Searching for the elusive: IceCube observes seven potential tau neutrinos

Researchers at the IceCube Neutrino Observatory in Antarctica have discovered seven signals that may indicate tau neutrinos, which are notoriously difficult to detect from astrophysical objects.

Neutrinos are among the most difficult particles to detect because they have extremely low mass and interact weakly with matter. One of the reasons scientists are interested in these particles is that they can travel long distances, meaning they can preserve information about astrophysical processes and objects that occur far away from us.

The IceCube collaboration aims to study these neutrinos by observing the traces they leave as they interact on a detector or travel through ice.

This study was published in Physical Review Letterswhich details how IceCube observes neutrino signals, seven of which may be tau neutrinos.

The researchers used convolutional neural networks (CNN) to sift through 9.7 years of data collected by Antarctic observatories. Their main challenge was to distinguish the three “flavors” of neutrinos, all of which leave similar signals.

Muons, electrons and tau neutrinos

As the scientific community knows, neutrinos come in three variations, or flavors: electron neutrinos, muon neutrinos, and tau neutrinos. They are the most massive particles in the universe, with 100 trillion particles passing through your body every second!

However, as mentioned earlier, they are notoriously difficult to detect and even harder to distinguish between flavors.

“Isolating neutrinos is particularly challenging compared to other particles because they interact weakly with matter. Tau neutrinos can easily mimic electron neutrinos or muon neutrinos, the other two neutrinos are known, so isolating them is more challenging,” explained the professor. Doug Cowen from Penn State University is one of the study’s co-authors.

The IceCube Neutrino Observatory consists of thousands of optical sensors located under one cubic kilometer of Antarctic ice. When neutrinos pass through the ice on the detector, they leave two types of traces: tracks and waterfalls.

How to spot the difference?

Trails, the most common type of pattern left behind when muon neutrinos collide with ice, are straight lines of photons.

Cascades, on the other hand, are less common. The patterns consist of two spots, or bright spots, of light that result from initial interaction with the ice and subsequent delay into electrons or tau particles.

“The second photosphere produced by the electron neutrino is so close to the first that IceCube sees them as a single sphere. By comparison, the tau neutrino can travel about 10 meters before decaying, producing The IceCube could distinguish the second photosphere from the start,” said Professor Cowan.

The challenge is that the patterns on the detectors look very similar, making them difficult to distinguish. This ambiguity has led researchers to use CNNs to “process the myriad patterns that tau neutrinos can produce,” as Professor Cowen puts it.

CNNs and patterns

“CNNs are designed to differentiate between images, such as a photo of a dog and a photo of a cat, and differentiate between different breeds, different backgrounds, different lighting, etc.,” Professor Cowan explained.

This makes them perfect candidates for sifting through data collected by the IceCube Neutrino Observatory and identifying signals belonging to tau neutrinos.

To train the network, the researchers used simulated data that included various patterns corresponding to tau neutrino interactions and background noise.

In this case, background noise refers to signals that may be caused by other astrophysical sources but have very similar characteristics to tau neutrinos.

By training a CNN on tau neutrino signals and background noise, the researchers aimed to develop a model that could distinguish real tau neutrino signals from other sources.

“With over 100 million trainable parameters, our CNN can extract all tau neutrino needles from the background haystack,” said Professor Cowan.

Seven tau neutrino candidates

The researchers expected to see six tau neutrinos, but ended up seeing seven. This is a continuation of their work in 2013, when IceCube successfully identified hundreds of muon neutrinos and an electron antineutrino coming from a black hole.

Their analysis confirmed that all types of neutrinos behave as expected, even after traveling astronomical distances and extremely high energies, with each of the seven neutrinos having energies of 20 TeV or higher. For reference, 1 TeV is equivalent to the energy of movement of a flying mosquito.

“We can determine that our seven tau neutrinos come from astrophysical sources because neutrino sources on Earth, such as the atmosphere, cannot produce tau neutrinos at this energy scale. Therefore, seven tau neutrinos This provides strong confirmation for IceCube’s 2013 discovery.

The fact that all three neutrino flavors were confirmed is significant. This is because neutrinos are able to switch between different flavors as they travel through space, a phenomenon called neutrino oscillations.

For the first time, researchers have demonstrated that neutrino oscillations occur at such high energies and over such long distances.

Although the researchers are not 100% certain that the seven signals are tau neutrinos, they are confident in their predictions. According to their statistical analysis, there is a 1 in 3.5 million chance that the observed signal is caused by random fluctuations in the data.

Professor Cowan added: “Roughly speaking, there is a 25% chance that one of our seven events is an astrophysical electron or muon neutrino, rather than a tau neutrino.”

Pattern recognition and astrophysics sources

One of the interesting observations the researchers made was how the CNN identified the patterns left by tau neutrinos. The double cascade mode is characteristic of tau neutrinos and is what researchers believe sensitive analysis relies on.

However, what they noticed was much more interesting. While some of the seven signals had this characteristic pattern, several did not.

Professor Cowan explained: “We then determined that the CNN is actually focused on the overall pattern of light produced by the two photospheres and is insensitive to the signal pattern in the individual sensors.”

This means that the CNN is looking at the overall pattern, including neighboring photons around two bright spots.

The discovery’s relevance extends all the way to the origin of high-energy neutrinos themselves.

“As we improve our techniques for finding tau neutrinos and determine their properties based on the patterns they produce in detectors, we expect to be able to exploit their pointing abilities to search for astrophysical sources, perhaps discovering new neutrinos , or sharpen our current image of neutrinos.

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