g kornakov e a smultivariate analysis

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

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Page 1: G Kornakov  E A Smultivariate Analysis

Detecting EAS with TRASGOs-a simulation-

G. Kornakov

February, 2010, Santiago de Compostela

Page 2: G Kornakov  E A Smultivariate Analysis

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 102 0 eV), -understanding of formation process

Page 3: G Kornakov  E A Smultivariate Analysis

The knee region

Knee

1 Partícle/m2-y

1 Partícle/km2-y

1 Partícle/km2-y

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EAS statistics in knee region

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.

[CCOU02]

Mass of the primary cosmic ray vs energy measured in different experiments

Page 5: G Kornakov  E A Smultivariate Analysis

EAS simulation

Code: AIRES

Simulations characteristics:

-energy: 101 5 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

Extensive showers detection on Earth surface

Page 6: G Kornakov  E A Smultivariate Analysis

Variables simulated

● x,y,● θ,φ● time of arrival● energy● height of production

of secondary part.● id. of the secondary

particle

EAS simulation

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EAS simulation

e μ

Some results

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EAS simulationSome results

e μ

Difference between azimuthal angles of electrons and muons vs time φφ

time

time

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e μ

time

θ

time

r

r

θ

EAS simulationSome results

Page 10: G Kornakov  E A Smultivariate Analysis

Lateral distribution in a EAS induced by proton

Lateral distribution of μ+e at different primary energies

~30m

~90m~200m

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R=5particles/m2

R~30m for 101 5ev proton

110

8

6

12

11

9 7

13

3

2

5

4

R

We have started to analyse the answer of a single detector at different distances from the shower core:We assumed S=1m2 detectors

EAS simulation

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RESULTS (time of arrival)

Iron

Carbon

0m R/2~15 m R ~30m

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0m R/2~15 m R ~30m

Proton

Gamma

RESULTS (time of arrival)

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RESULTS (zenithal angle)

0m R/2~15 m R ~30m

Iron

Carbon

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0m R/2~15 m R ~30m

Proton

Gamma

RESULTS (zenithal angle)

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RESULTS (Azimuthal angle in one detector)

Proton Gamma

Iron Carbon

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NEXT STEPS

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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...

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One dream

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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

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Still a lot of work

Page 22: G Kornakov  E A Smultivariate Analysis

Acknowledgments

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