The KASCADE-Grande Experiment

Transcription

1 The KASCADE-Grande Experiment O. Sima 1 for the KASCADE-Grande Collaboration 2 1 University of Bucharest, Romania 2 CSSP14 Sinaia 2014

2 Overview 1. KASCADE-Grande experimental facilities 2. Calibration and primary data analysis 3. Shower reconstruction 4. Standard energy and mass reconstruction 5. Energy spectrum and composition 6. S(500) and Constant Intensity Cut method 7. LOPES 8. KCDC 9. Conclusions

3 High energy cosmic rays Direct measurement: baloons, satellites Indirect measurements based on Extensive Air Showers (EAS) Konrad Bernlöhr

4 1. KASCADE-Grande experimental facilities Purpose study of cosmic rays in the energy range ev - energy spectrum - mass composition Location Karlsruhe Institute of Technology (KIT Campus North) N, 8.4 E, 110 m a.s.l g cm -2 - magnetic field: 47.8 mt, inclination 65 downward - multidetector system

5

6 KASCADE = KArlsruhe Shower Core and Array DEtector

7

8 dj A tr N j C pa(lg Ne, j,lg Nm, j E) lg( E) d lg( E) A Correlation between the truncated number of muons and the number of electrons in KASCADE (Astropart Phys 31 (2009) 86)

9 Light primaries spectrum All particles spectrum Main results of KASCADE: - energy spectrum in the range ev - knee in the spectrum of light components (p, He, possibly CNO) at increasing energies - gradual increase of the heavy component with energy - no severe problem with data and analysis, consistent results - high energy model dependence still the limiting factor in the analysis of KASCADE data

10 KASCADE-Grande:measurements of air showers with energy 100 TeV - 1 EeV Grande Array KASCADE-Grande Grande station KASCADE Lopes Piccolo Array

11 Detector Particle Area[m 2 ] Threshold Grande Array (plastic scintillator) e/ + m MeV Piccolo Array (plastic scintillator) e/ + m 80 3 MeV KASCADE Array (liquid scintillator) e/ MeV (plastic scintillator) m MeV Muon Tracking Detector (streamer tubes) m 128x4 800 MeV Calorimeter (liquid ionisation chambers) h 304x8 50 GeV Top Cluster (plastic scintillator) e/ 23 5 MeV Top Layer (liquid ionisation chambers) e/ + m MeV Trigger Layer (plastic scintillator) m MeV Multiwire Proportional Chambers m 129x2 2.4 GeV Limited Streamer Tubes m GeV

12 37 detector stations (370 m 2 ) 18 trigger clusters (7 detectors)

13 2. Calibration and primary data analysis Calibration of Grande detectors The single particle spectrum compared to simulations Energy calibration in terms of the energy deposited by a vertically incident muon In shower analysis => Conversion of the energy deposited in the detector in particle density Lateral Distribution Function

14 In standard analysis Lateral Energy Correction Function LECF: LECF = function(r), r radial coordinate, independent of Standard LECF LDF for muons and electrons very important for shower reconstruction, for obtaining information on energy spectrum and mass composition

15 More realistic Lateral Energy Correction Function (LECF) LECF mean energy deposit per charged particle (e, m) - contributions to LECF from, p, n - radial dependence of LECF: fractional contribution of, p, n changes with r angular distribution of particle momentum => length of the trajectory in the detector - azimuthal dependence of LECF angular distribution of particle momentum => length of the trajectory in the detector S q Early O Late

16 -For the computation of LECF including all ingredients (particles, energies, angular distribution), efficient procedures to evaluate energy deposition are required - GEANT simulations - time consuming - not appropriate

17 Fast simulation procedure of energy deposition Method: Step 1 (data base) - full simulations with GEANT for e, m,, p, n for a set of - incident energies - incident angles - fit each GEANT distribution with a combination of simpler distribution functions (Landau, exponential, polynomial) - fit the dependence of the parameters of the resulting functions on the energy and the angle of incidence Step 2 (simulation) - find the parameters of the distribution functions corresponding to the particle, energy and angle of incidence -apply the Composition Method for Monte Carlo simulation of energy deposition by sampling from the simpler distributions Gain in computation speed: factor of in comparison with GEANT simulation Nucl. Instrum Methods A 638 (2011) 147

18 m e 1.2 GeV 50 GeV 50 TeV m e p n E(MeV) E(MeV) E(MeV) Electrons and muons q=0 o Electrons and muons q=40 o All particles, 50 GeV, q=40 o GEANT3.21 energy deposition (MeV)

19 GEANT distributions are decomposed into simpler distributions: - Landau - exponential - polynomial

20 Fit of the Landau peak Muons E=50 GeV 0, 20, 30, 40 o Angle dependence of the fit parameters

21 => computation of LECF as a function of - incidence angle of the shower - radial distance from the shower core - azimuthal position Refinement: use of GEANT4, implement complete geometry of the hut and detector (A. Gherghel-Lascu) Correct density of particles in the observation level

22 Mapping of LDF in instrinsic shower plane Asymmetry of LDF in detector plane: shower development ( attenuation ) geometry effects geomagnetic field Information from the KASCADE-Grande detectors does not allow a complete integration of the lateral density function (LDF) around the shower core => deviations from azimuthal symmetry may be important - especially at large radial distances (S500) - muon density is reconstructed from KASCADE array (located in the NE corner of the Grande area) S Early O Late CSSP10 Sinaia 2010

23

24 CORSIKA simulation without the Earth s magnetic field => Projection onto the normal plane reduces the asymmetry, but does not eliminate it => The simple model not adequate Method 1: orthogonal projection Method 2: along particle momentum Method 3: triangulation based on arrival time Differences between projection methods Still important asymmetry

25 Correction Factor: Exponential attenuation coefficient -function of angle -function of radial coordinate Symmetry restored

26 Test of the LDF Reconstruction: Comparison with density reconstructed by KASCADE

27 Nucl. Instrum. Methods A 620 (2010) 202 Energy calibration: uncertainty 15-17%

28 Arrival Time and Shower Direction Timing uncertainty: 2 ns Direction: degree Core position: 5-8 m Shower size Shower core position Grande versus KASCADE Arrival direction Grande versus KASCADE Nucl. Instrum. Methods A 620 (2010) 202

29 3. Shower reconstruction - Direction - Energy of the primary particle - Mass of the primary particle - Primary experimental information - KASCADE-Grande: energy deposition in detectors => charged particle density - Arrival time - KASCADE: muon density, electron density - High energy muons map of the atmospheric depth of production - Radio signal (LOPES)

30 The recorded data is used to infer information on the primary particle QGSJETII Detector calibration Conversion of detector signal in particle density Mapp the density in intrinsic shower plane Construct observables Inference of the parameters of the primary particle Crosschecks between results are intended/possible

31 The recorded data is used to infer information on the primary particle QGSJETII Detector calibration Conversion of detector signal in particle density Mapp the density in intrinsic shower plane Construct observables Inference of the parameters of the primary particle Crosschecks between results are intended/possible

32 Standard shower reconstruction: KRETA calibrated detector signal converted to charged particle density using LECF (mean energy deposit per charged particle) muon density obtained by fitting the data from KASCADE muon detectors electron density obtained by fitting charged particle density and muon density extrapolated from KASCADE to Grande detectors using specific LDFs primary energy evaluated using the muon and the electron size of the shower primary particle identification based on the correlation of the electron size and the muon size of the shower LECF, LDF, energy estimator, mass estimator obtained from the analysis of simulated showers using CORSIKA

33 Lateral Density Function (LDF) Energy deposition in detectors converted in particle density using LECF Particle density in intrinsic shower core information about primary energy and about primary composition NKG Linsley Lagutin Polynomial

34 S 100 S 600

35 Fiducial Area Trigger Efficiency Reconstruction Efficiency

36

37 4. Standard energy and mass reconstruction - Number of charged particles: power law in function of energy - Logarithm of E linear function of logarithm of N ch, but: - Dependence on primary mass Log 10 (E)=a(m) log 10 (N ch ) + b(m) - a, b dependence on primary mass through the ratio R=(N ch /N m ): a=a p +(a Fe -a p ) k; b=b p +(b Fe -b p ) k k=(log 10 (R)-log 10 (R p )/(log 10 (R Fe )-log 10 (R p ) R p =(N ch /N m ) p, R Fe =(N ch /N m ) Fe - The coefficients depend on the zenith angle (muons and electrons attenuate differently) Coefficients determined by simulations Astropart. Phys. 36 (2012) 183 Tests: application to simulated showers

38 Reconstructed vs simulated number of showers in energy bins Epos simulations QGSJet-II used used for calibration Astropart. Phys. 36 (2012) 183

39 Reconstructed vs simulated energy average and standard deviation Astropart. Phys. 36 (2012) 183

40 5. Energy spectrum and composition All particle spectrum, calibration based on QGSJet-II - With Epos 1.99 calibration, spectrum goes down by 10% Astropart. Phys. 36 (2012) 183

41 Conclusions from Astropart. Phys. 36 (2012) 183: Measured all particle spectrum with a systematic uncertainty <15% Spectrum between knee and ev: - Not a single power law - Spectrum hardening above ev - Spectrum steepening around ev Reconstruction of energy spectra of groups of primary mass: - Mass separation k coefficient k=(log 10 (R)-log 10 (R p )/(log 10 (R Fe )-log 10 (R p ) R p =(N ch /N m ) p, R Fe =(N ch /N m ) Fe => Proton primary: k=0 Iron primary: k=1 Electron rich showers: light primary Electron poor showers: heavy primary

42 Reconstructed spectrum for electron poor [k>(k Si +k C )/2] and electron rich showers Phys. Rev. Lett. 107 (2011)

43 Steepening of the all particle spectrum around ev First evidence that this knee-like break in the spectrum is due to the heavy primaries Spectrum of light primaries re-evaluated Phys. Rev. D 87 (2013) Definition of light primaries: electron rich showers, with small k, k < (k C +k He )/2 - Improved statistics: - Additional observation time - Increased fiducial area

44 => Ankle like structure in the spectrum of light primaries at about ev (energy above the knee of the heavy primaries)

45 Spectrum of the light component of cosmic rays - Slope change from to at around ev - Possible indication of the transition from galactic to extragalactic cosmic rays

46 Dependence of reconstructed spectrum on interaction models (low energy interaction model: Fluka) Bands in the figure denote the effect of systematic uncertainties Adv. Space Research 53 (2014) 1456

47 Model dependence: EPOS produces larger number of muons than QGSJet or SIBYLL, with SIBYLL correponding to the lowest number of electrons and muons at sea level => EPOS gives lower values of energy than QGSJet, SIBYLL higher Reconstruction of the flux of showers simulated with SIBYLL, QGSJet and EPOS using calibration based on QGSJet Mixed composition with 5 primaries with equal contribution Adv. Space Research 53 (2014) 1456

48 Differences between the composition based on SIBYLL and EPOS However, the spectrum behaviour for the electron rich and electron poor showers is the same => Knee around ev for the electron poor (heavy) primary => Ankle for the electron rich (light) primary

49 Slight sensitivity to the k value for the selection of electron poor vs electron rich samples Adv. Space Research 53 (2014) 1456

50 Nucl. Phys. B Proc. Supplement (2014) in press

51 Nucl. Phys. B Proc. Supplement (2014) in press

52 Nucl. Phys. B Proc. Supplement (2014) in press

53 Conclusions concerning the spectrum: - KASCADE: knee of the light primaries at about ev - Spectrum hardening at ev due to medium mass primaries - KASCADE-Grande: knee of heavy primary around ev - Ankle due to the light primaries at ev - Mixed composition between ev

54 6. S(500) and Constant Intensity Cut method Independent approach G. Toma, ICRC For KASCADE-Grande array, at 500 m from the core the density of charged particles S(500) is independent of primary mass S(500) energy estimator Calibration by Monte Carlo simulation

55

56

57

58

59 Good accord of the reconstructed energy by S(500) and by the standard method for Corsika simulated showers Discrepancy in the case of experimental data Inconsistency between simulations and data higher muon multiplicity?

60 7. LOPES Radio emission from air showers - Geomagnetic deflection of electrons and Positrons thickness of the shower front 1 m, frequencies of tens of MHz - Askaryan effect, charge excess Advantages: - High duty cycle - Precision - E: ev Nature 435 (2005) Correlation of radio emission with EAS Detected by KASCADE-Grande

61 30 dipole antennas

62 F. Schroeder, ECRS 2012 Energy reconstruction

63 Radio detection of EAS implemented in other high energy cosmic ray installations

64 8.KCDC KASCADE-Grande what s next? KASCADE and KASCADE-Grande closed and dismantled

65 KASCADE Cosmic Data Center KCDC

66 9. Conclusions KASCADE-Grande a unique high energy cosmic ray detector - multidetector, hadron, electromagnetic, muon, radio components - Provided energy spectrum and mass composition of high energy cosmic rays with a well controlled uncertainty - Observed the spectrum structures heavy ion knee, ankle of the light component, besides the knee due to the light primaries at ev - The results do not require new interaction features at the energies up to ev - Implemented and tested novel experimental techniques, refined analysis procedures - Provided information for testing the models of acceleration and propagation of cosmic rays

67 Thank you!

68 p, ev, q=45 o from North CSSP10 Sinaia 2010

69 Fe, ev, q=45 o from North CSSP10 Sinaia 2010

70

71 CSSP10 Sinaia 2010