Blog

I occasionally have things to say.

  • Handling X-ray FITS files and Forward Folding

    In high-energy astronomy/astrophysics, we are often performing the task of fitting model photon spectra to counts data. I put emphasis on photon and counts because these terms represent two very different things that often get confused or interchanged with one another. Astrophysical sources emit photon fluxes. A quick refresher in Rybiki and Lightman reminds us that a differential photon flux has units photons/s/cm2/keV. While an x-ray instrument measures this photon flux, it gets converted into an electronic signal and recorded as a count rate (counts/s/PHA channel).

  • Spectral Width of Gamma ray Bursts

    The spectral width and sharpness of unfolded, observed GRB spectra have been presented as a new tool to infer physical properties about GRB emission via spectral fitting of empirical models. Following the tradition of the ‘line-of-death’, the spectral width has been used to rule out synchrotron emission in a majority of GRBs. This claim is investigated via examination of both cataloged GRB spectra as well as reanalyzed spectra leading to the introduction of another empirical characterization of the spectra: the data width. This new auxiliary quantity is a direct measure of the folded data’s width. Examination of the distribution of data widths suggests that a large fraction of GRBs can be consistent with synchrotron emission. To assess this prediction, a sample of peak-flux GRB spectra are fit with an idealized, physical synchrotron model. It is found that many spectra can be adequately fit by this model even when the width measures would reject it. Thus, the results advocate for fitting a physical model to be the sole tool for testing that model.

  • COIN Residence Program 4

    I will participate in this year’s COIN residence program to work with other astronomers/astrostatisticians to develop new tools and methods (hopefully for gamma-ray spectroscopy). The Cosmostatistics Initiative (COIN), an international group built under the auspices of the International Astrostatistics Association (IAA), aims to create an interdisciplinary environment where collaborations between astronomers, statisticians and machine learning experts can flourish.

  • BALROG

    The accurate spatial location of gamma-ray bursts (GRBs) is crucial for both producing a detector response matrix (DRM) and follow-up observations by other instruments. The Fermi Gamma-ray Burst Monitor (GBM) has the largest field of view (FOV) for detecting GRBs as it views the entire unocculted sky, but as a non-imaging instrument it relies on the relative count rates observed in each of its 14 detectors to localize transients. Improving its ability to accurately locate GRBs and other transients is vital to the paradigm of multi-messenger astronomy, including the electromagnetic follow-up of gravitational wave signals. Here we present the BAyesian Location Reconstruction Of GRBs ({\tt BALROG}) method for localizing and characterising GBM transients. Our approach eliminates the systematics of previous approaches by simultaneously fitting for the location and spectrum of a source. It also correctly incorporates the uncertainties in the location of a transient into the spectral parameters and produces reliable positional uncertainties for both well-localized sources and those for which the GBM data cannot effectively constrain the position. While computationally expensive, {\tt BALROG} can be implemented to enable quick follow-up of all GBM transient signals. Also, we identify possible response problems that require attention as well as caution when using standard, public GBM DRMs. Finally, we examine the effects of including the variance in location on the spectral parameters of GRB 080916C. We find that spectral parameters change and no extra components are required when these effects are included in contrast to when we use a fixed location. This finding has the potential to alter both the GRB spectral catalogs as well as the reported spectral composition of some well-known GRBs.