- Email: [email protected]
Performance of the CMS tracker in high level trigger
ARTICLE IN PRESS
Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
Performance of the CMS tracker in high level trigger M. Lenzi* CERN, EP Division, 1211 Geneva 23, Switzerland On behalf of the CMS Tracker Collaboration
Abstract The Compact Muon Solenoid (CMS) detector will have a large tracking system entirely based on silicon detectors. This will be a key element for the discovery potential of the CMS experiment. The Tracker layout is presented and the performance for several benchmark topologies is discussed. In particular the CMS Tracker can provide a robust partial reconstruction using the absolute minimum number of reconstruction steps inside a region of interest, tuned according to the specific benchmark channel. Recent results have shown that the performance of partial reconstruction in terms of resolution and CPU time allows the use of the Tracker at the first stage of the High Level Trigger (HLT) on all physics events. The role of the Tracker in b and t triggers will be also discussed. r 2003 Elsevier B.V. All rights reserved. Keywords: CMS; Tracker; High Level Trigger
1. Introduction The Large Hadron Collider (LHC) will be installed in the LEP tunnel at CERN in order to provide proton–proton collisions at a center of mass energy of 14 TeV with a very high bunch crossing rate such as 40 MHz: In the initial phase LHC will run with a luminosity of 2 1033 cm2 s1 ; to be increased after a few years up to an unprecedented luminosity of 1034 cm2 s1 : The high energy and luminosity of the LHC offer a large range of physics opportunities, from the precise measurement of the properties of known objects to the exploration of the high *Tel.: +41-22-767-1551; fax: +41-22-767-8940. E-mail address: [email protected] (M. Lenzi).
energy frontier. Robust tracking and detailed vertex reconstruction within a strong magnetic field are powerful tools to reach these objectives. A severe consequence of the high energy and luminosity of the LHC machine is the elevated number of pp events piled up at each bunch crossing. About 25 minimum bias events are expected during the high luminosity phase, with the direct consequence that about 500 low momentum charged tracks will constitute an unavoidable background to the interesting signatures. In order to provide an efficient and robust pattern recognition, high granularity and large hit redundancy are thus required. But the more worrying consequence of the high rate of primary interaction is the level of radiation, particularly high around the collision region. In addition, a high flux of neutrons will be present in
0168-9002/$ - see front matter r 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.nima.2003.08.103
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
barrel geometry, while at higher values of rapidity they are deployed as disks, organised into endcaps. The CMS pixel system consists of three barrel layers and two disks for each endcap and covers the region below 20 cm in radius. The layers are composed of modular detector units, each one consisting of a thin silicon sensor segmented with nþ -pixels on a n-type substrate. Since the main task required to the pixel system is to measure track impact parameter, a square pixel shape has been chosen so as to optimise the spatial resolution measurement in both coordinates simultaneously. The resolution can be much improved by tilting the forward devices in order to exploit charge sharing effects, together with an analog signal readout, to profit from position interpolation between pixels sharing the hit signal. With a cell size of 150 150 mm2 and exploiting the large Lorentz angle, a transverse impact point resolution of about 20 mm is obtained for tracks with Pt E10 GeV: In addition the fine granularity of pixel devices ensure a detector occupancy of E104 thus making the pixel layers the fastest starting point for track reconstruction despite the extremely high track density, as we will see in Section 3. The Silicon Strip Tracker is made of 10 barrel layers and 9 disks for each endcap; some of them
the tracking volume due to the backscattering of albedo neutrons emitted by the surrounding electromagnetic calorimeters. This implies that the inner tracker of an LHC experiment will have to deal with unprecedented radiation levels. For this reason, a big effort has been required in order to develop new radiation hard technologies to ensure full functionality of the tracker for the whole lifetime of the experiment. In addition, the high bunch crossing rate requires an unprecedented fast readout electronic in order not to integrate the signals coming from tracks of previous bunch crossings.
2. Tracker layout The Tracker layout is designed to provide good precision measurements of transverse momentum and impact parameter in order to ensure the ability respectively to reconstruct narrow heavy objects and to tag b and t particles through secondary vertexes. Starting from the inner part of the detector, the CMS Tracker [1,2] consists of silicon pixel and silicon microstrip devices. A longitudinal section of one quarter of the silicon strip detector is shown in Fig. 1. The silicon tracker covers the radial region up to 110 cm and it is 270 cm long. In the central rapidity region detectors are arranged in a 0.1 0.2 0.3
0.4 0.5 0.6
0.7
0.8
181
0.9
1
1.1
1.2
1.3
1.4
1.5 1.6
z-view 1200 1100 1000 900 800 700 600 500 400 300 200 100 0
1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5
0
200
400
600
800
1000 1200 1400 1600 1800 2000 2200 2400 2600 2800
Fig. 1. Longitudinal section of one quarter of the CMS Silicon Strip Tracker.
ARTICLE IN PRESS 182
M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
provides 2D position information being made of two single sided devices coupled back to back with a tilt angle of 100 mrad: As stated before, to solve the pattern recognition problem at high luminosity low cell occupancy and consequently small detection cell sizes is required. The very high magnetic field of CMS affects event topologies, by confining low pT charged particle to small radius helical trajectories. Coupled with the steeply falling pT spectrum characteristic of minimum bias events, this results in a track density that rapidly decreases with increasing radius. This allows to relax the stringent requirement on cell size at larger radius. For this reason while the strip pitch in the inner region ranges from 80 to 160 mm; in the outer part it is increased up to 205 mm: Then two daisychained sensors are used for outer modules with a total strip length up to 21 cm to be compared with the maximum length of 13:5 cm in the inner modules. The longer strip length will increase the detector noise by 20%. The effect on the signal to noise ratio will be compensated through the use of 500 mm thick sensors in the outer part compared to the usual 320 mm in the inner part, thus increasing the collected charge. The silicon sensors are single sided p-on-n strip sensors with integrated AC coupling of the readout strips and poly-silicon resistor biasing the implant strips. They have been optimised for low capacitance and stable high bias operation and will thus ensure low noise and efficient charge collection even after the radiation damage induced type inversion of the bulk. Several studies on radiation hardness of silicon sensors show that the surface radiation damage increases the inter-strip capacitance and consequently the detector noise. This effect can be reduced by using a /1 0 0S crystal lattice orientation instead of the standard /1 1 1S: This solution has thus been adopted for the CMS silicon sensors. In addition, the whole tracker volume will be held at 10 C temperature, in order to reduce the detector current and, hence, the power consumption. That low operating temperature will also be useful in keeping the depletion voltage of irra-
diated sensors near the minimum of the annealing curve. Finally a specific chip, the APV25, has been designed in 0:25 mm CMOS technology for the read-out of the signal and has been proved to be radiation hard. It works as a charge sensitive amplifier, with 50 ns shaping time, sampled at the bunch crossing rate ð40 MHzÞ; a deconvolution procedure is then applied to restore the 25 ns timing accuracy.
3. Pattern recognition performance The track finding strategy for the CMS Tracker exploits a small number of high precision hits in a very high magnetic field ð4 TÞ: The pattern recognition algorithm [3] starts constructing a trajectory seed that can be an external seed from other detectors such as calorimeters or muon stations or an internal seed i.e. a pair of tracker hits on selected seeding layers. In case of tracker seeding, an obvious choice for starting layers would be the outermost ones since the track density is lowest there. But in the CMS Tracker a large fraction of low energy pions interacts in the first few layers. In addition the outer layers provide the less precise measurements since they don’t have stereo information. On the other side, the innermost layers are equipped with pixel detectors which provide very low channel occupancy and excellent 2D resolution. The pixel layers are then the favoured seeding layers in the CMS Tracker. Starting from a seed, the next step to reconstruct all possible trajectories is to find the ‘‘next’’ layers to use (accounting for multiple scattering and energy loss). On those layers the hits compatible with the predicted track state are found and the track state is updated using the Kalman Filter algorithm for each compatible hit in that layer. Then the procedure starts again with the selected trajectory candidates looking for the ‘‘next layer’’. Some logic is applied at each step in order to keep the number of candidates reasonable and avoid a combinatorial explosion. The performance of the pattern recognition algorithm are shown in Figs. 2 and 3 in terms of reconstruction efficiency as a function of
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
rate lower than 1%. This result indicates that the high granularity of the detector and the algorithms used for track reconstruction are well suited to the high density environment, expected at LHC. The robustness of the CMS pattern recognition can be proved by looking at the track parameters as a function of the number of tracker layers used for the reconstruction; the results are shown in Figs. 4 and 5 for tracks in bb jets with a Pt between
1
Global Efficiency
0.95
0.9
0.85
PT = 1 GeV
0.8
183
PT = 10 GeV 0.75
PT = 100 GeV
1.2
0.7 0
0.25 0.5 0.75
1
1.25 1.5 1.75
2
2.25 2.5
1
Fig. 2. Track reconstruction efficiency as a function of pseudorapidity for bb-jets events. 1
σ (P t) [GeV/c]
η
Global Efficiency
0.95
0.8
0.6
0.4
0.2
0.9
0
0.85
2
3
4
5
6
7
8
9
10
11
12
# layers 0.8
Fig. 4. Transverse momentum resolution as a function of the number of tracker layers used for the reconstruction for tracks in bb jets with a Pt between 5 and 10 GeV=c in the barrel region.
ET = 50 GeV ET = 200 GeV
0.75
0.7 0
0.25 0.5 0.75
1
1.25 1.5 1.75
2
2.25 2.5
η
90
Fig. 3. Track reconstruction efficiency as a function of pseudorapidity for single muon events.
80
σ (d 0) [µm]
70
pseudo-rapidity, respectively, for single muon samples and bb-jets. In case of jets the reconstructed tracks are selected in a cone of radius R ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi f2 þ Z2 o0:4 around the jets axis. The efficiency is defined as the fraction of simulated tracks that has been correctly reconstructed. For single muons we observe full efficiency up to Z ¼ 2; after that it is limited by pixel geometrical acceptance, while for jet events the loss of efficiency is dominated by hadronic interactions in Tracker material. However the track efficiency in jets turns out to be more than 95% in the full Z range with a fake
60 50 40 30 20 2
3
4
5
6
7
8
9
10
11
12
# layers Fig. 5. Transverse impact point resolution as a function of the number of tracker layers used for the reconstruction for tracks in bb jets with a Pt between 5 and 10 GeV=c in the barrel region.
ARTICLE IN PRESS 184
M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
5 and 10 GeV=c in the barrel region. It is evident that we can achieve a good resolution for track parameters already with 4 or more hits. This feature has been exploited to use the track reconstruction in HLT, as we will see in the next section.
4. Use of tracker in High Level Trigger To handle a collision rate as high as the LHC’s one the CMS experiment needs a very fast and efficient trigger system, able to select the interesting events in the presence of an overwhelming background. The trigger system of CMS is realized in several sequential stages. The First Level (L1) Trigger is made of a custom-built electronics system that processes data from a small subsets of the calorimeter and muon chamber informations [4]. The goal of the Level-1 Trigger is to reduce the filtered event rate down to 100 kHz of accepted events. At this point, a software High Level Trigger (HLT) system would employ two more physical decision levels, a Level2 and a Level-3 trigger. After the HLT the filtered event rate must not exceed 100 Hz; this limit is driven by the capacity of the on-line computing resources. Since the current DAQ design provides fully assembled events after Level-1 Trigger there are no data volume constraints for the HLT, the only constraint is the CPU time: the average CPU time available per event is of order of a few hundreds ms on the currently used 1 GHz processors. The task of the tracker collaboration was then to understand what the contribution of the tracker can be at the HLT. There are two possible approaches to utilise the tracker informations: to perform the fastest, and consequently the most approximate reconstruction or to perform the minimal amount of precise reconstruction. So far the Tracker Collaboration has chosen the second option, essentially for two reason: first of all the most precise treatment of hits (using the Kalman filter) is also the most efficient on our case. In fact it leads to smallest search windows and to greatest rejection power of outlying hits thus reducing the combinatorics. The
second reason is that in the CMS tracker the use of fast approximations results difficult because it is impossible to ignore the multiple scattering and energy loss for tracks below about 10 GeV; which are the most time consuming. The Tracker HLT strategy is based on different speed-up algorithms. At high LHC luminosity and for QCD type of events the number of trajectory seeds compatible with the full length of the interaction region can be very large (tens or hundreds of thousands). A very efficient way to reduce this number is to find the longitudinal primary vertex using only the pixel informations before starting the track reconstruction. Another speed-up strategy consists in using a partial reconstruction as shown in Section 3. The basic idea is to do the absolute minimum of reconstruction steps needed to answer a specific question. Then better performance in terms of speed can be reached performing a regional reconstruction i.e. build trajectory seeds and tracks only in a preselected cone or region around L1 or L2 objects (i.e. jet or tau direction). These procedures have been applied to b and t tagging algorithms in order to investigate the possibility to be used at the HLT.
4.1. b-tagging The purpose of a traditional Level-2 trigger is to validate physics objects that triggered the Level-1. To the extent to which no b object at Level-1 is defined, there is not any particular need for a refinement of the first level trigger decision. Nevertheless, the search for b objects can be initiated using the Level-1 primitives (jets, leptons) to investigate the presence of a b hadron. Keeping in mind that the main constraint is the CPU time needed to take the trigger decision, a study of the b-tagging performance has been carried out using the speed-up reconstruction procedures described in the previous section. In Fig. 6 the efficiency and fake rate are shown for bb jets with ET ¼ 100 GeV using a partial reconstruction that employs only the first 5 layers traversed by the track. The reconstruction efficiency turns out to be around 80% in the whole Z range while maintaining the fake rate below 1%.
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
185
1
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 0.9
0.9 0.8
10
-2
Fake Rate
Efficiency
0.6 0.5 0.4 0.3 0.2
Efficiency
0.1
Fake Rate
0
10 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5
b-tagging efficiency
0.8 0.7
0.7 0.6 0.5 0.4 0.3
barrel offline barrel HLT forward offline forward HLT
0.2 0.1 -3
0 10
η Fig. 6. Track reconstruction efficiency and fake rate for bb jets with ET ¼ 100 GeV using a partial reconstruction that employs only the first 5 layers traversed by the track.
Such promising results suggest the possibility to apply b-tagging algorithms during the HLT. The b-tagging algorithm is based on the knowledge of the jet direction but the measurement provided by the calorimetric L1 turns out to be too poor in order to be utilised. A possible solution can be to use the calorimetry L2 or to add the tracker informations to the calorimetry L1. A deeper study demonstrates that while in terms of resolution we can achieve similar results using the L2 calorimetry or the L1 calorimetry plus the tracker, in terms of CPU time the former method needs 70 ms for event in addition to the L1 while the latter one needs only 2 ms more for event. For this reason the second option has been adopted and the jet direction is thus measured using the reconstructed tracks. The resolution in the Z and F jet direction turns out to be, respectively, 0.037 and 0:034 mrad: The b-tagging algorithm is based on the track impact parameter that is calculated as the minimum distance between the particle trajectory and the beam axis in the transverse plane. To the impact parameter is then attributed the sign of the projection of the impact point onto the jet axis. A jet is tagged if at least Ntracks have a SIP significance (Signed Impact Point divided by its error s) larger than Ns : Typical values for Ntracks and Ns are 2 or 3.
-2
10
-1
mis-tagging rate (u jets) Fig. 7. b-tagging efficiency as a function of the mistagging rate for the off-line analysis (i.e using total reconstruction) and for the HLT analysis (i.e. using regional seeding and partial reconstruction with 7 layers).
In Fig. 7 the b-tagging efficiency is shown as a function of the mistagging rate for the off-line analysis (i.e using total reconstruction) and for the HLT analysis (i.e. using regional seeding and partial reconstruction); the results are shown both in the barrel and forward region. The used event samples are bb-jets with a transverse energy of 100 GeV: The HLT trigger results are obtained using the jet direction measurement obtained by the calorimetric Level 1 plus the reconstructed tracks informations. It turns out that we can achieve b-tagging performance near to the off-line results using a CPU time of a few hundreds of ms for event, less than 10 ms=eV being needed for the b-tagging algorithm and the rest is for the track reconstruction. It should be also stressed that the speed-up procedures are still on-going and that recent progress in track propagation have shown a very promising reduction of about 70 ms=eV in the track reconstruction phase.
4.2. t-tagging The proposed t-tagging algorithm for HLT is applied to sample events of SUSY Higgs bosons decaying into two t leptons with two t hadronic jets in the final state. The main background for
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
such events are QCD 2-jet events in the Pt range 50–170 GeV=c: The HLT t-tagging algorithm is based on track isolation criteria and it is schematically shown in Fig. 8. The t-jet direction is defined by the calorimeter trigger. All track candidates in the matching cone around the jet direction and above the Pmatch cut are considered in the search for t signal tracks, i.e. tracks which originate from the hadronic t decay. The track with the highest pt is declared the leading track. Any other track which is in the narrow signal cone around the leading track is also assumed to come from the t decay. A larger isolation area is now searched for tracks above the Piso cut. If no tracks are found in the t isolation cone, except the ones which are already in the signal cone, the isolation criteria is fulfilled and the jet is labelled as a t-jet. The narrow signal cone around the leading track is needed in order to trigger on 3 prong t decays in addition to 1 prong. Typical values of the cuts used above are: signal radius ¼ 0:07; matching radius ¼ 0:1; isolation radius ¼ 0:2–0.5, Psig t ¼ 7 GeV=c and Piso t ¼ 1 GeV=c: Two different approaches have been tried and the performance will be compared: the first one uses short tracks reconstructed using only the pixel
ion
t isola
cone
jet axis
signal cone
jet m atc ∆R= hing co ne 0.1
leading track
0.9
0.8
H → ττ Efficiency
186
0.7
0.6
Tracker algo (MH = 500 GeV) Tracker algo (MH = 200 GeV) Pixel algo (MH = 500 GeV) Pixel algo (MH = 200 GeV)
0.5
0.4
0.3 0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
QCD 50-170 GeV Efficiency Fig. 9. Variation of the QCD background and the Higgs signal efficiency is for two approach for different isolation cone radius ranging from 0.2 to 0.45 and for two different Higgs mass hypothesis.
detector informations while the second one uses also the silicon strip hits in the reconstruction procedure. In this case the trajectory seeds are limited by searching the vertex using the pixel measurements. The variation of the QCD background and the Higgs signal efficiency is shown in Fig. 9 for the two approach for different isolation cone radius ranging from 0.2 to 0.45 and for two different Higgs mass hypothesis. As expected, we can observe that the second approach gives an Higgs efficiency slightly higher; the price being that it is more time consuming. Indeed about 80 ms per Higgs event are needed using the only pixel tracks against about 240 ms using also the silicon strip informations.
5. Conclusions
ne
reg
TK
co
Signal vertex Fig. 8. Track isolation criteria applied by the HLT t-tagging algorithm.
In the last few years the silicon strip technology, developed for use in vertex detectors, has evolved to be used in very large scale tracking detectors. Currently the CMS silicon tracker is the most extreme example of this trend. These steps forward have been made possible by combination of several aspects. First of all an extensive and successful R&D program has allowed a deep understanding of the sensor operation in high
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
fluence environments. Then the production of strip sensors was moved to large volume 600 industrial lines, thus allowing for large modules. In addition techniques for automated module assembly have been developed which make possible the production of almost 20 000 modules in approximately 2 years. Finally the standard 0:25 mm technology has been successfully applied to custom radiation hard front end read-out electronics. The results is that the CMS silicon tracker has robust performance in a difficult environment. The pixel vertex detector allows fast and efficient track seed generation as well as excellent 3-D secondary vertex identification. The fine granularity of the pixel and strip sensors, together with the powerful CMS magnet allow for a good determination of track parameters using only a few hits (4–6). This capability will be used extensively at High Level Trigger. In particular we studied the performance of b and t tagging algorithms that have been optimized in order to be used at trigger level. An
187
efficiency of about 60% for a mistagging rates of 0.1% has been achieved for trigger b-tagging to be compared with an efficiency of 70% obtained with the off-line algorithm with the same rejection factor. In case of Higgs events decaying into two t with 2 jets in the final state we achieve an efficiency of 80% for a background efficiency of 0.1%. In both cases, even if the optimisation of algorithms is still on-going, we already achieve close to 100 ms CPU times for complex HLT tracker algorithms. These results prove that the CMS tracker can be used at trigger level 2 on all physics events.
References [1] The Tracker Project, Technical Design Report, CERN/ LHCC 98-6 CMS TDR 5, 15 April 1998. [2] CMS Tracker Collaboration, Addendum to the CMS Tracker TDR, CERN/LHCC 2000-016. [3] A. Khanov, et al., Nucl. Instr. and Meth. A 478 (2002) 460. [4] C.E. Wulz, Nucl. Instr. and Meth. A 473 (2001) 231.
Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
Performance of the CMS tracker in high level trigger M. Lenzi* CERN, EP Division, 1211 Geneva 23, Switzerland On behalf of the CMS Tracker Collaboration
Abstract The Compact Muon Solenoid (CMS) detector will have a large tracking system entirely based on silicon detectors. This will be a key element for the discovery potential of the CMS experiment. The Tracker layout is presented and the performance for several benchmark topologies is discussed. In particular the CMS Tracker can provide a robust partial reconstruction using the absolute minimum number of reconstruction steps inside a region of interest, tuned according to the specific benchmark channel. Recent results have shown that the performance of partial reconstruction in terms of resolution and CPU time allows the use of the Tracker at the first stage of the High Level Trigger (HLT) on all physics events. The role of the Tracker in b and t triggers will be also discussed. r 2003 Elsevier B.V. All rights reserved. Keywords: CMS; Tracker; High Level Trigger
1. Introduction The Large Hadron Collider (LHC) will be installed in the LEP tunnel at CERN in order to provide proton–proton collisions at a center of mass energy of 14 TeV with a very high bunch crossing rate such as 40 MHz: In the initial phase LHC will run with a luminosity of 2 1033 cm2 s1 ; to be increased after a few years up to an unprecedented luminosity of 1034 cm2 s1 : The high energy and luminosity of the LHC offer a large range of physics opportunities, from the precise measurement of the properties of known objects to the exploration of the high *Tel.: +41-22-767-1551; fax: +41-22-767-8940. E-mail address: [email protected] (M. Lenzi).
energy frontier. Robust tracking and detailed vertex reconstruction within a strong magnetic field are powerful tools to reach these objectives. A severe consequence of the high energy and luminosity of the LHC machine is the elevated number of pp events piled up at each bunch crossing. About 25 minimum bias events are expected during the high luminosity phase, with the direct consequence that about 500 low momentum charged tracks will constitute an unavoidable background to the interesting signatures. In order to provide an efficient and robust pattern recognition, high granularity and large hit redundancy are thus required. But the more worrying consequence of the high rate of primary interaction is the level of radiation, particularly high around the collision region. In addition, a high flux of neutrons will be present in
0168-9002/$ - see front matter r 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.nima.2003.08.103
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
barrel geometry, while at higher values of rapidity they are deployed as disks, organised into endcaps. The CMS pixel system consists of three barrel layers and two disks for each endcap and covers the region below 20 cm in radius. The layers are composed of modular detector units, each one consisting of a thin silicon sensor segmented with nþ -pixels on a n-type substrate. Since the main task required to the pixel system is to measure track impact parameter, a square pixel shape has been chosen so as to optimise the spatial resolution measurement in both coordinates simultaneously. The resolution can be much improved by tilting the forward devices in order to exploit charge sharing effects, together with an analog signal readout, to profit from position interpolation between pixels sharing the hit signal. With a cell size of 150 150 mm2 and exploiting the large Lorentz angle, a transverse impact point resolution of about 20 mm is obtained for tracks with Pt E10 GeV: In addition the fine granularity of pixel devices ensure a detector occupancy of E104 thus making the pixel layers the fastest starting point for track reconstruction despite the extremely high track density, as we will see in Section 3. The Silicon Strip Tracker is made of 10 barrel layers and 9 disks for each endcap; some of them
the tracking volume due to the backscattering of albedo neutrons emitted by the surrounding electromagnetic calorimeters. This implies that the inner tracker of an LHC experiment will have to deal with unprecedented radiation levels. For this reason, a big effort has been required in order to develop new radiation hard technologies to ensure full functionality of the tracker for the whole lifetime of the experiment. In addition, the high bunch crossing rate requires an unprecedented fast readout electronic in order not to integrate the signals coming from tracks of previous bunch crossings.
2. Tracker layout The Tracker layout is designed to provide good precision measurements of transverse momentum and impact parameter in order to ensure the ability respectively to reconstruct narrow heavy objects and to tag b and t particles through secondary vertexes. Starting from the inner part of the detector, the CMS Tracker [1,2] consists of silicon pixel and silicon microstrip devices. A longitudinal section of one quarter of the silicon strip detector is shown in Fig. 1. The silicon tracker covers the radial region up to 110 cm and it is 270 cm long. In the central rapidity region detectors are arranged in a 0.1 0.2 0.3
0.4 0.5 0.6
0.7
0.8
181
0.9
1
1.1
1.2
1.3
1.4
1.5 1.6
z-view 1200 1100 1000 900 800 700 600 500 400 300 200 100 0
1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5
0
200
400
600
800
1000 1200 1400 1600 1800 2000 2200 2400 2600 2800
Fig. 1. Longitudinal section of one quarter of the CMS Silicon Strip Tracker.
ARTICLE IN PRESS 182
M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
provides 2D position information being made of two single sided devices coupled back to back with a tilt angle of 100 mrad: As stated before, to solve the pattern recognition problem at high luminosity low cell occupancy and consequently small detection cell sizes is required. The very high magnetic field of CMS affects event topologies, by confining low pT charged particle to small radius helical trajectories. Coupled with the steeply falling pT spectrum characteristic of minimum bias events, this results in a track density that rapidly decreases with increasing radius. This allows to relax the stringent requirement on cell size at larger radius. For this reason while the strip pitch in the inner region ranges from 80 to 160 mm; in the outer part it is increased up to 205 mm: Then two daisychained sensors are used for outer modules with a total strip length up to 21 cm to be compared with the maximum length of 13:5 cm in the inner modules. The longer strip length will increase the detector noise by 20%. The effect on the signal to noise ratio will be compensated through the use of 500 mm thick sensors in the outer part compared to the usual 320 mm in the inner part, thus increasing the collected charge. The silicon sensors are single sided p-on-n strip sensors with integrated AC coupling of the readout strips and poly-silicon resistor biasing the implant strips. They have been optimised for low capacitance and stable high bias operation and will thus ensure low noise and efficient charge collection even after the radiation damage induced type inversion of the bulk. Several studies on radiation hardness of silicon sensors show that the surface radiation damage increases the inter-strip capacitance and consequently the detector noise. This effect can be reduced by using a /1 0 0S crystal lattice orientation instead of the standard /1 1 1S: This solution has thus been adopted for the CMS silicon sensors. In addition, the whole tracker volume will be held at 10 C temperature, in order to reduce the detector current and, hence, the power consumption. That low operating temperature will also be useful in keeping the depletion voltage of irra-
diated sensors near the minimum of the annealing curve. Finally a specific chip, the APV25, has been designed in 0:25 mm CMOS technology for the read-out of the signal and has been proved to be radiation hard. It works as a charge sensitive amplifier, with 50 ns shaping time, sampled at the bunch crossing rate ð40 MHzÞ; a deconvolution procedure is then applied to restore the 25 ns timing accuracy.
3. Pattern recognition performance The track finding strategy for the CMS Tracker exploits a small number of high precision hits in a very high magnetic field ð4 TÞ: The pattern recognition algorithm [3] starts constructing a trajectory seed that can be an external seed from other detectors such as calorimeters or muon stations or an internal seed i.e. a pair of tracker hits on selected seeding layers. In case of tracker seeding, an obvious choice for starting layers would be the outermost ones since the track density is lowest there. But in the CMS Tracker a large fraction of low energy pions interacts in the first few layers. In addition the outer layers provide the less precise measurements since they don’t have stereo information. On the other side, the innermost layers are equipped with pixel detectors which provide very low channel occupancy and excellent 2D resolution. The pixel layers are then the favoured seeding layers in the CMS Tracker. Starting from a seed, the next step to reconstruct all possible trajectories is to find the ‘‘next’’ layers to use (accounting for multiple scattering and energy loss). On those layers the hits compatible with the predicted track state are found and the track state is updated using the Kalman Filter algorithm for each compatible hit in that layer. Then the procedure starts again with the selected trajectory candidates looking for the ‘‘next layer’’. Some logic is applied at each step in order to keep the number of candidates reasonable and avoid a combinatorial explosion. The performance of the pattern recognition algorithm are shown in Figs. 2 and 3 in terms of reconstruction efficiency as a function of
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
rate lower than 1%. This result indicates that the high granularity of the detector and the algorithms used for track reconstruction are well suited to the high density environment, expected at LHC. The robustness of the CMS pattern recognition can be proved by looking at the track parameters as a function of the number of tracker layers used for the reconstruction; the results are shown in Figs. 4 and 5 for tracks in bb jets with a Pt between
1
Global Efficiency
0.95
0.9
0.85
PT = 1 GeV
0.8
183
PT = 10 GeV 0.75
PT = 100 GeV
1.2
0.7 0
0.25 0.5 0.75
1
1.25 1.5 1.75
2
2.25 2.5
1
Fig. 2. Track reconstruction efficiency as a function of pseudorapidity for bb-jets events. 1
σ (P t) [GeV/c]
η
Global Efficiency
0.95
0.8
0.6
0.4
0.2
0.9
0
0.85
2
3
4
5
6
7
8
9
10
11
12
# layers 0.8
Fig. 4. Transverse momentum resolution as a function of the number of tracker layers used for the reconstruction for tracks in bb jets with a Pt between 5 and 10 GeV=c in the barrel region.
ET = 50 GeV ET = 200 GeV
0.75
0.7 0
0.25 0.5 0.75
1
1.25 1.5 1.75
2
2.25 2.5
η
90
Fig. 3. Track reconstruction efficiency as a function of pseudorapidity for single muon events.
80
σ (d 0) [µm]
70
pseudo-rapidity, respectively, for single muon samples and bb-jets. In case of jets the reconstructed tracks are selected in a cone of radius R ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi f2 þ Z2 o0:4 around the jets axis. The efficiency is defined as the fraction of simulated tracks that has been correctly reconstructed. For single muons we observe full efficiency up to Z ¼ 2; after that it is limited by pixel geometrical acceptance, while for jet events the loss of efficiency is dominated by hadronic interactions in Tracker material. However the track efficiency in jets turns out to be more than 95% in the full Z range with a fake
60 50 40 30 20 2
3
4
5
6
7
8
9
10
11
12
# layers Fig. 5. Transverse impact point resolution as a function of the number of tracker layers used for the reconstruction for tracks in bb jets with a Pt between 5 and 10 GeV=c in the barrel region.
ARTICLE IN PRESS 184
M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
5 and 10 GeV=c in the barrel region. It is evident that we can achieve a good resolution for track parameters already with 4 or more hits. This feature has been exploited to use the track reconstruction in HLT, as we will see in the next section.
4. Use of tracker in High Level Trigger To handle a collision rate as high as the LHC’s one the CMS experiment needs a very fast and efficient trigger system, able to select the interesting events in the presence of an overwhelming background. The trigger system of CMS is realized in several sequential stages. The First Level (L1) Trigger is made of a custom-built electronics system that processes data from a small subsets of the calorimeter and muon chamber informations [4]. The goal of the Level-1 Trigger is to reduce the filtered event rate down to 100 kHz of accepted events. At this point, a software High Level Trigger (HLT) system would employ two more physical decision levels, a Level2 and a Level-3 trigger. After the HLT the filtered event rate must not exceed 100 Hz; this limit is driven by the capacity of the on-line computing resources. Since the current DAQ design provides fully assembled events after Level-1 Trigger there are no data volume constraints for the HLT, the only constraint is the CPU time: the average CPU time available per event is of order of a few hundreds ms on the currently used 1 GHz processors. The task of the tracker collaboration was then to understand what the contribution of the tracker can be at the HLT. There are two possible approaches to utilise the tracker informations: to perform the fastest, and consequently the most approximate reconstruction or to perform the minimal amount of precise reconstruction. So far the Tracker Collaboration has chosen the second option, essentially for two reason: first of all the most precise treatment of hits (using the Kalman filter) is also the most efficient on our case. In fact it leads to smallest search windows and to greatest rejection power of outlying hits thus reducing the combinatorics. The
second reason is that in the CMS tracker the use of fast approximations results difficult because it is impossible to ignore the multiple scattering and energy loss for tracks below about 10 GeV; which are the most time consuming. The Tracker HLT strategy is based on different speed-up algorithms. At high LHC luminosity and for QCD type of events the number of trajectory seeds compatible with the full length of the interaction region can be very large (tens or hundreds of thousands). A very efficient way to reduce this number is to find the longitudinal primary vertex using only the pixel informations before starting the track reconstruction. Another speed-up strategy consists in using a partial reconstruction as shown in Section 3. The basic idea is to do the absolute minimum of reconstruction steps needed to answer a specific question. Then better performance in terms of speed can be reached performing a regional reconstruction i.e. build trajectory seeds and tracks only in a preselected cone or region around L1 or L2 objects (i.e. jet or tau direction). These procedures have been applied to b and t tagging algorithms in order to investigate the possibility to be used at the HLT.
4.1. b-tagging The purpose of a traditional Level-2 trigger is to validate physics objects that triggered the Level-1. To the extent to which no b object at Level-1 is defined, there is not any particular need for a refinement of the first level trigger decision. Nevertheless, the search for b objects can be initiated using the Level-1 primitives (jets, leptons) to investigate the presence of a b hadron. Keeping in mind that the main constraint is the CPU time needed to take the trigger decision, a study of the b-tagging performance has been carried out using the speed-up reconstruction procedures described in the previous section. In Fig. 6 the efficiency and fake rate are shown for bb jets with ET ¼ 100 GeV using a partial reconstruction that employs only the first 5 layers traversed by the track. The reconstruction efficiency turns out to be around 80% in the whole Z range while maintaining the fake rate below 1%.
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
185
1
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 0.9
0.9 0.8
10
-2
Fake Rate
Efficiency
0.6 0.5 0.4 0.3 0.2
Efficiency
0.1
Fake Rate
0
10 0 0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5
b-tagging efficiency
0.8 0.7
0.7 0.6 0.5 0.4 0.3
barrel offline barrel HLT forward offline forward HLT
0.2 0.1 -3
0 10
η Fig. 6. Track reconstruction efficiency and fake rate for bb jets with ET ¼ 100 GeV using a partial reconstruction that employs only the first 5 layers traversed by the track.
Such promising results suggest the possibility to apply b-tagging algorithms during the HLT. The b-tagging algorithm is based on the knowledge of the jet direction but the measurement provided by the calorimetric L1 turns out to be too poor in order to be utilised. A possible solution can be to use the calorimetry L2 or to add the tracker informations to the calorimetry L1. A deeper study demonstrates that while in terms of resolution we can achieve similar results using the L2 calorimetry or the L1 calorimetry plus the tracker, in terms of CPU time the former method needs 70 ms for event in addition to the L1 while the latter one needs only 2 ms more for event. For this reason the second option has been adopted and the jet direction is thus measured using the reconstructed tracks. The resolution in the Z and F jet direction turns out to be, respectively, 0.037 and 0:034 mrad: The b-tagging algorithm is based on the track impact parameter that is calculated as the minimum distance between the particle trajectory and the beam axis in the transverse plane. To the impact parameter is then attributed the sign of the projection of the impact point onto the jet axis. A jet is tagged if at least Ntracks have a SIP significance (Signed Impact Point divided by its error s) larger than Ns : Typical values for Ntracks and Ns are 2 or 3.
-2
10
-1
mis-tagging rate (u jets) Fig. 7. b-tagging efficiency as a function of the mistagging rate for the off-line analysis (i.e using total reconstruction) and for the HLT analysis (i.e. using regional seeding and partial reconstruction with 7 layers).
In Fig. 7 the b-tagging efficiency is shown as a function of the mistagging rate for the off-line analysis (i.e using total reconstruction) and for the HLT analysis (i.e. using regional seeding and partial reconstruction); the results are shown both in the barrel and forward region. The used event samples are bb-jets with a transverse energy of 100 GeV: The HLT trigger results are obtained using the jet direction measurement obtained by the calorimetric Level 1 plus the reconstructed tracks informations. It turns out that we can achieve b-tagging performance near to the off-line results using a CPU time of a few hundreds of ms for event, less than 10 ms=eV being needed for the b-tagging algorithm and the rest is for the track reconstruction. It should be also stressed that the speed-up procedures are still on-going and that recent progress in track propagation have shown a very promising reduction of about 70 ms=eV in the track reconstruction phase.
4.2. t-tagging The proposed t-tagging algorithm for HLT is applied to sample events of SUSY Higgs bosons decaying into two t leptons with two t hadronic jets in the final state. The main background for
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
such events are QCD 2-jet events in the Pt range 50–170 GeV=c: The HLT t-tagging algorithm is based on track isolation criteria and it is schematically shown in Fig. 8. The t-jet direction is defined by the calorimeter trigger. All track candidates in the matching cone around the jet direction and above the Pmatch cut are considered in the search for t signal tracks, i.e. tracks which originate from the hadronic t decay. The track with the highest pt is declared the leading track. Any other track which is in the narrow signal cone around the leading track is also assumed to come from the t decay. A larger isolation area is now searched for tracks above the Piso cut. If no tracks are found in the t isolation cone, except the ones which are already in the signal cone, the isolation criteria is fulfilled and the jet is labelled as a t-jet. The narrow signal cone around the leading track is needed in order to trigger on 3 prong t decays in addition to 1 prong. Typical values of the cuts used above are: signal radius ¼ 0:07; matching radius ¼ 0:1; isolation radius ¼ 0:2–0.5, Psig t ¼ 7 GeV=c and Piso t ¼ 1 GeV=c: Two different approaches have been tried and the performance will be compared: the first one uses short tracks reconstructed using only the pixel
ion
t isola
cone
jet axis
signal cone
jet m atc ∆R= hing co ne 0.1
leading track
0.9
0.8
H → ττ Efficiency
186
0.7
0.6
Tracker algo (MH = 500 GeV) Tracker algo (MH = 200 GeV) Pixel algo (MH = 500 GeV) Pixel algo (MH = 200 GeV)
0.5
0.4
0.3 0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
QCD 50-170 GeV Efficiency Fig. 9. Variation of the QCD background and the Higgs signal efficiency is for two approach for different isolation cone radius ranging from 0.2 to 0.45 and for two different Higgs mass hypothesis.
detector informations while the second one uses also the silicon strip hits in the reconstruction procedure. In this case the trajectory seeds are limited by searching the vertex using the pixel measurements. The variation of the QCD background and the Higgs signal efficiency is shown in Fig. 9 for the two approach for different isolation cone radius ranging from 0.2 to 0.45 and for two different Higgs mass hypothesis. As expected, we can observe that the second approach gives an Higgs efficiency slightly higher; the price being that it is more time consuming. Indeed about 80 ms per Higgs event are needed using the only pixel tracks against about 240 ms using also the silicon strip informations.
5. Conclusions
ne
reg
TK
co
Signal vertex Fig. 8. Track isolation criteria applied by the HLT t-tagging algorithm.
In the last few years the silicon strip technology, developed for use in vertex detectors, has evolved to be used in very large scale tracking detectors. Currently the CMS silicon tracker is the most extreme example of this trend. These steps forward have been made possible by combination of several aspects. First of all an extensive and successful R&D program has allowed a deep understanding of the sensor operation in high
ARTICLE IN PRESS M. Lenzi / Nuclear Instruments and Methods in Physics Research A 514 (2003) 180–187
fluence environments. Then the production of strip sensors was moved to large volume 600 industrial lines, thus allowing for large modules. In addition techniques for automated module assembly have been developed which make possible the production of almost 20 000 modules in approximately 2 years. Finally the standard 0:25 mm technology has been successfully applied to custom radiation hard front end read-out electronics. The results is that the CMS silicon tracker has robust performance in a difficult environment. The pixel vertex detector allows fast and efficient track seed generation as well as excellent 3-D secondary vertex identification. The fine granularity of the pixel and strip sensors, together with the powerful CMS magnet allow for a good determination of track parameters using only a few hits (4–6). This capability will be used extensively at High Level Trigger. In particular we studied the performance of b and t tagging algorithms that have been optimized in order to be used at trigger level. An
187
efficiency of about 60% for a mistagging rates of 0.1% has been achieved for trigger b-tagging to be compared with an efficiency of 70% obtained with the off-line algorithm with the same rejection factor. In case of Higgs events decaying into two t with 2 jets in the final state we achieve an efficiency of 80% for a background efficiency of 0.1%. In both cases, even if the optimisation of algorithms is still on-going, we already achieve close to 100 ms CPU times for complex HLT tracker algorithms. These results prove that the CMS tracker can be used at trigger level 2 on all physics events.
References [1] The Tracker Project, Technical Design Report, CERN/ LHCC 98-6 CMS TDR 5, 15 April 1998. [2] CMS Tracker Collaboration, Addendum to the CMS Tracker TDR, CERN/LHCC 2000-016. [3] A. Khanov, et al., Nucl. Instr. and Meth. A 478 (2002) 460. [4] C.E. Wulz, Nucl. Instr. and Meth. A 473 (2001) 231.