Muon Hunters 2.0

Gamma-Ray Astronomy

Gamma rays are the most energetic radiation in the universe and scientists study them to explore exotic and extreme processes and physical conditions. Objects that emit gamma rays include supernova remnants—the remains of stars that exploded at the end of their life; active galactic nuclei—supermassive black holes at the centers of galaxies that are accreting matter to produce jets thousands of light years long; and potentially even dark matter—an unidentified type of matter comprising approximately 27% of the mass and energy in the observable universe. In fact, gamma rays offer the only direct probe of the extreme conditions in these exciting phenomena.

About VERITAS

VERITAS is an array of four telescopes designed to detect the very highest energy gamma rays (>1x10^11 eV, or 100,000,000,000 eV), which are roughly equivalent to the energy of a small fly in flight carried by a single photon, through their interaction with the Earth's atmosphere. The gamma rays produce a shower of particles that travel through the atmosphere, emitting Cherenkov light which is then detected by the array’s 12-m telescopes.
For more about VERITAS and the science we do see our website or follow us on facebook or Twitter @veritasgammaray.

How does VERITAS work?

VERITAS detects the light induced by gamma ray showers as they pass through the Earth's atmosphere and, a bit like a sonic boom, they induce blue/UV light, or Cherenkov light, named for Pavel Cherenkov, who first detected it experimentally. Each telescope uses large mirrors to collect this faint, short flash of light and focus it onto a camera made up of 499 photo-multiplier tubes, which forms the pixels you see in the images you are identifying. VERITAS uses a very fast camera and electronics to record this light whilst minimizing other recorded light from stars, the moon, air glow, nearby light sources, etc. What we are showing in the images in the color scale is how much light we are detecting from the shower relative to the background light from other sources, with reds indicating a strong signal and blues a weak one. If the level of signal light to background light is small, then we have set the scale to zero so it is easier to analyze (both for you and for the computer).

About Muon Hunters 2: Return of the Ring

As well as showers produced by gamma rays, VERITAS also sees showers produced by cosmic rays that come from high-energy particles such as protons and electrons. These provide a background of showers above which we have to detect gamma rays. Think of trying to pick out the light of a candle, at 500m, on a bright day—not easy! Fortunately, these cosmic showers look different in our cameras and we can tell them apart, allowing us to only select showers that look like they were produced by gamma rays. This makes the problem more like picking out the light from a candle at 500m at night - this is still not easy, but it is possible.

Sometimes these cosmic-ray showers produce muons—think of them as the electron's heavier cousin— as they pass through Earth's atmosphere. Muons produce distinctive ring-shaped images in our cameras. If we get a good image of a ring it can be very useful for us. The diameter of the ring and how bright it appears are related, so by detecting lots of rings we can use them to check that our telescopes are working properly. If muon rings all appear brighter or dimmer than they should for their diameter then we know that something is wrong!

Unfortunately, while muon rings can be helpful, not all rings are good.
If we capture only the edge of a ring in the camera then it can look like a long ellipse of pixels, the shape we are looking for to detect gamma-ray showers. The computer finds it very difficult to tell the difference between a small part of a ring and a complete ellipse. This is where you come in. By identifying these partial rings you help us to reduce our background and also provide us with more images to use in calibrating our telescopes.

What’s New in Muon Hunters 2

In a previous version of Muon Hunters the aim was to use the project images that you identified to better train our algorithms and improve our ability to tell the different image types apart. In this version we want to do the same, but this time we have employed a machine learning algorithm which has learned to identify images that it "thinks" are similar, without being told if the image contains a muon or not. This technique, known as unsupervised learning, generates clusters of images with similar qualities, allowing us to sample the clusters and randomly select images into a 6x6 grid. But, the machine is still learning, and it needs humans to give its clusters meaning.
We need your help to tell how well the machine is doing and give us feedback to help it do better. Because each grid should have like images, you ideally should be able to quickly classify the types of showers you see. But, be careful! Because the machine is still learning, sometimes muons may be clustered with non-muons and vice-versa. Once you have provided your labels for a grid, we will use those to retrain the machine.
A side note: Although we're looking for clusters of muons and non-muons, it is entirely possible that the machine may have found a cluster of images that have some as-yet unknown physical significance. As you classify the grids, keep your eyes open for grids that have unusual properties shared amongst the images and tell us about them on Talk. The machines still can't do that! Another side note: some of the images we have used are derived from simulated air showers. We use these simulations in our research often to give us the "answer in the back of the book" - whether an image is a muon or non-muon. Why can't we just use simulated images to do the work we're asking you to do? As with any simulation, it is only as good as our knowledge of physics - and we have reason to believe that our knowledge of physics could be incomplete when it comes to the particle physics that gives rise to high energy air shower interactions. If the properties of the labels you provide for the simulated images differ from those for the real data, who knows, but one of the outcomes of this project could lead to a better understanding of high energy physics. So - it is important for you to try not to think about the fact that there are simulated images here, but to just try your best at deciding whether an image is a muon or not.

What causes the differences in the muon images

Three parameters dictate the differences between the different muon images you see.

1. Direction of the muon relative to the telescope pointing.

If a muon impacts at an angle relative to the pointing of the telescope then the position of the ring in the camera moves. This is how truncated rings form when the edge of the ring moves outside the field of view of the VERITAS cameras.

2. Position of the impact position relative to the telescope centerline.

Muons impacting at a distance offset from the telescopes’ centerline result in images that are brighter on one side than on the other. This is how partial rings form where the fainter side is too weak to be seen by the VERITAS cameras.

3. Energy of the muon.

More energetic muons produce brighter images with larger radii. This relationship between the total signal measured in the ring (the brightness) and the size of the ring are well-understood.

By using all three of these relationships we can look at any changes in the relationship between image brightness and ring size. This is what we use to check that the telescopes are operating as we would expect. The following figure shows how the average charge of the muons (how bright they are) varies over an observing season for one of our telescopes. As you can see, over time the average charge drops; we expect this to happen and account for it in our work. The jump in the charge that you see in April is because we replaced some mirrors, these new mirrors reflect more light—the mirrors are in the open desert giving them a gentle sandblasting over time and degrading their performance—and give us a stronger signal. Understanding these changes is where your work comes in. With more muons we can see more detail, allowing us to better study what is going on in our telescopes.