Supernova Burst Movies

3D Movie depicts what the data would look like if you could see the events happening while looking into the detector.

Unrolled view movie shows the same data, but unrolled to make it easier to analyze and with some graphs showing collected data on the sides.

The final versions of these movies are by Cully Little; they incorporate work by Steve Farrell and Ben Reed. The 3D movie makes use of the tscan event display (primary author Tomasz Barsczak) and both have made use of Super-K collaboration software tools. These movies show what the Super-K detector sees, a large number of little blips on its radar. The way it sees these is not by seeing the actual neutrinos themselves, but instead by seeing events happen because of a neutrino. Basically, if something happens within the detector, Super-K is able to detect it. What you're seeing in the movies are every single event that it detects, which can then be broken down into data and observed later on.

The layout of Super-K, showing how far underground it is and what the actual detector looks like.

In a relevant context, if Super-K were to think that a neutrino burst from a supernova was happening, it'd be because there would be a sharp increase in the number of events taking place. Something similar to this (most detectors have different looks or set-ups but ultimately get similar results) would appear in other detectors as well, with the actual size of the burst depending on how big the detector actually is. At this point they all automatically send out an alert, and if enough alerts are recieved, SNEWS sends out the alert to let people know a supernova is coming.

The events that it is seeing however are primarily those of anti-electron neutrinos, a specific flavor of neutrino, but what you're seeing in the movies is only about a third of what would be expected if all flavors were detected, since the others are detected via a less probable reaction, compared to the main one. A flavor doesn't specifically mean that one tastes different from another, it is more just a placeholder word to let poeple know that there are different types. The three types are electron, muon, and tau neutrinos, all of which have different attributes and characteristics. However, it was discovered that these three flavors can oscillate between one or another type quite frequently. The 2015 Nobel Prize in Physics was awarded for this discovery, which explained why detectors were seeing one third of the neutrinos that physicists were predicting would be seen from the Sun since they could primarily only see the electron neutrino.

If you look carefully you can also see little rings on the detector occasionally forming, this is due to an effect called Cherenkov radiation. The pixels in the rings are each a "photomultipler tube" which produced an electrical signal when hit by light caused by a particle zipping off through the water after being knocked loose by an incoming neutrino. The easiest way to think of this effect is by looking at a boat on the water. As your boat passes through water, it makes ripples in the water due to the boat itself passing through, if you are moving this creates a doppler effect in the water, but what happens if you're moving faster than the waves you are creating? This causes the waves to get run over as soon as they are created, and forces them all to get heavily piled up, often getting pushed to the side, this creates the effect of a wake. This same process is taking place with these electrons, and while they aren't going faster than the universal constant c, light only moves about .75c in water, this means that if you accelerate an electron past that .75c, it will causes a "wake" of light, which then builds up and hits the detector as the rings that you can see if you pause at the right time.

Neutrino Count
A count of neutrinos, showing the two different ways of detecting, and how many times each are being seen.

You may also notice on the graphs of the unrolled view there is a neutrino count, an energy graph, and a neutrino direction. Let's first explain the neutrino count, on which there are two colors of bars, the first, larger one, is the electrons that Super-K is detecting due to electron neutrinos hitting a proton, causing it to form together with it, creating a neutron, also in the reaction a positron is released, which is what Super-K is detecting, using the same method that they see electrons. This is the primary way that these neutrinos are detected, as evidenced by the much larger amount of them seen. The other way they see them is by a neutrino ramming into an electron, this neutrino can be any flavor, however, the reaction itself won't tell us anything about the flavor, since this is essentially just a momentum transfer, which doesn't rely on flavor at all. This is the smaller blue bar that you are seeing, which occurs much less mainly because the target that the neutrino has to hit for the first reaction is much larger than the one it hits for the second one.

Neutrino Direction
A graph showing the infered direction of the neutrino based on the information from the particles the detector sees.

This also ties into the neutrino direction graph, which can give you a decent idea of where a group of neutrinos may be coming from. The majority of that graph is near useless, since the primary reaction that Super-K is detecting gives us almost no information as to it's direction, since the positron comes rocketing out in a near random direction. The reason you are seeing that slightly darker spot though is due to the fact that the secondary reaction gives us a lot of information about where it came from, since it it essentially a collision problem, which is fairly easy to figure out how the neutrino must have hit the electron to move it in such a direction. The final graph on energy is essentially just showing the energies of the detected particles as they get seen by the detector.

See a supernova burst movie in 3D in the DiVE. This shows what it would look like to stand inside the detector (a much smaller version of it) while a burst is hitting using Duke University's virtual reality room.