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Computing in High Energy Physics John Apostolakis SoFTware for Physics Group, PH Dep, CERN v0.98.3 2014.03.10

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Presentation on theme: "Computing in High Energy Physics John Apostolakis SoFTware for Physics Group, PH Dep, CERN v0.98.3 2014.03.10"— Presentation transcript:

1 Computing in High Energy Physics John Apostolakis SoFTware for Physics Group, PH Dep, CERN v

2 11 March 2014 J. Apostolakis 2 Outline Uses of Computers Reconstruction: Online, and off-line ySimulation yData analysis) Size of challenge the GRID solution and its other applications

3 Reconstruction A lightning introduction

4 The Reconstruction challenge 11 March 2014 J. Apostolakis 4

5 11 March 2014 J. Apostolakis 5 What is reconstruction Tracker hits form a puzzle Which tracks created them? Each energy deposition is a clue There are thousands of measurements in each snap-shot The experiments reconstruction must obtain a solution! In well measured magnetic field Matches the traces to tracks

6 How it works – a simple example Start with the locations of the traces on first two planes 11 March 2014 J. Apostolakis 6 Magnetic field Β

7 Ανακατασκευη στην πραξη Start with the locations of the traces on first two planes Try different combinations Project to subsequent planes Calculate differences between measured positions and predictions 11 March 2014 J. Apostolakis 7 Μαγνητικο Πεδιο Β (Kalman filter)

8 Ανακατασκευη: αποτελεσμα Start with the locations of the traces on first two planes Try different combinations Project to subsequent planes Calculate differences between measured positions and predictions Finally the candidate tracks are ή «στα γρηγορα» αυτες με μεγαλη ορμη- οι κυριες τροχιες 11 March 2014 J. Apostolakis 8 Μαγνητικο Πεδιο Β P= 7.5 GeV/c P= 11 GeV/c P= 22 GeV/c

9 last update 03/06/ :29 LCG 11 March 2014 J. Apostolakis 9 Data Organisation

10 Simulation and Detectors What is simulation ? Why it exists ? How is it done ?

11 11 March 2014 J. Apostolakis 11 Todays detectors Many different parts Different capabilities Measuring Location (trackers) Measuring energy (calorimeters) Due to complexity Different materials, Most studies must use computers to create samples of tracker hits & energy deposition

12 11 March 2014J. Apostolakis 12 Todays detector Technologies: ATLAS

13 11 March 2014 J. Apostolakis 13 What is simulation ? We build models Detectors Geometry Shape, Location, Material Physics interactions All known processes Electromagnetic Nuclear (strong) Weak (decay Silicon Tracker σ total = Σ σ per-interaction 2.5 MeV e - electron 300 μ

14 11 March 2014 J. Apostolakis 14 Example detailed geometry

15 11 March 2014 J. Apostolakis 15 Ενα απλο παραδειγμα In lead many secondary particles are produced Most are contained A few escape into CO2 Energy deposition is measured in gas Charged tracks ionise gas Fewer new tracks produced Pb CO 2 G EANT 3

16 11 March 2014 J. Apostolakis 16

17 11 March 2014J. Apostolakis17 Atlas : Physics Signatures and Event Rates Beam crossing rate 40 MHz inelastic = 80 mb In each beam crossing (rising each year, in 2012 ~ 25 interactions) Different physics targets Higgs Boson(s) (Discovery 2012) Supersymmetric partner particles Unexpected Matter-antimatter differences (B mesons) Many examples of each channel are simulated

18 11 March 2014 J. Apostolakis 18 Why simulate ? To design detectors Decise details To prepare the reconstruction Before the detector is built and operates To understand events in the analysis

19 Data Analysis 11 March 2014 J. Apostolakis 19

20 Data Analysis Uses the results of Reconstruction the products are reconstructed tracks, Energy deposits (calorimeters) Hierarchy of data from original ( RAW), to summary (AOD) An experiments physics teams use the (large) pool of data No longer in one central location, but in multiple locations (cost, space of building, computers, disks, network).... using the GRID Hypatia: a small part of analysis for a school setting Introduction /PortalPortal # # March 2014J. Apostolakis20

21 11 March 2014J. Apostolakis21 Data Hierarchy RAW Detector digitisation 10 9 events/yr * 2 MB =2 PB/yr ~2 MB/event ESD Pattern recognition information: Clusters, track candidates ~100 kB/event AOD Physical information: Transverse momentum, Association of particles, jets, (best) id of particles, ~10 kB/event TAG ~1 kB/event Relevant information for fast event selection Raw data (DAQ) First reconstruction data Summary data for analysis Classification information

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27 last update 03/06/ :29 LCG LCG depends on two major science grid infrastructures …. EGEE - Enabling Grids for E-Science OSG - US Open Science Grid les robertson - cern-it-27

28 Enabling Grids for E-sciencE EGEE-II INFSO-RI Εφαρμογες Δεκαδες εφαρμογες σε διαφορους τομεις –Φυσικη Υψηλων Ενεργειων (Pilot domain) 4 πειραματα LHC, DESY, Fermilab –Βιοϊατρική (Pilot domain) Βιοπληροφορική ( Bioinformatics) Ιατρική απεικόνιση ( Medical imaging) –Γεωεπιστημεs Γεω-επισκόπηση Φυσικη Στερεας Γης (Solid Earth Physics) Υδρολογία, Κλίμα –Υπολογιστική Χημεία –Τηξη (Fusion) –Αστρονομία Κοσμικό υπόβαθρο μικροκυμάτων ακτίνων-γ –Γεωφυσικη –Βιομηχανικές εφαρμογές 28 J. Apostolakis

29 Backup More on simulation

30 11 March 2014 J. Apostolakis 30 Describes a Detector zHierarchy of volumes zMany volumes repeat yVolume & sub-tree zUp to millions of volumes for LHC era zImport detectors from CAD systems Navigates in Detector z Locates a point z Computes a step yLinear intersection Geant4 geometry: what it does

31 11 March 2014 J. Apostolakis 31 Propagating in a field Charged particles follow paths that approximate their curved trajectories in an electromagnetic field. zIt is possible to tailor ythe accuracy of the splitting of the curve into linear segments, ythe accuracy in intersecting each volume boundaries. zThese can be set now to different values for a single volume or for a hierarchy.

32 11 March 2014 J. Apostolakis 32 Electromagnetic physics zGammas: yGamma-conversion, Compton scattering, Photo-electric effect Leptons(e, ), charged hadrons, ions yEnergy loss (Ionisation, Bremstrahlung) or PAI model energy loss, Multiple scattering, Transition radiation, Synchrotron radiation, zPhotons: yCerenkov, Rayleigh, Reflection, Refraction, Absorption, Scintillation zHigh energy muons and lepton-hadron interactions zAlternative implementation (low energy) yfor applications that need to go below 1 KeV

33 11 March 2014 J. Apostolakis 33 Shower profile 1 GeV electron in H 2 O G4, Data G3 zGood agreement seen with the data

34 11 March 2014 J. Apostolakis 34 Antiproton annihilation - CHIPS Modelπ proton neutron deuteron He-4 He-3 K triton M. Kossov

35 11 March 2014 J. Apostolakis 35 Simulation packages zProvides the means to simulate ythe physical processes and ydetector response of an experiment. zAs was realised by many in the past, ymost of the parts needed can be common between experiments (eg physics, geometry blocks). zSo it makes eminent sense to create and use a general purpose package yThat includes the common parts, yAnd enables an experiment to describe those parts with are specific to it.

36 11 March 2014 J. Apostolakis 36 ESA Space Environment & Effects Analysis Section X-Ray Surveys of Asteroids and Moons Induced X-ray line emission: indicator of target composition (~100 m surface layer) Cosmic rays, jovian electrons Geant3.21 ITS3.0, EGS4 Geant4 C, N, O line emissions included Solar X-rays, e, p Courtesy SOHO EIT

37 11 March 2014 J. Apostolakis 37 High Energy K,pi on Al, Au

38 11 March 2014J. Apostolakis38 individual physics analysis batch physics analysis batch physics analysis detector Event Summary Data (ESD) raw data event reconstruction event reconstruction event simulation event simulation event filter (selection & reconstruction) event filter (selection & reconstruction) processed data HEP Processing stages and datasets Analysis Object Data (AOD) (extracted by physics topic)

39 11 March 2014J. Apostolakis39 CERN Centre Capacity Requirements for all expts. (made July 2003) LHC Other experiments LHC Other experiments Moores law

40 11 March 2014J. Apostolakis40 Event Data Complex data models ~500 structure types References to describe relationships between event objects unidirectional Need to support transparent navigation Need ultimate resolution on selected events need to run specialised algorithms work interactively Not affordable if uncontrolled Event Raw Rec Phys VeloCalo Coord Tracks Event Cand RAWESDAOD versions Event MyTrk Phys Private Event AOD Collaboration Data

41 11 March 2014J. Apostolakis41 HEP Metadata - Event Collections Bookkeeping Run Data Event 1 Event 2 … Event 3 Run Data Event 1 Event 2 … Event 3 Run Data Event 1 Event 2 … Event N Run Catalogue Physics : Run MC: B -> π π MC: B -> J/Ψ (μ + μ - ) … Dataset Event 1 Event 2 … Event 3 Dataset Event 1 Event 2 … Event 3 Event tag collection Tag Tag … Tag M8 3.1 Collection Catalogue B -> ππ Candidates (Phy) B -> J/Ψ (μ + μ - ) Candidates …

42 11 March 2014J. Apostolakis42 Detector Conditions Data Reflects changes in state of the detector with time Event Data cannot be reconstructed or analyzed without it Versioning Tagging Ability to extract slices of data required to run with job Long life-time Tag1 definition Time Version Data Item Version Time t1t2t3t4t5t6t7t8t9t10t11 VDET alignment HCAL calibration RICH pressure ECAL temperature Time = T

43 11 March 2014J. Apostolakis43 A Multi-Tier Computing Model Tier 1 (Main Regional Centres) Tier 3 Desktop Tier2 Tier 0 (Experiment Host lab) CERN FNALRALIN2P3 622 Mbps 2.5 Gbps 622 Mbps 155 mbps Lab aUni bLab cUni n physics group regional group Tier2 Lab a Uni a Lab c Uni n Lab m Lab b Uni b Uni y Uni x Tier3 Desktop Germany Tier 1 USA UK France Italy ………. CERN Tier 1 ………. Manager View User View

44 11 March 2014J. Apostolakis44 Distributed Analysis – the real challenge Analysis will be performed with a mix of official experiment software and private user code How can we make sure that the user code can execute and provide a correct result wherever it lands? Input datasets not necessarily known a-priori Possibly very sparse data access pattern when only a very few events match the query Large number of people submitting jobs concurrently and in an uncoordinated fashion resulting into a chaotic workload Wide range of user expertise Need for interactivity - requirements on system response time rather than throughput Ability to suspend an interactive session and resume it later, in a different location Need a continuous dialogue between developers and users

45 11 March 2014 J. Apostolakis 45 Visualization zMuch functionality is implemented zSeveral drivers: yOpenGL, VRML, Open Inventor, Opacs, DAWN renderer (G4) zAlso choice of User Interfaces: yTerminal (text) or yGUI: Momo (G4), OPACS yEditors for geometry, EM physics code generation

46 11 March 2014 J. Apostolakis 46 One area: Tracking zWhat a simulation code needs to do for each step of particle: yDetermine the step length xCorresponding to the applicable physics processes xChecking if it crosses a geometrical boundary yModel the final state of the track, xAdvancing it, potentially in an EM field, xApplying the actions of the physics processes, which can create secondary particles. yDeposit energy in current position (hit).

47 11 March 2014 J. Apostolakis 47 Actions during a Step zDuring each step yEach physics process is given the opportunity to limit the step, xas is the geometry module (at a boundary), and xleading to the decision on this steps length. yPhysics processes are allowed to apply their effect xIf they occur along a step (continuous) xIf they caused the hard event that limited the step (discreet).

48 11 March 2014 J. Apostolakis 48 Actions during a Step (cont) zDuring a step (continued) yAn (optional) user-written action is called, xWhich can be used eg to create histograms or tallies. yIf the current volume contains a sensitive detector, that is addressed, allowing it eg xto record the energy deposited, xto record the exact position in general to create a hit that store all information that is relevant for that detector.

49 11 March 2014 J. Apostolakis 49 Actions during a Step (cont) zDuring a step (continued) yA parametrisation can be triggered (Geant4) xTaking over from detailed simulation xGenerating directly several hits This application-specific operates instead of normal physics processes until it returns control and/or resulting particles for further detailed simulation. Begin of step point End of step point Step Boundary

50 11 March 2014 J. Apostolakis 50 G EANT 4 zDetector simulation tool-kit for HEP yoffers alternatives, allows for tailoring zSoftware Engineering and OO technology yprovide the method for building, maintaining it. zRequirements from: yLHC yheavy ions, CP violation, cosmic rays ymedical and space science applications zWorld-wide collaboration

51 11 March 2014 J. Apostolakis 51

52 11 March 2014 J. Apostolakis 52 Multiple scattering model zA new model for multiple scattering based on the Lewis theory is implemented since public release in zIt randomizes momentum direction and displacement of a track. yStep length, time of flight, and energy loss along the step are affected, and yIt does not constrain the step length.

53 11 March 2014 J. Apostolakis 53 Multiple scattering zExamples of comparisons: y15.7 MeV e- on 19 mg/cm2 gold foil (8 um) figure y6.56 MeV proton xon 93 microns Si y70 GeV/c proto

54 11 March 2014 J. Apostolakis 54


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