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Properties of Jets and Inputs to Jet Reconstruction and Calibration with the ATLAS Detector Using Proton-Proton Collisions at sqrts(s) = 7 TeV ATLAS-CONF-2010-053 17 July 2010
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| Main document (CDS record) - internal | pdf from CDS | |
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| Abstract | ||
| Preliminary results are presented on the properties and calibration of jets in the ATLAS detector at the LHC using a sample of proton-proton collisions at a center-of-mass energy of $\sqrt{s}=7$ TeV. Comparisons of multiple inputs to jet reconstruction and calibration are studied, as well as the properties of charged tracks in jets and the internal jet structure. For some quantities of interest, the effect of the noise modeling is presented using inputs to jet finding with and without noise suppression. The inputs to the different jet calibration schemes developed in ATLAS are studied, and the corrections applied by the calibration schemes validated with data. These studies will help the Monte Carlo tuning effort and provide the first steps towards the successful commissioning of jet calibration in ATLAS. | ||
| Figures | ||
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Figure 01a: Topological cluster jets Transverse momentum (p_T) distributions using the Monte Carlo-based p_T and ^jet calibration for three different input constituents. png (344kB) eps (11kB) pdf (5kB) |
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Figure 01b: Noise-suppressed tower jets Transverse momentum (p_T) distributions using the Monte Carlo-based p_T and ^jet calibration for three different input constituents. png (348kB) eps (11kB) pdf (5kB) |
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Figure 01c: Ghost-tower jets Transverse momentum (p_T) distributions using the Monte Carlo-based p_T and ^jet calibration for three different input constituents. png (344kB) eps (17kB) pdf (5kB) |
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Figure 02a: Topological cluster jets y^ jet distributions for jets above p_T^ jet >30 GeV and for three different input constituents: (a) topological clusters, (b) towers with topological noise suppression and (c) towers without noise suppression. png (334kB) eps (22kB) pdf (7kB) |
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Figure 02b: Noise-suppressed tower jets y^ jet distributions for jets above p_T^ jet >30 GeV and for three different input constituents: (a) topological clusters, (b) towers with topological noise suppression and (c) towers without noise suppression. png (337kB) eps (22kB) pdf (7kB) |
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Figure 02c: Ghost-tower jets y^ jet distributions for jets above p_T^ jet >30 GeV and for three different input constituents: (a) topological clusters, (b) towers with topological noise suppression and (c) towers without noise suppression. png (314kB) eps (19kB) pdf (7kB) |
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Figure 03a: Number of towers per jet Number of constituents (top) in jets built with noise-suppressed towers (left) and topological clusters (right), compared between data and Monte Carlo simulation for central jets (|y^ jet |<0.3). The variation of the constituent multiplicity as a function of y^ jet is also shown (bottom). png (352kB) eps (13kB) pdf (7kB) |
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Figure 03b: Number of clusters per jet Number of constituents (top) in jets built with noise-suppressed towers (left) and topological clusters (right), compared between data and Monte Carlo simulation for central jets (|y^ jet |<0.3). The variation of the constituent multiplicity as a function of y^ jet is also shown (bottom). png (357kB) eps (15kB) pdf (7kB) |
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Figure 03c: Number of towers vs. y^ jet Number of constituents (top) in jets built with noise-suppressed towers (left) and topological clusters (right), compared between data and Monte Carlo simulation for central jets (|y^ jet |<0.3). The variation of the constituent multiplicity as a function of y^ jet is also shown (bottom). png (351kB) eps (12kB) pdf (7kB) |
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Figure 03d: Number of clusters vs. y^ jet Number of constituents (top) in jets built with noise-suppressed towers (left) and topological clusters (right), compared between data and Monte Carlo simulation for central jets (|y^ jet |<0.3). The variation of the constituent multiplicity as a function of y^ jet is also shown (bottom). png (360kB) eps (13kB) pdf (8kB) |
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Figure 04a: Track multiplicity (p_T^ track > 0.5 GeV) Distribution of the number of charged tracks (N_track) matched to the calorimeter jet for both (a) the nominal p_T^ track >0.5 GeV requirement and (b) an increased p_T^ track >1 GeV selection. png (381kB) eps (15kB) pdf (6kB) |
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Figure 04b: Track multiplicity (p_T^ track > 1 GeV) Distribution of the number of charged tracks (N_track) matched to the calorimeter jet for both (a) the nominal p_T^ track >0.5 GeV requirement and (b) an increased p_T^ track >1 GeV selection. png (369kB) eps (13kB) pdf (6kB) |
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Figure 05a: N_track vs. p_T^ jet (p_T^ track > 0.5 GeV) Correlation of the number of charged tracks (N_track) matched to the calorimeter jet with p_T^ jet for both (a) the nominal p_T^ track >0.5 GeV requirement and (b) an increased p_T^ track >1 GeV selection. png (320kB) eps (11kB) pdf (4kB) |
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Figure 05b: N_track vs. p_T^ jet (p_T^ track > 1 GeV) Correlation of the number of charged tracks (N_track) matched to the calorimeter jet with p_T^ jet for both (a) the nominal p_T^ track >0.5 GeV requirement and (b) an increased p_T^ track >1 GeV selection. png (321kB) eps (11kB) pdf (4kB) |
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Figure 06a: Charged fraction (f_track) (a) Distribution of the charged particle fraction, f_track, for calorimeters jets built from topological clusters and (b) its correlation with p_T^ jet . The same trends are observed for noise-suppressed tower jets. png (327kB) eps (14kB) pdf (5kB) |
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Figure 06b: Dependence of f_track on p_T^ jet (a) Distribution of the charged particle fraction, f_track, for calorimeters jets built from topological clusters and (b) its correlation with p_T^ jet . The same trends are observed for noise-suppressed tower jets. png (319kB) eps (12kB) pdf (4kB) |
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Figure 07a: 20 png (351kB) eps (13kB) pdf (7kB) |
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Figure 07b: 40 png (340kB) eps (13kB) pdf (7kB) |
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Figure 08a: 2^nd EM layer (|y^ jet |<0.3) Example distributions of energy deposited by jets with p_T^ jet >20 GeV in layers of the calorimeter compared to that predicted from Monte Carlo simulation for (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region, and (d) the end-cap presampler layer. png (361kB) eps (25kB) pdf (8kB) |
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Figure 08b: 2^nd EM layer (2.1<|y^ jet |<2.8) Example distributions of energy deposited by jets with p_T^ jet >20 GeV in layers of the calorimeter compared to that predicted from Monte Carlo simulation for (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region, and (d) the end-cap presampler layer. png (353kB) eps (24kB) pdf (8kB) |
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Figure 08c: 2^nd HAD layer (|y^ jet |<0.3) Example distributions of energy deposited by jets with p_T^ jet >20 GeV in layers of the calorimeter compared to that predicted from Monte Carlo simulation for (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region, and (d) the end-cap presampler layer. png (370kB) eps (25kB) pdf (9kB) |
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Figure 08d: End-cap presampler (1.2<|y^ jet |<2.1) Example distributions of energy deposited by jets with p_T^ jet >20 GeV in layers of the calorimeter compared to that predicted from Monte Carlo simulation for (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region, and (d) the end-cap presampler layer. png (378kB) eps (23kB) pdf (9kB) |
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Figure 09a: 2^nd EM layer (|y^ jet |<0.3) Example distributions of the mean energy deposited by jets in layers of the calorimeter as a function of the calibrated jet p_T and compared to that predicted from Monte Carlo simulation. The layers shown are (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region and (d) the end-cap presampler layer. png (297kB) eps (16kB) pdf (5kB) |
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Figure 09b: 2^nd EM layer (2.1<|y^ jet |<2.8) Example distributions of the mean energy deposited by jets in layers of the calorimeter as a function of the calibrated jet p_T and compared to that predicted from Monte Carlo simulation. The layers shown are (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region and (d) the end-cap presampler layer. png (314kB) eps (15kB) pdf (5kB) |
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Figure 09c: 2^nd HAD layer (|y^ jet |<0.3) Example distributions of the mean energy deposited by jets in layers of the calorimeter as a function of the calibrated jet p_T and compared to that predicted from Monte Carlo simulation. The layers shown are (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region and (d) the end-cap presampler layer. png (302kB) eps (16kB) pdf (5kB) |
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Figure 09d: End-cap presampler (1.2<|y^ jet |<2.1) Example distributions of the mean energy deposited by jets in layers of the calorimeter as a function of the calibrated jet p_T and compared to that predicted from Monte Carlo simulation. The layers shown are (a) the second layer of the electromagnetic calorimeter in the central region, (b) the second layer of the electromagnetic calorimeter in the end-cap, (c) the second layer of the hadronic calorimeter in the central region and (d) the end-cap presampler layer. png (290kB) eps (14kB) pdf (5kB) |
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Figure 10a: 20Ge-0.1em V png (294kB) eps (9kB) pdf (5kB) |
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Figure 10b: 40Ge-0.1em V png (294kB) eps (9kB) pdf (5kB) |
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Figure 11a: Jet width Jet width distribution (see Eq. 3) for jets built from topological clusters within |y^ jet | < 2.8 (a) for all jets with p_T^ jet > 20 GeV and (b) as a function of p_T^ jet . png (357kB) eps (14kB) pdf (8kB) |
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Figure 11b: Jet width vs p_T^ jet Jet width distribution (see Eq. 3) for jets built from topological clusters within |y^ jet | < 2.8 (a) for all jets with p_T^ jet > 20 GeV and (b) as a function of p_T^ jet . png (293kB) eps (11kB) pdf (5kB) |
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Figure 12a: Delta R(trk_1,trk_2) of the two hardest tracks in jets The angular spread of the two hardest tracks inside jets for (a) an inclusive selection of jets within |y^ jet |<1.9 and (b) as a function of p_T^ jet . png (350kB) eps (14kB) pdf (6kB) |
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Figure 12b: Dependence of Delta R(trk_1,trk_2) with p_T^ jet The angular spread of the two hardest tracks inside jets for (a) an inclusive selection of jets within |y^ jet |<1.9 and (b) as a function of p_T^ jet . png (316kB) eps (12kB) pdf (5kB) |
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Figure 13a: Jet shape using calorimeter clusters Ratio of measured jet energy distributions in annuli around the jet axis in data compared to MC for |y^ jet |<0.3 using both (a) topological clusters and (b) towers with p_T^ jet >20 GeV, while (c) uses tracks matched to cluster jets to measure the energy deposited in annuli within the jet (for jets with 20 png (264kB) eps (14kB) pdf (6kB) |
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Figure 13b: Jet shape using calorimeter towers Ratio of measured jet energy distributions in annuli around the jet axis in data compared to MC for |y^ jet |<0.3 using both (a) topological clusters and (b) towers with p_T^ jet >20 GeV, while (c) uses tracks matched to cluster jets to measure the energy deposited in annuli within the jet (for jets with 20 png (265kB) eps (14kB) pdf (5kB) |
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Figure 13c: Jet shape using tracks Ratio of measured jet energy distributions in annuli around the jet axis in data compared to MC for |y^ jet |<0.3 using both (a) topological clusters and (b) towers with p_T^ jet >20 GeV, while (c) uses tracks matched to cluster jets to measure the energy deposited in annuli within the jet (for jets with 20 png (246kB) eps (14kB) pdf (6kB) |
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Figure 14a: Topological cluster jets Comparison of calorimeter-based measurements of the radial jet energy profiles to the same measurements performed using tracks. This double-ratio compares the transverse energy in annuli around the jet axis measured with the two methods in data to that expected from Monte Carlo simulation for |y^ jet |<0.3. The calorimeter-based measurements are performed using both (a) topological clusters and (b) towers with noise-suppression, for jets with p_T^ jet >20 GeV. The results are similar for other regions. png (250kB) eps (12kB) pdf (5kB) |
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Figure 14b: Noise-suppressed tower jets Comparison of calorimeter-based measurements of the radial jet energy profiles to the same measurements performed using tracks. This double-ratio compares the transverse energy in annuli around the jet axis measured with the two methods in data to that expected from Monte Carlo simulation for |y^ jet |<0.3. The calorimeter-based measurements are performed using both (a) topological clusters and (b) towers with noise-suppression, for jets with p_T^ jet >20 GeV. The results are similar for other regions. png (251kB) eps (12kB) pdf (5kB) |
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Figure 15a: 1^st layer of Tile calorimeter Jet energy response as a function of the fraction of the electromagnetic-scale jet energy deposited in the first layer of the Tile calorimeter f_tile1 (a), the third layer of the electromagnetic calorimeter f_em3 (b), the barrel presampler f_pres (c) and as a function of the width (d) obtained with Monte Carlo simulation using jets with |y^ jet |<0.3 and for different bins of matched particle-jet p_T. The distributions of the different variables with an arbitrary normalization, common to all p_T bins, are shown for reference. png (359kB) eps (26kB) pdf (9kB) |
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Figure 15b: 3^rd layer of EM calorimeter Jet energy response as a function of the fraction of the electromagnetic-scale jet energy deposited in the first layer of the Tile calorimeter f_tile1 (a), the third layer of the electromagnetic calorimeter f_em3 (b), the barrel presampler f_pres (c) and as a function of the width (d) obtained with Monte Carlo simulation using jets with |y^ jet |<0.3 and for different bins of matched particle-jet p_T. The distributions of the different variables with an arbitrary normalization, common to all p_T bins, are shown for reference. png (366kB) eps (25kB) pdf (8kB) |
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Figure 15c: Pre-sampler Jet energy response as a function of the fraction of the electromagnetic-scale jet energy deposited in the first layer of the Tile calorimeter f_tile1 (a), the third layer of the electromagnetic calorimeter f_em3 (b), the barrel presampler f_pres (c) and as a function of the width (d) obtained with Monte Carlo simulation using jets with |y^ jet |<0.3 and for different bins of matched particle-jet p_T. The distributions of the different variables with an arbitrary normalization, common to all p_T bins, are shown for reference. png (373kB) eps (25kB) pdf (9kB) |
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Figure 15d: Calorimetric jet width Jet energy response as a function of the fraction of the electromagnetic-scale jet energy deposited in the first layer of the Tile calorimeter f_tile1 (a), the third layer of the electromagnetic calorimeter f_em3 (b), the barrel presampler f_pres (c) and as a function of the width (d) obtained with Monte Carlo simulation using jets with |y^ jet |<0.3 and for different bins of matched particle-jet p_T. The distributions of the different variables with an arbitrary normalization, common to all p_T bins, are shown for reference. png (375kB) eps (27kB) pdf (10kB) |
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Figure 16a: 1^st layer of Tile calorimeter Asymmetry as a function of the four variables used by the GS calibration in the barrel in data and Monte Carlo simulation for a di-jet system with 20 Ge-0.1em V png (326kB) eps (13kB) pdf (7kB) |
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Figure 16b: 3^rd layer of EM calorimeter Asymmetry as a function of the four variables used by the GS calibration in the barrel in data and Monte Carlo simulation for a di-jet system with 20 Ge-0.1em V png (323kB) eps (12kB) pdf (7kB) |
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Figure 16c: Pre-sampler Asymmetry as a function of the four variables used by the GS calibration in the barrel in data and Monte Carlo simulation for a di-jet system with 20 Ge-0.1em V png (346kB) eps (14kB) pdf (7kB) |
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Figure 16d: Calorimetric jet width Asymmetry as a function of the four variables used by the GS calibration in the barrel in data and Monte Carlo simulation for a di-jet system with 20 Ge-0.1em V png (332kB) eps (13kB) pdf (7kB) |
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Figure 17a: Barrel pre-sampler Cell energy density distributions used in the GCW jet calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells in the barrel pre-sampler (a) second layer of the barrel electromagnetic calorimeter (b) and second layer of the barrel hadronic Tile calorimeter (c). The ratio between data and Monte Carlo simulation is shown on the lower part of the figure. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. png (468kB) eps (27kB) pdf (9kB) |
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Figure 17b: Second layer of EM barrel Cell energy density distributions used in the GCW jet calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells in the barrel pre-sampler (a) second layer of the barrel electromagnetic calorimeter (b) and second layer of the barrel hadronic Tile calorimeter (c). The ratio between data and Monte Carlo simulation is shown on the lower part of the figure. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. png (504kB) eps (32kB) pdf (10kB) |
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Figure 17c: Second layer of hadronic barrel Cell energy density distributions used in the GCW jet calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells in the barrel pre-sampler (a) second layer of the barrel electromagnetic calorimeter (b) and second layer of the barrel hadronic Tile calorimeter (c). The ratio between data and Monte Carlo simulation is shown on the lower part of the figure. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. png (483kB) eps (29kB) pdf (9kB) |
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Figure 18a: Second layer of EM endcap Cell energy density distributions used in the GCW jet calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells (a) in the second layer of the end-cap electromagnetic calorimeter, (b) first layer of the end-cap hadronic calorimeter (c) and the first layer of the forward calorimeter. The ratio between data and Monte Carlo simulation is shown on the lower part of the figure. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. png (516kB) eps (35kB) pdf (11kB) |
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Figure 18b: First layer of HEC Cell energy density distributions used in the GCW jet calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells (a) in the second layer of the end-cap electromagnetic calorimeter, (b) first layer of the end-cap hadronic calorimeter (c) and the first layer of the forward calorimeter. The ratio between data and Monte Carlo simulation is shown on the lower part of the figure. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. png (495kB) eps (32kB) pdf (10kB) |
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Figure 18c: First layer of FCAL Cell energy density distributions used in the GCW jet calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells (a) in the second layer of the end-cap electromagnetic calorimeter, (b) first layer of the end-cap hadronic calorimeter (c) and the first layer of the forward calorimeter. The ratio between data and Monte Carlo simulation is shown on the lower part of the figure. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. png (477kB) eps (27kB) pdf (9kB) |
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Figure 19a: Electromagnetic clusters Distributions of cluster isolation for clusters tagged as electromagnetic (a) and clusters tagged as hadronic (b) in data (points) and Monte Carlo simulation (histograms). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used. png (413kB) eps (17kB) pdf (9kB) |
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Figure 19b: Hadronic clusters Distributions of cluster isolation for clusters tagged as electromagnetic (a) and clusters tagged as hadronic (b) in data (points) and Monte Carlo simulation (histograms). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used. png (421kB) eps (17kB) pdf (9kB) |
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Figure 20a: Electromagnetic clusters Mean value of cluster isolation for (a) clusters tagged as electromagnetic and (b) clusters tagged as hadronic in data (black points) and Monte Carlo simulation (red points). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used (i.e. within the electromagnetic and hadronic end-caps). png (376kB) eps (14kB) pdf (6kB) |
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Figure 20b: Hadronic clusters Mean value of cluster isolation for (a) clusters tagged as electromagnetic and (b) clusters tagged as hadronic in data (black points) and Monte Carlo simulation (red points). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used (i.e. within the electromagnetic and hadronic end-caps). png (381kB) eps (14kB) pdf (6kB) |
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Figure 21a: Electromagnetic clusters Distributions of_center for clusters tagged as electromagnetic (a) and clusters tagged as hadronic (b) in data (points) and Monte Carlo simulation (histograms). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used. png (371kB) eps (13kB) pdf (6kB) |
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Figure 21b: Hadronic clusters Distributions of_center for clusters tagged as electromagnetic (a) and clusters tagged as hadronic (b) in data (points) and Monte Carlo simulation (histograms). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used. png (382kB) eps (16kB) pdf (9kB) |
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Figure 22a: Electromagnetic clusters Mean value of_center (a) for clusters tagged as electromagnetic and (b) clusters tagged as hadronic in data (black points) and Monte Carlo simulation (red points). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used. png (367kB) eps (14kB) pdf (6kB) |
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Figure 22b: Hadronic clusters Mean value of_center (a) for clusters tagged as electromagnetic and (b) clusters tagged as hadronic in data (black points) and Monte Carlo simulation (red points). Clusters in jets with p_T^LCW+JES >20Ge-0.1em V and |y^ jet |<2.8 were used. png (372kB) eps (14kB) pdf (7kB) |
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Figure 23a: Hadronic response weights Mean calibrated cluster energy divided by uncalibrated cluster energy in data (points) and Monte Carlo simulation (histograms) as a function of cluster energy after (a) hadronic response weights, (b) out-of-cluster weights, and (c) dead material weights are applied to clusters in jets with |y^ jet |<0.3 and p_T^LCW+JES >20Ge-0.1em V. png (393kB) eps (19kB) pdf (9kB) |
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Figure 23b: Out-of-cluster weights Mean calibrated cluster energy divided by uncalibrated cluster energy in data (points) and Monte Carlo simulation (histograms) as a function of cluster energy after (a) hadronic response weights, (b) out-of-cluster weights, and (c) dead material weights are applied to clusters in jets with |y^ jet |<0.3 and p_T^LCW+JES >20Ge-0.1em V. png (384kB) eps (18kB) pdf (8kB) |
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Figure 23c: Dead material weights Mean calibrated cluster energy divided by uncalibrated cluster energy in data (points) and Monte Carlo simulation (histograms) as a function of cluster energy after (a) hadronic response weights, (b) out-of-cluster weights, and (c) dead material weights are applied to clusters in jets with |y^ jet |<0.3 and p_T^LCW+JES >20Ge-0.1em V. png (404kB) eps (19kB) pdf (9kB) |
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Figure 24a: Hadronic response weights Mean calibrated cluster energy divided by uncalibrated cluster energy in data (points) and Monte Carlo simulation (histograms) as a function of cluster after (a) hadronic response weights, (b) out-of-cluster weights, and (c) dead material weights are applied to clusters in jets of p_T^LCW+JES >20Ge-0.1em V. png (395kB) eps (20kB) pdf (10kB) |
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Figure 24b: Out-of-cluster weights Mean calibrated cluster energy divided by uncalibrated cluster energy in data (points) and Monte Carlo simulation (histograms) as a function of cluster after (a) hadronic response weights, (b) out-of-cluster weights, and (c) dead material weights are applied to clusters in jets of p_T^LCW+JES >20Ge-0.1em V. png (408kB) eps (21kB) pdf (11kB) |
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Figure 24c: Dead material weights Mean calibrated cluster energy divided by uncalibrated cluster energy in data (points) and Monte Carlo simulation (histograms) as a function of cluster after (a) hadronic response weights, (b) out-of-cluster weights, and (c) dead material weights are applied to clusters in jets of p_T^LCW+JES >20Ge-0.1em V. png (395kB) eps (19kB) pdf (10kB) |
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Figure 25a: Global sequential calibration Mean calibrated jet energy over uncalibrated jet energy as a function of calibrated jet p_T for jets constructed of topological clusters calibrated with (a) the global sequential, (b) the global cell energy-density weighting, and (c) local cluster weighting calibration schemes. The mean value is shown as obtained in data (black points) and in Monte Carlo simulation (red open squares). png (333kB) eps (13kB) pdf (6kB) |
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Figure 25b: Global cell-weighting calibration Mean calibrated jet energy over uncalibrated jet energy as a function of calibrated jet p_T for jets constructed of topological clusters calibrated with (a) the global sequential, (b) the global cell energy-density weighting, and (c) local cluster weighting calibration schemes. The mean value is shown as obtained in data (black points) and in Monte Carlo simulation (red open squares). png (341kB) eps (17kB) pdf (6kB) |
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Figure 25c: Local cluster calibration Mean calibrated jet energy over uncalibrated jet energy as a function of calibrated jet p_T for jets constructed of topological clusters calibrated with (a) the global sequential, (b) the global cell energy-density weighting, and (c) local cluster weighting calibration schemes. The mean value is shown as obtained in data (black points) and in Monte Carlo simulation (red open squares). png (340kB) eps (17kB) pdf (6kB) |
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Figure 26a: Global sequential calibration Mean calibrated jet energy over uncalibrated jet energy as a function of the rapidity for jets constructed of topological clusters calibrated with (a) the global sequential, (b) the global cell energy-density weighting, and (c) local cluster weighting calibration schemes. The mean value is shown as obtained in data (black points) and in Monte Carlo simulation (red open squares). png (342kB) eps (16kB) pdf (10kB) |
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Figure 26b: Global cell-weighting calibration Mean calibrated jet energy over uncalibrated jet energy as a function of the rapidity for jets constructed of topological clusters calibrated with (a) the global sequential, (b) the global cell energy-density weighting, and (c) local cluster weighting calibration schemes. The mean value is shown as obtained in data (black points) and in Monte Carlo simulation (red open squares). png (354kB) eps (21kB) pdf (10kB) |
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Figure 26c: Local cluster calibration Mean calibrated jet energy over uncalibrated jet energy as a function of the rapidity for jets constructed of topological clusters calibrated with (a) the global sequential, (b) the global cell energy-density weighting, and (c) local cluster weighting calibration schemes. The mean value is shown as obtained in data (black points) and in Monte Carlo simulation (red open squares). png (352kB) eps (21kB) pdf (10kB) |
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