The document summarizes a simulation of extensive air showers (EAS) using the AIRES code. Key points: 1) Simulations were run for primaries of protons, carbon, iron, and gamma rays with energies of 1015 eV in the "knee" region to study EAS characteristics. 2) Variables like energy, arrival time, production height, and identity of secondaries were recorded. Results showed differences in lateral distribution and time profiles between primaries. 3) Further analysis of observables like particle counts, arrival times, and azimuthal/zenith angles at different distances from the core is planned to better understand correlations with primary properties. Multivariate analysis techniques may help reveal hidden

1. Detecting EAS with TRASGOs
-a simulation-
G. Kornakov
February, 2010, Santiago de Compostela

2. Extensive air shower
(EAS)
● How does an EAS occur?
-High energy primary cosmic rays
interact at the high atmosphere with
production of billions of secondaries and
shower formation
● Why are they interesting?
-Astroparticle Physics:
– Where do they come from?
– How are they accelerated?
– How do they propagate?
– and many other...
-very high energy (up to 1020 eV),
-understanding of formation process

3. The knee region
1 Partícle/m2-y
1 Partícle/km2-y
1 Partícle/km2-y
Knee

4. EAS statistics in knee region
Mass of the primary cosmic ray vs energy measured in different experiments
[CCOU02]
The scatter plot of the average logarithm of the nuclear
mass number of the primary cosmic rays versus energy
clearly shows the need for more input from accelerators.

5. EAS simulation
Extensive showers detection on Earth surface
Code: AIRES
Simulations characteristics:
-energy: 1015 eV (Knee region)
-primary particles: P,C,Fe,Gammas
-depth of first interaction:30g/cm2
-number of simulations: 100 for each case.
-height of measurement plane: 1400 m

6. EAS simulation
Variables simulated
● x,y,
● θ,φ
● time of arrival
● energy
● height of production
of secondary part.
● id. of the secondary
particle

7. EAS simulation
Some results
e μ

8. EAS simulation
Some results
e μ
time
time
φ φ
Difference between azimuthal angles of electrons and muons vs time

9. EAS simulation
Some results
e μ
θ
time
r
time
θ
r

10. Lateral distribution in a EAS
induced by proton
Lateral distribution of μ+e at different primary energies
~200m
~90m
~30m

11. EAS simulation
We have started to analyse the answer of a single
detector at different distances from the shower core:
We assumed S=1m2 detectors
8 R=5particles/m2
9 7
R~30m for 101 5ev
3 proton
R
10 4 1 2 6
5
11 13
12

12. RESULTS (time of arrival)
0m R/2~15 m R ~30m
Iron
Carbon

13. RESULTS (time of arrival)
0m R/2~15 m R ~30m
Proton
Gamma

14. RESULTS (zenithal angle)
0m R/2~15 m R ~30m
Iron
Carbon

15. RESULTS (zenithal angle)
0m R/2~15 m R ~30m
Proton
Gamma

16. RESULTS (Azimuthal angle in one detector)
Iron Carbon
Proton Gamma

17. NEXT STEPS

18. To define some secondary
observables
● Number of particles <N>, <Ne>,<Nμ>
● Arrival Times: <T><Te><Tμ>
● Th <Th> and σ(Th) for e and μ at t=5ns,
t=10ns, t=20ns.
● <Ph> and σ(Ph) as a function of position
Analyse their behaviour,
their correlations, their
clusters...

19. One dream

20. Why multivariate analysis?
● A lot of information spread out in many observable variables (many
dimensions problem)
● Some variables are strongly correlated and dependent on the primary
cosmic ray characteristics (energy, mass, direction)
● Many multivariate techniques developed recently and not yet
commonly used in astroparticle physics: clusters analysis, PAC
analysis …
Problems we expect:
● High fluctuations in different EAS from the same primary
● High statistical fluctuations inside a single shower
Hope:
● To find some hidden relationship among all the observables informing
us about the properties of the primitive cosmic ray

21. Still a lot of work

22. Acknowledgments
especially want to thank R.Vázquez for his
help with the simulations