Energy [keV]
Chapter 7 Conclusion
B.2 High Energy Extension of the Spectral Analysis
The mask weight technique in the BAT standard analysis (described in §5.2) makes use of the difference between the count rates at open mask and at close mask. Since the coded aperture mask made of 1 mm lead becomes transparent over 150 keV, the effective area becomes quite small above this energy. To utilize the events in higher energy band, we just use the count rates without the mask decoding. In this case, we extract spectra for foreground and background from different time domains, to perform the background subtraction. This method does not lose the events above 150 keV. However, since the photons coming from the source hit the spacecraft and produce a large amount of scat-tering component, it is required to create a response with high fidelity mass model. We realize this by the SwiMM simulation.
Here we demonstrate the method using GRB 041223 data. For this event, the best fit to the spectrum is provided by the cut-off power law model, but Epeakobs is not constrained
Figure B.1: The Swift Mass Model, containing most of all the components in the spacecraft. The coded aperture mask is not drawn in this figure to show the CdZnTe detector array.
very well (364.0+572.6−121.6 keV). The spectra for foreground and background are subtracted from the time domains shown in Fig. B.2. The response is produced by the simulation for the GRB direction. The spectral fit is performed jointly between the mask weight method and the SwiMM, giving the better constraint as Epeakobs = 371.1+66.6−48.2 keV. This is consistent with Konus results of Epeakobs = 332+28−26 keV.
MET Time - 125503577.3 [sec]
-300 -200 -100 0 100 200 300
Rate [cnts/sec]
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 22000 24000
GRB 041223
foreground background
Figure B.2: The light curve of GRB 041223 before the background subtraction.
The foreground and background time interval used in the SwiMM analysis is shown.
10−5 10−4 10−3
normalized counts s−1 keV−1
GRB 041223
100
20 50 200
−2 0 2
∆Sχ2
Energy (keV)
Figure B.3: The joint spectral analysis of GRB 041223 using mask weight technique and SwiMM. The data indicated by black and red are the spectra extracted by the mask weight method and that extracted by the time domain background subtraction method.
100
20 50 200
10 100
5 20 50
keV2 (Photons cm−2 s−1 keV−1)
Energy (keV) Unfolded Model
Figure B.4: The same spectra with Fig. B.3 in νFν representation. The fit extended to 350 keV in conjunction with the SwiMM Monte Carlo method provides better finding of Epeakobs .
Appendix C
Afterglow Temporal and Spectral indices for the previous GRBs
Fig. C.1 shows an α−β (temporal and spectral indices) relation derived for the previous GRBs with jet break features in their optical afterglows. We used temporal indices listed in Ghirlanda et al. (2004a) and spectral indices analyzed by Panaitescu (2006). The sample is limited to six bursts because we just picked up bursts where both indices are available before and after jet break from these two papers. Please note that it is not certain that these two papers used the same numbers for the jet break time. Before jet break, the bursts have relations consistent with the theoretical predictions. Some bursts also satisfy the relation after jet break, though the data are somewhat scattered. Please compare it with the α − β relation which we derived from X-ray afterglows of three Swift GRBs (Fig. 6.9).
(spectral index) β
-2.5 -2 -1.5 -1 -0.5 0 0.5
(temporal index)α
-2.5 -2 -1.5 -1 -0.5
0
a. 990123 b. 990510 c. 991216 d. 010222 e. 020813 f. 030226
a b c d e f
a
b c d
e
f νc
ν<
<m
ν
before Jet break, νc
ν>
before Jet break,
νc
ν<
<m
ν
after Jet break, νc
ν>
after Jet break,
Figure C.1: The temporal index α as a function of the spectral index β (=
I+ 1) for the previous GRBs with jet break. The indices are derived from their optical afterglows. The open marks are for an epoch before the jet break, while the closed marks are for an epoch after the break.
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Acknowledgments
I am deeply grateful to Prof. Tadayuki Takahashi for his continuous guidance over the six years of my graduate course. In the earlier days I had a lot of opportunities to be trained by him through experiments performed at the ISAS/JAXA laboratory. Those were indispensable days to learn a lot in his way of pursuing something hidden based on physics. I believe those experiences led me to the accomplishment of this thesis.
I would like to thank very much Dr. Kazuhiro Nakazawa, Dr. Shin Watanabe and Prof. Makoto Tashiro for their support at every time and everywhere. They repeatedly visited NASA/GSFC (Goddard Space Flight Center) and gave me useful advice. I greatly appreciate the support of Dr. Hideki Ozawa, who visited and stayed at the Goddard prior to me and started the hard work under the Japan-US collaboration for theSwiftmission.
I would express my thank to Dr. Masahiko Sugiho for his help on coding the spectral model. I am also grateful to Mr. Manabu Kouda, who was sadly taken away from us too early. He was not only a good friend of mine but also a very good rival to me.
Studying about X-ray and gamma-ray detectors/astrophysics, we sometimes taught and encouraged each other.
I also appreciate the decision of Prof. T. Takahashi to send young graduate students including me to NASA/GSFC, where it is not easy to survive without struggling very hard. I clearly remember precious words of advice from Dr. Scott Barthelmy, the BAT team lead: “This is not a school but a factory!” The Goddard people did not regard us as beginners, but were willing to work with us on equal terms, and required us to work at a professional level instead. Dr. Ann Parsons took the lead of the detector response work.
It would have been impossible for us to accomplish the work without her perseverance.
I don’t know how to express my thanks to Dr. S. Barthelmy, Dr. A. Parsons, and all the BAT team members for their support during my stay for one and half years in total. I am much obliged to Dr. Neil Gehrels, the SwiftPI (Principal Investigator), for providing me the opportunity to carry out the research for this thesis.
I thank Dr. Derek Hullinger, who has been working on the BAT instrument and obtained a Ph. D. at almost the same time with me. I admire his abilities of accurate calculation and careful thinking. Discussion with him was always valuable. I thank deeply Dr. Yu Okada, Dr. Hiromitsu Takahashi, Dr. Masaya Suzuki, and Dr. Takefumi Mitani, who also stayed at Goddard and spent those exciting days together with me. I wish to acknowledge their intensive work on the energy calibration and the development of the