Difference: ApprovedPlotsTilePileUpNoisePerformance (1 vs. 3)

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Pile-up Noise (2016)

Energy distribution for data collected in 2016 in the zero-bias stream with 25 ns bunch spacing at a centre-of-mass energy of 13 TeV (runs 310247, 310249, 310341, 310370) and Pythia 8 Monte Carlo simulation with A3 Minimum Bias tune for the layer A cell with in the Tile Calorimeter. An integration over all modules has been performed. The energy reconstruction method is the default reconstruction method used in Run 2. The depicted distributions correspond to two different pile-up conditions with (blue) and (red). The ratio between Data and Monte Carlo simulation is shown in the lower plot. The energy distribution gets wider for higher values of , showing an increasing pile-up noise.
Contact: Aliaksei Hrynevich aliaksei.hrynevich@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2017-007
Date: February, 2017

[PDF] [EPS]
The noise distributions in different Tile Calorimeter cells are represented as a function of for zero-bias data collected in 2016 (runs 310247, 310249, 310341, 310370) and Pythia 8 Monte Carlo simulation with A3 Minimum Bias tune at a centre-of-mass energy of 13 TeV with a bunch spacing of 25 ns selected with an average number of interactions per bunch crossing. The noise was estimated as the standard deviation of the measured cell energy distribution. The data (Monte Carlo) is represented with closed (open) markers. The cells of Layer A, Layer BC, Layer D and Layer E are shown with different colors.
Contact: Aliaksei Hrynevich aliaksei.hrynevich@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2017-007
Date: February, 2017

[PDF] [EPS]
The Tile Calorimeter noise dependence with the average number of interactions per bunch crossing, , is represented, for several zero-bias data runs of 2016 (runs 310247, 310249, 310341, 310370) and Pythia 8 Monte Carlo simulation with A3 Minimum Bias tune at a centre-of-mass energy of 13 TeV with a bunch spacing of 25 ns. The noise was estimated as the standard deviation of the energy distribution per cell. The data (Monte Carlo) is represented with closed (open) markers. The noise is shown for one Tile Calorimeter tower with cells A5, BC5 and D2 in . Only are shown in data were the reliable statistics is observed.
Contact: Aliaksei Hrynevich aliaksei.hrynevich@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2017-007
Date: February, 2017

[PDF] [EPS]
The Tile Calorimeter noise dependence with the average number of interactions per bunch crossing, , is represented, for several zero-bias data runs of 2016 (runs 310247, 310249, 310341, 310370) and Pythia 8 Monte Carlo simulation with A3 Minimum Bias tune at a centre-of-mass energy of 13 TeV with a bunch spacing of 25 ns. The noise was estimated as the standard deviation of the energy distribution per cell. The data (Monte Carlo) is represented with closed (open) markers. The noise is shown for one Tile Calorimeter tower with cells A13, BC13, D6 and E3 in . Only are shown in data were the reliable statistics is observed.
Contact: Aliaksei Hrynevich aliaksei.hrynevich@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2017-007
Date: February, 2017

[PDF] [EPS]
 

Pile-up Noise (2012)

The noise distribution in different TileCal cells is represented as a function of || of the cells for zero bias run 208781 of 2012 at a centre-of-mass energy of 8 TeV with a bunch spacing of 50 ns and an average number of interactions < > = 15.7 per bunch crossing). The Monte Carlo was reweighted to the average number of interactions in data, according to the weight given by the PileUpReweighting tool. The noise was estimated as the standard deviation of the measured cell energy distribution. The top left (right) histogram shows the results obtained for the cells of Layer A (Layer BC). The bottom left (right) histogram shows the results obtained for the cells of Layer D (Special Cells).


Contact: Juan Pedro Araque juan.pedro.araque.espinosa@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

[pdf] [eps]
The noise distribution in different TileCal cells is represented as a function of || of the cells for zero bias run 216416 of 2012 at a centre-of-mass energy of 8 TeV with a bunch spacing of 25 ns and an average number of interactions < > = 10.0 per bunch crossing). The Monte Carlo was reweighted to the average number of interactions in data, according to the weight given by the PileUpReweighting tool. The noise was estimated as the standard deviation of the measured cell energy distribution. The top left (right) histogram shows the results obtained for the cells of Layer A (Layer BC). The bottom left (right) histogram shows the results obtained for the cells of Layer D (Special Cells).


Contact: Juan Pedro Araque juan.pedro.araque.espinosa@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

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Introduction

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Pile-up Noise Performance.
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This page lists the public plots illustrating pile-up noise performance studies.
 

Pile-up Noise Performance

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ApprovedPlotsTilePileUpNoisePerformance

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Introduction

Pile-up Noise Performance.

Pile-up Noise Performance

Pile-up Noise (2012)

The noise distribution in different TileCal cells is represented as a function of || of the cells for zero bias run 208781 of 2012 at a centre-of-mass energy of 8 TeV with a bunch spacing of 50 ns and an average number of interactions < > = 15.7 per bunch crossing). The Monte Carlo was reweighted to the average number of interactions in data, according to the weight given by the PileUpReweighting tool. The noise was estimated as the standard deviation of the measured cell energy distribution. The top left (right) histogram shows the results obtained for the cells of Layer A (Layer BC). The bottom left (right) histogram shows the results obtained for the cells of Layer D (Special Cells).


Contact: Juan Pedro Araque juan.pedro.araque.espinosa@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

[pdf] [eps]
The noise distribution in different TileCal cells is represented as a function of || of the cells for zero bias run 216416 of 2012 at a centre-of-mass energy of 8 TeV with a bunch spacing of 25 ns and an average number of interactions < > = 10.0 per bunch crossing). The Monte Carlo was reweighted to the average number of interactions in data, according to the weight given by the PileUpReweighting tool. The noise was estimated as the standard deviation of the measured cell energy distribution. The top left (right) histogram shows the results obtained for the cells of Layer A (Layer BC). The bottom left (right) histogram shows the results obtained for the cells of Layer D (Special Cells).


Contact: Juan Pedro Araque juan.pedro.araque.espinosa@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

[pdf] [eps]

The noise in D5 and D6 cells of the Tile calorimeter, located at the outermost layer with 0.9 < |η| < 1.3, is plotted against the average number of interactions per event. The dashed line shows the electronic noise contribution estimated from special pedestal runs.

The noise was estimated as the RMS of the energy deposited in the cell in zero bias data in collisions with a center-of-mass energy of 8 TeV and bunch spacing of 25 ns. The data beam parameters and structure were simulated in the Monte-Carlo events. The data points refer to the D5 and D6 cells of the Extended Barrel modules EBA39 and EBC39 because they were powered by the new generation low noise Low Voltage Power Supplies, which are going to be used in the whole calorimeter in Run 2.

Contact: Vladimir Drugakov v.drugakov@cernNOSPAMPLEASE.ch

Reference: ATL-COM-TILECAL-2013-035
Date: 16 Aug 2013

noise_D5D6_8TeV_25ns_newLVPS_v2.png

eps version of the figure

Energy distribution for data collected in 2012 in the zero-bias stream with 50 ns bunch spacing at a centre-of-mass energy of 8 TeV and Monte Carlo simulation for the layer A cell with $1.1 < \eta < 1.2$ in the Tile Calorimeter. An integration over all modules has been performed. The energy reconstruction method is the default reconstruction method used in Run 1. The depicted distributions correspond to two different pile-up conditions with $\langle\mu\rangle = 20$ (blue) and $\langle\mu\rangle = 30$ (red). The ratio between Data and Monte Carlo simulation is shown in the lower plot. It can be seen that for higher values of $\langle\mu\rangle $ the energy distribution gets wider, showing an increasing pile-up noise. A reasonable agreement between data and Monte Carlo simulation is found above 200 MeV. The small difference in the energy distribution between the Data and Monte Carlo simulation translates into a few tens of MeV difference in the pile-up noise, as can be seen comparing the $\sigma$ values written in the figure.
Contact: Aliaksei Hrynevich aliaksei.hrynevich@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2015-012
Date: March 10, 2015

[PDF]
Noise comparison as a function of the mean number of interactions per crossing between data collected in 2012 in the zero-bias stream with 50 ns bunch spacing at a centre-of-mass energy of 8 TeV and Monte Carlo simulation for the cells in the layer A of the Tile Calorimeter. For data the runs 201555, 205112, 207397, 208781, 210302, 211973 have been used. The noise is derived as the standard deviation of the energy distribution. In the region where data and Monte Carlo simulation overlap a good agreement can be seen, with the highest different being of the order of $\sim15$ MeV.
Contact: Juan Pedro Araque jp.araque@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2015-012
Date: March 10, 2015

[PDF]
The energy distribution for the cell in the layer A with $0.6 < \left| \eta \right| < 0.7$ as a function of the mean number of interactions per crossing using data collected in 2012 in the zero-bias stream with 50 ns bunch spacing and a centre-of-mass energy of 8 TeV using the default energy reconstruction method used in Run 1. The runs 201555, 205112, 207397, 208781, 210302, 211973 have been used. Different colours represent different regions populated by the 68.27%(red), 95.45% (yellow), 99.73% (green) and 99.99% (blue) of the events. These regions have been derived using the quantiles of the energy distribution which are used to find the energy values defining the regions populated by each percentage of events. This figure shows the non-gaussian behaviour of the energy distribution given that in a gaussian regime each of the for regions would scale with the standard deviation and be symmetric.
Contact: Juan Pedro Araque jp.araque@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2015-012
Date: March 10, 2015

[PDF]
Comparison between the RMS of the energy distribution scaled by a factor of 2 (dark yellow circle) and 4 (blue circle) and the width of the regions that contains the 95.45% (filled dark yellow circle) and 99.99% (filled blue circle) of the events in the energy distributions (solid circles) for the cell in the layer A with $0.6 < \left| \eta \right| < 0.7$. Data collected in 2012 in the zero-bias stream with 50 ns bunch spacing and a centre-of-mass energy of 8 TeV has been used. The runs 201555, 205112, 207397, 208781, 210302, 211973 have been analysed. Both methods should be similar for the yellow and blue values respectively if the energy distribution were gaussian. It can be seen that given the non-gaussian behaviour of the energy distribution the scaled RMS values are different from the quantiles approach, usually larger due to the larger tails in comparison with what would be expected in a gaussian regime.
Contact: Juan Pedro Araque jp.araque@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2015-012
Date: March 10, 2015

[PDF]
Comparison between the RMS of the energy distribution scaled by a factor of 2 (dark yellow circle) and 4 (blue circle) and the width of the regions that contains the 95.45% (filled dark yellow circle) and 99.99% (filled blue circle) of the events in the energy distributions (solid circles) for the cell in the layer D with $0.6 < \left| \eta \right| < 0.8$. Data collected in 2012 in the zero-bias stream with 50 ns bunch spacing and a centre-of-mass energy of 8 TeV has been used. The runs 201555, 205112, 207397, 208781, 210302, 211973 have been analysed. Both methods should be similar for the yellow and blue values respectively if the energy distribution were gaussian. It can be seen that given the non gaussian behaviour of the energy distribution the scaled RMS values are different from the quantiles approach, usually larger due to the larger tails in comparison with what would be expected in a gaussian regime.
Contact: Juan Pedro Araque jp.araque@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2015-012
Date: March 10, 2015

[PDF]
Comparison between the RMS of the energy distribution scaled by a factor of 2 (hollow markers) and the width of the regions that contains the 95.45% of the events in the energy distributions (filled markers) for the cell in the layer A with $0.6 < \left| \eta \right| < 0.7$ (circular markers) and the cell in the layer D with $0.6 < \left| \eta \right| < 0.8$ (squared markers). Data collected in 2012 in the zero-bias stream with 50 ns bunch spacing and a centre-of-mass energy of 8 TeV has been used. The runs 201555, 205112, 207397, 208781, 210302, 211973 have been analysed.It can be seen how different can have different shape in the energy distribution, e.g. the difference seen for the cell in the layer A is smaller for low values of $\langle\mu\rangle $ and grows bigger for high values of $\langle\mu\rangle $ while the difference for the layer D cell is maintained.
Contact: Juan Pedro Araque jp.araque@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2015-012
Date: March 10, 2015

[PDF]

Pile-up Noise (2011)

The noise distribution in different TileCal cells is represented as a function of || of the cells for zero bias run 182424 of period F2 of 2011 data (at a centre-of-mass energy of 7 TeV with a bunch spacing of 50 ns and an average number of interactions < > = 4.8 per bunch crossing). The Monte Carlo was reweighted to the average number of interactions in data, according to the weight given by the PileUpReweighting tool. The noise was estimated as the standard deviation of the measured cell energy distribution. The top left (right) histogram shows the results obtained for the cells of Layer A (Layer BC). The bottom left (right) histogram shows the results obtained for the cells of Layer D (Special Cells).


Contact: Susana Santos Susana.Patricia.Santos@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

[pdf] [eps]
The noise distribution in different TileCal cells is represented as a function of || of the cells for zero bias run 190617 of period M2 of 2011 data (at a centre-of-mass energy of 7 TeV with a bunch spacing of 50 ns and an average number of interactions < > = 11.3 per bunch crossing). The Monte Carlo was reweighted to the average number of interactions in data, according to the weight given by the PileUpReweighting tool. The noise was estimated as the standard deviation of the measured cell energy distribution. The top left (right) histogram shows the results obtained for the cells of Layer A (Layer BC). The bottom left (right) histogram shows the results obtained for the cells of Layer D (Special Cells).


Contact: Susana Santos Susana.Patricia.Santos@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

[pdf] [eps]
The TileCal noise dependence with the actual number of interactions, , is represented, for several zero bias data runs from different periods of 2011. The noise was estimated as the standard deviation of the mean energy value per cell. The black markers represent data and the red points Monte Carlo. The different marker styles correspond to different cell layers in the TileCal.


Contact: Serguei Yanush Serguei.Yanush@cernNOSPAMPLEASE.ch
Reference: ATL-COM-TILECAL-2011-022

[pdf] [eps]

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