# Monte Carlo simulations in High Energy Experiments

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1 CSFI 2008 Calcolo Scientifico nella Fisica Italiana Sessione di Fisica Nucleare e Subnucleare Monte Carlo simulations in High Energy Experiments Rimini May Senigallia 31 May

2 Page 2 Outline Introduction Why and how Monte Carlo simulations are used in High Energy Experiments Walk through the various aspects covered by MC simulations in experiments Generation Tracking Detector response How does it all fit together LHCb example Statistics and CPU

3 Introduction Page 3 In High Energy Experiments when elementary particles collides in accelerators (for example) unstable particles are created, these particles decay quickly. it is necessary to reconstruct an image of the event through measurements by complex detectors comprising many subdetectors. The Monte Carlo simulation role is to mimic what happens in the spectrometers to understand experimental conditions and performance. Monte Carlo data processed as real data in Reconstruction and Physics Analysis BUT we know the truth Comparing the simulation with what is measured in reality we can interpret the results Monte Carlo Event Generation Tracking particles through material Detector Response Detector DAQ system High Level Trigger Reconstruction Physics Analysis

4 Why to use Monte Carlo simulations Page 4 Want to generate events in as much detail as Mother Nature get average and fluctuations right make random choices, ~ as in nature an event with n particles involves O(10n) random choices multiple variables: flavour, mass, momentum, spin, production vertex, lifetime,... At LHC: ~ 100 charged and ~ 200 neutral (+ intermediate stages) several thousand choices This applies also to the transport code through the spectrometer and the detectors response want to track the particles in the geometrical setup and have them interact with the matter energy loss, multiple scattering, magnetic field want to simulate the detection processes and response of a given detector ionization, scintillation, light the interaction events are stochastic and so is the transport process A problem well suited for Monte Carlo method simulations computational algorithms relying on repeated random sampling to compute their results In fact a Monte Carlo simulation in a High Energy Experiment is a collection of different Monte Carlo, each specialized in a given domain, working together to provide the whole picture

5 How are MC simulations used? Page 5 Detailed simulations are part of HEP physics Simulations are present from the beginning of an experiment Simple estimates needed for making detector design choices Develop reconstruction and analysis programs Evaluate physics reach We build them up over time Adding/removing details as we go along We use them in many different ways Detector performance studies Providing efficiency, purity values for analysis Looking for unexpected effects, backgrounds When theory is non well known compare to various models and accounts for different detector acceptance - bb angular production 3 θb [rad] MC 3 θb [rad] B J/Ψ K* shape of the detector Data

6 Page 6 Traditional flow of simulated data and applications Generators Specific reaction Two independent phases that can be split Geometry Simulation Response Simulation Particle paths Recorded signals DAQ system LHCb example Reconstruction Observed tracks, etc Physics Tools Interpreted events Individual Analyses

7 Experiments simulation software Page 7 HEP experiments have their own software frameworks and use external packages developed in the physics community for Generators and for Transport in the detectors Athena (ATLAS), CMSSW (CMS), Gauss (LHCb), VMC (ALICE, Minos), bbsim (BaBar), etc. Response of the detectors is often in- house and requires detectors experts tuned first with test beam data, then with measurements in the experiment Experiment applications provide Interfaces to event generators Interface to transport code Event model for MC truth and Persistency Access to snap-shots of process to understand what happened Histograms, messaging Physicists in the experiments are shielded from Generators and transport code (eg. Geant4) to different degrees different in the various experiments different for different roles

8 Structure of a simulation application Page 8 Gauss the LHCb simulation application as example Two INDEPENDENT phases normally run in sequence in a single job JobOpts Initialize JobOpts Initialize Interface Pythia, EvtGen Exchange model HepMC Monitor Cnv GiGa Geant4 Cnv Geometry Cnv LHCb Event model HepMC MCParticle MCVertex MCHits POOL Monitor Event Generation primary event generator specialized decay package pile-up generation Detector Simulation geometry of the detector (LHCb Geant4) tracking through materials (Geant4) hit creation and MC truth information (Geant4 LHCb)

9 Event generation Page 9 Many programs available in the physics community to generate primary collisions specialized for hard processes, resonance, decays, parton showers, hadronization, etc. often best at given task, but not always directly usable by experiments general-purpose PYTHIA (T.Sijostrand et al.) HERWIG (G.Marchesini et al.) ISAJET (H.Baer et al.) SHERPA (F.Kraus et al.) LCG Generators Service at CERN provides libraries for many of them Experiments generally use one generator for massive production and make smaller data sets with others Pythia/Herwig have different hadronisation mechanism (clusters as opposed to strings) for example and specialized codes when necessary BaBar and LHCb use EvtGen (D.Lange and A.Ryd) for b-hadrons decays ATLAS and CMS use MCatNLO (S.Frixione, B.Webber), AlpGen (M.Mangano et al) for matrix elements to feed to general purpose ALICE uses Hiijing (M.Gyulassy and X.-N. Wang) for Pb-Pb interaction

10 Generator phase in practice Page 10 In LHCb as example in Gauss proton-proton interactions at E cm = 14 TeV are generated using Pythia 6 First simulate the hard processes in colliding particles, then the subsequent hadronisation LHAPDF for Parton Density Functions particles are then decayed by EvtGen (+PHOTOS and Pythia) Various type of events generated Minimum bias includes hard QCD processes, single and double diffractive events Signal b and bb events obtained from minimum bias events with b or b-hadron Cosmics and particle guns (ie. a given particle with given kinematic) Choose Pythia setting that would agree with experiments measured particle multiplicities Simulate running conditions Luminous region with smearing of primary vertex according to bunch sizes Pileup (number of pp collisions per bunch) at running luminosity

11 Page 11 Detectors simulation, eg. the LHC experiments ALICE Solenoid and dipole magnets ATLAS Toroid and Solenoid magnets 45m long, 25m diameter CMS LHCb Solenoid magnet 22m long, 15m diameter Dipole magnet 22m long, up to 10 m height

12 Transport through detectors Page 12 Complex detectors and a large variety of physics processes that need to be simulated Closer to pp collision Photons Farther to pp collision Photons Muons e ± Muons π ±, p, K ± π ±, p, K ± e ± Neutrons Neutrons Tracking detectors Muon detectors Hadronic calorimeter Electromagnetic calorimeter At LHC particle energies range from few MeV to TeV and special particle ID detectors (eg. Ring Imaging Cerenkov) What is signal for one detector can be background for another HEP Experiments use in their framework packages developed in the physics community for transport of particles: GEANT4 and/or FLUKA

13 Detector simulation: transport codes Page 13 GEANT4 is a C++ toolkit to track particles through the detector developed in the Physics community GEANT4 International Collaboration ~ 10 year old used in HEP, nuclear physics, heavy ion physics, cosmic ray physics, astrophysics, space science and medical applications GEANT4 is the successor of GEANT3, the world-standard toolkit for HEP detector simulation All LHC experiments use GEANT4 for transporting particles in the experimental setup and simulating the physics processes that can occur Navigation in EM fields Physics processes for a variety of particles at different energies ALICE also uses FLUKA (A.Ferrari et al) FORTRAN-based Couples low energy neutron transport and particle transport Other LHC experiments use it radiation levels

14 Page 14 Detector simulation: Geant 4 GEANT4 coverage of physics comes from mixture of theorydriven, parameterized, and empirical formulae. Both crosssections and models (final state generation) can be combined in arbitrary manners as necessary. Standard and Low energy EM processes, Hadronic processes, Optical photon processes, Decay processes, etc. Each particle is moved in steps (few microns to cm) For each step: The material the particle is in is found The energy loss and directional change due to multiple scattering is applied The effects of electric and magnetic fields on charged particles are calculated The particle might generate photons by bremstrahlung or Cherenkov radiation The particle might decay in flight The particle might collide with a nucleus and generate more particles If the particle enters or leaves a detector it is recorded

15 Page 15 EM and hadronic showers in material Hadronic shower shapes Electro-magnetic showers In dense material number of particles created and tracked by Geant grows quickly and with that the CPU time! Atlas event from their publicity page

16 Geometry modeling Page 16 Need accurate modeling to have the most accurate results but more volumes, more memory, more CPU time A wide variety of dimensions in an HEP experiment Choose depending on relevance to physics study LHCb LHCb VErtex LOcator For trackers detailed description of all active and passive components; material budget

17 Physics processes and cuts Page 17 Need to describe physics processes as accurate as needed by resolution of detectors Choose appropriate physics models and set cuts: more accuracy more CPU CMS: Pion HCAL Longitudinal Shower Profile Timing Performance vs Range Cut E=300 GeV In LHCb full simulation QGSP takes ~ 10% longer that LHEP V. Ivanchenko, Geant4

18 Page 18 Simulation of Detector response (aka digitization) Simulation of detector response transforming hits in sensitive detectors to produce digitized data and provide them in DAQlike format is provided by separate application Convenience Flexibility Each detector has its own detailed detector response simulation and imperfections Detections efficiencies and resolutions are adjusted according to test beam data Electronic noise and cross-talk for each specific detector are added Time information is correctly taken into account by all detectors Handling of spill-over effects (data from adjacent beam crossings) A detector is sensitive to previous or subsequent bunch crossings depending on its electronics LHCb, Boole output In LHCb last proceessing of Boole is the L0 harwdare trigger emulation

19 Statistics and CPU time Page 19 Statistics required of the same order of real events for LHC feasible for signal (O(10)-O(10 6 )/year), even many times more. while impossible for all pp collisions (O(10 7 )-O(10 8 )/sec) months of running on the GRID to generate few seconds generic b events of LHC(b) data taking Simulations are the most CPU time consuming applications of HEP experiments in LHCb the simulation takes KSI2k sec/event (Gauss + Boole) while the reconstruction takes 2.5 KSI2k sec/event Transport through the detectors is the longest in LHCb: generator phase 1/100 th of simulation phase The CPU time depends on the complexity of the primary events LHCb: minimum bias 20 KSI2k sec/event generic b events 50 KSI2k sec/event ALICE: pp collisions 39 KSI2k sec/event Pb-Pb collisions 7000 KSI2k sec/event with tricks to save time Require a production system and GRID resources to simulate events in LHC experiment computing model Tier2 are used to produce them and Tier1 to store the output data ensure non-overlap of samples with control of random number generators seeds

20 Page 20 Simplify simulation by crossing levels Generators Specific reaction eg. Atlfast (ATLAS) parameterized simulation Advantages: Fast and flexible for what if analysis studies Retains flexibility to choose generators Disadvantages Often not sufficiently realistic Only certain information, tools available Can use similar techniques at other levels Interpreted events Individual Analyses

21 Conclusions Page 21 Events studied in High Energy Physics experiments at more and more complex. With LHC very high energy will be reached. Simulations of such events are an integral part of an experiment in all of its phases from design to physics analysis Simulations applications are a complex system of dedicated software developed by the physics community and by the experiments Considerable computing resources are (and will be) necessary: the GRID is already extensively used for this

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