ATLAS is one of the four major LHC experiments, designed to cover a wide range of physics topics. In order to cope with a rate of 40 MHz and 25 interactions per bunch crossing, the ATLAS trigger system is divided in three different levels. The first one (LVL1, hardware based) identifies signatures in 2 microseconds that are confirmed by the the following trigger levels (software based). The Second Level Trigger (LVL2) only looks at a region of the space around the LVL1 signature (called Region of Interest or ROI), confirming/rejecting the event in about 10 ms, while the Event Filter (Third Level Trigger, EF) has potential full event access and larger processing times, of the order of 1 s. The jet selection starts at the LVL1 with dedicated processors that search for high ET hadronic energy depositions. At the LVL2, the jet signatures are verified with the execution of a dedicated, fast jet reconstruction algorithm. Given the fact that the main jet's background are jets,the energy calibration at the LVL2 is one of the major dificulties of this trigger, allowing to distinguish low/high energy jets. The algorithm for the calibration has been chosen to be fast and robust, with a good performance. The other major dificulty is the execution time of the algorithm,dominated by the data unpacking time due to the large sizes of the jet ROI. In order to reduce the execution time, three possible granularities have been proposed and are being evaluated: cell based (standard), energy sums calculated at each Fron-End Board (FEB) and the use of the LVL1 Trigger Towers. The FEB and Trigger Tower granularities are also being used/evaluated for the reconstruction of the missing ET triggers at the Event Filter, given the short times available to process the full event. In this presentation, the design and implementation of the jet trigger of ATLAS will be discussed in detail, emphasasing the major dificulties of each selection step. The performance of the jet algorithm, including timing, eficiencies and rates will also be shown, with detailed comparisons of the different unpacking modes

Aracena, I

Brelier, B

Conde-Muíño, P

Cranmer, K

Delsart, P A

Dufour, M A

Eckweiler, S

Ferland, J

Idarraga, J

Johns, K

LeCompte, T

Potter, C

Robertson, S

Santamarina-Rios, C

Segura, E

Silverstein, D

Vachon, B

CERN Document Server

Implementation and performance of the ATLASsecond level jet triggerConde Mu´ın˜o P1, Aracena I2, Brelier B3, Cranmer K5, Delsart P-A3,Dufour M-A4, Eckweiler S6, Ferland J3, Idarraga J3, Johns K7,LeCompte T8, Potter C4, Robertson S4, Santamarina Rios C4, SeguraE9, Silverstein D2 and Vachon B41Laborato´rio de Instrumentac¸a˜o e F´ısica Experimental de Part´ıculas (LIP), Lisbon, Portugal2Stanford Linear Accelerator Center (SLAC), Stanford, USA3University of Montreal, Montreal, Canada4Department of Physics, McGill Univerity, Montreal, Canada5Brookhaven National Laboratory (BNL), Upton, New York, USA6Institut fu¨r Physik, Universita¨t Mainz, Mainz, Germany7University of Arizona, Tucson, Arizona, USA8Argonne National Laboratory, Argonne, Illinois, USA9Instituto de F´ısica d’Altas Energias (IFAE), Universitat Auto´noma de Barcelona, Bellaterra(Barcelona), SpainE-mail: Patricia.Conde.Muino@cern.chAbstract. ATLAS is one of the four major LHC experiments, designed to cover a wide rangeof physics topics. In order to cope with a rate of 40 MHz and 25 interactions per bunch crossing,the ATLAS trigger system is divided in three different levels. The jet selection starts at firstlevel with dedicated processors that search for high ET hadronic energy depositions. At theLVL2, the jet signatures are verified with the execution of a dedicated, fast jet reconstructionalgorithm, followed by a calibration algorithm. Three possible granularities have been proposedand are being evaluated: cell based (standard), energy sums calculated at each Front-End Boardand the use of the LVL1 Trigger Towers. In this presentation, the design and implementation ofthe jet trigger of ATLAS will be discussed in detail, emphasazing the major difficulties of eachselection step. The performance of the jet algorithm, including timing, efficiencies and rateswill also be shown, with detailed comparisons of the different unpacking modes.1. IntroductionATLAS is one of the LHC multipurpose experiments that will start operation in 2008. At thedesign luminosity of the LHC, 1034 cm−2s−1, and with a bunch crossing rate of 40 MHz theinteraction rate will be of the order of 1 GHz, imposing strong demands on the trigger system,that has to be efficient to select the interesting events while rejecting most of the interactions.The trigger system has to be very flexible, prepared to select both, expected and unexpectedinteresting physics events. It does so by selecting high pT1 objects like muons, electrons, photons,taus, jets and/or large missing transverse energy2.1 Momentum relative to the beam axis.2 Energy imbalance in the calorimeter, measured in the plane transverse to the proton beam direction.ATL-DAQ-CONF-2007-02508 October 2007The ATLAS trigger system was organized in three levels. LVL1 (first level) is hardwarebased, with coarse granularity and a maximum latency of 2 µs. Using only the information fromthe muon system and the calorimeters, it does a fast search for high pT objects, reducing therate from 40 MHz to about 75 kHz. The High Level Trigger (HLT) formed by the Second LevelTrigger (LVL2) and the Event Filter (EF) is software based. LVL2 uses the information providedby LVL1 about the position of the high transverse energy energy deposition (seeds) to start thesearch for interesting signatures. It is run before the event is built and therefore it asks for theevent fragments to the Read-Out Buffers (ROB). To save time it only reconstructs a region ofthe detector around the seed provided by LVL1, that is known as Region of Interest (RoI). Ituses the full granularity of the subdetectors and has a maximum processing time of the orderof 40 ms in a 1.8 GHz processor, reducing the rate by a factor 100, approximately. The EFmay run in seeded mode, receiving the seeds from LVL2, or in full event access. It runs moresophisticated algorithms and has access to better calibration constants, improving the selectiondone in the previous steps. It has to reduce the rate to about 200 Hz.The EF uses an oﬄine-like environment and algorithms, while LVL2 has fast, dedicatedalgorithms that have to run in a multi-threaded environment. In both levels, a sequence ofalgorithms is run in order to verify or reject as fast as possible a given signature [1].2. The ATLAS Jet TriggerAt the HLT, jets with high pT are selected by running a sequence of algorithms. At LVL2, thefirst one is a feature extraction algorithm, called TrigT2CaloJet, that uses a basic cone algorithmto reconstruct a jet in the RoI. After that, a hypothesis algorithm is run in order to verify ifthe pT of the jet is over the threshold. At the EF, oﬄine-like algorithms are used. Typically, amore sophisticated cone algorithm is run, although there is the possibility to choose also kT orother oﬄine available algorithms.TrigT2CaloJet is an iterative algorithm that starts by requesting to the Read-Out Buffersthe event fragments in a region around the seed provided by LVL1. It receives the data in abytestream format that has to be unpacked (translated into the C++ objects that the algorithmuses). This is one of the most time consuming parts of the algorithms. To be able to reduce theunpacking time, three possible granularities are being considered:• Cells: the standard one. Each cell in the RoI is unpacked.• FEBs: the energy sums of all the cells belonging to a Front End Board (FEB) are calculatedat the Read-Out Driver (ROD) and sent directly to LVL2, that unpacks only the informationcorresponding to the FEB energy sums. For the electromagnetic calorimeter, each FEBcontains 128 cells, reducing considerably the amount of data transfered and unpacked.• The possibility of using the information of LVL1 Trigger Towers is also under considerationbut its feasibility is not yet demonstrated.After unpacking the data, a grid with the list of detector elements in the RoI is built. Thealgorithm loops in this grid and calculates the energy weighted η, φ3 position of the detectorelements (cells, FEBs) inside a cone with fixed radius4 around the center of the RoI. The center ofthe cone is updated and the calculation is iterated few times in order to improve the measurementof the jet center position. Reducing the granularity by using FEB based energy sums has theadvantage that the time to loop over the detector elements is shorter, improving even furtherthe algorithm performance.3 The ATLAS coordinate system is a right-handed system with the x axis pointing towards the center of theLHC ring, the z axis following the direction of the beam and the y axis pointing upwards. The azimuthal angle,φ is measured from the positive x axis and the polar angle θ is measured from the positive z axis. Frequently, thepseudorapidity variable, defined as η = − log(tan θ2), is used.4 The cone radius is measured as a distance in the (η,φ) plane, defined as R =√(∆η)2 + (∆φ)2The jet reconstruction at LVL2 finishes with a fast calibration algorithm that sets the hadronicenergy scale for the jets. The algorithm used is called the Sampling calibration method[2]. Theenergy is corrected by applying two weights, one to the energy measured in the electromagnetic(EM) calorimeter and another one to the energy measured in the hadronic calorimeter (Had):Ecorrjet = ω1EEM + ω2EHadThe weights have a logarithmic dependence on the total energy of the jet: ωi = ai+bi ·log Ejet,where ai and bi are two different constants for the EM and hadronic energies, that can havedifferent values for different bins in η. Since the total energy of the jet is not know a priori, thecalibration is applied in an iterative procedure that converges in few iterations. The samplingmethod is fast and uses a negligible amount of time in comparison with the previous steps inthe jet reconstruction. The calibration constants are calculated using the Monte Carlo (MC)simulation. This algorithm is simpler and faster than the ones being considered for the oﬄineATLAS jet reconstruction [3].The calibration of the jets is one of the most important steps in the jet algorithm given thefact that the main background for the jets are also jets, and therefore the most difficult taskis to discriminate the energies that are above the threshold with high efficiency while rejectingmost of the jets under the threshold.3. The Second Level Jet Trigger Performance3.1. Timing PerformanceThe timing performance of the algorithm has been measured by running the trigger software onMC simulated fully hadronic tt¯ events that were stored in a bytestream format, the same thatis expected to be used for the real data once the detector starts operation. Computers withprocessors of similar speed to the ones that will be used in the LVL2 farm5 at ATLAS wereused. The average processing time per RoI is shown in figure 1 for the two possible granularitiesstudied up to now. For the cell based jets, the average processing time, with the current defaultreconstruction parameters, is around 30 ms. Taking into account that the average number ofRoI’s per event is expected to be of the order of 1.6, this average time seems too large. It can,however, be improved by optimizing the reconstruction parameters like the number of iterationsthat the algorithm executes to determine the center of the jet and the size of the RoI. These twopoints will be discussed in the next section. By choosing the FEB based granularity the totalprocessing time can be reduced by approximately a factor 3, as seen in figure 1. The physicsperformance of the FEB based jet reconstruction will be discussed in section 3.3.3.2. Optimization of the reconstruction parametersThe default parameters used in the reconstruction of the LVL2 jets are summarized in table1. A detailed study was performed in order to understand if these parameters can be changedto improve the timing performance without loosing precision in the jet energy and positionmeasurements.The variation of the coordinates of the jet center after each iteration of the jet reconstructionalgorithm is shown in figure 2. The largest variaton of η, φ happens after the first iteration andthus it has the largest impact on the precision. This suggests that the number of iterationscould be reduced to 2 without loosing too much precision on the jet position.In order to study the effect of the RoI size, the RoI was reduced to 1.0x.1.0 in η, φ, thatis a bit larger than the diameter of the jet. Notice that the maximum displacement of thecenter of the RoI is of the order of 0.2 in ∆η or ∆φ, as it can be seen in figure 2, and thereforean RoI of 1.0x1.0 seems enough for the jet reconstruction. The total time spent by the LVL25 8 core computers with 1.8 GHz CPU’s.time[ms]0 5 10 15 20 25 30 35 40entries0500100015002000250030003500Figure 1. Time spent by the LVL2 jet reconstruction algorithm per RoI for cell granularitywith a dashed line and for the FEB granularity with a solid line.Table 1. Default parameters used in the reconstruction of the ATLAS Second Level Jets.Parameter Default valueCone radius 0.4Number of iterations 3RoI size 1.4x1.4 in (η, φ)Figure 2. Variation in the φ (left) and η (right) position of the jets with the number of iterationsrun by the LVL2 jet reconstruction algorithm.jet algorithm, using 3 iterations, is shown in figure 3. The reduction of the RoI size means aconsiderable reduction of processing time, of the order of 30%. As it will be shown in the nextsection, the energy reconstruction is not affected by this reduction of the size of the RoI.3.3. Jet Energy ScaleThe ATLAS jet trigger menu will cover a wide range of energies, as it can be seen in tables 2 and3 for the single jet triggers. In addition to those, there will be multi-jet triggers (di-jet, tri-jet,tetra-jet) and triggers combined with missing transverse energy. The jet energy should thereforebe properly calibrated for a large range of transverse energies, from 10 GeV to 400 GeV.The jet energy scale and resolutions were calculated using the standard reconstruction, basedon cells. The calibration constants were previously extracted using di-jet simulated events. Theresults are shown in figure 4. The energy scale, defined as the LVL2 jet energy divided byFigure 3. Time spent by the LVL2 jet reconstruction algorithm for two different RoI sizes:1.4x1.4 (dashed line) and 1.0x1.0 (solid line).Table 2. Single jet triggers for the designluminosity of the LHC (1034 cm−2s−1).Threshold Prescale factor25 GeV 17,280,00035 GeV 5,760,00050 GeV 1,440,00065 GeV 360,00090 GeV 72,000130 GeV 12,000170 GeV 3000300 GeV 200400 GeV 1Table 3. Single jet trigger menu for thestart-up luminosity (1031 cm−2s−1).Threshold Prescale factor5 GeV 1,000,00010 GeV 42,00018 GeV 6,00023 GeV 2,00035 GeV 50042 GeV 5070 GeV 5100 GeV 1the truth jet energy6, is around 1 for all the η coverage of the LVL2 jet trigger and all theenergies studied, demonstrating that the energy is correctly measured within 2%. This is a goodprecission for LVL2. The jet energy resolution decreases from 12% for the smallest energies to4% for energies above 1000 GeV. The resolutions were fit with the following expression, thatincludes an stochastic term convolved with a constant term:σ(E)E=A(GeV 1/2)√E⊕B (1)On the table 4 the results of the fit are shown for all the η bins, before and after calibration.A few percent improvement in the resolution is obtained with the current calibration method. Afurther improvement can be achieved in future by exploiting the correlation between the fractionof electromagnetic energy and the calibration weights[4].In another study, two different RoI sizes were used in order to study its effect on the jetenergy scale and resolution. One of the RoI sizes was chosen to be slightly smaller than the conediameter (0.7x0.7 in η, φ) so some of the energy of the jet was lost outside the RoI. The other onehad the default dimensions. The jet energy calibration constants were calculated independentlyin both cases and the resulting jet energy scale and resolutions were compared. In both cases,6 The truth energy of the jet is calculated in the following way: first, jets are reconstructed with the cone algorithmrunning on the MC-truth particles. The total energy of the jet is calculated by summing up all the energies ofthe MC-truth particles that fall inside the cone. The MC-truth jet that is closer to the LVL2 reconstructed jet isused to calculate the energy scale. (GeV)truthE210 310truth/ELVL2E0.960.9811.021.041.061.08 < 0.7η0 <  < 1.5η0.7 <   < 2.5η1.5 <  < 3.2η2.5 <  (GeV)truthE210 310LVL2E resolution/E0.020.040.060.080.10.120.14 < 0.7η0 <  < 1.5η0.7 <   < 2.5η1.5 <  < 3.2η2.5 < Figure 4. Left: jet energy scale for the LVL2 jets as a function of the truth energy of the jet,for four different bins in η. Right: jet energy resolution as a function of the truth energy of thejet, for four different bins in η.Table 4. Results of the fit of the jet energy resolution as a function of the jet energy, beforeand after applying the calibration. The fit was done assuming the expression 1.η region Before calib. After calib.a b a b(0.0,0.7) 1.03 0.06 0.96 0.04(0.7,1.5) 1.28 0.06 1.18 0.04(1.5,2.5) 1.53 0.05 1.37 0.03(2.5,3.7) 1.86 0.06 1.46 0.04the jet energy scale was found to be within 2% around 1. The resolution of the jets was alsofound to be the same. This means that, in case that some small fraction of the jet energy wouldbe lost outside the RoI the calibration algorithm would correct for it. Therefore, using an RoIof 1.0x1.0 will reduce processing time while keeping the same physics performance.Finally, the jet energy scale and resolution were calculated also for the case when the FEBgranularity is used. The results obtained, for both the scale and the resolution, were compatiblewith the ones obtained for the cell based jets, demonstrating that the FEB granularity fullfillsthe timing and performance requirements of the ATLAS LVL2 jet selection.4. ConclusionsThe ATLAS Second Level jet trigger uses a cone algorithm to reconstruct the jets and appliesa simple calibration procedure. Two possible granularities have been studied up to now: usingcell energies and FEB based energy sums. In both cases similar performance in terms of energymeasurement and resolution were obtained while the FEB based approach has been proben tobe a factor 3 faster, being more addequate for the ATLAS LVL2 trigger. The cell based methodcan also fullfill the timing requirements provided the reconstruction parameters (like the RoIsize or the number of iterations of the jet algorithm) are properly chosen. For the cell basedalgorithm, the jet energy scale was found to be correct with a 2% accuracy, for all η regions andall the energies. The calibration method improves the jet energy resolution by a few %.References[1] George S et al. 2007 The ATLAS High Level Trigger steering This proceedings.[2] Gupta A and Wood M 2005 Jet Energy Calibration in the ATLAS detector using DC1 samples ATLASinternal note CERN-ATL-COM-CAL-2005-002.[3] Menke S et al. 2007 Hadron Collider Physics Symposium (La Biodola, Isola d’Elba, Italy) PreprintarXiv:0706.1474.[4] Gupta A, Merritt F and Proudfoot J 2006 Jet Energy Correction Using Longitudinal Weighting ATLASinternal note CERN-ATL-COM-PHY-2006-062.

Implementation and Performance of the ATLAS Second Level Jet Trigger

Implementation and Performance of the ATLAS Second Level Jet Trigger

Abstract

Similar works

Full text

Available Versions

CERN Document Server