region. In thsese chains, events from the prescaled random trigger are input directly to Event Filter, without having to pass L1 nor L2, allowing to considerably lower the threshold below those of full efficiency of the previous levels. | ![]() [pdf] |
Figure 5: Efficiency for high-pT Event Filter trigger chains in data and Pythia and Herwig Monte Carlo, calculated using the bootstrap method. For data, the efficiency is computed with respect to events taken by a Level-2 trigger 100% efficient in the relevant region. These Event-Filter chains are all seeded by the same Level-1 and Level-2 combination. | ![]() [pdf] |
Figure 6: Offset between transverse energies of jets at Event Filter (where jet energies are the sum of the electromagnetic and hadronic components) and offline (where a proper compensation for hadronic energy is applied) as a funciton of the offline jet pseudorapidity, for jets with offline pT > 100 GeV | ![]() [pdf] |
Figure 7: Transverse energy resolution as a function of the jet offline pseudo-rapidity for jets with offline pT > 100 GeV | ![]() [pdf] |
Figure 8: Offset between transverse energies of jets at Event Filter (where jet energies are the sum of the electromagnetic and hadronic components) and offline (where a proper compensation for hadronic energy is applied) as a funciton of the offline jet transverse momentum, for jets with offline pseudo-rapidity between 0 and 0.75 | ![]() [pdf] |
Figure 9: Transverse energy resolution as a function of jet offline transverse momentum, for jets with offline pseudo-rapidity between 0 and 0.75 | ![]() [pdf] |
Ratio of the per-jet L1.5 trigger efficiency as a function of the minimum separation between any two offline anti-kt jets having ET>40 GeV. Only statistical uncertainties are shown. The rise at low DeltaR indicates that L1.5 jet finding was more efficient than L1 jet finding for event configurations with several nearby jets. The result is independent of the tower size. The trigger was re-run offline on a sample collected with a random trigger. Jet finding at L1 used a sliding window algorithm on 0.2x0.2 towers. The L1.5 jet trigger ran within L2 but used either 0.1x0.1 or 0.2x0.2 towers from L1 and applied the anti-kt jet algorithm. | ![]() [ps] |
Jet resolution in eta for trigger jets as compared to geometrically-matched offline anti-kt jets. Only statistical uncertainties are shown. The trigger was re-run offline on a sample collected with a random trigger. Jet finding at L1 used a sliding window algorithm on 0.2x0.2 towers. The L1.5 jet trigger ran within L2 but used either 0.1x0.1 or 0.2x0.2 towers from L1 and applied the anti-kt jet algorithm. Jet finding at L2 used the cone jet algorithm but with the full calorimeter segmentation. | ![]() [ps] |
Schematic illustrating the jet trigger implementation in 2011. Jets were identified at Level 1 (L1) using 0.2x0.2 towers (nominal) with a sliding windows algorithm. In the original scheme, jets were found at Level 2 (L2) with a simple cone jet algorithm, seeded by the L1 jets (region-of-interest or ROI), using noise-suppressed calorimeter cells. An unseeded anti-kT jet algorithm was run over topological clusters formed from calorimeter cells at Event Filter (EF) independent of any jets found at L1 or L2. In the new scheme (added during the 2011 Heavy Ion run), jets could also be found at L2 with an unseeded anti-kT jet algorithm using either the 0.1x0.1 (egamma/tau) or 0.2x0.2 (jet/Etmiss) towers from the L1 calorimeter system. These L1.5 jets could be used in L2 trigger decisions and could seed L2 ROI-based jet finding. | ![]() [ps] |
The time taken to read out the tower information from the Level 1 calorimeter readout system. The black solid line shows the time taken to read out 0.2x0.2 (jet/Etmiss) towers and the blue dashed line shows the time for 0.1x0.1 (egamma/tau) towers. The timing was measured during 2011 Pb-Pb collisions at sqrt{s_{NN}}=2.76 TeV. The nominal time limit at this stage of the trigger is about 40 ms. | ![]() [eps] |
The time taken to find jets using the anti-kT jet algorithm with a distance parameter R=0.4. The black solid line shows the time taken for 0.2x0.2 (jet/Etmiss) towers and the blue dashed line shows the time for 0.1x0.1 (egamma/tau) towers. The timing was measured during 2011 Pb-Pb collisions at sqrt{s_{NN}}=2.76 TeV. The nominal time limit at this stage of the trigger is about 40 ms. | ![]() [eps] |
The jet position resolution (in pseudorapidity) of the L1, L1.5 and L2 jet triggers in 2011 proton-proton collisions (trigger run offline). The jet finding algorithm for L1 is a 0.8x0.8 sliding window, for L1.5 it is anti-kT with R=0.4 and for L2 a three-iteration cone R=0.4 seeded by a L1 jet. The jet position resolution is evaluated with respect to offline anti-kT R=0.4 jets. The offset toward high Delta eta observed at L1 is an artefact of how L1 position is recorded. | ![]() [eps] |
The efficiency for L1 (0.8x0.8 sliding window) and L1.5 (anti-kT R=0.4) jets to satisfy a six jet trigger (trigger run offline) in events where at least six anti-kT R=0.4 jets have been identified offline with ABS(eta) <2.8, ET>30 GeV (these events were pre-selected using a four jet trigger). The efficiency is plotted as a function of the sixth offline jet ET. | ![]() [eps] |
#EffEFLowComp The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger for three choices of threshold. The EF-jet conditions were applied to random-triggered events. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities and in two different data-taking scenarios: before (empty markers) and after (full markers) pile-up noise suppression was applied to EF-jets. The overall 99% efficiency point improved by ~5 GeV by suppressing the pile-up noise. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger for three choices of threshold. The EF-jet conditions were applied to random-triggered events. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. The figure is identical to the one shown in Fig.~ #EffEFLowComp, but only the results with pile-up noise suppression are shown. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
#EffEF40Comp The efficiency for anti-kt jets with R=0.4 to satisfy Level 1 (L1), Level 2 (L2), and the Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities and in two different data-taking scenarios: before (empty markers) and after (full markers) pile-up noise suppression was applied to both L2- and EF-jets. The overall 99\% efficiency point improved by ~5 GeV by suppressing the pile-up noise. The shift due to noise suppression is larger at L2 than at EF since the EF jets are based on topological clusters of calorimeter cells and already included some noise suppression. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy Level 1 (L1), Level 2 (L2), and the Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. The figure is identical to the one shown in Fig. #EffEF40Comp, but only the results with pile-up noise suppression are shown. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
#EffEF55Comp The efficiency for anti-kt jets with R=0.4 to satisfy Level 1 (L1), Level 2 (L2), and the Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with forward rapidities and in two different data-taking scenarios: before (empty markers) and after (full markers) pile-up noise suppression was applied to both L2- and EF-jets. The overall 99\% efficiency point improved by ~2 GeV by suppressing the pile-up noise. The shift due to noise suppression is larger at L2 than at EF since the EF jets are based on topological clusters of calorimeter cells and already included some noise suppression. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy Level 1 (L1), Level 2 (L2), and the Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with forward rapidities. The figure is identical to the one shown in Fig. #EffEF55Comp, but only the results with pile-up noise suppression are shown. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
#EffEF75Comp The efficiency for anti-kt jets with R=0.4 to satisfy Level 1 (L1), Level 2 (L2), and the Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities and in two different data-taking scenarios: before (empty markers) and after (full markers) pile-up noise suppression was applied to both L2- and EF-jets. The overall 99\% efficiency point improved by ~5 GeV by suppressing the pile-up noise. The shift due to noise suppression is larger at L2 than at EF since the EF jets are based on topological clusters of calorimeter cells and already included some noise suppression. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy Level 1 (L1), Level 2 (L2), and the Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. The figure is identical to the one shown in Fig. #EffEF75Comp, but only the results with pile-up noise suppression are shown. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger for five choices of threshold. The EF-jet conditions were applied to events selected with lower-ET jet triggers. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. These data correspond to the period when pile-up noise was suppressed during L2 and EF jet finding. (Jet energies in the trigger are measured at the electromagnetic scale.) | ![]() [eps] |
The efficiency for anti-kT jets with R=0.4 to satisfy the Level 1 trigger with a 5 GeV threshold as a function of the calibrated offline jet pT. Trigger jets were evaluated at electromagnetic scale. The efficiency was extracted using a minimum bias trigger. Data are indicated by the closed black circles; results from the Pythia simulation are represented by the open red circles. | ![]() [png] [eps] |
The efficiency for anti-kT jets with R=0.4 to satisfy the Level 1 trigger with a 5 GeV threshold as a function of the offline jet eta for jets with calibrated pT between 40 and 60 GeV. Trigger jets were evaluated at electromagnetic scale. The efficiency was extracted using a minimum bias trigger. Data are indicated by the closed black circles; results from the Pythia simulation are represented by the open red circles. The dips in the efficiency near ABS(eta) =1.5 are in the transition region between the barrel and end-cap calorimeters. | ![]() [png] [eps] |
The efficiency for anti-kT jets with R=0.4 to satisfy the Level 1 trigger with a 5 GeV threshold as a function of the offline jet eta for jets with calibrated pT above 60 GeV. Trigger jets were evaluated at electromagnetic scale. The efficiency was extracted using a minimum bias trigger. Data are indicated by the closed black circles; results from the Pythia simulation are represented by the open red circles. | ![]() [png] [eps] |
The efficiency for anti-kT jets with R=0.4 to satisfy the Level 1 trigger with a 15 GeV threshold as a function of the calibrated offline jet pT. Trigger jets were evaluated at electromagnetic scale. The efficiency was extracted using a minimum bias trigger. Data are indicated by the closed black circles; results from the Pythia simulation are represented by the open red circles. | ![]() [png] [eps] |
The efficiency for an event with at least three anti-kT jets reconstructed with R=0.4, plotted as a function of the calibrated pT of the third jet, to have fired a Level 1 trigger that required at least three Level 1 jets which satisfied 5 GeV thresholds. Trigger jets were evaluated at electromagnetic scale. The efficiency was extracted using a minimum bias trigger. Data are indicated by the closed black circles; results from the Pythia simulation are represented by the open red circles. | ![]() [png] [eps] |
Delta eta between an offline anti-kT R=0.4 jet and the nearest Level 2 trigger jet. Data are indicated by the points; results from the Pythia dijet simulation are represented by the yellow filled histogram. The High Level Trigger, which includes Level 2, was not needed to reduce the rate for this data set and did not contribute to the trigger decision. | ![]() [png] [eps] |
The efficiency for anti-kT jets with R=0.4 to satisfy the Level 2 trigger with a 30 GeV threshold as a function of the calibrated offline jet p_T. Trigger jets were evaluated at electromagnetic scale. No Level 1 trigger requirement was applied for this distribution. Data are indicated by the closed black circles; results from the Pythia simulation are represented by the open red circles. The High Level Trigger, which includes Level 2, was not needed to reduce the rate for this data set and did not contribute to the trigger decision. | ![]() [png] [eps] |
Fig. 2a: Combined L1+L2 jet trigger efficiency as a function of reconstructed jet pT for anti-kt jets with R = 0.6 in the central region ABS(y) < 0.3 (a) and barrel-endcap transition region 1.2 < ABS(y) < 2.1 (b), shown for different L2 trigger thresholds. The trigger thresholds are at the electromagnetic scale, while the jet pT is at the calibrated scale (see Sec. 6.3). The highest trigger chain does not apply a threshold at L2, so its L1 threshold is listed. | ![]() ![]() [eps] ![]() |
Fig. 2b: Combined L1+L2 jet trigger efficiency as a function of reconstructed jet pT for anti-kt jets with R = 0.6 in the central region ABS(y) < 0.3 (a) and barrel-endcap transition region 1.2 < ABS(y) < 2.1 (b), shown for different L2 trigger thresholds. The trigger thresholds are at the electromagnetic scale, while the jet pT is at the calibrated scale (see Sec. 6.3). The highest trigger chain does not apply a threshold at L2, so its L1 threshold is listed. | ![]() ![]() [eps] ![]() |
Fig. 3a: Combined L1+L2 jet trigger efficiency as a function of reconstructed jet pT for anti-kt jets with R = 0.6 in the HEC-FCal transition region 2.8 < ABS(y) < 3.6 (a) and FCal region 3.6 < ABS(y) < 4.4 (b), shown for various L2 trigger thresholds. Due to the presence of a dead FCal trigger tower, which spans 0.9% of the (eta;phi)-acceptance, the efficiency is not expected to reach 100%. This inefficiency is accounted for in the measurement. | ![]() ![]() [eps] ![]() |
Fig. 3b: Combined L1+L2 jet trigger efficiency as a function of reconstructed jet pT for anti-kt jets with R = 0.6 in the HEC-FCal transition region 2.8 < ABS(y) < 3.6 (a) and FCal region 3.6 < ABS(y) < 4.4 (b), shown for various L2 trigger thresholds. Due to the presence of a dead FCal trigger tower, which spans 0.9% of the (eta;phi)-acceptance, the efficiency is not expected to reach 100%. This inefficiency is accounted for in the measurement. | ![]() ![]() [eps] ![]() |
The efficiency for passing the primary first-level trigger as a function of the dijet invariant mass, mjj. The uncertainties are statistical. | ![]() ![]() [eps] ![]() |
The invariant mass of the leading two reconstructed jets for events passing L1_J55 (red) and L1_J95 (black), after requiring the pt of the leading jet to be greater than 150 GeV. | ![]() ![]() [eps] ![]() |
The efficiency for passing L1_J95 using L1_J55 as the baseline. We plot the ratio of events passing L1_J55 and L1_J95 to events passing L1_J55. Note the y-axis starts from 95%. | ![]() ![]() [eps] ![]() |
Trigger mjj efficiency curves, for the highest threshold triggers used for the angular analysis: Periods A-F L1 J95. | ![]() ![]() [eps] ![]() |
Trigger mjj efficiency curves, for the highest threshold triggers used for the angular analysis: Periods G-I EF L1J95 NoAlg. | ![]() ![]() [eps] ![]() |
J95 trigger efficiency (per event) for anti-kt R=0.6 jets using the J30 trigger as a reference. The results are compared to Pythia QCD dijet Monte Carlo samples without pile-up and with in-time pile-up overlaid with the signal interaction. | ![]() ![]() [eps] ![]() |
J95 trigger efficiency (per event) for anti-kt R=1.0 jets using the J30 trigger as a reference. The results are compared to Pythia QCD dijet Monte Carlo samples without pile-up and with in-time pile-up overlaid with the signal interaction. | ![]() ![]() [eps] ![]() |
J95 trigger efficiency (per event) for Cambridge-Aachen R=1.2 jets using the J30 trigger as a reference. The results are compared to Pythia QCD dijet Monte Carlo samples without pile-up and with in-time pile-up overlaid with the signal. | ![]() ![]() [eps] ![]() |
J95 trigger efficiency (per event) for Cambridge-Aachen R=1.2 jets after splitting and filtering using the J30 trigger as a reference. The results are compared to Pythia QCD dijet Monte Carlo samples without pile-up and with in-time pile-up overlaid with the signal interaction. | ![]() ![]() [eps] ![]() |
J95 using J30 as a reference, per event efficiencies for events with an anti-kt R=0.6 jet with pT > 300 GeV. The efficiency of the trigger is shown as a function of mass. | ![]() ![]() [eps] ![]() |
J95 using J30 as a reference, per event efficiencies for events with an anti-kt R=1.0 jet with pT > 300 GeV. The efficiency of the trigger is shown as a function of mass. | ![]() ![]() [eps] ![]() |
J95 using J30 as a reference, per event efficiencies for events with an Cambridge-Aachen R=1.2 jet with pT > 300 GeV. The efficiency of the trigger is shown as a function of mass. | ![]() ![]() [eps] ![]() |
J95 using J30 as a reference, per event efficiencies for events with an Cambridge-Aachen R=1.2 jet after splitting and filtering with pT > 300 GeV. The efficiency of the trigger is shown as a function of mass. | ![]() ![]() [eps] ![]() |
The efficiency for anti-kt jets with R=0.4 to satisfy the Level 1 (L1), Level 2 (L2), and Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with forward rapidities. (Jet energies are measured at electromagnetic scale in the trigger.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger for three choices of threshold. The EF-jet conditions were applied to random-triggered events. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. (Jet energies are measured at electromagnetic scale in the trigger.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger for three choices of threshold. The EF-jet conditions were applied to random-triggered events. The efficiency is plotted as a function of the offline calibrated jet ET for jets with forward rapidities. (Jet energies are measured at electromagnetic scale in the trigger.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger for three choices of threshold. The EF-jet conditions were applied to events selected with lower-ET jet triggers. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. (Jet energies are measured at electromagnetic scale in the trigger.) The efficiency for the Level 1 (L1) and Level 2 (L2) thresholds are shown in <ahref="/twiki/pub/AtlasPublic/JetTriggerPublicResults/EF_j10_j15_j20.eps">[eps] together with the efficiency for the 100 GeV EF threshold. | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Event Filter (EF) inclusive jet trigger binned in the number of reconstructed $pp$ interactions in the triggered events. The EF-jet conditions were applied to events selected with a lower ET jet trigger (shown in Fig. [eps]). The efficiency is plotted as a function of the offline calibrated jet E_T for jets with forward rapidities where the effects of multiple overlapping $pp$ interactions are expected to be greatest. (Jet energies are measured at electromagnetic scale in the trigger.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Level 1 (L1), Level 2 (L2), and Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while keeping acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. (Jet energies are measured at electromagnetic scale in the trigger.) | ![]() [eps] |
The efficiency for anti-kt jets with R=0.4 to satisfy the Level 1 (L1), Level 2 (L2), and Event Filter (EF) inclusive jet trigger for a single L1->L2->EF trigger chain. Different thresholds are applied at each level of the trigger to increase rejection of events while maintaining acceptance for events with high probability of satisfying the overall jet trigger. The efficiency is plotted as a function of the offline calibrated jet ET for jets with central rapidities. (Jet energies are measured at electromagnetic scale in the trigger.) | ![]() [eps] |
Inclusive-jet L1 trigger efficiency as a function of reconstructed jet pT for jets identified using the anti-kt algorithm with R = 0.4. | ![]() ![]() [eps] ![]() |
Inclusive-jet L1 trigger efficiency as a function of reconstructed jet pT for jets identified using the anti-kt algorithm with R = 0.4. | ![]() ![]() [eps] ![]() |
Et distribution of Level 1 trigger jets at the electromagnetic scale, for events selected in a single ATLAS run from April 2010 by the Minimum Bias trigger, expected to be 100% efficient for jetevents. The three colours represent jets selected by the three lowest trigger thresholds of 5, 10 and 15 GeV, respectively. | ![]() [gif] |
Pseudorapidity difference between Level 1 trigger and offline jets, reconstructed with the AntiKt algorithm (cone size 0.6) from a single run taken by ATLAS in April 2010. The three colours represent the three lowest jet trigger thresholds of 5, 10 and 15 GeV at the electromagnetic scale | ![]() [gif] |
Absolute value of the azimuthal angle difference between Level 1 trigger and offline jets, reconstructed with the AntiKt algorithm (cone size 0.6) from a single run taken by ATLAS in April 2010. The three colours represent the three lowest jet trigger thresholds of 5, 10 and 15 GeV at the electromagnetic scale. The rise for values close to π corresponds to the second jet (all combinations of offline and trigger jets are included) | ![]() [gif] |
L1 Efficiency for the trigger selecting jets above 5 counts (~ 5 GeV) as a function of the offline jet pT at the EM scale. The turn-on is shown for data (black triangle points) and MC simulations (red circle points). The following fit function has been used: ![]() The fit parameter for MC: μ = (12.6 + 0.7) GeV, σ = (3.6 + 0.4) GeV, ε = 0.96 + 0.02. |
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L1 Efficiency for the trigger selecting jets above 10 counts (~ 10 GeV) as a function of the offline jet pT at the EM scale. The turn-on is shown for data (black triangle points) and MC simulations (red circle points). The following fit function has been used: ![]() The fit parameter for MC: μ = (18.3 + 1.0) GeV, σ = (3.6 + 0.4) GeV, ε = 0.92 + 0.03. |
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L1 Efficiency for the trigger selecting Electromagnetic clusters in the forward region ( ABS(pseudorapidity) >3.2) above 3 counts (~ 3 GeV) as a function of the raw offline cluster transverse energy. The turn-on is shown for data (black triangle points) and MC simulations (red circle points). | ![]() |