Data-driven core collapse supernova multilateration with first neutrino events

A Galactic core-collapse supernova (CCSN) is likely to be observed in neutrino detectors around the world minutes to hours before the electromagnetic radiation arrives. The SNEWS2.0 network of neutrino and dark matter detectors aims to use the relative arrival times of the neutrinos at the different experiments to point back to the supernova so as to facilitate follow-up observation. One of the simplest methods to estimate the CCSN direction is to use the first neutrino events detected through the inverse beta decay (IBD) process, $\overlineν_e p\rightarrow e^+n$. We will consider neutrino detectors sensitive to IBD interactions with low backgrounds. The difference in signal arrival times between a large and a small detector will be biased, however, with the first event at the smaller detector, on average, arriving later than that at the larger detector. This bias can be mitigated by using these first events in a data-driven approach without recourse to simulations or models. The resulting method requires, at minimum, only the times of the first events at most detectors, along with a longer time series of events from one larger detector to act as a reference lightcurve. In this article, we demonstrate this method and its uncertainty estimate using pairs of detectors of different sizes and with different supernova distances. Finally, we use this method to calculate probability skymaps using four detectors currently in operation (Super-Kamiokande, JUNO, LVD, and SNO+) and show that the calculated probabilities yield appropriate confidence intervals for all supernova directions. The area of the 68% confidence interval varies by distance and direction, but is expected to be a few thousand square degrees. The resulting skymaps should be useful for the multi-messenger community as a rapid, initial pointing to follow up on the SNEWS2.0 Galactic CCSN neutrino alert.

💡 Research Summary

The paper presents a practical, data‑driven method for rapidly locating a Galactic core‑collapse supernova (CCSN) using the arrival times of the first inverse‑beta‑decay (IBD) neutrino events recorded by a network of detectors. The authors focus on the SNEWS 2.0 system, which will disseminate an early neutrino alert minutes to hours before any electromagnetic signal. Traditional multilateration techniques rely on the time differences between detectors, but when the detectors have very different sizes the simple “first‑event” approach is biased: a larger detector tends to record its first neutrino earlier than a smaller one, leading to systematic errors in the inferred direction.

To eliminate this bias without resorting to Monte‑Carlo simulations or detailed supernova models, the authors develop a purely statistical correction based on the observed event times themselves. For a detector that records N events at times t₁, t₂, …, t_N (ordered chronologically), the expected time of the first event is approximated by a weighted average

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