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Correlations between Lag, Duration, Peak Luminosity, Hardness, and Asymmetry in Long GRB Pulses

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Title: Correlations between Lag, Duration, Peak Luminosity, Hardness, and Asymmetry in Long GRB Pulses


1
Correlations between Lag, Duration, Peak
Luminosity, Hardness, and Asymmetry in Long GRB
Pulses
  • Jon Hakkila1 and Renata S. Cumbee2
  • 1 Dept. Physics and Astronomy, College of
    Charleston
  • 2 Dept. Physics and Astronomy, Francis Marion
    University
  • Acknowledgements
  • Poster evaluation committee
  • Collaborators on various aspects of this project
    over the years Jay Norris, Tim Giblin, Chris
    Fragile, Jerry Bonnell, students Renata Cumbee
    and Mark Wells
  • Collaborators-to-be Tom Loredo, Rob Preece, and
    (hopefully) many others

2
There is a Long History of Studying GRB Pulses
  • Pulses exhibit a rich phenomenology, including
    (1) inherent time asymmetry as characterized by
    longer decay than rise rates, (2) hard-to-soft
    spectral evolution, and (3) broadening at lower
    energies (e.g., Norris et al. 1996, Ramirez-Ruiz
    Fenimore 2000, Norris 2002, Ryde 2005).
  • However, until recently, little work has been
    done on fitting pulses at different energies.

3
Semi-automated code for identifying and fitting
GRB pulses.
  • Bayesian Blocks routine (Scargle 1998)
    identifies potential pulses in 64ms, summed
    4-channel data (BATSE and Swift).
  • Four-parameter pulse model (Norris et al.
    2005) plus background Pulses and background
    simultaneously fit using MPFIT (Markwardt 1998).
  • Dual timescale peak flux (Hakkila et al. 2003)
    used to remove statistically significant pulses
    process is not biased pulse toward being either
    long or short.
  • Pulses obtained from summed data used as
    initial guesses for pulses in individual energy
    channels.

4
RESULTS
  • Database 307 pulses in 106 Long and 46 Short
    GRBs as we move sequentially through the BATSE
    catalog.
  • The energy-independent pulse-finding process
    regularly recovers energy-dependent pulse
    properties.
  • Every pulse has its own lag lag is a pulse
    property rather than a bulk GRB property.
  • It is difficult to unambiguously identify and
    fit low intensity pulses and/or pulses in crowded
    regions.
  • Low fluence events (LFEs) are occasionally
    present and are difficult to fit. They could be
    subpulses or a noise process.

5
Pulse-fitting example GRB 950325a (BATSE 3480)
6
Pulse-fitting example GRB 930123 (BATSE 2600)
7
Results are not always clean GRB 950625 (BATSE
3649)
25 keV - 1 MeV
1
2
3
8
Reulsts are not always clean GRB 060418 (Swift)
10 keV - 300 keV
1
2
9
What does GRB lag measure (as obtained from the
CCF)?
  • GRB 930123 (BATSE 2600)

The CCF lag is dominated by large amplitude,
narrow pulses with short lags. Longer-lag pulses
can smear out this behavior. The GRB peak flux is
not generally the pulse peak flux of the
brightest pulse, due to pulse overlap.
10
The durations of pulses from Long (blue diamonds)
and Short (violet squares) BATSE GRBs are plotted
against their positive lags.
Pulse durations vs. lags demonstrate distribution
of lag uncertainties. Short GRB pulse lags are
consistent with a mean near 0 s, while some Long
GRB pulses have extremely negative lags
consistent with hidden pulse contamination.
11
Pulse with negative lag BATSE 1807 (2nd pulse
lag -4.2 s)
2nd pulse is apparently composed of two fainter
pulses the second of these is harder than the
first.
12
Short GRB pulse peak intensities strongly
correlate with pulse durations Long GRB pulses
only weakly do.
Durations of Long BATSE GRB pulses are plotted
against their asymmetries longer pulses are
typically more asymmetric than shorter ones.
Short GRB pulse asymmetries are difficult to
measure on the 64 ms timescale and are not
plotted.
13
Pulse peak fluxes of pulses from Short (violet
squares) and Long (blue diamonds) BATSE GRBs are
plotted against their durations. Although both
pulse types suggest correlated properties, the
relationship is different, suggesting different
mechanisms and/or origins.
14
Long GRB Pulse Correlations
  • The tables give rank order correlation
    probabilities that the pulse characteristics in
    question are random, with correlations in black
    and anti-correlations in red. A large font
    indicates a stronger correlation, and a bold
    large font indicates a very strong correlation.
  • Since lags and durations of Long GRB pulses are
    indicators of pulse peak luminosities (Hakkila et
    al. 2008), the correlated pulse properties of
    spectral hardness and pulse asymmetry are
    luminosity indicators as well.
  • Although there is some overlap in the observed
    properties of Short GRB and Long GRB pulses, the
    differing luminosities, spectral hardnesses, and
    durations suggest that Short GRB pulses are
    inherently different than Long GRB pulses, and
    that either different mechanisms or different
    environments are involved.
  • The relationships between pulse peak flux, pulse
    duration, and (weakly) spectral hardness of Short
    GRB pulses could be be partially due to distance
    and cosmology (pulses belonging to distant GRBs
    will appear to be fainter, longer, and softer
    than those belonging to nearer GRBs). However,
    Short GRB pulse durations span almost two orders
    of magnitude this is too large to be caused by
    time dilation alone for Short GRBs typically
    found at z 1.

Short GRB Pulse Correlations
15
The redshift z of each pulse can be estimated
from its duration (Hakkila et al. 2008) and from
its luminosity distance DL this is similar to
the technique used for burst lags by Kocevski and
Liang (2006). By averaging these redshifts
together over many pulses, an independent
estimate can be made of the mean burst
redshift where d? is the beaming factor,
f256 is the 256 ms peak flux, and the assumed
cosmology is defined by H0 65 km s-1 Mpc-1, ?m
0.3, and ?? 0.7.
16
The z-distribution of 106 Long BATSE GRBs, with
external errors of ?z 0.7. The distribution
implies that high redshift bursts are rare in the
BATSE catalog in agreement with Ashcraft
Schaefer (2007). In fact, the GRB at z 8 is
very faint with a short, asymmetric pulse and may
not be a Long GRB.
17
Some low-z BATSE bursts
18
Some high-z BATSE bursts
19
Is BATSE GRB 0809 a Short or a Long burst?
  • Consistent with being a Short GRB based on
    duration and spectral hardness.
  • However, overlapping pulses are also consistent
    with pulse width, lag, and luminosity relation
    suggesting a possible redshift of z 2.1 0.7.

20
Conclusions
  • The process of identifying and fitting pulses
    can be complicated, but the results are
    remarkably self-consistent.
  • Pulse properties are central to explaining GRB
    prompt emission, whereas bulk properties turn out
    to be constructed by combining and smearing out
    pulse characteristics in ways that potentially
    lose valuable information.
  • Pulse properties can be used to estimate GRB
    redshifts the results are consistent with
    previous redshift distributions, including burst
    complexity vs. luminosity findings.
  • Work still needs to be done on measuring and
    accounting for pulse spectral characteristics.
    These results will help determine how
    well-defined relationships between pulse
    properties and luminosity are.
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