WIPAC finds Wisconsin IceCube data hints at proton interactions near black holes

Embedded within a cubic kilometer of Antarctic ice, the IceCube Neutrino Observatory has detected an unexpected feature in the distribution of neutrinos arriving from across the cosmos. Scientists at the Wisconsin IceCube Particle Astrophysics Center recently reported a feature in the expected smooth energy distribution of these weakly interacting particles.

This anomaly, not predicted by standard particle acceleration theories, may originate from proton interactions with X-ray radiation near supermassive black holes, creating a short-lived particle called a delta baryon. “It turns out when protons hit light, they can turn into other subatomic particles,” explains Dan Hooper, a professor of physics at UW-Madison and WIPAC Director.

IceCube Data Reveals Spectral Break in High-Energy Neutrino Distribution

Ke Fang, an associate professor of physics at UW-Madison, explains that the high-energy neutrino spectrum was previously consistent with a power law, a simple, featureless energy distribution expected from many standard particle acceleration processes. This consistency has now been disrupted by the identification of a distinct “break” in the spectrum, prompting investigation into its origin and potential implications for understanding neutrino production. Their analysis, submitted to The Astrophysical Journal Letters, suggests that collisions between protons and photons create a short-lived particle known as a delta baryon, ultimately influencing the neutrino spectrum.

Arifa Khatee Zathul, a PhD graduate student at UW-Madison, detailed that they explored the multimessenger consequences of the neutrino spectral break at 30 TeV, finding that a soft X-ray target with an energy of approximately 0.3 keV is needed to produce such a diffuse spectrum. The researchers acknowledge the possibility that the sources of these neutrinos may also emit high-energy gamma rays, a factor they continue to investigate. Future observations with IceCube and its planned extension, IceCube-Gen2, are expected to refine the understanding of the neutrino spectrum and pinpoint the precise origins of these high-energy particles.

We explored the multimessenger consequences of the neutrino spectral break at 30 TeV, notably showing that a soft X-ray target with an energy of ~0.3 keV is needed to produce such a diffuse spectrum.

Arifa Khatee Zathul, PhD Graduate Student at UW-Madison
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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