1. 1 Analysis of GRBs KONUS/Wind Spectra from 2002 to 2004 : The correlation R-H ? Mourad FOUKA CRAAG, Algiers Observatory, Algeria Gamma Ray Bursts & Neutron Stars March 30 - April 4, 2009 Cairo & Alexandria, Egypt

2. 2 ► Model of fit : PLE+PL ► Results and discussion: ● Distribution of spectral parameters ● Correlations: □ E peak -H □ F total - H □ Correlation R – H ? how to interpret it ? ► SSC model and the high energy range ? ► Unified model for Konus spectra: SSC (internal)+IC (external)

3. 3 PLE PL Models of fits First question: why this increasing shape in Konus spectra, in terms of E 2 N(E) for high energy range ?

4. 4 Baring & Braby Apj 2004 Tavani (1996) electron distribution: Thermal Non Thermal Pure Synchrotron model

5. 5 Both pure Synchrotron and Inverse Compton models can’t explain the increasing part in E 2 N(E) of Konus-Wind spectra, even with two components for electron distribution n e (E) = NT+TH. Baring & Braby Apj 2004 Pure Inverse Compton model For external monoenergetic soft photons

6. 6 354 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

7. 7 The spectra are presented and fitted in terms of S(E): We put 1 st 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 E L for the low energy range to fit only by using the PLE component. We can write:

8. 8 ELEL

9. 9 ► The problem become linear, and we have and for functions we have The function

10. 10 where is the weight of the i th point, given by We finally obtain the linear system 2nd Step ► After having the parameters we introduce the PL component: ► We consider the data:

11. 11 As for the 1 st step we can have Where and ► For this step we refine our parameters to minimize the. We define: 3 rd Step ► We omit the points whose. ► We continue as for the 1st step

12. 12 ♦ The final result depend on the value of the energy E L. ♦ we repeat this procedure for many values of the energy E L in 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 ?

13. 13 Lac because of the range of Konus spectrometers: 13.12 keV – 9.17 MeV (Low energy index) (E peak of E 2 N(E))

14. 14 (High energy index) (Hardness)

15. 15 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. ▶ GRBs: 26.1% ▶ XRRs: 36.1% ▶ XRFs: (bad statistics) For Two remarks: 1. GRB% < XRR% for: 2. Values of alpha around zero

16. 16 Now, Lets focusing on bursts whose Lac of data For Konus spectra 13.12 keV < E KONUS < 9.17 MeV  1. Determinations of slop alpha depends on the range 13.12 keV < E < E peak, i.e. when E p is close to 13.12 keV, the value of index-alpha is more uncertain. Two suggested interpretations:

17. 17 Lac of data Need of soft GRBs  2. Contribution of Inverse Compton for external soft photons ( ): around zero for low E peak values Final GRB spectrum = Inverse Compton for soft external photons + GRBs internal photons

18. 18

19. 19 Dispersion in Log(E p )-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 ?

20. 20 Correlation Log(F total )-Log(H) But a true correlation may be between E source (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 D L (z) ► Apparent correlation Log(F total )-Log(H) 3. Need of jet angle

21. 21 An apparent correlation R-H: We defined the parameter R as the ratio of the PLE fluency F PLE (the low energy range) to the PL fluency F PL (high energy range) : ► The Figure show an apparent correlation between the ratio R ( defined here) and the hardness H.

22. 22 ► 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=F gamma /F X ), the inverse Compton scattering is efficient (large Sigma IC ). So that, as the jet is reach on hard synchrotron photons (large H=F gamma /F X ), the inverse Compton fluency F IC is much lower than the synchrotron fluency F Sy  R=F Sy /F IC  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

23. 23 Final GRB spectrum = Unified model for all Konus wind spectra may be: 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.

24. 24 Typical Konus spectrum

25. 25 Some XRFs fits in the PLE+PL model

26. 26 Some XRRs fits in the PLE+PL model

27. 27 Some classical GRBs fits in the PLE+PL model

28. 28 Thank you for your attention CRAAG, Algiers Observatory, Algeria