1. LHC-Collider Physics and Simulation for High Energy Cosmic Rays
J. N. Capdevielle, APC, University Paris Diderot

2. Outline General properties of giant EAS The extrapolation at UHE
The treatment of inclined GAS in AGASA
The treatment of the vertical energy estimator
Amendments of experimental data and general convergence to GZK prediction
Mass composition at UHE

3. Hybrid approach to the primary cosmic ray composition
R. Attallah1 and J.N. Capdevielle2
1Physics Department, Univ. of Annaba, Algeria
2APC, Univ. of Paris 7, France

4. Introduction
The chemical composition of primary cosmic rays furnishes crucial clues on their sources;
A direct measurement of their high energy component runs out of statistics;
Above 1014 eV, observation must resort to indirect method (air shower measurements);

5. Chemical composition
Air shower interpretation is hampered by our lack of knowledge of the particle interaction physics;
Air showers present very large fluctuations;
Classic air shower experiments only sample the air shower at one depth.
Extensive fitting and interpolation are needed.

6. A novel technique by IACT
Ground-based detection of the Direct Cherenkov (DC) light emitted by the primary particle;
The intensity of this light is proportional to Z 2;
Measurement of the energy spectrum for cosmic ray nuclei in the range TeV (H.E.S.S.);
Limited energy window.

7. (

8. Hybrid detector
DC-light detection can be combined with a classic air shower experiment in order to measure on an event-by-event basis:
1. the mass and energy of the primary particle;
2. the particle content of the shower;
to test experimentally the different critera used for the identification of primary cosmic rays.
to approach the elemental composition around the knee with validated criteria.

9. Monte Carlo calculations
CORSIKA package v (Heck et al. 1998).
Two independant high energy hadronic interaction models:
1. QGSJET v. II-03 (Ostapchenko 2006)
2. SIBYLL v. 2.3 (Engel et al. 1999).
Fluka model v at low energy (Ferrari et al. 2005).

10. Experimental conditions
Primary particles considered: p, N, Fe (vertical).
Primary energy: 50 TeV and 200 TeV
Observation level at H.E.S.S. altitude
(1830 m; g/cm2).
Detection energy thresholds:
E  300 MeV, Ee  2 MeV
100 showers per run.

11. Electron lateral distribution

12. Muon lateral distribution

13. Hadron lateral distribution

14. Number of particles (50 TeV)
Muons
Hadrons
10 m
20 m
Proton
8.8
(8.3)
24.3
(23.2)
6.5
(4.9)
11.1
(8.5)
Nitrogen
6.9
(6.9)
21.9
(21.5)
2.5
(2.6)
5.5
(5.3)
Iron
4.9
(4.5)
16.6
(14.7)
1.0
(0.8)
2.3

15. Number of particles (200 TeV)
Muons
Hadrons
10 m
20 m
Proton
40.0
(37.2)
105.4
(97.8)
38.2
(35.4)
62.8
(56.5)
Nitrogen
38.0
(33.1)
104.7 (94.7)
20.7
(18.1)
37.6
(32.1)
Iron
29.5
(26.0)
89.1
(82.6)
13.0
(9.7)
25.4
(19.8)

16. Electrons vs. positrons

17. Electron size

18. Muon size

19. Primary Energy

20. Conclusion
DC-light detection can be combined with a classic air shower experiment.
Such a hybrid detector is able to test the different criteria used for primary cosmic ray identification.
Validated criteria can be used to study the cosmic ray compostion around the knee.

24. Total p-p Cross-Section
~ ln2 s
Current models predictions: mb
Aim of TOTEM: ~1% accuracy
COMPETE Collaboration fits all available hadronic data and predicts:
LHC:
[PRL (2002)]

26. Acceptance All detectors with trigger capability
non-diffractive minimum bias events
dNch/dh [1/unit]
Energy(GeV) per event
Charged particles
per event
single-diffractive events
 = - ln tg 
All detectors with trigger capability
Trigger acceptance > 95%
for all inelastic events

32. Concorde Fox Charlie, Roissy, Octobre 78 Une centaine d’AR Paris New York pour exposer à 17000m d’altitude deux chambres à émulsion (pendant 270H).

33. Chambers for Balloon and Airborne Experiments
Evis=E(h)+E
Energy threshold
Stratospheric 200 GeV
Mountain altitude 2-4 TeV
Particle physics observed in XREC
- n, E, <r>, < E r>
nch, EH, <rH>, < EH rH>
- Energy and PT distributions
- pseudorapidity distributions
- dN/d=f()
- correlations <PT>, dN/d
(more or less completely)
- direct interaction in the chambers
- near direct interactions with
localized origin

34. CERN Courier Octobre 1981 Début des expériences Octobre 1978
Une collision de 106 GeV (forte multiplicité, spikes dans la distribution de pseudo-rapidité)

36. Chambres à émulsion sur Concorde
Impact d ’un photon de 200 TeV, l ’un des 211 g d ’une collision de 107 GeV.
Evènement à émission coplanaire.
50ch sur A H
500 p 1PeV, PeV
250 familles g , 10 PeV , 3 au LHC (100 PeV)

38. JF2af2 (Concorde) Xray film under 8 c.u.
Lego plot with the 4 most energetic Gamma ’s

39. Jf2af2 (Concorde)
34 g ’s aligned
about 50% of the visible energy

41. Very large tension for the diquark partners ?

42. 3 most energetic clusters in JF2af2

43. One possible configuration
External ’s and total <ER> factors indicate a common origin under 2.2km above the chamber
Like in Strana, we need pt ‘ s > 10 GeV/c for the emission of 3 high energy hadrons generating A, Ap, B
Threshold energy for valence quarks in alignment ~200 GeV in c.m.s.(proton of 1016 eV in Lab)

45. Most energetic events above LHC energy
Tadjikistan
Andromeda
Fianit
normal hadron and g ’s content reproduced with CORSIKA (1500 g ’s in Fianit, but few chances to reproduce the 10 PeV g ’s in the halo)

46. ANDROMEDA

48. TADJIKISTAN

49. Comment
Coplanar emission , even if partly explained by fluctuations, needs more attention
p-A and A-A collisions have to be considered, for peripheral collisions (RHIC results) to point out QGP signatures in spikes or very large Pt .Semi inclusive data consequences may be important
New experiements(LHC energy, forward region) with emulsion bricks can be performed with air cargo liners and at mountain altitude

53. Xmax (g/cm2) and Nmax for p, Fe initiated showers

55. Propagation : coupure GZK
Greisen, Zatsepin, Kuzmin
Interaction des hadrons avec le fond de photons à 3K (CMB)
Eseuil = 70 EeV
protons
Les sources doivent être proches !

56. Treatment of inclined EAS data from surface arrays and GZK prediction
Jean Noël CAPDEVIELLE, F.COHEN, B.SZABELSKA, J.SZABELSKI
Georgi Timofeevich
Zatsepin (2006)
Vadim Alekseyevich
Kuzmin (2006)

57. Individual showers

58. Fonction Gaussienne hypergéométrique
f(x) = Ne x s-a (1+x) s-b(1+d.x)-c
Électrons
Avec x = r / r0 et d = r0 / r1
f(x) = N x - (1+x)-(-)(1+.x)-
Muons
Avec x = r / r’0 et  = r’0 / r’1
À angle fixe, il va falloir ajuster les paramètres :
a, b, c, r0, r1, , , , r’0 et r’1
Ne , N et “s” sont donnés par la simulation

59. Résultats des ajustements

60. Résultats des ajustements

63. Differential Primary Energy Spectrum of Cosmic Rays
Isotropic distribution
of sources

65. Treatment of inclined EAS data from surface arrays and GZK prediction
Jean Noël CAPDEVIELLE, F.COHEN, B.SZABELSKA, J.SZABELSKI
Measured: lateral distribution + direction (θ, φ)
Density (600m, θ)  Density(600m, 0)  Energy
AGASA conversion 600 600:
1 = 500 g/cm2 2 = 594 g/cm2
That conversion is energy/size independent

67. Treatment of inclined EAS data from surface arrays and GZK prediction
Jean Noël CAPDEVIELLE, F.COHEN, B.SZABELSKA, J.SZABELSKI
Conversion to ''vertical density''
example:
Results of CORSIKA
simulations show
complicated
and energy dependent
form

68. Treatment of inclined EAS data from surface arrays and GZK prediction
Jean Noël CAPDEVIELLE, F.COHEN, B.SZABELSKA, J.SZABELSKI
Cascade theory and CORSIKA simulations
results for the highest energies
depend on interaction model,
but suggest overestimation of energy at AGASA

70. Treatment of inclined EAS data from surface arrays and GZK prediction
Jean Noël CAPDEVIELLE, F.COHEN, B.SZABELSKA, J.SZABELSKI
From Bergman spectrum to AGASA spectrum
using AGASA conversion
Red points: AGASA
energy spectrum
Grey area: D.R.Bergman et al. (HiRes Collaboration)
29th ICRC, Pune, India, 2005
histograms:
MC generated spectrum following Bergman
approximately recalculated spectrum using AGASA conversion

71. Treatment of inclined EAS data from surface arrays and GZK prediction
Jean Noël CAPDEVIELLE, F.COHEN, B.SZABELSKA, J.SZABELSKI
How does the conversion to ''vertical density'' work ?

76. Treatment of inclined EAS data from surface arrays and GZK prediction
The spectrum from surface array has to be corrected from the overestimation of the primary energy between 10°-35° in the last decade
the amended spectrum of AGASA (ISVHECRI aug. 06) is progressing in this direction
GZK after 4 decades is going to be confirmed by HIRES, AUGER, AGASA…
The overestimation in AGASA data was mainly coming of the special properties of 3D Electromagnetic cascade near maximum

102. JEM-EUSO FoV EUSO ~ 1000 x AGASA ~ 30 x Auger
EUSO (Instantaneous) ~ 5000 x AGASA
　　　　　　　　　　　　　　　　　　　~ 150 x Auger
JEM-EUSO tilt-mode
AGASA

103. Principle of EUSO - first remote-sensing from space, opening a new window for the highest energy regime
TPC-like
natural
chamber
1020 eV
Cf: Ground-based arrays < 100 EUSO
Scintillator array,(2)Fluorescence telescope array
From College de France: better data now

104. Conclusions
New chances for Proton &Gamma ray Astronomy at UHE from ISS with JEM-EUSO
New results of LHC updating the simulation
GZK tendancies confirmed after specific treatment of inclined EAS and particular procedure in the conversion of vertical signal to primary energy.
Xmax behaviour and change in p-Air interaction above 3 EeV?
Ratio of light at 500g/cm2 to 1100g/cm2 depends on mass (in favour of p composition at UHE for HIRES

106. Ne t
G.COCCONI, 1961 De r

107. Cascade électromagnétique (NKG)

108. Signal (r) = C1 e+e- (r) + C2 (r)
Signal dans Auger
Simulation  densité de particules
Détecteurs Auger  signal en Vertical Equivalent Muons (VEM)
Signal (r) = C1 e+e- (r) + C2 (r)
VEM
Des simulations avec géant4 de la cuve d’Auger :
C1 = 0,47
C2 = 0,9 – 1

109. Trans GZK AREA New scales Adequate Advanced Technologies
Milesbornes to Quantum Gravity
earliest approaches, EUSO and JEM-EUSO

110. Astronomie proton
1000 evts à répartir sur un certain nombre de sources éventuelles avec leur spectre respectif

112. LPM effect Maximum deeper in atmosphere for pure e.m. cascades
trigger more difficult for registration of near vertical e.m. cascade with surface arrays

116. Total p-p Cross-Section
~ ln2 s
Current models predictions: mb
Aim of TOTEM: ~1% accuracy
COMPETE Collaboration fits all available hadronic data and predicts:
LHC:
[PRL (2002)]

117. Extrapolation des modèles d’interactions hadroniques
Distribution de pseudo-rapidité
Première interaction importante
 donne les caractéristiques générales
de la gerbe (Nmax, Xmax et
profil latéral)
Modèles théoriques sont ajustés
sur les données expérimentales
Or pas de données
au-delà de 1,8 TeV
dans le centre de masse (collisions pp)
 extrapolation

118. Distribution de pseudo-rapidité
Incertitudes
Distribution de pseudo-rapidité
Pythia A
Pythia modele 4
Pythia Atlas
PHOJET 1.11sajet
Herwig 5.9
Isajet 7.32
Prédictions pour le LHC
à 14 TeV dans le centre de masse
Multiplicité entre 70 (Isajet )
et 125 (Pythia 6.122A)
Combien de particules ?
Quelle énergie emportée par
la particule leader

120. Violation du scaling de KNO (1000 collisions) 1020 eV