Dave Tierney S. McBreen, R. Preece, G. Fitzpatrick and the GBM Team

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.