DIFFERENT H.E. INTERACTION MODELS

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1 COMPARISON OF EAS SIMULATION RESULTS USING CORSIKA CODE FOR DIFFERENT H.E. INTERACTION MODELS Dept. of Physics, Gauhati University, Assam, INDIA 15th Sep, 2010

2 Out line of the talk Introduction Primary Energy Spectra Need for Simulation Monte-Carlo & CORSIKA About Monte Carlo Method CORSIKA Hadronic Interaction Models Hadronic Interaction Models Method Result Discussion

3 Primary Energy Spetra

4 Primary Energy Spectra 1 Count-rate for cosmic ray of energy ev is one count per m 2 per second, where 2 at knee 4x10 15 ev is one count per m 2 per year whereas 3 at ankle 5x10 18 ev is one count per km 2 per year. Hence Cosmic Rays of energy above ev, because of very low flux, can be studied indirectly by detecting secondary particles produced in the atmosphere using ground based particle detector array.

5 Primary Energy Spectra 1 Count-rate for cosmic ray of energy ev is one count per m 2 per second, where 2 at knee 4x10 15 ev is one count per m 2 per year whereas 3 at ankle 5x10 18 ev is one count per km 2 per year. Hence Cosmic Rays of energy above ev, because of very low flux, can be studied indirectly by detecting secondary particles produced in the atmosphere using ground based particle detector array.

6 Primary Energy Spectra 1 Count-rate for cosmic ray of energy ev is one count per m 2 per second, where 2 at knee 4x10 15 ev is one count per m 2 per year whereas 3 at ankle 5x10 18 ev is one count per km 2 per year. Hence Cosmic Rays of energy above ev, because of very low flux, can be studied indirectly by detecting secondary particles produced in the atmosphere using ground based particle detector array.

7 Primary Energy Spectra 1 Count-rate for cosmic ray of energy ev is one count per m 2 per second, where 2 at knee 4x10 15 ev is one count per m 2 per year whereas 3 at ankle 5x10 18 ev is one count per km 2 per year. Hence Cosmic Rays of energy above ev, because of very low flux, can be studied indirectly by detecting secondary particles produced in the atmosphere using ground based particle detector array.

8 Need for Simulation Also, to study and analyse Cosmic Rays above 1PeV, one has to rely heavily on Monte-Carlo Simulation models. These theoretical models are developed based on high energy particle interaction characteristics derived mostly from accelerator data.

9 Need for Simulation Also, to study and analyse Cosmic Rays above 1PeV, one has to rely heavily on Monte-Carlo Simulation models. These theoretical models are developed based on high energy particle interaction characteristics derived mostly from accelerator data.

10 Monte Carlo Method The Monte Carlo method provides approx. solutions to a variety of mathematical problems by performing statistical sampling of experiments on a computer. In this method computer generated pseudo numbers are used to simulate a physical process, which is divided into step by step procedures.

11 Monte Carlo Method The Monte Carlo method provides approx. solutions to a variety of mathematical problems by performing statistical sampling of experiments on a computer. In this method computer generated pseudo numbers are used to simulate a physical process, which is divided into step by step procedures.

12 Monte Carlo Method Using a known probability distribution of the physical process at every step, the outcome is determined using random numbers. Thus in Monte Carlo simulation one generates many virtual or artificial events according to model selected with particular choices.

13

14 Monte Carlo Method These events may then be statistically analyzed to yield real observable parameters and compared with the existing real data. This method applies to problems with no probabilistic content as well as those with inherent probabilistic structure.

15 Monte Carlo Method These events may then be statistically analyzed to yield real observable parameters and compared with the existing real data. This method applies to problems with no probabilistic content as well as those with inherent probabilistic structure.

16 Monte Carlo Method These events may then be statistically analyzed to yield real observable parameters and compared with the existing real data. This method applies to problems with no probabilistic content as well as those with inherent probabilistic structure.

17 About CORSIKA CORSIKA (COsmic Ray SImulations for KAscade) is a detailed Monte Carlo program to study the 4-D evolution and properties of extensive air showers in the atmosphere. It was developed to perform simulations for the KASCADE experiment at Karlsruhe in Germany. Now various features of this versatile code is exploited by scientific community around the globe.

18 About CORSIKA CORSIKA (COsmic Ray SImulations for KAscade) is a detailed Monte Carlo program to study the 4-D evolution and properties of extensive air showers in the atmosphere. It was developed to perform simulations for the KASCADE experiment at Karlsruhe in Germany. Now various features of this versatile code is exploited by scientific community around the globe.

19 About CORSIKA CORSIKA (COsmic Ray SImulations for KAscade) is a detailed Monte Carlo program to study the 4-D evolution and properties of extensive air showers in the atmosphere. It was developed to perform simulations for the KASCADE experiment at Karlsruhe in Germany. Now various features of this versatile code is exploited by scientific community around the globe.

20 About CORSIKA The CORSIKA program allows simulating interactions and decays of nuclei, hadrons, muons, electrons, and photons in the atmosphere up to energies of some ev. It gives type, energy, location, direction, and arrival times of all secondary particles that are created in an air shower and pass a selected observation level.

21 About CORSIKA The CORSIKA program allows simulating interactions and decays of nuclei, hadrons, muons, electrons, and photons in the atmosphere up to energies of some ev. It gives type, energy, location, direction, and arrival times of all secondary particles that are created in an air shower and pass a selected observation level.

22 About CORSIKA CORSIKA basically consists of 4 parts. The first part is a general program frame handling the input and output, performing decay of unstable particles, and tracking of the particles taking into account ionization energy loss and deflection by multiple scattering and the Earth s magnetic field.

23 About CORSIKA CORSIKA basically consists of 4 parts. The second part treats the hadronic interactions of nuclei and hadrons with the air nuclei at higher energies. The third part simulates the hadronic interactions at lower energies, and, The fourth part describes transport and interaction of electrons, positrons, and photons.

24 About CORSIKA CORSIKA basically consists of 4 parts. The second part treats the hadronic interactions of nuclei and hadrons with the air nuclei at higher energies. The third part simulates the hadronic interactions at lower energies, and, The fourth part describes transport and interaction of electrons, positrons, and photons.

25 About CORSIKA CORSIKA basically consists of 4 parts. The second part treats the hadronic interactions of nuclei and hadrons with the air nuclei at higher energies. The third part simulates the hadronic interactions at lower energies, and, The fourth part describes transport and interaction of electrons, positrons, and photons.

26 About CORSIKA CORSIKA contains several models for the latter three program parts that may be activated optionally with varying precision of the simulation and consumption of CPU time. High-energy hadronic interactions may be treated by one of the models:

27 About CORSIKA 1 DPMJET (Dual Parton Model with JETs) 2 EPOS (Electron Positron Scattering) 3 NEXUS (NEXt generation Unified Scattering approach) 4 QGSJET (Quark-Gluon String model with JETs) 5 SIBYLL(QCD Based mini jet model) 6 VENUS (Very Energetic NUclear Scattering ) 7 FLUKA (FLUctuating KAscade) 8 GHEISHA (Gamma Hadron Electron Interaction SHower code) 9 UrQMD (Ultra relativistic Quantum Molecular Dynamics)

28 About CORSIKA 1 DPMJET (Dual Parton Model with JETs) 2 EPOS (Electron Positron Scattering) 3 NEXUS (NEXt generation Unified Scattering approach) 4 QGSJET (Quark-Gluon String model with JETs) 5 SIBYLL(QCD Based mini jet model) 6 VENUS (Very Energetic NUclear Scattering ) 7 FLUKA (FLUctuating KAscade) 8 GHEISHA (Gamma Hadron Electron Interaction SHower code) 9 UrQMD (Ultra relativistic Quantum Molecular Dynamics)

29 Interaction Model QGSJET... Quark Gluon String with JETs is the most successful model describing the HE hadronic interaction. This model offered relatively easy approach to the simulation of cosmic ray interactions at higher energies, as well as ensured a good agreement to the accelerator data at lower energies.

30 Interaction Model QGSJET... In this model the appropriate cross sections for the inelastic interaction between hadrons i and j are calculated using the expression χ ij (s, b) = χ s ij (s, b) + χh ij (s, b) where χ s ij (s, b) and χh ij (s, b) represent the soft and semihard pomerons respectively. s is the centre of mass energy and b is the impact parameter.

31 Interaction Model QGSJET... The total cross section in this model is given by the formula σij t (s) = 1 e ij d 2 b [ 1 exp { e ij (χ s ij (s, b) + χh ij (s, b))}] where e ij is the so-called shower enhancement co-efficient, for pp interactions e pp = 1.5.

32 Interaction Model DPMJET... Dual Parton Model with JETs is based on the two components Dual Parton Model and contains multiple soft chains as well as multiple minijets.it relies on the Gribov-Regge theory and the interaction is described by multi Pomeron exchange.

33 Interaction Model DPMJET... The total cross section in this model is given by the formula σ t ij (b, s) = 4π inf 0 bdb [1 exp(χ ij (s, b)] where χ ij (s, b) represents total Pomeron in this model.

34 Interaction Model EPOS... EPOS is a simple model where an exchange of a parton ladder between the two hadrons can be related to high energy hadron-hadron interaction. According to this model, parton ladder contains two parts where the hard part describes the parton-parton hard scattering, while the soft part is a purely phenomenological object, parameterized in Regge pole fashion.

35 Interaction Model EPOS... EPOS is a simple model where an exchange of a parton ladder between the two hadrons can be related to high energy hadron-hadron interaction. According to this model, parton ladder contains two parts where the hard part describes the parton-parton hard scattering, while the soft part is a purely phenomenological object, parameterized in Regge pole fashion.

36 Interaction Model EPOS... EPOS is a consistent quantum mechanical multiple scattering approach based on partons and strings, where cross sections and the particle production are calculated consistently, taking into account of energy conservation in both cases

37 Method Method To study the different shower parameters due to change in hadronic interaction model, we have generated extensive air showers using CORSIKA simulation with six hadronic interaction models. Here we have considered two primary masses (proton and iron) and four primary energies (10 14 ev, ev, ev and ev). There are altogether 46 sets of events with 1000 showers each.

38 Method 1 Simulation is performed considering only the vertical showers at the average sea level. 2 THIN options are selected for flat horizontal detector. 3 The relevant data are extracted from the output DATA files using inbuilt FORTRAN program. 4 The extracted data are then analysed using simple C++ program in the ROOT environment.

39 Method 1 Simulation is performed considering only the vertical showers at the average sea level. 2 THIN options are selected for flat horizontal detector. 3 The relevant data are extracted from the output DATA files using inbuilt FORTRAN program. 4 The extracted data are then analysed using simple C++ program in the ROOT environment.

40 Method 1 Simulation is performed considering only the vertical showers at the average sea level. 2 THIN options are selected for flat horizontal detector. 3 The relevant data are extracted from the output DATA files using inbuilt FORTRAN program. 4 The extracted data are then analysed using simple C++ program in the ROOT environment.

41 Method 1 Simulation is performed considering only the vertical showers at the average sea level. 2 THIN options are selected for flat horizontal detector. 3 The relevant data are extracted from the output DATA files using inbuilt FORTRAN program. 4 The extracted data are then analysed using simple C++ program in the ROOT environment.

42 Method 1 Simulation is performed considering only the vertical showers at the average sea level. 2 THIN options are selected for flat horizontal detector. 3 The relevant data are extracted from the output DATA files using inbuilt FORTRAN program. 4 The extracted data are then analysed using simple C++ program in the ROOT environment.

43 Result No.of Muon Vs No. of Electron

44 Result Findings 1 It is observed that for all the models iron primary showers produce greater no. of muons as compared to that produced by proton primary showers 2 The model dependence of the parameter< N µ > is studied by calculating Merit Factor (MF)for each model(m) compared to QGSJET, MF= <Nµ(M)> <Nµ(Q)> σ 2 M +σq 2 3 The values of MF for each case found to be < 0.1.This shows that there is no significant differences.

45 Result Findings 1 It is observed that for all the models iron primary showers produce greater no. of muons as compared to that produced by proton primary showers 2 The model dependence of the parameter< N µ > is studied by calculating Merit Factor (MF)for each model(m) compared to QGSJET, MF= <Nµ(M)> <Nµ(Q)> σ 2 M +σq 2 3 The values of MF for each case found to be < 0.1.This shows that there is no significant differences.

46 Result Muon no divided by Energy Vs Energy

47 Result Muon no divided by Energy Vs Energy

48 Result Findings 1 The EPOS and VENUS curves are flatter 2 Both the curves have significantly higher values than that predicted by the DPMJET and SYBILL. 3 Predictions by the QGSJET01 and QGSII have the values in between these values. 4 Slope of the curves for DPMJET, SYBILL, QGSJET01 and QGSII are almost equal. 5 Relative differences between for example epos-proton curve and the dpmjet-proton curve increases gradually with energy from about 10 % at ev to about 33 % at ev

49 Result Findings 1 The EPOS and VENUS curves are flatter 2 Both the curves have significantly higher values than that predicted by the DPMJET and SYBILL. 3 Predictions by the QGSJET01 and QGSII have the values in between these values. 4 Slope of the curves for DPMJET, SYBILL, QGSJET01 and QGSII are almost equal. 5 Relative differences between for example epos-proton curve and the dpmjet-proton curve increases gradually with energy from about 10 % at ev to about 33 % at ev

50 Result Findings 1 The EPOS and VENUS curves are flatter 2 Both the curves have significantly higher values than that predicted by the DPMJET and SYBILL. 3 Predictions by the QGSJET01 and QGSII have the values in between these values. 4 Slope of the curves for DPMJET, SYBILL, QGSJET01 and QGSII are almost equal. 5 Relative differences between for example epos-proton curve and the dpmjet-proton curve increases gradually with energy from about 10 % at ev to about 33 % at ev

51 Result Findings 1 The EPOS and VENUS curves are flatter 2 Both the curves have significantly higher values than that predicted by the DPMJET and SYBILL. 3 Predictions by the QGSJET01 and QGSII have the values in between these values. 4 Slope of the curves for DPMJET, SYBILL, QGSJET01 and QGSII are almost equal. 5 Relative differences between for example epos-proton curve and the dpmjet-proton curve increases gradually with energy from about 10 % at ev to about 33 % at ev

52 Result Findings 1 The EPOS and VENUS curves are flatter 2 Both the curves have significantly higher values than that predicted by the DPMJET and SYBILL. 3 Predictions by the QGSJET01 and QGSII have the values in between these values. 4 Slope of the curves for DPMJET, SYBILL, QGSJET01 and QGSII are almost equal. 5 Relative differences between for example epos-proton curve and the dpmjet-proton curve increases gradually with energy from about 10 % at ev to about 33 % at ev

53 Result Findings 1 The EPOS and VENUS curves are flatter 2 Both the curves have significantly higher values than that predicted by the DPMJET and SYBILL. 3 Predictions by the QGSJET01 and QGSII have the values in between these values. 4 Slope of the curves for DPMJET, SYBILL, QGSJET01 and QGSII are almost equal. 5 Relative differences between for example epos-proton curve and the dpmjet-proton curve increases gradually with energy from about 10 % at ev to about 33 % at ev

54 Result Depth of Shower maximum Vs Energy

55 Result Findings 1 It is observed that irrespective of High Energy Hadronic Interaction Models, the experimental data fall in between the iron and proton curves as expected.

56 Discussion Discussion 1 So far depth of shower maximum and muon Vs electron number is considered, all the models show consitancy among themselves. 2 But when we consider ratio of muon to primary energy, SIBYLL and EPOS gives significantly higher values compared to that obtained by the rest of the models. 3 This parameter may be used to study model dependence at higher energy.

57 Discussion Discussion 1 So far depth of shower maximum and muon Vs electron number is considered, all the models show consitancy among themselves. 2 But when we consider ratio of muon to primary energy, SIBYLL and EPOS gives significantly higher values compared to that obtained by the rest of the models. 3 This parameter may be used to study model dependence at higher energy.

58 Discussion Discussion 1 So far depth of shower maximum and muon Vs electron number is considered, all the models show consitancy among themselves. 2 But when we consider ratio of muon to primary energy, SIBYLL and EPOS gives significantly higher values compared to that obtained by the rest of the models. 3 This parameter may be used to study model dependence at higher energy.

59 To Be Done.. Simulation to be done for higher energies. Study Zenith angle dependence To Find sensitive parameter Observables sensitive to model Viable Statistical Tests Low Energy Subroutines To compare different low energy subroutines Compare diff. cross section predictions

60 Thank You.. T HAN K YOU FOR ATTENTION

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