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Low-Energy Spectral Deviations in a Sample of GBM GRBs. Dave Tierney S. McBreen, R. Preece, G. Fitzpatrick and the GBM Team. DT acknowledges support from SFI under grant No. 09-RFP-AST-2400. Introduction. Band Model Spectral model for fitting prompt GRB emission Consistent across GRBs - PowerPoint PPT Presentation
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Dave TierneyS. McBreen, R. Preece, G. Fitzpatrick and the GBM Team
Low-Energy Spectral Deviationsin a Sample of GBM GRBs
DT acknowledges support from SFI under grant No. 09-RFP-AST-2400
Introduction
Previous WorkAn X-ray excess of greater than 5 sigma above the Band model (~ 5 – 20 keV) was reported for ~14% of an 86 burst sample observed by BATSE (Preece et al 1996).
Band ModelSpectral model for fitting prompt GRB emissionConsistent across GRBsParameterised by , , Epeak
Empirical Model
Additional components using FermiBand+PL Abdo et al. 2009, Ackermann et al. 2010Band+BB Guiriec et al. 2011, McGlynn et al. in prepBand+PL+BB Guiriec et al. in prep,
Fermi – GBM
Key Advantages of GBM over BATSEMuch higher data resolutionSingle detector from 8 – 1000 keV
Sample Selection
GoodIn Sample
Bad Not In Sample
BlockagesFluence > 2x10-5 erg / cm2
10 -1000 keV (Paciesas et al. 2012)
Detector Angle< 60o
Analysing the Sample (Initial)
45 GRBs from the first 2 years
Performed for time-integrated fitting only.
Single Fit
Select all good NaIs
Select at least 1 BGO
Perform a Band fit from 8 keV - 40 MeV
Sum Low-Energy Residuals below15, 20, 25, 30, 50, 100 keV
Select all good NaIs
Select at least 1 BGO
Perform a Band fit from LET* keV - 40 MeV
Extrapolate function downwards to 8 keV
Compare data to extrapolated function
Sum Low-Energy Residuals between 8 keVand the LET
Extrapolated Fit
Analysing the Sample (Extended)
45 GRBs from the first 2 years
Blind search using time-integrated, time-resolved spectral analysis.*LET = Low-Energy Threshold. Selected to be 15, 20, 25, 30, 50 & 100 keV
Some cuts are appliedto the results… Epeak > 100 keVfor LET = 15, 20, 25, 30
Epeak > 300 keV for LET = 50, 100
Alpha_Err < 0.2
Epeak_Err/Epeak < 0.45
Time-Resolved (SN 50)Time-Integrated
Distributions of Low-Energy Residuals
GRB090902B
How to quantify the uncertainty...
Simulations…
Left: Combined distribution of 5 GRBs simulated with perfect Band modelRight: Time-Integrated Data Distribution
Simulations (Perfect Band) Sample Data
How to quantify the uncertainty...
Simulations…Simulations…
GRB080817.161 – No Deviations in the Time-Integrated
GRB090902.462 – Strong Deviations in the Time-Integrated
Distributions (Blue) showing when no deviations are present and a line (Red) showing the deviations in the data.
How to quantify the uncertainty...
Simulations…Simulations…Simulations…
GRB090926.181 – Strong Excess in the Time-Resolved (9 – 10 s)
GRB090424.592 – Strong Deficit in the Time-Resolved (2 – 3 s)
Distributions (Blue) showing when no deviations are present and a line (Red) showing the deviations in the data.
Low-Energy ExcessesGRB090902B - PL (TI) GRB090926A – PL (TR)GRB090323 – BB (TR)
Low-Energy DeficitsGRB090424 – BB (TR) GRB090820 – BB (TR)
Closer Analysis
This method demonstrates the requirement for an extra component without any prior knowledge of the nature of the extra component.
ConclusionsExcesses and Deficits can mean additional components…Excess tend to be an additional component dominant at low energies.Deficits tend to be an additional component dominant between the LET and Epeak, forcing alpha higher.
Systematic blind search shows that low-energy deviations are rarer than previously thought. 2% of my sample compared to 14% from BATSE (Time-Integrated).
Additional components can become washed out with time-integrated spectral fitting. Time-resolved analysis is a must.
There is more spectral curvature in some bursts than expected.This gives hints of extra-components BB, PL, other / new models.