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Analysis of GRBs KONUS/Wind Spectra from 2002 to 2004 : The correlation R-H ?. Gamma Ray Bursts & Neutron Stars March 30 - April 4, 2009 Cairo & Alexandria, Egypt. Mourad FOUKA CRAAG, Algiers Observatory, Algeria. ► Model of fit : PLE+PL ► Results and discussion:

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slide1

Analysis of GRBs KONUS/Wind Spectra from 2002 to 2004 :

The correlation R-H ?

Gamma Ray Bursts & Neutron Stars

March 30 - April 4, 2009

Cairo & Alexandria, Egypt

Mourad FOUKA

CRAAG, Algiers Observatory, Algeria

slide2

► Model of fit : PLE+PL

► Results and discussion:

● Distribution of spectral parameters

● Correlations:

□Epeak -H

□Ftotal - H

□ Correlation R – H ? how to interpret it ?

► SSC model and the high energy range ?

► Unified model for Konus spectra: SSC (internal)+IC (external)

slide3

Models of fits

First question: why this increasing shape in Konus spectra, in terms of E2N(E)for high energy range ?

PLE

PL

slide4

Pure Synchrotron model

Baring & Braby Apj 2004

Tavani (1996) electron distribution:

Thermal

Non Thermal

slide5

Baring & Braby Apj 2004

Pure Inverse Compton model

For external monoenergetic soft photons

Both pure Synchrotron and Inverse Compton models can’t explain the increasing part in E2N(E) of Konus-Wind spectra, even with two components for electron distribution ne(E) = NT+TH.

slide6

354 GRBs KONUS-Wind spectra for the years 2002, 2003 and 2004 are analyzed.

Model of fits

The sum of two components

i) PLE component, dominant at low energies

ii) a PL component, dominant at high energies

slide7

The spectra are presented and fitted in terms of S(E):

We put

1st Step

► It becomes very easy to fit the data in term of

to have a linear problem.

► In first time we consider a limit energy EL for the low energy range to fit only by using the PLE component. We can write:

slide9

► The problem become linear, and we have

and for functions we have

The function

slide10

where is the weight of the ith point, given by

We finally obtain the linear system

2nd Step

►After having the parameters we introduce the PL component:

►We consider the data:

slide11

As for the 1st step we can have

Where

and

3rd Step

► For this step we refine our parameters to minimize the . We define:

► We omit the points whose .

► We continue as for the 1st step

slide12

♦ The final result depend on the value of the energy EL.

♦ we repeat this procedure for many values of the energy ELin some range of low energies 

Results and discussion

For a sample of 354 GRB we find:

►6 XRFs (1.7%)(bad statistics)

►214 XRRs (60.5%) 26.1% with

►134 GRBs (37.8%) 36.1% with

?

Why not all GRBs with

slide13

(Low energy index)

(Epeak of E2N(E))

Lac because of the range of Konus spectrometers: 13.12 keV – 9.17 MeV

slide15

Class distributions

It’s interesting to present the parameter distributions for each class of gamma-ray bursts to more investigate results and to show if they exist important differences between the three classes.

For

▶ GRBs: 26.1%

▶ XRRs: 36.1%

▶ XRFs: (bad statistics)

Two remarks:

1. GRB% < XRR% for:

2. Values of alpha around zero

slide16

Now, Lets focusing on bursts whose

For Konus spectra 13.12 keV < EKONUS < 9.17 MeV

Lac of data

Two suggested interpretations:

1. Determinations of slop alpha depends on the range 13.12 keV < E < Epeak,

i.e. when Ep is close to 13.12 keV, the value of index-alpha is more uncertain.

slide17

2. Contribution of Inverse Compton for external soft photons ( ):

around zero for low Epeak values

Need of soft GRBs

Lac of data

Final GRB spectrum

=

Inverse Compton for soft external photons

+

GRBs internal photons

slide19

Dispersion in Log(Ep)-Log(H)

It’s interesting to remark and evaluate the dispersion for data:

Is this dispersion a property of Konus spectra or a property of GRBs ?

slide20

Correlation Log(Ftotal)-Log(H)

But a true correlation may be between Esource (intrinsic energy of the source) and hardness H.

But : 3 problems:

1. Redshift z not measured for all GRBs !

2. Need of true cosmological model to calculate DL(z)

3. Need of jet angle

►Apparent correlation Log(Ftotal)-Log(H)

slide21

An apparent correlation R-H:

We defined the parameter R as the ratio of the PLE fluency FPLE (the low energy range) to the PL fluency FPL(high energy range):

► The Figure show an apparent correlation between the ratio R ( defined here) and the hardness H.

slide22

►This apparent correlation can be easily explained:

In fact,In the commoving frame of GRB jet, as the initial flash is rich on soft synchrotron photons (low H=Fgamma /FX), the inverse Compton scattering is efficient (large SigmaIC). So that, as the jet is reach on hard synchrotron photons (large H=Fgamma /FX), the inverse Compton fluency FIC is much lower than the synchrotron fluency FSy R=FSy /FIC  large. As a consequence the more hard GRBs (large H) are more reach on synchrotron photons than inverse Compton ones (large R) .

Finally

We can conclude that correlation R-H, revealed here, give a direct proof of contribution of Inverse Compton mechanism in GRB’s jets  this favorite the SSC (Synchrotron-Self Compton) mechanism ?

SSC with NT + TH electrons

The high energy part can be interpreted by an SSC Thermal term

slide23

Unified model for all Konus wind spectra may be:

Final GRB spectrum

=

Inverse Compton for soft external photons

+

GRBs internal photons in the SSC model with NT+TH electrons

And, Synchrotron self-absorption can also be involved for low energy photon energies if data are available.

slide28

Thank you for your attention

CRAAG, Algiers Observatory, Algeria

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