An Event Display for the ATLAS Experiment ATLANTIS: CHEP, Interlaken, 30 th September 2004 Janice Drohan Jon Couchman Nikos Konstantinidis Zdenek Maxa University College London Frans Crijns Eric Jansen Peter Klok Charles Timmermans University of Nijmegen Hans Drevermann CERN Dumitru Petrusca Gary Taylor UC, Santa Cruz

30th September 2004CHEP, Interlaken2 Overview Introduction to ATLAS Aims of the Event Display Program Overview Data Orientated Projections Analysis Techniques Advanced Features Summary

30th September 2004CHEP, Interlaken3 Introduction and Aims Atlantis is an Event Display for ATLAS: Proton-Proton collider 14TeV Center Mass Energy Design Luminosity = cm -2 s -1 Bunch crossing rate = 40Mhz (25ns) Approx 23 interactions per bunch crossing Understanding and checking analysis: Detector Check Clustering Tracking Associations (Tracks to clusters, tracks to tracks) Not to understand detector construction (detector shown to understand event) Primary Goal: Easy, fast, error free visual investigation and physical understanding of complete ATLAS events

30th September 2004CHEP, Interlaken4 Program Overview Atlantis is a JAVA application –Uses Java2D graphics libraries –User configurable Swing GUI –Uses Layered Canvas to show multiple views on screen at once Access to Event Data –Atlantis reads in events from XML –JiveXML is an ATHENA algorithm to produce such files Can produce full reconstruction or fast simulation events –Data can be Stored locally Accessed from over network Obtained from XMLRPC server (online mode) –Design Luminosity event ~20MB (4MB zip)

30th September 2004CHEP, Interlaken5 Program Overview Detector Geometry –Used to convey quickly to the user the context in which hits are to be viewed –Idealised geometry is adequate and desirable (LAr PreSampler) –Read in from 2 XML files Image Output –EPS, PNG Easily Configurable –Possible to modify and save: Colour maps Projection/window setup on startup GUI content

30th September 2004CHEP, Interlaken6 Menus Data –Turn on/off, Re-order Projection –Change projection and projection parameters Cuts Sub Detector Menus –Change data colour and sizes Interaction Control Zoom, Move, Rotate Rubberband (zoom, summarise, select) Pick (hits and tracks, detectors) Fisheye (radial zoom) Clock (angular zoom) Synchro-cursors Window Control zoom, copy (drag and drop) Information Output

30th September 2004CHEP, Interlaken7 Data oriented projections ATLANTIS is based on the ALEPH Event Display DALI: –x,y,z not always optimal for colliding beam experiments –More natural and useful are the non-linear combinations which reflect the design of ATLAS  = (x 2 +y 2 ),   = atan2(y, x),  = log( z/(z/ 2 +1) Intuitive ProjectionsNon-Intuitive Y/X, Y’/Z, X’/Z, ρ/Zφ/ρ, V-Plot, φ/Z

30th September 2004CHEP, Interlaken8 Y/X projection – TILE, LAr barrel, RPC (intuitive) RPC

30th September 2004CHEP, Interlaken9 projection – calorimeters, muon hits ( sector ) (intuitive)

30th September 2004CHEP, Interlaken10 X'projection – muon hits and their association to Moore tracks

30th September 2004CHEP, Interlaken11 projection – like Y/X, but prompt tracks are straight lines

30th September 2004CHEP, Interlaken12 projection and the V-Plot    Max  cm V-PlotDraw each space point twice at  +k*(  Max ) and  -k*(  Max )  3D information For tracks can judge   pt (slope of V arms) charge (  -ve V +ve) Distorted V’s track not from IP low p, -ve high p, +ve

30th September 2004CHEP, Interlaken13 V-Plot

30th September 2004CHEP, Interlaken14 Fisheye view

30th September 2004CHEP, Interlaken15 Analysis techniques Data to be viewed may be: Cut - e.g. by p T, energy, association… Coloured - by associations, layer, sub-detector More powerful when used in combination, e.g. –Select only hits belonging to truth tracks –Colour them by their associated reconstructed track Inconsistencies indicate problems

30th September 2004CHEP, Interlaken16 Analysis techniques

30th September 2004CHEP, Interlaken17 Advanced Features Filtering Algorithm Inner Detector views for high luminosity events not very useful Algorithm uses histogram(η,φ) based technique –Select hits consistent with tracks originating from the primary vertex –Accept hits in bin if there are hits in >5 layers –Time = 1 sec/event –Basis of LVL2 Tracking Algorithm (IDScan)

30th September 2004CHEP, Interlaken18 36 tracks 440 GeV 34 tracks 410 GeV 25 tracks 222 GeV 27 tracks 270 GeV Filtered hits iPatRec tracks True tracks Comparison to Track Reconstruction

30th September 2004CHEP, Interlaken19 Advanced Features – cont. Lists –Allow user to dynamically create and manage their own associations grouping of objects perform context dependent operations e.g. vertex a set of reconstructed tracks 3D Box –Allows the user to investigate small 3D region around secondary vertex

30th September 2004CHEP, Interlaken20 Summary Atlantis is an event display tailored for visual investigation of complete ATLAS events Uses Data Orientated Projections and the V-Plot Fast and easy to use Documentation, Download, Picture Database –