Trying to understand the physical emission processes occurring in gamma-ray burst (GRB) prompt emission has been and still is a tumultuous story. Unlike many high-energy astrophysical sources, GRBs happen once, and give us typically a few seconds of emission. Moreover, the instruments we use to examine them require a lot of mathematical gymnastics to get the data into a format we can use. On top of all of this, whatever is producing this emission is likely happening at the very extremes of the physics we study in other sources. A jet is launched from a cataclysmic stellar event; the death of a massive star. The forces of this death push the jet to speeds that are just shy of the the speed of light, magnetic fields twist, turn and possibly reconnect, electrons are kicked into high velocities, radiate, interact, surf on turbulence… in a word, completely freak out. All of this results in a brief flash of gamma-rays, distributed in a spectrum that we have to use to “infer” which, if any of these, processes were at work. Imagine that this is like looking at Earth from a distant star and with only the blue light observed in a telescope trying to understand the current political climate.
So naturally, one of the first approaches to deciphering these signals is to simply try to and get the best shape of the spectrum that we observe with our gamma-ray telescopes. Simple enough? Well, gamma-ray spectrometers (the instruments we use to measure the distribution of energy in a gamma-ray spectrum) have a bit of a problem. Since we cannot use filters for the different energies to count the amount of light at different energies as would be done for visible light, the detectors we often use, scintillators, imprint their characteristics on the observed data. Remember all of those processes occurring in the GRB jet itself? Nearly as many occur in the detectors as they measure the incoming gamma-rays. Thus, we have to use something called a detector response which maps the true incoming shape of the spectrum into the shape we see in the data after the photons are absorbed in the detector. The figure below illustrates this process. The problem is we cannot invert this response. Meaning, we cannot take the data and push or fold it back through the response as see what the shape of the gamma-ray spectrum looks like. Instead, we have to make an educated guess about the shape, fold it through the response producing a shape that now has the detector imprinted upon it, and compare that (with rigorous statistical methods) to the data we observed. If we iterate this a few times, we will find a shape that looks a lot like our data! Eureka! We found it! Well… almost.
An easy shape to start with is a mathematical function that has no connection to physics. An empirical function that can bend if you change its parameters just enough to closely resemble the data can be used to fit the data. You can then ask what properties of this empirical shape match closely enough to the shapes produced by actual physical processes. This is how GRB research proceeded for the last 30 years. Two of the main emission models considered were optically-thin synchrotron (discussed below) and photospheric emission, emission coming from a hot fireball dumping all of its energy when the gas in the jet becomes thin enough to see through. By fitting empirical shapes to the data, researchers could use the assumptions about the asymptotic physical shapes of the emission processes to determine which one was producing the observed emission. This led to a conclusion that synchrotron was likely not producing the emission because these empirical shapes did not match what was expected of synchrotron.
Synchrotron emission is produced when relativistic electrons spiral around magnetic field lines. As they produce this emission, they lose energy. In GRB jets, these electrons are shedding the energy given to them via either shocks or magnetic reconnection inside the turbulent outflow. The electrons start off very hot, and then cool via the synchrotron emission. This process leaves very distinct signatures in the shapes of emission spectra that would be observed if it was occurring. However, if synchrotron was ruled out using the empirical shapes, why did we keep looking? The issue is that in the past the process of pushing or folding the empirical shapes through the detector response limits an observer to those empirical shapes. If those shapes are not flexible enough to capture the shape of the physical emission process, then an observer would mistakenly rule out that process. Thus, we decided to write software that would simulate this synchrotron emission from cooling electrons, and then fold that through the detector response directly. Then we could avoid using the empirical shapes and compare these models directly to the data.
After selecting a sample of GRBs with measured distances and with simple temporal profiles, our visiting master student, Ana Bacelj reduced all the data into a form that we could use to perform a giant analysis on lots of data in one go. Then we used Bayesian analysis via a tool we helped to develop called 3ML to fit nearly 200 observed GRB spectra. While the fits ran for a few weeks on our local cluster “necromancer” (nearly all our computers are named from the Tolkien universe) we came up with ways to use the results from these fits to tell us something deeper about the jets we observed *if* the fits worked. These calculations were done during the hot Munich summer, and many of them were performed as Damien and I enjoyed the local beautiful beer gardens. Once the fits completed, we were surprised to find that only a handful were not compatible with synchrotron. Many that were successful would have been ruled out via an analysis of empirical shapes as was done in the past! This was an extremely exciting moment, and the work in the paper proceeded from there. Even though the data from all of these GRBs appear consistent with synchrotron, this raises many more questions. We still do not know how so much energy can be squeezed out of a dying star in so little time that it can outshine the rest of the Universe in gamma-rays from such vast distances. These are the questions we will explore in the next few years.
An important thing about the work is that it only tests one model. Since these models can take a long time to calculate on a computer, we are just at the beginning of a new age in the study of GRB spectra. We need to test more models. We also explored some fun and rigorous data analysis techniques which helped our results to be robust and we hope that these techniques serve as inspiration for future research. All of the work was made possible by an engaged group of researchers interested in understanding what is in our data.