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NSW background NSW background studies studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

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Page 1: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

NSW backgroundNSW backgroundstudiesstudies

Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher

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Page 2: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

IntroductionIntroduction

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Summary of the results for three background studies:

1.Overlay method

2.Injection method

3.Full pile up NSW simulation

Page 3: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

NSW backgroundNSW backgroundmodeling: overlaymodeling: overlay

Max Bellomo, Niels van Eldik, Andrew Haas, Jochen Meyer, Peter Kluit

Muons NSW 25 April, Simulation PP 22 AprilMuon NSW 18 April

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Page 4: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Overlay modelingOverlay modeling

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Details have been presented in the Simulation PP meetinghttps://indico.cern.ch/conferenceDisplay.py?confId=247906

Slides 5-7: TDR plot for EI occupancy @ 2.6e34 cm-2s-1Contains now 100 events with each 10 events overlaid.

Backup material for the method:• Slides 809 Cross check Data-Data 2012: overlay of 3 times for run 206573 vs run 205010. Overlay of 3 times for run 206573 and comparison to run 205010 shows that on average the clusters multiplicities in the Inner wheel agree at the 20% level.• Slides 10-13 Other cross check plots:-Validation of the EM and EO rate with the overlay @ 5%- Limitations of the present software: CSC are a factor 1.4 too high

Page 5: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

MDT EI occupancy: saturation and MDT EI occupancy: saturation and non-linearitynon-linearity

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Occupancy is the number of times a tube fires per event

For the overlay data (Zero Bias) is used.

Page 6: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

TDR textTDR text

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caption: a) The occupancy vs the MDT tube number for the EI chamber for Overlay data (black) and Zero Bias data scale up by a factor 10. b) The ratio of the Overlay to Zero Bias (x 10) occupancy vs MDT tube number.

A study has been performed overlaying events to determine the impact on the current EI detector. The overlay method is described in detail ATL-SOFT-SLIDE-2012-188.Here 10 Zero Bias events are overlaid to produce 1 event. The Zero Bias events have been collected in 2012 with a dedicated trigger. The instantanuous luminosity corresponded to 2.6e33 cm-2s-1. The overlayed events correspond to the background one would expect for a luminosity of 2.6e34 cm-2s-1.

Page 7: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

TDR textTDR text

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The results for this study are shown in Figure ~xxxx.Only the EI MDT chambers closest to the beamline were selected.The black curve corresponds to the Zero bias occupancy in these chambers detector averaged over the sectors and the two endcaps scaled up by a factor of 10.The red curve the result of the overlay with 10 Zero bias events.One can observe - in particular in the ratio plot - that the red curve does not scale to the black curve at high occupancies. At high tube nrs and low occupancies below 20% it does scale.

This effect is due to the fact that at high occupancy MDT hits get masked: the total number of hits will not scale linearly with the background level and saturation takes place.

This saturation effect that will lead to MDT hit efficiency losses is one of the reasons to replace the EI MDTs by the proposed NSW.

Page 8: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Data-Data 2012 cross checkData-Data 2012 cross check

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Page 9: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Data-Data 2012 cross checkData-Data 2012 cross check

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Overlay of 3 times for run 206573 and comparison to run 205010 shows that on average the clusters multiplicities in the Inner wheel agree at the 20% level.

The scale factor for the MDT = 1.22 the TGC 1.27 and the CSC 0.97. The numbers are dominated by systematic errors that are at the level of 20%.

Page 10: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

MDT EM occupancy:MDT EM occupancy:

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Occupancy is the number of times a tube fires per event

Here –as expected - no saturation is observed. The ratio should go to 1-occupancy = 0.85. This is indeed observed

Page 11: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

MDT EO occupancy:MDT EO occupancy:

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Here –as expected - no saturation is observed. The ratio should go to 1-occupancy = 0.95. This is indeed observed.

Conclusion: Overlay method in MDT Endcaps is OK at the 5% level.

Page 12: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

CSC phi occupancy:CSC phi occupancy:

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Here a discrepancy is found: the overlay produces a 40% too much background.

Page 13: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

CSC eta occupancy:CSC eta occupancy:

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Conclusion: Overlay method for the CSC produces about 40% too much background in eta and phi.

Page 14: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

NSW backgroundNSW backgroundmodeling: modeling:

hits and segment Injectionhits and segment Injection

Niels van Eldik, Peter Kluit, Felix Rauscher

Muon NSW 26 April 2013 e.g.

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Page 15: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

IntroductionIntroduction

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Method: use the injection of hits segments in the Inner wheel for the estimation of the background

This is done in three steps:1) Validate and parametrize the hits and segments MDTs and TGCs in the Inner wheel using the high mu single bunch run. No out of time pile up is present here. Sim hits are produced and run though the standard digitization and analyzed.

2) Apply time wrapping +- 40 BCs to these hits and segments and compare this to the backgrounds in the Z mumu period D data. This is a crucial test of the injection method. Note that the Z data doesnot only contain pile up but also cavern background.

3) Simulate these hits and segments in the NSW detectors using a 25 nsec bunch spacing. The generated Sim hits are run through the fast digitization for the NSW detectors and analyzed.

Page 16: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Cross checks step 1Cross checks step 1TGC clustersTGC clusters

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Note the target for Data/MC is 0.5Because only 1 endcap is simulated

In step 2 the TGC will increased by a factor of 3

Page 17: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Cross checks step 1Cross checks step 1MDT clusters / TGC confirmedMDT clusters / TGC confirmed

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In step 2 the TGC will increased by a factor of 3

Page 18: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Cross checks step 1Cross checks step 1MDT segment clustersMDT segment clusters

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Conclusions: reasonable description of the in time pile up in the MDTs and TGCs both for high and low cluster multiplicities.

A more quantitative statement will be given at the next step.

Page 19: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Cross checks step IICross checks step IITGC clustersTGC clusters

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Note the target for Data/MC is 0.5Because only 1 endcap is simulated

Here time wrapping +- 40 BC is applied and the “SimInjection” data is compared to the Z data that includes pile up and cavern background

TGC rate is 0.39/0.5 = 0.78

Page 20: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Cross checks step 1ICross checks step 1IMDT clusters / TGC confirmedMDT clusters / TGC confirmed

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MDT cluster rate is too low: 0.148/0.5 = 0.30

Page 21: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Cross checks step 1ICross checks step 1IMDT segment clustersMDT segment clusters

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Cluster segment rate is too low by a factor:0.443/0.5 = 0.88

Page 22: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Conclusions from step 1-2Conclusions from step 1-2

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• The injection method: works reasonably

• The step 2 test shows that:

• TGC injected clusters are OK at the 20% level• MDT injected segments rates are OK at the 20% level

• However the MDT clusters rate are about a factor 3 too low This could be due to the presence of cavern background

Page 23: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

NSW backgroundNSW backgroundmodeling: Simulationsmodeling: Simulations

Pile up vs Injection Pile up vs Injection

Nektarios Benekos, Niels van Eldik, Peter Kluit, Felix Rauscher

Muon NSW 12 May 2013

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Page 24: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

IntroductionIntroduction

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The results of two NSW simulations will be compared.

1)Full pile up simulation chain with new NSW detectors and fast digitisation. The sample was generated by Nektarios: sLHC, pileups ~120 to 140 with 25ns bunch spacing /eos/atlas/user/n/nectar/NSW/PileUpProduction_sLHC/MC12.107209.ParticleGenerator_dimu_Pt10_100.atlasG4.0001/ See also: https://indico.cern.ch/getFile.py/access?contribId=7&resId=0&materialId=slides&confId=248974 This corresponds – my calculation - to a luminosity of 3e34 cm-2s-1.

In the plots sample 1) is scaled to a luminosity of 2.6e34 cm-2s-1.

Page 25: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

IntroductionIntroduction

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The second sample is:

2) The hit and segment Injection method. Background hits and segments are added in the Inner wheel using a 25 nsec bunch spacing. The injected background is increased by a factor of 10 (wrt the 2012 period D data), it corresponds a luminosity of 2.6e34 cm-2s-1. The samples was produced by Felix. wget http://pcphmpi00/NSW_production/download_all.sh [pcphmpi00] bash download_all.sh NOTE: this works only in the CERN network. The files with 1x the background are digi_rt1_evt*.nSW_DigitizationOutput.pool.root ant the ones with 10x the background are digi_rt01_evt*.nSW_DigitizationOutput.pool.root

In both cases the generated Sim hits are run through the fast digitization for the NSW detectors and analyzed.

In the fast digitization the energy thresholds for the sTgc and MicroMegas were put to the value of 1 MeV.

Page 26: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Comparison PileUp vs Comparison PileUp vs InjectionInjection

MDT and MicroMegasMDT and MicroMegas

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NSW layout

EI MDTs: the |eta|>2 chambers on the Inner wheel

The MDTs and CSC near beamline are replaced by MM and sTgc

Page 27: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Comparison PileUp vs Comparison PileUp vs InjectionInjectionsTGCssTGCs

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Page 28: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Occupancy PileUpOccupancy PileUp

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STgc only for current BC

MM assumesfour strips firing per gasgap

Page 29: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

Occupancy InjectionOccupancy Injection

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Odd shape for MicroMegas

Bug that shifts the strip nr for odd/even chambers

Page 30: NSW background studies Max Bellomo, Nektarios Benekos, Niels van Eldik, Andrew Haas, Peter Kluit, Jochen Meyer, Felix Rauscher 1

ConclusionsConclusions

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Results for two methods for the occupancy of the NSW Detectors.The injection method predicts rates that are about 30% to60% higher than the Full Sim.Maximum occupancy @ luminosity of 2.6e34 cm-2s-1: Micromegas 4% sTGC pads 1% sTGC strips 0.4% sTGC wires 0.8% The systematic uncertainty on these numbers is rather largebecause – mainly because they should include cavern background and the singles that are difficult to predict. A safety factor 3-4 is probably reasonable (see also slide

22).These numbers could be quoted in the TDR.Both the Pile Up and the Injection samples can be used fore.g. NSW segment or track reconstruction studies in a high background environment.