RECONSTRUCTION OF EXTENSIVE AIR SHOWERS FROM SPACE
Download
1 / 24

P ierre Colin Dmitry Naumov Patrick Nedelec - PowerPoint PPT Presentation


  • 75 Views
  • Uploaded on

RECONSTRUCTION OF EXTENSIVE AIR SHOWERS FROM SPACE. Stand alone method using only EAS induced light . General algorithms for any space project. ( EUSO, OWL, TUS, KLYPVE… ). P ierre Colin Dmitry Naumov Patrick Nedelec. Physics hopes. Purpose : Reconstruct initial UHECR parameters.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'P ierre Colin Dmitry Naumov Patrick Nedelec' - konala


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

RECONSTRUCTION OF EXTENSIVE AIR SHOWERS FROM SPACE

  • Stand alone method using only EAS induced light.

  • General algorithms for any space project.

  • ( EUSO, OWL, TUS, KLYPVE… )

Pierre Colin

Dmitry Naumov

Patrick Nedelec


Physics hopes

Purpose: Reconstruct initial UHECR parameters

Energy (spectrum)

Direction (UHECR sources map)

Particle type

(proton, iron, neutrino, gamma, etc.)

?


Shower parameters

UHECR :

Angles (Zenithal θ and Azimuthal φ)

Altitude of shower maximum: Hmax

Depth of shower maximum: Xmax

Total energy released E

E

Xmax

Hmax


Detection from space
Detection from space

EUSO simulation

Extensive air shower

Air fluorescence (isotropic)

Cerenkov light

(directional)

Ground scattering

Space telescope

SIGNAL = f(t)

UHECR

Cerenkov

echo

Fluorescence

Cloud


Data fit
Data fit

Available information: for every GTU (Time Unit ~2.5 µs)

Number of detected photons: Ni

fit: 2 Gaussians: Fluorescence + Cerenkov

+ constant: Background noise

  • Monte Carlo data

  • - Global fitFluorescence Cerenkov Background


Key parameter

Golden event

Need Cerenkov echo

Fluorescence event

Only signal shape

TWO METHODS

Monte Carlo Data

Signal analysis (Trigger conditions): 3 samples of events

Fluorescence events

Golden events (Fluo+Cer)

Cerenkov events

Reconstruction


z

EUSO

R

α

Fluorescence

ΔH = Hmax - Hcer

ΔH

y

Cerenkov echo

x

ΔH

Hmax = ΔH + Hcer

  • Disadvantage:

  • We need to know Hcer to reconstruct Hmax

    • : Relief, Cloud altitude (Lidar?)

Hmax reconstruction : Cerenkov method

(Classical method)

For golden events :

We use Cerenkov echo

: Time between Cerenkov and fluorescence maximum


Hmax reconstruction : Cerenkov method

Test of the method: no cloud events (Hcer = 0 )

Reconstructed Hmax vs Simulated Hmax

Relative Erreur

Error<10% for <60°

  • Method not efficient for large  angle (horizontal EAS)


In one GTU i: Li = LGTU

Ni η·Y·Ne·LGTU

= # detected ph/GTU

Transmission η has also a smooth variation with altitude

Niis quite independent of the altitude: Ni Ne

Nmax (η·Y)max·Nemax·LGTU

Hmax reconstruction : Shape method

(Brand new method)

For Fluorescence event:

We use only Fluo signal

= # emitted photon

L= EAS track length

Fluorescence Yield (ph/m)

Ne = # charged particles in EAS

Y = Fluorescence Light Yield

Y: smooth variation with altitude


Hmax reconstruction : Shape method

For horizontal showers:

Total shower lenght: L =  LGTU = xtot / (h)

L20=100 km

5 km

20 km

Xtot = L·(h)

L5 = 15 km

Ntot =  Ni  η·Y·< Ne>·L  η·Y·<Ne>· xtot / (h)

Ntot varies dramatically with altitude:


Hmax reconstruction : Shape method

Generalization for all  angles :

Thanks to η & Y smooth variation with altitude

Approximation:

<η·Y·Ne>= (η·Y)max·< Ne>

< (h) > = (Hmax)

Varies like ln(E)

Nmax/Ntot  (Hmax)

(Hmax)

Hmax


Hmax reconstruction : Shape method

Test of the method:

Reconstructed vs Simulated Hmax

Relative Erreur

Error<10% for >60°

Good Method to reconstruct large  angle EAS !


Direction reconstruction :

Available information: for every GTU

Photon incident angles: ix, iy

There is relationship between (ix,iy) and (θ,φ) angle of EAS.

Reconstruct Θ

Reconstruct 

Direction:

σ ~ 2°

Simulated 

Simulated

Assuming infinite pixel resolution


Xmax reconstruction

(reconstructed Xmax – simulated Xmax)(Θ)in g/cm2

Golden events

fluorescence events

Hmax by shape method

Hmax by Cerenkov echo

σ<5% for <50°

σ ~ 10 %


Energyreconstruction

for 1020 eV proton

σ = 22%

E reconstructed by shape method (fluorescence)


Shape method good for uhe neutrinos
Shape method good for UHE neutrinos!

neutrinos

protons

Neutrinos create mainly horizontal EAS without Cerenkov echo.


Conclusion

  • We have developed two complementary methods to reconstruct EAS from space using UV light signal.

  • using Cerenkov echo

  • Efficient for “vertical” showers (<60°)

  • Need complementary information (echo altitude)

  • using only signal shape

  • Efficient for “horizontal” showers (>60°)

  • UHE Neutrino astronomy from space is possible

We can reconstruct any  EAS: 0° to 90° or more !

This first trial is very promising.



Simulated data
Simulated data

Available information:

for every GTU

(Time Unit ~2.5 µs)

Photon incident angles: ix, iy

Number of detected photons: Ni

z

Space telescope

ix, iy EUSO simulation

αy

αx

Extensive air shower

Hmax

y

x


If we add pixel resolution
If we add pixel resolution:

EUSO simulation

EUSO event on focal plan (M36)

Error : more from detector than from method


Xmax reconstruction

SLAST simulation of Xmax(g/cm2)

Xmax change with RCUE type:

Xmax = f(E/A)

(E/A is energy by nucleon)

Iron

proton

Test with 10 000 protons and 10 000 iron nuclei

Xmaxfor fluorescence events

Xmaxfor Golden events


Energyreconstruction

Y : Fluorescence yield (ph/m)

Kakimoto Model

η : Atmosphere transmission

Lowtran Model

ε : Detector efficiency

ΔΩ : Detector solid angle


Energyreconstruction


Detection from space1
Detection from space

EUSO simulation

SIGNAL = f(t)

Extensive air shower

Air fluorescence (isotropic)

Cerenkov light

(directional)

Air scattering

Ground scattering

Space telescope

UHECR

Cloud


ad