Can we establish the Vela SNR and its shock-cloud interaction as a possible site where cosmic rays are produced?

For a refresher, check out the last blog post (linked above) and to remind yourself what a cosmic ray is check out this post.

Where do they come from? Where do they go? Where do they come from, cotton-eyed Joe?
Shock-cloud interactions are commonly observed with core collapse supernovae. This is because core collapse supernovae generally occur in dense regions of space as these are the most massive stars that explode. The most massive stars run through their lifespans quicker and therefore have less time to leave the dense stellar nursery of gas and dust of which they were born. When they collapse and explode, a violent shockwave bounces from the inert core of the star (now mostly neutrons) and out into space where it will interact with pre-existing matter. Many tracers astrophysicists look for to determine if a supernova shock is interacting with its surroundings include what the light tells us and the shape in each wavelength. Here are some examples (I will link free but non-peer reviewed articles – the accepted peer-reviewed submissions cost $$ if you are not associated to an academic institution unfortunately but these articles should still be close to what they actually published):

  • Look for asymmetries in the shape of the formed supernova remnants. Dents and “break out regions” (i.e. where the shock wave appears to have expanded much farther in one direction than another) can be good indicators of how the surrounding matter is impacting the shock wave expansion. Essentially anything that is not perfectly circular gives you indicators of the density of the ambient material and how it changes in any direction of the supernova remnant. The shape of a supernova remnant can change dramatically by what wavelength you are looking at. The wavelength can also give you different information!
    • Radio: Radio emission is one of the best regimes to identify supernova remnants and classify them. Radio emission is often coupled to the X-ray radiation present and can give information on the electrons responsible for emission in both wavelengths. Radio waves can also map the supernova remnants’ surroundings, showing what pre-existing neutral matter might be lurking in the vicinity of nearby shockwaves. 
    • ​Infrared (IR)​: IR emission can show dust from the surroundings that has been swept up by the supernova remnant shock wave and has been shocked and heated.
    • Optical: Filaments visible in the optical regime can tell you how the shock wave has impacted pre-existing clouds of material. Filaments form when the ambient material is shocked and heated. A really good indicator of a shock-cloud interaction is confirming an optical filament that coincides with a bright X-ray boundary. This is supportive that you have found the position of the shock wave boundary of the remnant and its surroundings, indicating it is pushing up against something.
    • X-ray: This regime alone tells you a lot about the morphology of a supernova remnant and potentially even what type of explosion occurred that gave rise to this emission.  X-rays do a great job of showing you where the shockwave is in space because the material that is swept up, shocked, and heated, will be excited enough to radiate a lot in this regime. Finding those boundaries and comparing across wavelengths can make a more complete picture. 
    • Gamma-ray: Gamma-rays tell you an environment has been disturbed so aggressively, the particles are accelerated to very high energies. Gamma-rays are also the product of cosmic rays interacting with ambient material. Because cosmic rays are observed to be mostly protons or ions, we look for gamma-ray signatures that indicate a high proton population presence and acceleration mechanism.

Tying all of the information from each wavelength together creates a robust picture in order to determine if a shock-cloud is in fact happening. When gamma-ray emission is present as well, this presents the possibility for particles to be efficiently accelerated at the shock-cloud boundary to cosmic ray (CR) energies that then decay to gamma-rays when interacting with their dense surroundings. 


What we want to do next then is understand more about the shock-cloud boundary we have discovered to the west of the Vela SNR. We performed broadband modeling to try to see if we could constrain the gamma-ray models using either 1) leptonic gamma-ray emission (i.e. electrons via nonthermal bremsstrahlung or inverse Compton scattering) or 2) hadronic gamma-ray emission (i.e. proton-proton collisions generating the observed emission) but this is really hard to do, as both particles generate very similar gamma-ray signatures. Unless you have lots of data to confirm if the pion bump can be best fit to the data, it can be hard to rule out either scenario. The pion bump is the gamma-ray signature we look for for hadronic gamma-ray emission. I’ll show you what I mean.

The pion bump is the result of CR protons’ interaction with other ambient, less energetic protons. The protons collide and decay to neutral pions which then decay into gamma-rays. The gamma-ray signature will show up at the rest mass of the decayed neutral pion. On a standard spectral energy distribution (SED) plot, that would be around 200MeV. Here is a really great article discussing observations and modeling looking for the pion bump.


An SED model compared against gamma-ray observations for the SNR W44 adapted from the article linked above (Ackermann, et al. 2013).
Above is the gamma-ray spectrum of the supernova remnant as measured with the Fermi-LAT and AGILE. Purple-blue shaded areas bound by dashed lines show the best-fit broadband model (60 MeV to 2 GeV) and the gray-shaded bands show systematic errors below 2 GeV due mainly to imperfect modeling of the galactic diffuse emission (i.e. background). There is a lot here. Let’s unpack it together.

The first line indicated is showing you the best fit model for the gamma-ray emission, regardless of the particle population, and only dependent on the energy distribution. The data points are taken from two different telescopes 1) Fermi and 2) AGILE, another gamma-ray telescope. The solid purple-blue line models the emission if it were from pion decay (i.e. the pion bump). The dashed purple-blue line corresponds to the electron population generating the observed emission via nonthermal Bremsstrahlung. The dash-dotted line is a modified electron population generating the observed emission via nonthermal Bremsstrahlung. A careful inspection of this plot shows that the data points follow the pion decay model the best, thus confirming that the gamma-ray emission for this supernova remnant is dominated by proton-proton collisions, and hence makes W44 another candidate for fresh CR acceleration. This means the environment is energetic enough to produce their own CRs, as opposed to just boosting up pre-existing CRs that get tangled in the region.

With our SED, things are not so clear. It is shown below and is also discussed in the paper.


Our broadband SED model compared against data from radio (green), X-ray (red), gamma-rays from Fermi (blue), and TeV gamma-rays from HESS (black). Dashed models are for electrons. Solid models are for protons.
The arrows indicate upper limits. This means the data could fall anywhere under the upper limit data points. Therefore, we see, within the uncertainties of all our data for the Vela shock-cloud boundary, anything is possible! So we are not able to gain any insight to the likelihood of fresh CR acceleration occurring here based on SED modeling alone, unfortunately. Note: in both of these images, try to bog down that pion bump at 200MeV. It’s easier to see on our plot since we plot the energy already in MeV. The three solid curves modeling the gamma-ray emission, they all steeply rise beginning at about 200MeV – that’s the pion bump!! 

But it is not a lost cause. There are other things to look for. This requires a deeper investigation into the properties of the shock itself. If we can determine the interaction is relatively new we might be able to say fresh CRs are produced here. However, if the shock has pushed into this cloud for a while, it has probably lost a lot of speed with respect to the rest of the shockwave and thus, loses more opportunity to accelerate particles to CR energies. Ways we can do this are by looking back in the optical and looking for tracers that tell us if the shock has gone radiative.

When a shock has gone radiative, this is when rapid cooling takes place and will dominate with time, sucking energy away from the shock and dispensing it into its surroundings. When rapid cooling starts, elements can “recombine” and will radiate via optical radiation, further instigating the cooling mechanism. The first elements to show up are oxygen, silicon, and nitrogen. Specifically, O [III], Si [II], and N [II]. These are ions of the elements, where the numbers indicate the loss of electrons. For example, oxygen should have 8 electrons (just by looking at the periodic table), but its doubly ionized in O III, which means it only has 6 electrons (and therefore has a positive charge of 2+ because it now has 2 more protons than there are electrons). Therefore, observing the shock location in the optical range where these ions radiate when present will tell us if the shock is radiative, and whether it can freshly produce cosmic rays by itself in the shock-cloud boundary.

So we ask for time on an optical telescope, the Gemini telescope in Chile. It is an 8-meter telescope with spectacular angular resolution so we can probe the shock with sub-arcminute resolution to find radiative tracers. We ask for both imaging and spectroscopy to do a thorough study in this band. We got both! In my next post on this, I will share with you the preliminary findings from the imaging, which are spectacular to look at. Optical astronomers are so lucky – they produce such beautiful, whimsical, and informative images. The spectroscopy, on the other hand, is amazingly hard to reduce. Currently, I have no results from the spectroscopy (that make sense). This should excite you as I have yet to publish any results on these optical images but yet, you will be able to see them here first! 🙂

I have, for the first time, exposed you all to spectral energy distributions (SEDs). These plots may overwhelm you and seem confusing to grasp. This is totally normal and is not obvious to understand why we plot like this. In the future, I will make a post dedicated to SEDs and why we plot data in this way. For now, trust me when I say that we use SEDs as a way to see how the emission is dominated/distributed, just by observing the data by eye. Other methods are not as straight forward.

Quiz! Take it here: ​

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