The note describes the beam background conditions during first physics data taking with ALICE and the strategy for the evaluation of the LHC beam background contribution to the minimum bias event sample used for first physics

Fiete Grosse-Oetringhaus, J

Foka, Y

Kisiel, A

Morsch, A

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EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH European Laboratory for Particle Physics      Internal Note/ ALICE reference number  ALICE-INT-2009-022 version 1.0 Date of last change 30.11.09    Evaluation of the Beam Background Contribution to the pp Minimum Bias Sample Used for First Physics    Authors: Jan Fiete Grosse-Oetringhaus, Adam Kisiel, Andreas Morsch and Yiota Foka AbstractThe note describes the beam background conditions during first physics data taking with ALICE and the strategy for the evaluation of the LHC beam background contribution to the minimum bias event sample used for first physics.         Evaluation of the Beam BackgroundContribution to the pp Minimum Bias SampleUsed for First PhysicsJan Fiete Grosse-Oetringhaus, Adam Kisiel, Andreas Morsch and Yiota FokaNovember 30, 2009AbstractThe note describes the beam background conditions during first physicsdata taking with ALICE and the strategy for the evaluation of the LHCbeam background contribution to the minimum bias event sample usedfor first physics.1 IntroductionDuring first data taking with the ALICE detector [1] a minimum bias sampleof pp collisions will be collected by reading out the detector upon each bunchcrossing (BB). Initially the beam intensity and hence the interaction probabilityare low. Thus, a fraction of these events will have only detector hits causedby particles from beam background (beam-gas collisions, tertiary halo, ...) orcosmic radiation. Oﬄine trigger cuts will be applied to reduce the contributionof background events to the event sample. In order to quantify this contributionand correct the collision data in the analysis two additional triggers are needed:events with crossing of a bunch and an empty bunch position (EB or BE) andtwo empty bunches (EE) will be read. These special events will be also used foran optimization of the minimum bias event trigger to be used in future runs.As will be shown in the next section, the relative contribution of backgroundevents to the event sample is expected to be very low. However, at LHC start-up, when the running conditions are not yet stable and optimized one cannotexclude scenarios with much worse beam background condition than expected.Conservative trigger settings have to be planned. We need to collect a suffi-ciently large sample of (BE, EB, EE)-triggered events without compromisingthe statistics of the BB-sample. The results of such considerations will be dis-cussed in this note.In addition, the first sample of events, measured by ALICE on November23rd 2009 during the LHC commissioning, required a dedicated procedure ofbackground estimation and removal, described in Section 4.12 Expected beam background conditionBeam backgrounds comprise products of beam-gas collisions (BG) close to theIP within the experimental region ±20m and the so called beam halo (BH)which contains particles produced outside the experimental region from beam-gas scattering or from collisions with the tertiary collimators. In ALICE it isexpected that the background from the tertiary collimators is relatively small.The reason is that the tertiary collimators only protect the quadrupoles of theinner triplet but do not take part actively in the beam cleaning itself. Never-theless, a detailed evaluation of this contribution is currently in progress. Themain part of the beam halo comes from beam-gas collisions within the innertriplet at a distance of 20 − 40m from the IP. The running conditions duringfirst pp physics at√s = 900GeV and 7TeV are summarized in table 1.Table 1: LHC running conditions for planned collisions and background for firstpp physics.pp√s = 900GeV pp√s = 7TeVNumber of bunches 4 12Particles per bunch 4.0× 1010 3.0× 1010Initial Luminosity 6.6× 1027 1.7× 1029Interaction Rate [kHz] 0.33 13Gas density IR [equ.H2/m3] 2.0× 1010Gas density Machine [equ.H2/m3] 4.0× 1012BG Rate [Hz] 0.03 0.07BH Rate [Hz] 5 123 Bunch crossing trigger strategyOne of the most important measurements performed with the first physics dataset is the determination of the charged particle pseudo-rapidity density dN/dη.A systematic error on the measurement might be introduced by the presenceof beam-halo and beam-gas events. Usually the vertex position of these eventscannot be reconstructed, thus these events do not lead to the reconstructionof additional tracks. However, these events may cause a trigger (oﬄine or on-line) and thus influence the overall normalization of the dN/dη measurement.Without further correction the fraction of background events can be directly in-terpreted as a systematic error on the measurement. Depending on the analysisthe overall systematic error is in the range of 4% to 8%.A conservative choice of the number of (BE, EB) events needed can beobtained by the following conservative consideration: the smallest significantfraction of background events is 1% and we want to know this contributionwith a relative error of about 10% equivalent to 100 events. According to our2assumptions these 100 events are part of a sample of 10000 BB-events. For thedN/dη analysis itself 20000 collision events are needed. Thus our goal could beachieved by taking BB/EB/BE triggers with the ratio 4:1:1.In case the fraction fB of background events is even smaller, it becomescompletely negligible and we are safe. In case the fraction is higher the error onthe background contribution is 1/√fB %. For example for a 10% contributionthe error would be 3% and correcting the data we can expect to stay with thecontribution to the systematic error in the order of per cent.After a first run with these settings we can use the measured backgroundfraction in order to decide on the further strategy. In particular one might haveto consider second order effects that require more statics and different triggerstrategies.• Signal / Background rate variation with time. If there is a strong depen-dence one should try to equilibrate the number of signal and backgroundevents over the course of a run.• Background rate variation bunch to bunch, i.e. are the triggered BEsimilar to the BE in the BB sample ? This would require to use differentsets of bunches for the BE/EB triggers.4 Background estimation for the first data sam-pleDuring the first data taking run on November 23rd 2009 we have collected 284triggers, which were all taken in coincidence with the passage of both LHCbeams. Due to security reasons only the ITS detector was participating in thedata taking (layer 1 and 2 of the Silicon Pixel Detector SPD, layer 3 and 4 of theSilicon Drift Detector SDD, layer 5 and 6 of the Silicon Strip Detector SSD).For a run of such a limited statistics the statistical methods of backgroundestimation mentioned above were both not possible and not needed. Such asmall number of events could be checked one-by-one and background eventswere identified on an event-by-event basis with the methods described below.First used method was visual scanning of the events. It was performed usingthe dedicated ALICE Event Visualization Environment [4] software AliEVE,which is a part of the ALICE oﬄine framework AliRoot [2]. It enables a si-multaneous visualization of the detector raw data (with the current alignmentapplied), reconstructed clusters, the position of the primary vertex, the recon-structed tracklets formed from the primary vertex and clusters in the two layersof the ALICE SPD detector and finally the ITS stand-alone tracks reconstructedfrom up to six clusters in all the layers of the ALICE ITS.In order to be able to differentiate between valid and background events, weneeded examples of the detector response for the two types of events. For validpp events we have used the ones generated with the Monte-Carlo generatorPythia [3], then put through the simulation of the ALICE detector response3Figure 1: Example background “splash” event, “side” view. The rectangles showthe position of the 6 ALICE ITS layers. The blue crosses show ITS clusters, thelines show ITS-only tracks.and finally reconstructed with the AliRoot software as if they were real data.For the “background” sample we have used real events collected by ALICEwith exactly the same experimental conditions as the sample of interest, butwith only one LHC beam circulating. We were able to identify specific visualpatterns which were unique to the background events and were not seen in theMonte-Carlo simulations, for an example see Fig. 1. In general such events hada number of clusters randomly distributed over all ITS layers, most of them notassociated with tracks pointing to the vertex. Most of the events did not have areconstructed vertex. In a small number of cases they had one, which also meantthat there were reconstructed tracklets. However these were not confirmed byhits in the other layers of the ITS, namely the SDD and SSD, while real tracksshould have created a signal there. In contrast, for the Monte-Carlo events (foran example see Fig. [?]) the majority of the clusters were associated with tracks.Also, the SPD tracklets in the acceptance of the other layers of the ITS wereconfirmed by ITS-only tracks reconstructed out of up to 6 clusters in all ITSlayers.We scanned visually all 284 events in the sample of interest. We have indeedseen two distinctly different groups of events - one with clear “background” char-acteristics and another with the features seen in the Monte-Carlo simulation.We have tagged 29 events as “background” or “most probably background” withthis method. In addition 2 events were identified as cosmic muons.For the “background” events we have analyzed the distribution of the posi-tion of the reconstructed primary vertex in the z-direction (along the beam). Itwas found to be wide, approximately flat in the region of −10 to 10 cm used inthe analysis. We have also estimated the expected background event rate basedon runs with only one LHC beam circulating. In Fig. 3 we show the distributionof the longitudinal position of the reconstructed primary vertex before and afterthe subtraction of the background.4Figure 2: Example of a pp collision from MC, “side” view. The rectangles showthe position of the 6 ALICE ITS layers. The blue crosses show ITS clusters, thelines show ITS-only tracks.Several low multiplicity events were classified as “suspicious”, but eventswith similar topology and features were also seen in the MC sample. The 29events which were unambiguously identified as background correspond to the10% of the datasample, which is in agreement with the background fractioninferred from the z-vertex distribution of background events and rates measuredfor single-LHC-beam runs. Therefore we have decided to treat all “suspicious”events as valid pp collisions.The second method used the information from the ALICE V0 detector totag background events by looking for ones which produced a hit within the timewindow expected for the beam-gas interaction. The V0 information was onlyavailable for a subset of the 284 events. In this subsample 17 were flagged asbeam-gas interactions by the V0. We have correlated this information with theresult of the visual scanning and found excellent correlation: 16 of them wereflagged as “background” and the remaining one as “most probably background”by scanning. Out of the other 12 events tagged by scanning , 2 did not haveany hits in the V0, and for the other 10 the V0 information was not available.5 Identification with ITS information aloneStudying runs with one or two circulating beams without bunch crossings inALICE’s collisions points shows that background events usually have a highnumber of clusters but only a few reconstructed tracklets in the SPD. Figure 45z-vertex position [cm]-30 -20 -10 0 10 20 30zdN/dv110Figure 3: The distribution of the longitudinal position of the primary vertex inthe data sample of interest. Dashed histogram shows the final distribution afterbackground removal, dotted line shows the initial distribution.tracklets0 5 10 15 20 25 30clusters in ITS050100150200250300350400tracklets0 5 10 15 20 25 30clusters in ITS050100150200250300350400Figure 4: The plots show the total number of found clusters in the ITS vs. thenumber of found tracklets for a background run (left panel) and for the collisionrun (right panel). The line illustrates the cut that has been applied (see text).6shows the total number of clusters in the ITS vs. the number of found trackletsfor background run (left panel) and the collision run (right panel). In the rightpanel one can clearly identify the outliers that are confirmed by visual scanningas splash events. Events that fulfill the following condition were rejected:Nclusters > 80 +Ntracklets · 11 (1)This cut, that is also shown in Figure 4, identifies a big fraction of those eventsthat have been flagged by visual scanning.References[1] ALICE Collaboration, K. Aamodt et al., JINST 3 (2008) S08002.[2] ALICE Collaboration, AliRoot, ALICE Oﬄine simulation, reconstructionand analysis framework, http://aliceinfo.cern.ch/Oﬄine/[3] T.Sjostrand, Comput. Phys. Commun. 82 (1994) 74; T. Sjostrand, S.Mrenna and P. Skands, JHEP 2006 05 (2006) 026[4] M. Tadel, J. Phys. Conf. Ser. 119 (2008) 032036; M. Tadel, proceedings of“XII Advanced Computing and Analysis Techniques in Physics Research”,PoS(ACAT08)103.7

Evaluation of the Beam Background Contribution to the pp Minimum Bias Sample Used for First Physics

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