Accelerator Neutrinos

Abstract:

The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events.

Abstract:

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 SuperNova Early Warning System (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, ${\overline{\nu }}_{e}p\to e^{+}n$ . 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, Jiangmen Underground Neutrino Observatory (JUNO), Large Volume Detector (LVD), and $\mathrm{SNO}+$ , 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 multimessenger community as a rapid, initial pointing to follow up on the SNEWS2.0 Galactic CCSN neutrino alert.

Abstract:

A model-agnostic search for Beyond the Standard Model physics is presented, targeting final states with at least four light leptons (electrons or muons). The search regions are separated by event topology and unsupervised machine learning is used to identify anomalous events in the full 140 fb-1$$^{-1}$$ of proton–proton collision data collected with the ATLAS detector during Run 2. No significant excess above the Standard Model background expectation is observed. Model-agnostic limits are presented in each topology, along with limits on several benchmark models including vector-like leptons, wino-like charginos and neutralinos, or smuons. Limits are set on the flavourful vector-like lepton model for the first time.

Abstract:

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, v̄_ep → 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.

Abstract:

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment with a rich physics program that includes searches for the hypothetical phenomenon of proton decay. Utilizing liquid-argon time-projection chamber technology, DUNE is expected to achieve world-leading sensitivity in the proton decay channels that involve charged kaons in their final states. The first DUNE demonstrator, ProtoDUNE Single-Phase, was a 0.77 kt detector that operated from 2018 to 2020 at the CERN Neutrino Platform, exposed to a mixed hadron and electron test-beam with momenta ranging from 0.3 to $7\mathrm{GeV}/\mathrm{c}$ . We present a selection of low-energy kaons among the secondary particles produced in hadronic reactions, using data from the 6 and $7\mathrm{GeV}/\mathrm{c}$ beam runs. The selection efficiency is 1% and the sample purity 92%. The initial energies of the selected kaon candidates encompass the expected energy range of kaons originating from proton decay events in DUNE (below $\sim 200\mathrm{MeV}$ ). In addition, we demonstrate the capability of this detector technology to discriminate between kaons and other particles such as protons and muons, and provide a comprehensive description of their energy loss in liquid argon, which shows good agreement with the simulation. These results pave the way for future proton decay searches at DUNE.