Available on the CERN CDS information server
CMS PAS QCD-07-002
CMS Physics Analysis Summary
Contact: cms-pag-conveners-qcd@cern.ch
2012/02/10
Zero bias and HF-based minimum bias
triggering for pp collisions at 14 TeV in CMS
The CMS Collaboration
Abstract
The analysis of the underlying event structure in pp collisions begins with an efficient
and minimally biased data sample. This document describes the feasibility of obtaining zero bias data and presents an approach to triggering minimum bias collisions
with the CMS detector. Triggering such collisions that often have just a handful of
particles is difficult and can lead to severe biases on the data, thus the possibility to
obtain zero bias data is evaluated for various beam bunch patterns and luminosity
regions. For regions where zero bias triggering is not feasible, the merits of utilising
the forward hadronic calorimeter (HF) as a minimum bias trigger is discussed and
fully simulated. We find that using HF in a single-side configuration, a hard core
(non-diffractive) efficiency of ∼80% can be attained, whilst retaining some sensitivity to diffractive type collisions. Estimated rates and suggested prescale factors are
presented for each beam-bunch pattern configuration. The merits of zero-bias and
HF-triggered minimum bias are also discussed.
1
1
Introduction
Measurements of the underlying event structure, such as the pseudorapidity distributions and
transverse-momentum spectra of charged particles, rely on a physics data sample which is
100% efficient at collecting the data and is free from bias. It is thus of interest to evaluate if
it is possible to obtain such “zero bias” data during the various luminosity and beam bunch
configurations expected during the LHC startup. For the cases where this is not possible, it is
also equally prudent to be prepared with additional detector-based minimum bias triggering
possibilities and schemes.
The advantage of a detector based trigger is that it will be effective for all luminosities and
beam bunch configurations. The disadvantage, of course, is that it is very difficult to obtain a
detector triggered data sample that is 100% efficient; as with any triggered data sample some
events are not triggerable, whilst other events are sacrificed to decrease background contributions. The aim of the study presented here is to determine regions where zero bias triggering
is feasible and for all other regions to explore in detail a detector based minimum bias trigger
that maximises the efficiency while still maintaining a low background level.
It is proposed that an effective trigger for underlying event data utilises the CMS forward
hadronic calorimeters (HF) [1] which are located at 3<|η |<5. The HF position is similar to
what was done in other experiments that have measured underlying events in lower energy
pp(p) collisions (for example CDF [2], PHOBOS [3]). For triggering, energy deposits from predefined regions of HF are summed to form “trigger towers” allowing a fast read out at Level-1.
Two energy thresholds are applied to this trigger to remove effects of detector noise. First, a
threshold at the calorimeter tower level of 0.8 GeV (1-σ) is applied to the fibres, before summing
towers into the trigger towers. A second energy threshold is applied on each trigger tower with
ET > 0.5 GeV (see Tables 2, 3 and 4). This minimum threshold corresponds to 2.3σ above the
noise for η = 3.25 (outermost HF ring) and 10.4σ above the noise for η = 4.75 (innermost HF
ring). In the case of ET > 1.0 GeV the thresholds are 4.6σ for η = 3.25 and 20.8σ for η = 4.75.
To trigger the read out of the detector, the trigger towers (with energy above threshold) are
counted (independently for the +η HF and -η HF). If the number of trigger towers struck is
above a second (number, not energy) threshold, then the event will be considered for minimum bias triggering.
Background triggering may comprise a considerable amount of data for the first run. Effects
such as beam gas/halo and triggering noise pose problems which need to be overcome before
the trigger will be effective. The balance of rates from background sources to real collision
signals must be tuned carefully to minimise bias on the final data sample and maximise the
number of true pp collisions written to tape for use in physics analysis.
2
Expected luminosity at the LHC
The LHC will provide a steady increase of luminosity with differing beam bunch patterns
starting with 43 × 43 (out of a possible 3564 bunch buckets) and a luminosity of ≈ 3.8 ×
1029 cm−2 s−1 (see Table 1). This initial configuration will, perhaps, provide a significant fraction of the minimum bias dataset. For this bunch pattern configuration, the number of collisions (per bunch crossing) is expected to be small, O(10−3 ), as shown in Figure 1. As such,
triggering with the ZeroBias scheme would only yield a collision every 1000 read-out events.
At this time, the detector-based trigger would be more effective (see Figure 2).
A more detailed view of the triggering rate can be found in Figure 2. Here, the triggered rate
2
3
Triggering Scheme
and expected fraction of “ideal data” (one and only one collision per bunch crossing) are presented. Two regions are identified which would provide optimal detector-based triggering (at
the lowest luminosities) and ZeroBias triggering (when the fraction of ideal data exceeds 0.2,
i.e. at least 1 in 5 events contains a usable collision). It is immediately apparent that triggering
significant amounts of ZeroBias data in the low luminosity region would “waste” the valuable
bandwidth for detector read-out 1 . A similar analysis of each bunch configuration can be found
in the Appendix. It should be noted that the regions are defined with specific physics analyses in mind, such as charged hadron transverse momentum spectra. Some ZeroBias events
are necessary for all luminosities for calibration purposes; for example, to calibrate jet energy
backgrounds.
Table 1: Table representing possible expectations for beam bunch patterns and associated luminosities during early LHC operations. In the LHC commissioning plan, various combinations of bunch patterns and associated luminosity expectations are broken into “stages”. For
the purpose of this study, the bunch pattern and associated beam luminosity are the relevant
quantities.
Bunch Pattern
Luminosity Range [cm−2 s−1 ]
1×1
1027
43 × 43
3.8 × 1029 − 6.1 × 1030
156 × 156
1.1 × 1031 − 1.1 × 1032
936 × 936
2.3 × 1031 − 5.0 × 1032
2808 × 2808
1.7 × 1032 − 1.0 × 1034
It is possible to turn these expected rates into prescale factors to limit the Level-1 read-out rate
to 10 Hz, see Figure 3. Accounting for the empty and multiple collisions per read-out, the lower
panel of Figure 3 shows the expected rate of “ideal data” which will be written to tape.
3
Triggering Scheme
Three specific Level-1 minimum bias triggers are proposed in order to provide maximum flexibility in obtaining the highest quality of minimum bias data under a wide range of possible
backgrounds, beam conditions, luminosities and bunch pattern configurations.
• ZeroBias is a beam bunch crossing-time trigger used to obtain a “zero bias” data
sample, with 100% efficiency (by definition). Only active beam bunch crossings are
to be read out to maximise the probability of obtaining events with valid collisions.
• MinbiasHFsingle is the HF-based minimum bias detector trigger which requires at
least one HF trigger tower to fire above an energy threshold on either side, i.e. a
single-side trigger. This is more efficient than the double-side trigger, below, and
depending on the thresholds can accept a reasonable fraction of the diffractive type
collisions. This trigger is favourable over the ZeroBias when the luminosity, and
thus the rate of collisions to tape, is too low for ZeroBias to be effective.
• MinbiasHFdouble is a less efficient HF-based minimum bias detector trigger which
requires at least one HF trigger tower to fire above an energy threshold on both sides,
1 This statement assumes that every event should be used for physics analysis. A reasonable amount of empty
read-out events could provide useful information for detector noise evaluation, thus not “wasting” bandwidth.
Average Number of Collisions per Bunch Crossing
3
Regions of ideal data for different bunch patterns
p+p - √s = 14TeV (σ = 79mb)
10
1
Region not useful for ideal data
Region for ZeroBias and
triggered minimum
bias ideal data
-1
10
10-2
h
56
1
6x
15
nc
bu
rn
tte
pa
ern
att
hp
10-3
nc
bu
36
x9
6
3
c
un
b
ern
att
p
h
bu
nc
8
0
28
ern
att
hp
8x
0
28
9
CMS preliminary
3
x4
43
Region for triggered minimum bias ideal data
1028
1029
1030
1031
1032
1033
1034
Luminosity (cm-2 s-1)
Figure 1: The average number of collisions per beam bunch crossing versus beam luminosity
for the four beam bunch schemes that are expected to be used during the LHC commissioning
and early running. As shown on the figure, calculations assume a pp collision cross-section of
σ = 79 mb. One can identify three general regions of relevance when desiring to trigger on
“ideal data” (i.e. data with no pile-up). Regions were determined by requiring that ≥ 20% of
accepted events must be ideal data.
i.e. a double-side trigger. This trigger is most sensitive to hard-core collisions and
has the possibility of rejecting most beam gas/halo collisions that occur within the
CMS detector.
Each of these triggers will have unique efficiencies, sensitivity to various backgrounds, and
imposed biases on the resulting data sets, which must be understood to enable the reconstruction of, for example, the inelastic charged particle multiplicity. For this reason, a mixture of the
above triggers will comprise the minimum bias data sets. This mixture will enable studies of
bias for use in various physics analyses.
4
Estimated Efficiency
The efficiencies of the single and
√ double HF-based minimum bias triggers were evaluated using
simulations of pp collisions at s = 14 TeV from a sample of PYTHIA [4] events with the DWT
tune. The results for different HF trigger tower number requirements and energy thresholds
are given in Tables 2 (single-side) and 3 (double-side). The corresponding sensitivity of each
combination to the current expected level of noise in the HF is given in Table 4.
4
4
Estimated Efficiency
Triggered data rates and fraction of ideal data
Triggered Rate (Hz)
43x43 beam-bunch pattern
107
p+p - √s = 14TeV (σ = 79mb)
106
ZeroBias trigger
105
CMS preliminary
104
3
10
Fraction of ideal data
AllBucket trigger
1.0
m
Mini
ias
um b
er
trigg
28
10
29
10
30
10
31
10
Minimum bias trigger
0.8
0.6
Region for triggered minimum bias ideal data
0.4
0.2
Region for ZeroBias
and triggered minimum
bias ideal data
ZeroBias trigger
0.0
1028
1029
1030
1031
Luminosity (cm-2 s-1)
Figure 2: Triggering rate and fraction of ideal data for the 43 × 43 beam bunch pattern. Top
panel is the average triggered rate using a beam crossing-time trigger (dashed line), which
would yield “zero bias” data, and using a detector-based minimum bias trigger (solid line).
Bottom panel is the fraction of triggered data that would be usable as ideal (i.e. no pile-up)
minimum bias data in physics analyses. The detector triggered lines (solid) assume a 100%
efficient detector trigger that samples the full 79 mb cross-section assumed for 14 TeV pp collisions.
The lowest possible thresholds in both the single and double-side cases yield good efficiencies to all “types” of pp collisions (minimum bias, hard-core, single diffractive, and double
diffractive). Unfortunately, for the currently expected noise levels in HF, the minimal triggering energy threshold of ET ≥ 0.5 GeV (compressed scale EC
T ≥ 1) would allow a high rate of
noise triggers and significantly dilute the effectiveness of the minimum bias trigger in the low
luminosity regions where zero bias triggering is not feasible.
A detailed study of efficiency, the expected noise levels, and the loss of ideal minimum bias data
to same-bunch pile-up (also known as in-time pile-up) indicates that requiring one HF trigger
tower to fire (on either or both sides) above a default triggering transverse energy threshold of
1.0 GeV (compressed scale EC
T ≥ 2) is likely the most reasonable compromise. This transverse
energy threshold setting is equivalent to a total energy threshold of 10 GeV at η = 3 and 80 GeV
at η = 5.
Using these default settings (Ntt =1, ET ≥ 1.0 GeV) results in a hard-core triggering efficiency
5
Ideal Rate (Hz)
Prescale Factor (for 10Hz rate)
Prescale Factor To Achieve 10 Hz Trigger Rate
p+p - √s = 14TeV (σ = 79mb)
106
CMS preliminary
105
104
103
102
10
8
6
4
2
0
43×43
156×156
936×936
2808×2808
triggered
minimum
ZeroBias
bias
1028
1029
1030
1031
1032
1033
1034
1028
1029
1030
1031
1032
1033
1034
Luminosity (cm-2 s-1)
Figure 3: Upper panel: required prescale factor to achieve a data rate-to-tape of 10 Hz for each
bunch pattern at the LHC, versus luminosity, shown for triggering by zero bias (dashed lines)
and (100% efficient) minimum bias collision (solid lines). Lower panel: corresponding rate of
ideal data expected to be recorded to tape.
of ∼80.8% for the single-side trigger (Table 2). In this case, the diffractive type collisions are
also recorded at an efficiency level of ∼15%, although this trigger would be more susceptible
to beam gas/halo collisions. The double-side trigger (Table 3), with the default settings, has
a hard core efficiency of ∼47.5%. Unfortunately, the efficiency for recording diffractive collisions is negligible (∼ 0.6%) in this case as the symmetric triggering coupled with the high
energy thresholds largely removes the predominantly asymmetric diffractive events. Studies
of the triggering efficiencies using the EPOS [5] and QGSII [6] event generators indicate that
the efficiencies obtained using PYTHIA are a lower limit.
Increasing the energy thresholds and/or requiring a higher number of trigger towers hit, results in an increased loss of events, predominantly diffractive and low multiplicity collisions.
Decreasing the thresholds allows a larger fraction of diffractive collisions to be recorded, but at
the expense of allowing more noise triggers (see Table 4).
6
5
Conclusion
Table 2: Single-side HF trigger efficiencies. The number of trigger towers required to trigger
is shown in the first column. For example, the first row requires at least one trigger tower
on either the positive or negative HF. The compressed and the actual trigger tower energy
thresholds are noted in the second and third columns, respectively. In the remaining columns
the efficiencies are broken down into collision type.
Number
Required
1
HF Trigger Towers
Energy Threshold
Compressed
Actual (GeV)
(EC
≥
)
(ET >)
T
1
0.5
Collision Type Efficiency (%)
Minimum
Hard
Single
Double
bias
core
diffractive
91.9
98.9
74.9
76.8
1
2
1.0
61.1
80.8
15.0
15.3
1
2
2
2
3
1
2
3
1.5
0.5
1.0
1.5
41.2
78.7
40.8
23.6
57.4
93.9
57.6
33.7
3.1
41.6
1.5
0.1
3.4
44.8
1.3
0.0
Table 3: Double-side HF trigger efficiencies. The columns are as for Table 2, except that the
meaning of the first column has changed to be the number of trigger towers required to fire on
each of the positive and negative HF.
Number
Required
1
5
HF Trigger Towers
Energy Threshold
Compressed
Actual (GeV)
C
(ET ≥)
(ET >)
1
0.5
Collision Type Efficiency (%)
Minimum
Hard
Single
Double
bias
core
diffractive
71.5
88.7
31.3
30.9
1
2
1.0
33.5
47.5
0.6
0.7
1
2
2
2
3
1
2
3
1.5
0.5
1.0
1.5
18.7
53.3
20.3
10.7
26.7
73.0
29.0
15.2
0.0
7.8
0.0
0.0
0.0
5.9
0.0
0.0
Conclusion
Studies of minimum bias triggering for pp collisions at 14 TeV indicate that there are regions
of luminosity and beam bunch patterns that will require a detector-based minimum bias trigger as well as regions where a zero bias trigger could additionally be employed. The CMS
forward hadronic calorimeters (HF) are detectors that can be utilised to provide a reasonably
efficient trigger for minimum bias collisions, while also providing flexibility to handle possible high backgrounds from beam bas/halo events. Recommended default HF-based minimum
bias triggers are presented with corresponding hard core efficiencies of ∼80% for a single-side
trigger and ∼ 47% for a double-side trigger, which provides additional rejection capabilities
to beam gas/halo backgrounds. Sensitivity to diffractive collision processes with the default
threshold settings exists for the single-side trigger with an efficiency of ∼15%. Higher efficiencies are possible, depending on the noise levels in HF.
7
Table 4: Single- and double-side HF noise-only trigger efficiencies (Ncoll = 0) compared to
the single collision minimum bias efficiency (Ncoll = 1). Efficiencies for diffractive and nondiffractive collision types can be found in Tables 2 and 3.
Number
Required
1
HF Trigger Towers
Energy Threshold
Compressed
Actual (GeV)
C
(ET ≥)
(ET >)
1
0.5
Acceptance Efficiency (%)
Single-side
Double-side
Ncoll = 0
Ncoll = 1
Ncoll = 0
Ncoll = 1
50.2
91.9
15.0
71.5
1
2
1.0
0.04
61.1
0.00
33.5
1
2
2
2
3
1
2
3
1.5
0.5
1.0
1.5
0.00
16.1
0.00
0.00
42.1
78.7
40.8
23.6
0.00
1.52
0.00
0.00
18.7
53.3
20.3
10.7
References
[1] CMS Collaboration, “The Compact Muon Solenoid Technical Proposal”, CERN/LHCC
94-38 (1994).
[2] F. Abe et al., “Pseudorapidity
distributions of charged particles produced in pp
√
interactions at s=630 and 1800 GeV.”, Phys. Rev. D41 (1990) 2330.
[3] B. B. Back et al., “Charged antiparticle to particle ratios near midrapidity in p+p collisions
√
at s NN =200 GeV”, Phys. Rev. C71 (2005) 021901.
[4] T. Sjostrand, S. Mrenna, and P. Skands, “PYTHIA 6.4 physics and manual (*version 8 was
used)”, JHEP 05 (2006) 026.
[5] K. Werner et al., “Parton ladder splitting and the rapidity dependence of transverse
momentum spectra in deuteron gold collisions at RHIC”, Phys. Rev. C74 (2006) 044902,
arXiv:hep-ph/0506232.
[6] N. N. Kalmykov, S. S. Ostapchenko, and A. I. Pavlov, “Quark-gluon string model and EAS
simulation problems at ultra-high energies”, Nucl. Phys. Proc. Suppl. 52B (1997) 17–28.
8
A
A
Additional Supporting Figures and Tables
Additional Supporting Figures and Tables
LHC Luminosity
Ideal data fractions
Fraction of ideal data
for ZeroBias and triggered minimum bias
1.01
0.8
1
(a)
0.8
bunch pattern
bunch pattern
43×43
936×936
0.6
0.6
0.6
0.4
0.4
0.4
minimum bias
ZeroBias
0.2
0.2
0.00
1.01 10
28
0.8
0.8
(c)
0.8
Region for ZeroBias
and triggered minimum0.2
bias ideal data
Region for
triggered
minimum
bias ideal data
Region not useful
for ideal data
0
29
10
30
10
31
32
10
10
(b)
30
1 10
31
32
10
10
33
34
10
10
(d)
0.8
bunch pattern
bunch pattern
156×156
2808×2808
0.6
0.6
0.6
0.4
0.4
0.4
CMS preliminary
0.2
0.2
0.2
0.00
0
28
10 28
10
29
10 29
10
30
10 30
10
31
10 31
10
32
30
10 32 1030
10 10
31
10
32
1031
10
1032
33
10
1033
34
10
1034
Luminosity (cm -2 s-1)
Figure 4: The fraction of triggered data that would be usable as “ideal data” in physics analyses
for two different triggers, a beam crossing-time trigger (that would yield “zero bias” data) and
a 100% efficient detector-based trigger (that would yield “minimum bias” data). The shaded
regions have the same meaning as in Figures 1 and 2.
Table 5: Table of prescale factors to achieve 10 Hz of actual data-taking rate and the corresponding ideal data rates for the LHC Stage A commissioning. The ideal data rate refers to
minimum bias data with one and only one collision per bunch crossing.
Stage A Physics Run Plan∗
Average
Results for 10 Hz Data-Taking Rate
ZeroBias Trigger
Minimum Bias Trigger∗∗
Bunch
Luminosity
Events per
Prescale
Ideal Data
Prescale
Ideal Data
Pattern
(cm−2 s−1 )
Crossing
Factor
Rate (Hz)
Factor
Rate (Hz)
1×1
1.6 × 1027
0.011
1.1 × 103
0.11
1.3 × 101
9.9
43 × 43
7.0 × 1028
0.011
4.8 × 104
0.11
5.5 × 102
9.9
43 × 43
1.1 × 1030
0.18
4.8 × 104
1.5
8.7 × 103
9.1
43 × 43
6.1 × 1030
1.0
4.8 × 104
3.7
4.8 × 104
5.8
156 × 156
2.2 × 1031
1.0
1.8 × 105
3.7
1.7 × 105
5.9
156 × 156
1.1 × 1032
5.0
1.8 × 105
0.35
1.8 × 105
0.35
∗ CMS Week, 19sep07, Helmut Burkhardt, “LHC Backgrounds, Luminosity and more”
∗∗ These values assume a 100% efficient detector-based minimum bias trigger.
9
dNch
dη
from pp collisions at
1 dNch
N event ddN
η
ch
1
N event d η
Generated
p+p - √s = 14TeV
66
(b)
6
minimum bias
collisions
hard core
collisions
4
22
2
66
-10
0
10
(c)
0
-10
0
double diffractive
collisions
4
22
2
-10
0
-10
10
(d)
CMS preliminary
6
single diffractive
collisions
44
00
s = 14 TeV
(a)
pythia simulation
44
0
√
10
0
10
0
-10
0
-10
0
10
10
η
η
p+p - √s = 14TeV
8
1 dNch
N event d η
1 dNch
N event d η
Figure 5: The number of charged particles per unit pseudo-rapidity (averaged over many
events) for minimum bias collisions (a), hard core collisions (b) and single- (c) and doublediffractive collisions (d). The distributions were generated via the PYTHIA Monte-Carlo generator (DWT tune). Note in (c) open and closed symbols represent the possible fragmentation
directions. Effective triggering of all collision types is the main aim of the minimum bias trigger, although this is challenging in the context of diffractive collisions.
CMS preliminary
EPOS simulation
pythia simulation
p+p - √s = 14TeV
8
6
6
4
4
2
2
0
-10
0
0
10
η
CMS preliminary
QGSII simulation
pythia simulation
-10
0
10
η
Figure 6: Comparison of the minimum bias dNch /dη distributions from P YTHIA (open circles)
to EPOS (left panel, closed circles) and QSGII (right panel, closed circles). Both EPOS and
QSGII calculations predict more charged particles than P YTHIA.
10
A
Additional Supporting Figures and Tables
Table 6: HF trigger efficiencies for P YTHIA, EPOS and QGSII monte-carlo generators. The
number of trigger towers required to trigger is shown in the first column. For example, the first
row requires at least one trigger tower on either the positive or negative HF. The compressed
(actual) trigger tower energy threshold is noted in the second (third) column. The remaining columns show the minimum bias efficiencies for single- and double-side triggers for each
model used.
1 dNch
N event d η
HF Trigger Towers
Number
Energy Threshold
Required Comp’d
Actual
(EC
≥
)
(E
T >) (GeV)
T
1
1
0.5
1
2
1.0
1
3
1.5
2
1
0.5
2
2
1.0
2
3
1.5
Trigger Efficiency (%)
Single-side Triggers
Double-side Triggers
P YTHIA EPOS QGSII P YTHIA EPOS QGSII
91.9
61.1
41.2
78.7
40.8
23.6
95.6
68.7
50.2
83.2
51.5
33.5
p+p - √s = 14TeV
6
94.7
77.9
61.9
85.9
60.2
35.8
71.5
33.5
18.7
53.3
20.3
10.7
77.1
44.3
29.7
60.9
31.8
17.9
82.2
48.4
28.1
66.5
30.5
11.9
CMS preliminary
pythia simulation
minimum bias collisions
Fixed Target (7TeV)
hijing 1.383 simulation
p+O
p+p
HF region
4
2
0
-10
p(7TeV)
0
O(0TeV)
10
η
Figure 7: The number of charged particles per unit pseudo-rapidity for minimum bias collisions compared to beam gas collisions occurring at the centre of the detector. Closed circles
represent the minimum bias collisions at 14 TeV, open circles represent the collision of protons
on stationary protons (i.e. hydrogen nuclei). Closed grey squares represent the collision of protons on stationary oxygen nuclei, the largest nuclei of the expected beam gas/halo interactions.
The beam gas collisions show a distinctly one-sided distribution relative to the collision point.
P(Nch )×100
11
p+p - √s = 14TeV
1.5
CMS preliminary
pythia simulation
minimum bias collisions
minimum bias
hard core
single diffractive
double diffractive
1.0
0.5
0.0
0
100
200
300
Number of Charged Particles
Figure 8: The frequency distribution of the total number of charged particles, as calculated
over the whole pseudo-rapidity range for minimum bias (solid black circles), hard core (grey
circles), single-diffractive (black squares) and double-diffractive (open circles) collisions.
100
p+p - √s = 14TeV
80
Number of HF Trigger Towers (η>0)
Number of HF Trigger Towers
Triggering minimum bias collisions with HF
CMS preliminary
pythia simulation
minimum bias collisions
60
40
20
0
0
50
100
150
200
Number of Generated Particles (3<|η|<5)
50
p+p - √s = 14TeV
CMS preliminary
40 pythia simulation
minimum bias collisions
102
30
20
10
10
1
0
0
10
20
30
40
50
Number of HF Trigger Towers (η<0)
Figure 9: Left panel: correlation between the total number of trigger towers in the forward
hadronic calorimeters (HF) and the number of generated charged particles impinging the
pseudo-rapidity region covered by HF. Right panel: Correlation between the number of hit
trigger towers from the positive and negative forward hadronic calorimeters (HF).
12
ch
P(N )×100
A
p+p - √s = 14TeV
1.5
1.5
(a)
(b)
1.5
pythia simulation
minimum bias
collisions
hard core
collisions
1.0
1.0
1.0
0.5
0.5
0.5
0.0
0.0
0
100
Additional Supporting Figures and Tables
0.0
3000
200
non-triggered
No. of Trig. Towers Hit≥1
Trig. Tower TPG ET ≥1 (Comp.)
OR triggered
AND triggered
100
200
(c)
1.5
1.5
CMS preliminary
1.5
single diffractive
collisions
double diffractive
collisions
1.0
1.0
1.0
0.5
0.5
0.5
0.0
0.0
0
0
100
100
300
(d)
200
200
0.0
3000
0
100
100
200
200
300
300
Number of Charged Particles
Figure 10: Illustration of the triggering efficiency for minimum bias collisions (a), hard core
collisions (b) and single- (c) and double-diffractive collisions (d).
13
fake rate due to
pile-up
p+p - √s = 14TeV
100
(a)
pythia simulation
minimum bias collisions
100
50
50
0
1
2
0
1
2
100
50
0
0
1
1
2
2
0
1
2
0
(e)
100
100
50
50
0
(g)
0
1
2
0
(h)
100
100
50
50
0
0
0
1
1
2
2
0
0
1
2
1
2
1
2
(f)
0
CMS preliminary(i)
⟨N coll⟩ = 1.00
50
0
50
0
50
0
50
(d)
50
0
(c)
100
OR Trigger
AND Trigger
100
0
100
(b)
100
⟨N coll⟩ = 0.51
0
100
0
fake rate due to
empty events and pile-up
⟨N coll⟩ = 0.25
Single-Collision Minimum Bias Efficiency (%)
fake rate due to
empty events
0
0
1
2
Relative Rate: Fake
Ideal
Figure 11: The single collision (no pile-up) minimum bias efficiency
versus the rate of fake
collisions (relative to the ideal data collision rate). The columns show the fake rate for empty
events - random noise triggering - ((a),(d),(g)), the fake rate of pile-up only ((b),(e),(h)) and for
both combined ((c),(f),(i)). The rows show three average number of collision cases, illustrating
the relative interplay of noise and pile-up on the trigger. Each data point represents a different
triggering setup (various energy thresholds and number of towers hit). Dark (light) symbols
represent the single-side (double-side) triggering scenarios.
14
A
100
100
p+p - √s = 14TeV
ideal data loss due to
pile-up
(a)
pythia simulation
minimum bias collisions
50
50
OR Trigger
AND Trigger
50
100
100
(d)
50
100
50
50
0
0
0
0
50
50
100
(e)
0
0
50
50
(g)
0
0
50
100
(h)
0
0
100
100
50
50
0
0
100 0
50
50
100
0
0
100 0
50
100
50
100
50
100
(f)
CMS preliminary (i)
⟨N coll⟩ = 1.00
100
100
⟨N coll⟩ = 0.51
0
0
50
100
50
100
0
0
100
50
0
(c)
100
50
0
0
(b)
100
50
0
100
ideal data loss due to
empty events and pile-up
⟨N coll⟩ = 0.25
Single-Collision Minimum Bias Efficiency (%)
ideal data loss due to
empty events
Additional Supporting Figures and Tables
50
100
Fraction of Ideal Data (%)
Figure 12: The single collision (no pile-up) minimum bias efficiency versus the fraction of
ideal data (expected to be recorded to tape). The columns show this fraction for empty events
- random noise triggering - ((a),(d),(g)), the ideal fraction when only considering pile-up only
((b),(e),(h)) and for both combined ((c),(f),(i)). The rows show three average number of collision
cases, illustrating the relative interplay of noise and pile-up on the trigger. Each data point
represents a different triggering setup (various energy thresholds and number of towers hit).
Dark (light) symbols represent the single-side (double-side) triggering scenarios.
15
Effect of HF triggering on physical measurements
p+p - √s = 14TeV
CMS preliminary
ch
pythia simulation
P(N
non-triggered
No. of Trig. Towers Hit≥1
Trig. Tower TPG E ≥1 (Comp)
T
OR triggered
AND triggered
10
Efficiency (%)
|η|<2
)×100
15
100
5
50
00
50
100
Number of Charged Particles (|η|<2)
0
0
50
100
150
Number of Charged Particles (|η|<2)
p+p - √s = 14TeV
1 dNch
N event d η
1 dNch
N event d η
Figure 13: Multiplicity distribution of charged particles (|η | < 2). The black symbols represent
the total inelastic cross-section. Dark (light) grey symbols show the distribution for single-side
(double-side) HF triggers. The insert figure shows the efficiency versus the number of charged
particles (|η | < 2) for both HF triggers.
(a)
CMS preliminary
pythia simulation
6
4
p+p - √s = 14TeV
6
4
non-triggered
OR triggered
AND triggered
No. of Trig. Towers Hit≥1
Trig. Tower TPG E ≥1 (Comp)
2
non-triggered
OR triggered
AND triggered
No. of Trig. Towers Hit≥1
Trig. Tower TPG E ≥1 (Comp)
2
T
T
0
(b)
CMS preliminary
pythia simulation
-10
0
0
10
η
-10
0
10
η
ch
Figure 14: Panel (a) shows the dN
dη per event measured for the total (non-triggered) inelastic
cross-section (black symbols) single- (dark grey) and double-side (light grey) triggered events.
Panel (b) shows the same data as (a) but events are inverse-weighted by the efficiency found in
Figure 13.