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Table 3

Parameters of fitted power laws.

Bin JD′ F 100 Model Γ/α1 β2 E break ΔΓ −2Δ(ln   L) Significancea
[JD–2 454 000] (10-6 ph cm-2 s-1) (GeV) 2 − Γ1)

high 1042−1294 1.31  ±  0.02 PL 2.57  ±  0.01 ...
logP 2.74  ±  0.03 0.08  ±  0.01 ... 44.7 6.7σ
SBPL 2.47  ±  0.02 2.94  ±  0.06 1.2  ±  0.2 0.47  ±  0.06 40.5 6.1σ
low 1300−1720 0.24  ±  0.10 PL 2.87  ±  0.05 ...
logP 2.86  ±  0.04 0.09  ±  0.04 ... 9.9 3.3   σ
SBPL 2.70  ±  0.01 3.25  ±  0.10 1.0  ±  0.2 0.55  ±  0.10 11.9 3.3σ
Flare A 1058−1078 1.62  ±  0.07 PL 2.60  ±  0.05 ...
logP 2.82  ±  0.10 0.11  ±  0.04 ... 6.3 2.6σ
SBPL 2.48  ±  0.08 3.11  ±  0.28 1.0  ±  0.2 0.63  ±  0.28 9.8 2.9σ
Flare B 1086−1114 3.15  ±  0.08 PL 2.45  ±  0.03 ...
logP 2.63  ±  0.13 0.12  ±  0.06 ... 29.6 5.1σ
SBPL 2.32  ±  0.02 2.90  ±  0.09 1.2  ±  0.2 0.58  ±  0.09 24.9 4.7σ
Flare C 1140−1150 2.25  ±  0.11 PL 2.45  ±  0.04 ...
logP 2.56  ±  0.09 0.06  ±  0.02 ... 7.3 2.9σ
SBPL 2.37  ±  0.03 2.86  ±  0.08 1.3  ±  0.2 0.49  ±  0.08 9.9 2.9σ
Flare D 1202−1204 3.83  ±  0.32 PL 2.46  ±  0.08 ...
logP 2.74  ±  0.12 0.25  ±  0.06 ... 9.8 3.3σ
SBPL 2.47  ±  0.10 2.99  ±  0.13 1.6  ±  0.2 0.52  ±  0.16 6.3 2.2σ
Flare E 1260−1275 2.38  ±  0.11 PL 2.46  ±  0.02 ...
logP 2.63  ±  0.18 0.09  ±  0.07 ... 7.2 2.7σ
SBPL 2.36  ±  0.05 3.72  ±  0.18 1.9  ±  0.2 1.36  ±  0.18 12.1 3.1σ

Notes. Δ(ln   L) is the difference of the –log(likelihood) value of logP, SBPL with respect to PL.

(a)

We follow Wilks’ theorem to estimate the significance, i.e., twice the difference between the log(likelihood) values for the two spectral models is formally distributed as χ2 with Δn degrees of freedom, where Δn is the difference in the number of degrees of freedom between the two models.

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