Performance of the CMS Muon Detectors in early 2018 collision runs

NEW Page created on June 22nd, 2018

This TWIKI page contains the plots in CMS DP-2018/047, which summarizes the performance of the muon detectors as measured with collision data from the 2018 run collected until summer 2018. Clicking on a small image will open a full-size PNG. If a PDF version of a plot is available, click the pdf version link at the top of the image to display or download it (web-browser dependent).

Abstract

The performance of the CMS DT, RPC and CSC muon subdetectors was evaluated with the first collision data in 2018.

Contacts

CMS DPG conveners of the Muon subdetectors

subdetector email
Muon DPG Office cms-muon-DPGO@cernNOSPAMPLEASE.ch
RPC cms-dpg-conveners-rpc@cernNOSPAMPLEASE.ch
DT cms-dpg-conveners-dt@cernNOSPAMPLEASE.ch
CSC cms-dpg-conveners-csc@cernNOSPAMPLEASE.ch

References

This is the link to CMS DP-2018/047

Local Reconstruction Efficiency

DT Hit Efficiency

The DT efficiency to detect a single hit was defined and measured as the ratio between the number of detected and expected hits.

The position of expected hits was determined using as probes sets of track segments reconstructed in both φ and θ views.

  • At least 7 or at least 3 hits were required to be associated to a segment, in the φ and θ view respectively, in other layers than the one under study.
  • On the φ view the segment itself was required to cross the chamber with an inclination lower than 45 degrees.
  • To avoid any bias, segments crossing known dead cells were rejected.

The intersection of such a high quality track segment with the layer under study determined the position, therefore the cell, where a hit was expected: the cell was considered efficient if a hit was found within it.

Besides of the hit efficiency, also the hit association efficiency was computed: this is the efficiency to associate hits in the local segment reconstruction: it is obtained applying the same method, but requiring the hit in the layer under study not only to be present in the expected cell, but to be actually associated to the segment used as probe.

Note on method

The described method, requiring as probe local segments reconstructed with 7 out of 8, or 3 out of 4, hits in the φ and θ view respectively, can only be applied in regions where all wires are working.

The total fraction of not working wires in the sample used was < 1% and its effect was not taken into account in the results shown in this section.

Expected changes with respect to 2017

(2017 results are to be found here or in CMS-DP-2018-016)

The strategy based on High Voltage reduction on the anode wires, started last year with the aim to preserve from early ageing chambers most exposed to radiation, was continued in 2018.

Radiation reaches the DT detector both from the interaction region, due to high track multiplicity produced by PU, and from outside the detector, due to so called “neutron gas” that leaks from the detector and fills the cavern.

  • The first type of radiation is higher in the forward regions, i.e. in the external wheels: -2 and +2.
  • The second type concentrates in the top chambers, where more space is available to be filled by neutron gas (see following sketch).

fig0.png

Sketch of the CMS detector. The DT regions with higher background are:

  • the MB4 chambers of top sectors (4, 13, all wheels) exposed to the neutron gas
  • the MB1 chambers of Wheel-2 and Wheel+2 (all sectors) exposed to high track multiplicity from pileup

The following sketches show the HV configurations in 2017 and 2018.
configurazioneHV.png


Sketch of the DT High Voltage configuration in 2017 and 2018: HV has been lowered progressively in the regions with higher background.

Lower HV is expected to cause a slight loss of hit efficiency, which actually was observed last year.
In order to compensate this loss, the Front End thresholds were also lowered, from the beginning of 2018 data taking, from 30 mV to 20 mV, in all the DT chambers (this new threshold configuration had been tested on one single chamber in the last period of 2017: it allowed a ~2% efficiency recovery).

Summary Plots

Figure Caption
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SingleChamberAlivePerStation10fb.png

Fraction of working wires, chamber by chamber.

Since not working wires don’t contribute to the efficiency computation, this information is a complement to the efficiency results.

Only cells with zero occupancy are considered not working (this is e.g. the case in the presence of persistent readout problems). Cells with low occupancy (e.g. caused by HV problems) are considered inefficient and do contribute to the efficiency computation.

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SingleChamberEfficiencyPerStation10fb.png

DT hit efficiency chamber by chamber. Dead channels are not taken into account.

Chambers with lower efficiency had known hardware problems. In particular, MB2/Wheel2/Sector7 had a full inefficient Θ Superlayer.

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ChamberEfficiency10fb.png

DT hit efficiency distribution: 1 entry per chamber. Dead channels are not taken into account.

Trend Plots

Detector setting parameters, intrinsically affecting the hit efficiency, are the drift voltage (HV) and the Front End threshold.

Variations of the observed efficiency can be expected to depend on:

1) possible effects of detector ageing, related to the accumulated radiation dose

2) high background, interfering with:

  • the hit detection process (due to the dead time of the read out electronics)
  • the hit association process (due to high multiplicity spoiling the local reconstruction)

(Note that instantaneous pileup is not expected to affect the hit efficiency. In fact, since the maximum drift time is 16 bunch crossing periods, hits produced by several bunch crossings are read out together at every trigger.)

The trends of the DT hit efficiency and hit association efficiency have been checked as a function of of Instantaneous luminosity, to spot any effect caused by background.
The range of luminosity available this year extends up to 2 10^34 cm^-2 s^-1.
Examples are shown for chambers least and most exposed to radiation.
(Possible hints of detector ageing will be checked at the end of the data taking period)

Figure Caption
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MB3PhiHitvsLumi10fb.png

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MB3PhiAssvsLumi10fb.png

Hit Efficiency and Hit Association Efficiency of Φ layers of MB3 chambers, as a function of LHC Instantaneous Luminosity.

No trend is visible.

Some increase of Hit Association Efficiency, w.r.t 2017 is visible in the three central wheels (Wheel-1, Wheel0, Wheel+1) that had their FE threshold lowered, while preserving the same HV (see sketch of HV configurations above).

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MB1PhiHitvsLumi10fb.png

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MB1PhiAssvsLumi10fb.png

Hit Efficiency and Hit Association Efficiency of Φ layers of MB1 chambers, as a function of LHC Instantaneous Luminosity.

The mild trend observed last year in the external wheels (Wheel -2 and Wheel +2) is confirmed: the slope is < 0.5% / 10^34 cm^-2 s^-1 and it has no visible effect on the segment reconstruction efficiency (see next section).

The difference between external and central wheels is preserved, corresponding to the difference in HV.

The lower threshold compensates the lower HV (see sketch of HV configurations above) so that overall the loss of efficiency w.r.t. 2017 is < 0.5 %.

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MB4TopHitvsLumi10fb.png

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MB4TopAssvsLumi10fb.png

Hit Efficiency and Hit Association Efficiency of MB4 chambers in top sectors (Sec.4 and Sec.13), as a function of LHC Instantaneous Luminosity.

These chambers are exposed to the background caused by neutron gas.

The efficiency of bottom sectors is also shown for comparison.

No trend is visible.

The lower FE threshold increased the hit efficiency by up to 1.5%, in Wheel-1 and Wheel+1, w.r.t. 2017

DT Segment Efficiency

The DT efficiency to reconstruct a local track segment was defined and measured using a Tag & Probe method.

Events were selected to contain a pair of oppositely charged reconstructed muons.

Muon tracks were required to be well reconstructed in the tracker detector (≥ 6 hits in the strip detector and ≥ 1 hit in the pixel detector), to be well isolated in η and φ from other tracks and to have a separation between each other ΔR = √ (Δη^2+Δφ^2) > 0.3.

  • To ensure that they come from the same interaction vertex, their distance at the point of closest approach to the interaction point should be Δz < 0.1 cm.
  • Their invariant mass should be within 10 GeV of the Z0 mass.

The track used as tag is also required to be well reconstructed in the muon detector, with track segments matched in ≥ 2 muon stations and χ2 < 10. Furthermore, it is required to have a transverse momentum (pT) > 27 GeV and also to pass the High-Level Trigger selection of isolated muons with pT > 27 GeV.

The inner component of track used as probe is propagated inside-out to each station of the DT detector and must have segments matched in ≥ 1 muon stations different from the one under study. It also must have pT > 20 GeV.

A DT chamber crossed by a probe track is considered efficient if a reconstructed segment is found within 15 cm distance of the extrapolated track in the RΦ plane.

The DT Segment Reconstruction Efficiency can be computed:

  • within the full solid angle, in this case it also includes detector acceptance
  • within fiducial regions i.e. discarding probes that cross a chamber within 15 cm of its edges.

Note on method

The observed segment reconstruction efficiency is higher than the hit efficiency, in fact just 3 hits are needed to reconstruct a segment where in principle 8 are available in the Φ view and 4 in the Θ view.

On the other hand, detector regions where hardware problems completely prevented the hit detection (regions not taken into account in the the hit efficiency analysis) are well visible in the following results.

Figure Caption
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Carlo mappa1.png

DT Segment Reconstruction Efficiency computed chamber by chamber within fiducial regions.

Efficiencies for MB4 S4(10) and S13(14) were averaged in a single bin.

Efficiency is above 99%, with few exceptions due to known hardware problems.

pdf version
Carlo mappa2.png

DT Segment Reconstruction Efficiency computed chamber by chamber within fiducial regions.

The 4 chambers of each sector are grouped to form a ”super-box” in the plot.

Efficiencies for MB4 S4(10) and S13(14) were averaged in a single bin.

Efficiency is above 99%, with few exceptions due to known hardware problems.

pdf version
Carlo summary.png

Distribution of DT Segment Reconstruction Efficiency, one entry per chamber, computed within fiducial regions.

Efficiency is above 99%, with few exceptions due to known hardware problems.

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Carlo mappaMB1.png

Segment Reconstruction Efficiency in the MB station, computed for positively charged muons, within the full solid angle, as a function of the probe’s ɸ and η.

Efficiency is close to 100% with few exceptions due to: (i) gaps between wheels and sectors not covered by drift tube chambers, (ii) regions between wheels 0 and -/+1 around ɸ 1-1.5/1.5-2 hosting services, hence not instrumented and (iii) known hardware problems.

pdf version
Carlo mappaMB2.png

Segment Reconstruction Efficiency in the MB station, computed for positively charged muons, within the full solid angle, as a function of the probe’s ɸ and η.

Efficiency is close to 100% with few exceptions due to: (i) gaps between wheels and sectors not covered by drift tube chambers, (ii) regions between wheels 0 and -/+1 around ɸ 1-1.5/1.5-2 hosting services, hence not instrumented and (iii) known hardware problems.

pdf version
Carlo mappaMB3.png

Segment Reconstruction Efficiency in the MB station, computed for positively charged muons, within the full solid angle, as a function of the probe’s ɸ and η.

Efficiency is close to 100% with few exceptions due to: (i) gaps between wheels and sectors not covered by drift tube chambers, (ii) regions between wheels 0 and -/+1 around ɸ 1-1.5/1.5-2 hosting services, hence not instrumented and (iii) known hardware problems.

pdf version
Carlo mappaMB4.png

Segment Reconstruction Efficiency in the MB station, computed for positively charged muons, within the full solid angle, as a function of the probe’s ɸ and η.

Efficiency is close to 100% with few exceptions due to: (i) gaps between wheels and sectors not covered by drift tube chambers, (ii) regions between wheels 0 and -/+1 around ɸ 1-1.5/1.5-2 hosting services, hence not instrumented and (iii) known hardware problems.

pdf version
Carlo effVsEta.png

Segment Reconstruction Efficiency in the four MB stations, computed within the full solid angle, as a function of the probe’s η.

Variations are dominated by the presence of gaps between wheels, not covered by drift tube chambers.

Since here the efficiency is integrated over ɸ, the presence of gaps between sectors has the effect of lowering the efficiency observed within the η acceptance. Station 4 doesn’t have ɸ gaps between most sectors [1] therefore its efficiency, within the η acceptance, is higher than the other stations.

[1] see above the sketch of CMS and the plot of Segment Reconstruction Efficiency in MB4 as a function of ɸ and η.

pdf version
Carlo effVsLumi.png

DT Segment Reconstruction Efficiency computed station by station as a function of LHC instantaneous luminosity.

Efficiency was computed within fiducial regions.

No trend is visible: observed variations for each station are smaller than 0.5%.

pdf version
Carlo effVsVtx.png

DT Segment Reconstruction Efficiency computed station by station as a function of number of reconstructed vertices.

Efficiency was computed within fiducial regions.

No trend is visible: observed variations for each station are smaller than 0.5%.

RPC Hit Efficiency

Figure Caption
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RPC mass.png

tag-probe pair invariant mass distribution for the RPC performance study

Figure Caption
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RPC Barrel.png

RPC overall efficiency distribution in the Barrel

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RPC Endcap.png

RPC overall efficiency distribution in the Endcap

Figure Caption
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RPC EffCmpBarrel.png

2016-2018 comparison of RPC overall efficiency distribution in the Barrel

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RPC EffCmpEndcap.png

2016-2018 comparison of RPC overall efficiency distribution in the Endcap

Spatial Resolution

CSC Spatial Resolution

How CSC spatial resolution measurements are made

  • The spatial resolution was measured using a sample enriched in Z→μ+μ- events.
  • The resolution is estimated by fitting a Gaussian to the distribution of residuals between the reconstructed hit position in one layer of a chamber and the straight-line segment reconstructed from the hits on all other layers in the chamber.
  • Better resolution is expected for hits with muon passing near strip edges than hits with muon passes near the centre of a strip, due to charge sharing between neighboring strips. For non-ME1/1 chambers, alternate layers are offset from each other by half a strip width, and resolutions are determined separately for hits near the edge of a strip and those near the centre.
  • The measurements for each layer within a chamber are combined to obtain a spatial resolution for each chamber:
    • For ME1/1: 1/σstation2 = 6/σlayer2
    • For non-ME1/1: 1/σstation2 = 3/σcenter2 + 3/σedge2

Figure Caption
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csc resolution table.png

Spatial resolutions of CSCs in 2017 and 2018

The table summarizes the resolutions per station measured for all chamber types in the CMS CSC system in early 2018 data, and values measured in 2017 for comparison. These values have been normalized to 965 mbar atmospheric pressure. Statistical uncertainties from the fits are negligible, and systematic uncertainties (∼1-2 μm) dominate. These arise primarily from variation of the resolution with atmospheric pressure, with angle of incidence of the muon, and with muon momentum. The muons were selected from a sample of 2018 data collected in pp collisions at √s = 13 TeV and enriched in Z→μ+μ- events.

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csc spatial resolution plot.png

Spatial resolutions of CSCs in 2017 and 2018.

The plot summarizes the resolutions per station measured for all chamber types in the CMS CSC system in early 2018 data, and values measured in 2017 for comparison. These values have been normalized to 965 mbar atmospheric pressure. Statistical uncertainties from the fits are negligible, and systematic uncertainties (∼1-2 μm) dominate. These arise primarily from variation of the resolution with atmospheric pressure, with angle of incidence of the muon, and with muon momentum. The muons were selected from a sample of 2018 data collected in pp collisions at √s = 13 TeV and enriched in Z→μ+μ- events.

RPC Spatial Resolution

Figure Caption
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RPC cls Barrel.png

RPC cluster size distribution in the Barrel

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RPC cls Endcap.png

RPC cluster size distribution in the Endcap

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rpcBarrelResiduals v1.png

RPC Barrel residuals: Distance between DT-segment extrapolation and the closest RPCRecHit. Gaussian fit is performed on each distribution.

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rpcEndcapResiduals v1.png

RPC Endcap residuals: Distance between CSC-segment extrapolation and the closest RPCRecHit. Gaussian fit is performed on each distribution.

Time Resolution

CSC Time Resolution

How CSC timing measurements are made

  • The CSC reconstructed hit time is obtained by combining the times measured from matched cathode and anode hits.
  • The cathode time is determined from a template fit to the digitized cathode pulse, measured in 8 time bins of 50 ns width, where the peak of the pulse corresponds to the trigger at time = 0.
  • The anode hit times are recorded in bins of 25 ns width over a range of 16 bunch crossings around the trigger time, and the anode time is determined by finding the closest bin(s) to the cathode time. The anode times have a granularity of 12.5 ns, half the time-bin width.
  • Both the anode and cathode times are adjusted by overall offsets (one per ring for anode times, one per chamber for cathode times) in order that the distributions of times are centered at 0. The offsets used here are those derived from 2017 data, and are stored as condition data.
  • The segment time is calculated as an average of the cathode and anode times of the up to 6 hits forming the segment.
  • Muon selection

Figure Caption
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csc cathode time all.png

CSC cathode times

The distribution of times measured by the cathode strips of the CMS Cathode Strip Chambers. The cathode times contributing to this distribution are those associated with reconstructed muons of pT > 5 GeV produced from pp collisions at √s = 13 TeV in a sample of 2018 data collected with a Single Muon trigger. The reconstructed muons satisfy the CMS Muon POG tight muon id criteria. The distribution of times of the reconstructed hits in each chamber was calibrated in 2017 so that the mean time is zero for hits associated with muons directly produced in triggered pp collisions. The 2017 offsets are directly applied to the 2018 data. The mean of -0.3 ns, and RMS of 8.0 ns in 2018 are close to those measured in 2017, 0.0 ns and 7.9 ns respectively.

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csc cathode time rings.png

CSC cathode times per ring

The mean value and RMS width of the distribution of times measured by the cathode strips in the CMS Cathode Strip Chambers, for each ring of chambers in the CMS endcap muon system The cathode times are from hits used to build track segments associated with reconstructed muons of pT > 5 GeV produced in pp collisions at √s = 13 TeV in a sample of 2018 data collected with a Single Muon trigger. The reconstructed muons satisfy the CMS Muon POG tight muon id criteria. The distribution of times of the reconstructed hits in each chamber was calibrated in 2017 so that the mean time is zero for hits associated with muons directly produced in triggered pp collisions. The 2017 offsets are directly applied to the 2018 data.

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csc anode time all.png

CSC anode times

The distribution of times measured by the anode wires of the CMS Cathode Strip Chambers. The anode times contributing to this distribution are those associated with reconstructed muons of pT > 5 GeV produced from pp collisions at √s = 13 TeV in a sample of 2018 data collected with a Single Muon trigger. The reconstructed muons satisfy the CMS Muon POG tight muon id criteria. The distribution of times of the reconstructed hits in each ring was calibrated in 2017 so that the mean time is zero for hits associated with muons directly produced in triggered pp collisions. The 2017 offsets are directly applied to the 2018 data.The anode times have a granularity of 12.5 ns, half the time-bin width. The mean of 0.0 ns, and RMS of 8.5 ns in 2018 are close to those measured in 2017, 0.2 ns and 8.5 ns respectively.

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csc anode time rings.png

CSC anode times per ring

The mean value and RMS width of the distribution of times measured by the anode wires in the CMS Cathode Strip Chambers, for each ring of chambers in the CMS endcap muon system The anode times are from hits used to build track segments associated with reconstructed muons of pT > 5 GeV produced in pp collisions at √s = 13 TeV in a sample of 2018 data collected with a Single Muon trigger. The reconstructed muons satisfy the CMS Muon POG tight muon id criteria. The distribution of times of the reconstructed hits in each ring was calibrated in 2017 so that the mean time is zero for hits associated with muons directly produced in triggered pp collisions. The 2017 offsets are directly applied to the 2018 data.

pdf version
csc segment time all.png

CSC segment times

The distribution of times of reconstructed track segments in the CMS Cathode Strip Chambers. The segment time is calculated by averaging the times measured by the cathode strips and anode wires of the up to 6 reconstructed hits comprising a segment, after time calibration of the cathode and anode times. The segments contributing to this distribution are those associated with reconstructed muons of pT > 5 GeV produced from pp collisions at √s = 13 TeV in a sample of 2018 data collected with a Single Muon trigger. The reconstructed muons satisfy the CMS Muon POG tight muon id criteria. The time calibration was not redone in 2018 but directly used 2017 values. The mean of -0.2 ns, and RMS of 3.4 ns in 2018 are close to those measured in 2017, 0.1 ns, and 3.3 ns respectively.

pdf version
csc segment time rings.png

CSC segment times per ring

The mean value and RMS width of the distribution of times of reconstructed track segments in the CMS Cathode Strip Chambers, for each ring of chambers in the CMS endcap muon system. The segment time is calculated by averaging the times measured by the cathode strips and anode wires of the up to 6 reconstructed hits comprising a segment, after time calibration of the cathode and anode times. The segments are those associated with reconstructed muons of pT > 5 GeV produced in pp collisions at √s = 13 TeV in a sample of 2018 data collected with a Single Muon trigger. The reconstructed muons satisfy the CMS Muon POG tight muon id criteria. The time calibration was not redone in 2018 but directly used 2017 values.

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csc muon time all.png

Muon times from CSC measurements

The distribution of times measured for reconstructed muons based on the times of CSC segments associated with the muon. The muons were selected from a sample of 2018 data collected in pp collisions at √s = 13 TeV with a Single Muon trigger. They are reconstructed as global muons according to Muon POG criteria, and have pT > 5 GeV. The muon time is estimated at the primary pp collision vertex. The mean of -0.1 ns and RMS of 2.1 ns in 2018 are close to those measured in 2017, which were -0.1 ns and 2.3 ns respectively.

RPC Time Resolution

Figure Caption
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RPC bx Barrel.png

RPC bunch crossing distribution in the Barrel

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RPC bx Endcap.png

RPC bunch crossing distribution in the Endcap

Local Trigger Efficiency

TwinMux Efficiency In The Muon Barrel

The DT Local Trigger (DTLT) Efficiency was measured using the same Tag & Probe method and selection described in the previous section.

A DT chamber crossed by the extrapolation of a probe track is tested for the presence of a reconstructed track segment, matching the muon track.
The track segment must be reconstructed in both the Φ and Θ views, and have at least 4 associated hits in the Φ view.

Where those conditions are met, the DTLT is considered efficient if a trigger primitive is found, within the chamber, having the correct BX at the TwinMux output [1]: i.e. after eventual corrections, applied exploiting the RPC information.

In stations MB1 and MB2 also “RPC-only” primitives, merged by TwinMux [1], contribute to the total efficiency.

  • In MB3 and MB4 stations just one layer of RPC is present, therefore no RPC-only trigger is possible.
  • The effect of RPC-only primitives is to increase the efficiency of MB1 and MB2 compared to MB3 and MB4.

Previous results on DTLT using TwinMux "super-primitives", i.e. merging DT and RPC information, were obtained on early 2017 data and can be checked in CMS DP-2018/016 or in this twiki page, for comparison.

[1] see: CMS CMS DP-2016/074 or this twiki page

Figure CaptionSorted ascending
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DTLT efficiency chamber map.png

DT Local Trigger Efficiency chamber by chamber.

The empty box in MB2/Wheel2/Sector7 is due to the inefficient Θ Superlayer already mentioned in the "Hit efficiency" section, which prevents the probe conditions to be met in this chamber. When dropping the request of Θ hits to be associated to the reconstructed track segment, the computed trigger efficiency is > 95%.

The red box in MB3/Wheel1/Sector 4 is caused by a not working trigger board.

All other cases of efficiency lower than the average are due to known hardware problems.

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DTLTeff vs lumi.png

DT Local Trigger Efficiency computed station by station as a function of LHC instantaneous luminosity.

No trend is visible: observed variations for each station are smaller than 0.5%.

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DTLT etaVsphi.png

DT Local Trigger Efficiency computed within the full solid angle, as a function of the probe’s ɸ and η.

The separation between wheels and sectors and the not instrumented regions are well visible.

The apparent inefficiency of MB2/Wheel2/Sector7, discussed for the previous plot, is here split at the leftmost and rightmost φ values (±π), at η≅1.

pdf version
DTLTeff vs eta.png

DT Local Trigger Efficiency in the four MB stations, computed within the full solid angle, as a function of the probe’s η.

Variations are dominated by the presence of gaps between wheels, not covered by drift tube chambers. Far from these gaps, the efficiency is near 99% for MB1 and MB2. It is 95-96% for MB3 and MB4, where the RPC-only primitives are not implemented.

Event displays for two candidate Z→μ+μ- events

Figure Caption
zmm r316569 e1867479361 m92 i.png

Z→μ+μ- candidate event 1

Event display of a →μ+μ- candidate, drawn with iSpy (https://github.com/cms-outreach/ispy-webgl). There are two reconstructed global muons (red lines) with an invariant mass of 92 GeV. One muon is detected in the CSCs and the other in the Drift Tube chambers. The event display shows reconstructed tracks (yellow), hit strips and wiregroups in the CSCs (purple), the rechits built from these hits (turquoise), and track segments built from the rechits (pink). Also in the display are DT segments(yellow), RPC hits (yellow), ECAL rechits (green), HCAL rechits (blue), and HF rechits (cyan).

zmm r316569 e1867479361 m92 ii.png

Z→μ+μ- candidate event 1

Event display of a →μ+μ- candidate, drawn with iSpy (https://github.com/cms-outreach/ispy-webgl). There are two reconstructed global muons (red lines) with an invariant mass of 92 GeV. One muon is detected in the CSCs and the other in the Drift Tube chambers. The event display shows reconstructed tracks (orange), hit strips and wiregroups in the CSCs (purple), the rechits built from these hits (turquoise), and track segments built from the rechits (pink). Also in the display are DT segments(orange), RPC hits (orange), ECAL rechits (green), HCAL rechits (blue), and HF rechits (cyan).

zmm r316569 e1868238935 m93 i.png

Z→μ+μ- candidate event 2

Event display of a →μ+μ- candidate, drawn with iSpy (https://github.com/cms-outreach/ispy-webgl). There are two reconstructed global muons (red lines) with an invariant mass of 93 GeV. One muon is detected in the CSCs and the other in the Drift Tube chambers. The event display shows reconstructed tracks (yellow), hit strips and wiregroups in the CSCs (purple), the rechits built from these hits (turquoise), and track segments built from the rechits (pink). Also in the display are DT segments(yellow), RPC hits (yellow), ECAL rechits (green), HCAL rechits (blue), and HF rechits (cyan).

zmm r316569 e1868238935 m93 ii.png

Z→μ+μ- candidate event 2

Event display of a →μ+μ- candidate, drawn with iSpy (https://github.com/cms-outreach/ispy-webgl). There are two reconstructed global muons (red lines) with an invariant mass of 93 GeV. One muon is detected in the CSCs and the other in the Drift Tube chambers. The event display shows reconstructed tracks (orange), hit strips and wiregroups in the CSCs (purple), the rechits built from these hits (turquoise), and track segments built from the rechits (pink). Also in the display are DT segments(orange), RPC hits (orange), ECAL rechits (green), HCAL rechits (blue), and HF rechits (cyan).

-- CarloBattilana - 2018-06-26

Topic attachments
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PDFpdf csc_anode_time_rings.pdf r1 manage 31.6 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_anode_time_rings.png r1 manage 123.5 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_cathode_time_all.pdf r1 manage 32.6 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_cathode_time_all.png r1 manage 109.0 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_cathode_time_rings.pdf r1 manage 31.6 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_cathode_time_rings.png r1 manage 123.4 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_muon_time_all.pdf r1 manage 29.7 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_muon_time_all.png r1 manage 100.3 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_resolution_table.pdf r1 manage 21.3 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_resolution_table.png r1 manage 175.7 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_segment_time_all.pdf r1 manage 31.5 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_segment_time_all.png r1 manage 108.6 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_segment_time_rings.pdf r1 manage 31.2 K 2018-06-29 - 16:41 TimCox  
PNGpng csc_segment_time_rings.png r1 manage 117.0 K 2018-06-29 - 16:46 TimCox  
PDFpdf csc_spatial_resolution_plot.pdf r1 manage 29.0 K 2018-06-29 - 19:50 TimCox  
PNGpng csc_spatial_resolution_plot.png r1 manage 181.6 K 2018-06-29 - 19:50 TimCox  
PDFpdf rpcBarrelResiduals_v1.pdf r1 manage 68.0 K 2018-07-10 - 10:49 RoumyanaHadjiiska rpc residulas with segment extrapolation
PDFpdf rpcEndcapResiduals_v1.pdf r1 manage 71.9 K 2018-07-10 - 10:49 RoumyanaHadjiiska rpc residulas with segment extrapolation
PNGpng zmm_r316569_e1867479361_m92_i.png r1 manage 646.6 K 2018-06-29 - 16:46 TimCox  
PNGpng zmm_r316569_e1867479361_m92_ii.png r1 manage 641.7 K 2018-06-29 - 16:46 TimCox  
PNGpng zmm_r316569_e1868238935_m93_i.png r1 manage 637.2 K 2018-06-29 - 18:33 TimCox  
PNGpng zmm_r316569_e1868238935_m93_ii.png r1 manage 636.9 K 2018-06-29 - 16:46 TimCox  
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Topic revision: r9 - 2018-09-26 - TimCox
 
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