In this work several aspects of ATLAS RPC offline monitoring and data quality
assessment are illustrated with cosmics data selected by RPC trigger. These
correspond to trigger selection, front-end mapping, detection efficiency and
occupancy, which are studied in terms of low level quantities such as: RPC
off-line hits and standalone tracks. The tools and techniques presented are
also extended to the forthcoming LHC p-p beam collisions.Comment: Poster section at ICHEP08, Philadelphia, USA, July 2008. 3 pages,
  LaTeX, 3 eps figure

Bianco, M.

Chiodini, G.

Gorini, E.

Guida, A.

English

arXiv

In this work several aspects of ATLAS RPC offline monitoring and data quality assessment are illustrated with cosmics data selected by RPC trigger. These correspond to trigger selection, front-end mapping, detection efficiency and occupancy, which are studied in terms of low level quantities such as: RPC off-line hits and standalone tracks. The tools and techniques presented are also extended to the forthcoming LHC p-p beam collisions.In this work several aspects of ATLAS RPC offline monitoring and data quality assessment are illustrated with cosmics data selected by RPC trigger. These correspond to trigger selection, front-end mapping, detection efficiency and occupancy, which are studied in terms of low level quantities such as: RPC off-line hits and standalone tracks. The tools and techniques presented are also extended to the forthcoming LHC p-p beam collisions

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arXiv:0810.4362v2  [physics.ins-det]  24 Feb 200934th InternationalConferenceon High Energy Physics,Philadelphia,2008ATLAS RPC offline monitoring and data quality assessmentG. ChiodiniINFN-Lecce, via Arnesano 73100 Lecce - ItalyM. Bianco, E. Gorini and A. GuidaUniversita´ del Salento - Dipartimento Di Fisica and INFN-Lecce, via Arnesano 73100 Lecce - ItalyIn this work several aspects of ATLA S R PC o ine m onitoring and data quality assessm ent are illustrated withcosm ics data selected by R PC trigger. These correspond to trigger selection,front-end m apping,detection e ciencyand occupancy,which are studied in term s oflow levelquantities such as: R PC o -line hits and standalone tracks.The tools and techniques presented are also extended to the forthcom ing LH C p-p beam collisions.1. INTRODUCTIONThem uon spectrom eteroftheATLAS experim entattheLargeHadron Collider(LHC)isbuiltaround threelargesuper-conducting air-core toroids. In the barrelregion,where the m agnetic  eld is provided by eight radialcoils,m uon triggering is accom plished by 596 Resistive Plate Cham bers [1]arranged radially at about 5 m ,7.5 m ,and10 m from the beam line [2]. The  rsttwo are located inside the toroid coils and nam ed low-ptand pivotplanesrespectively;while the outeroneislocated justoutsidethe toroid and nam ed high-ptplane.The RPC planes are m ade ofone or two m echanically independent RPC units (for a totalof1116). Each unitconsistsof2 layersofactivegasvolum e,each oneinstrum ented with two orthogonalreadoutstrip panels(m easuringthe bending and non-bending viewswith a pitch ofabout3 cm )with built-in fastG aAsfront-end electronics.Theareacovered by theRPC detectoris3650m 2 and thefront-end electronicsconsistsofapproxim ately 355,000readoutchannels.Theo -linem onitoring and data quality assessm entofsuch a largesub-system arecrucialto m axim izethephysicsreach oftheexperim ent.Thiscan beaccom plished by a detailed knowledgeofthedetectorperform anceduring runsand ensuring a uniform detectorbehaviorbetween runsin orderto reducesystem aticerrors.2. RPC DATA QUALITYThereadoutand triggerschem eisim plem ented by on-detectorprogram m ableCoincidenceM atrix (CM A)ASICs[2]. A CM A triggerselection consistsofa fastgeom etrical25 nstem poralcoincidence of3 outof4 RPC layersforlow-pt triggers and 1 out of2 RPC layersfor high-pt triggers,in addition to a low-pt trigger. Figure 1.a) showsthe RPC layerspattern when a triggerispresentforcosm icsdata.The triggerwindow could be furtherdecreased,in steps of3.125 ns,thanks to the excellent 1 ns tim ing resolution ofthe RPC detector. The two inset plots ofFigure1.a)illustratetherelativetim ebetween RPC planesbelonging to thesam etriggertower.Insidea tower,them easured spread in tim e is dom inated by the signalpropagation speed along the detecting strip;instead betweentowers,it is dom inated by the particle tim e-of- ight. Both e ect can be corrected o -line and the RPC tim ing isa powerfultoolagainstcosm ics,cavern background,and eventspile-up. The width ofthe geom etricalcoincidence(nam ed ‘triggerroad’)can be program m ed up to 3+ 3 high transverse m om entum track values. Figure 1.b)clearlyshowsa projectivetriggerroad in non-bending view asextracted from cosm icsdata.TheRPC m apping isa nottrivialtask becausethesam eelectronicsim plem entsthetriggerlogicand thereadout.In fact,to avoid triggerine ciency a largefraction ofRPC stripsarereadoutby two adjacentcoincidencem atrix inem ail:gabriele.chiodini@ le.infn.it;presented at ICH EP2008,Philadelphia,U SA ,July 2008134th InternationalConferenceon High Energy Physics,Philadelphia,2008Figure 1: a) RPC layers pattern ofnon-bending view coincidence m atrix delivering a low-pt(high-pt)trigger. In the insetsthenot- lled ( lled)plotistherelative tim e distributionsbetween pivotplane and low-pt(high-pt)plane.b)Triggerroad innon-bending view asm easured from cosm ic data.Verticaltrackscorrespond to the dashed line.Figure2: a)Thefulland dashed linesrepresentthechannelpro lesoftwo coincidencem atrix reading outa non-bendingview64-strip detectorpanel. The  lled plotisthe relative counting di erence in the overlap region. b)The fulland dashed linesrepresentthestrip pro lesofprojected tracksand corresponding e cientstrips.The  lled plotisthe single strip ine ciency.thelow-ptand high-ptplanes(nam ed ‘cabling overlaps’).Thepointing geom etry requirescabling overlapswhich areposition dependentalongthebeam and when cham berboundariesarecrossed in thebendingview,afullnon-bendingview overlap isrequired between cham bers(nam ed ‘logical-or’).Figure 2.a) shows an exam ple ofchanneloverlaps between two coincidence m atrix,together with the relativeine ciency obtained with cosm icrays.Theresulting overlap ine ciency isa fraction ofpercentand com patiblewiththe random arrivaltim e ofcosm icsinside a 25 nsclock period.The softwaretoolsshould be capable to produce a fastfeedback on RPC detectordata quality,withoutrelay onthefullATLAS eventreconstruction and com bined quantities.A RPC standalonetrackingisim plem ented in o -linem onitoring [3].Thetracking isbased on RPC spacepoints,which arede ned by orthogonalRPC clusterhitsofthesam egasvolum e.Figure3.a)showstheaveragereadoutpanelclustersizedistribution ata gasvolum ehigh voltagevalueof9600 V and nom inalfront-end voltagethreshold.The pattern recognition isseeded by a straightline,which isde ned by two RPC spacepointsbelonging,respec-tively,to low-ptand pivotplanesofthe sam e ornearby station. RPC space pointsnotpartofany previoustracksand insidea prede ned distancefrom the straightlineareassociated to thepattern.Resulting patternswith pointsin atleast3 outof4 layersin low-ptand pivotplanes are retained and a linearinterpolation is perform ed in twoorthogonalviews.From cosm icdata about95 % percentofeventshaveatleastoneRPC track;thisisduethestrongcorrelation between thepattern recognition and thetriggeralgorithm .Applying a quality cutofchi2/dof< 1 about70 % ofeventshaveatleasta good tracksand 10 % with m orethan one.In orderto m easure the detection e ciency the RPC tracking isrepeated 6 tim es,each tim e rem oving the layerundertestfrom the pattern recognition and track  tting.Figure2.b)showsthe strip pro leofreadoutpanelunder234th InternationalConferenceon High Energy Physics,Philadelphia,2008Figure 3: a) Clusters size distribution of RPC readout strips. b) Hits m ultiplicity in the event considering cosm ic raystriggered by RPC (non  lled plot)and random trigger( lled plot).testin correspondence ofthe projected track and the pro le ofe cientstrip. The strip e ciency isalso shown onthe sam eplotand itresultsin an unbiased m easurebecauseofthe 3 outof4 m ajority triggerlogic.3. COSMIC RAYS VERSUS COLLISIONSThe RPC tracking standalone is extended to the forthcom ing LHC p-p beam collisions. Cosm ic rays arriverandom ly in tim eand notuniform ly on detectorsurface.Thism akesdetectorstudieswith cosm icsnotvery accurateand predictable. Tracks produced by beam collisions are synchronous with beam clock,pointing,and uniform inazim uthalangle and pseudo-rapidity. The di cultly with beam is due to the presence ofthe m agnetic  eld andoperation at high lum inosity. The above described pattern recognition and the track quality cut correspond,inm agnetic eld,to a cutin transversem om entum .Athigh lum inosity a largeuncorrelated and correlated backgroundcould increase the num ber offake tracks signi cantly. In order to m itigate such a problem we tune the patternrecognition and the track quality cutand rejectlow m om entum tracks.In Figure 3 the distribution ofRPC hits per eventwith RPC trigger and with random triggerare shown. Theaveragevalueofthesedistributionscorrespond to theaverageRPC detectoroccupancy dueto cosm icsand uncorre-lated noise.Thecosm icray and random triggerdata show a low levelofuncorrelated noisein RPC detector,whichcorrespondsto fraction ofHz=cm 2.During beam collisions,atnom inallum inosity,uncorrelated and correlated noiseisgoing to be dom inated by cavern background and low energy tracks.4. CONCLUSIONSData quality on triggerselection and detectorperform ance could be assesin a quite straightforward and sim plewayby lookingtodistributionsoflayerspattern in trigger,singlechanneloverlap e ciency,singlestrip e ciency,andaveragereadoutpaneloccupancy.Them onitoring ofthesedistributionsguaranteesgood data on tapeand prom ptlyspoteventually occurring problem s.References[1]R.Santonico R.Cardarelli:.NuclearInstrum entsand M ethods,187 (1981)377.[2]ATLAS TechnicalDesign Report.M uon Spectrom eter.CERN/LHCC/97-22,G eneva (1997).[3]G .Chiodini,etal.NuclearInstrum entsand M ethodsA 581 (2007)213.3

ATLAS RPC offline monitoring and data quality assessment

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