arXiv subjects

Hongzhao Yu

Publications and source records attributed to Hongzhao Yu.

3 recordsLinked to original sources

arXiv2026

Test of the JUNO 20-inch PMTs during Installation

Photomultiplier tubes (PMTs) are widely used in neutrino experiments. As a new-generation neutrino observatory, JUNO requires an excellent energy resolution of 3% at 1 MeV. This will be realized with a 20 kton liquid scintillator detector instrumented with more than 20000 20-inch PMTs and 25600 3-inch PMTs. These PMTs were successfully installed in JUNO from October 2022 to December 2024. During the installation, seven test campaigns were performed to validate the PMT functionality, including measurements dark count rate, gain, waveform, and charge spectrum. In this paper, we present the implementation of these tests and the corresponding results for the 20-inch PMTs throughout the installation process.

physics.ins-det↗

arXiv2020

Synergies and Prospects for Early Resolution of the Neutrino Mass Ordering

The measurement of neutrino Mass Ordering (MO) is a fundamental element for the understanding of leptonic flavour sector of the Standard Model of Particle Physics. Its determination relies on the precise measurement of $\Delta m^2_{31}$ and $\Delta m^2_{32}$ using either neutrino vacuum oscillations, such as the ones studied by medium baseline reactor experiments, or matter effect modified oscillations such as those manifesting in long-baseline neutrino beams (LB$\nu$B) or atmospheric neutrino experiments. Despite existing MO indication today, a fully resolved MO measurement ($\geq$5$\sigma$) is most likely to await for the next generation of neutrino experiments: JUNO, whose stand-alone sensitivity is $\sim$3$\sigma$, or LB$\nu$B experiments (DUNE and Hyper-Kamiokande). Upcoming atmospheric neutrino experiments are also expected to provide precious information. In this work, we study the possible context for the earliest full MO resolution. A firm resolution is possible even before 2028, exploiting mainly vacuum oscillation, upon the combination of JUNO and the current generation of LB$\nu$B experiments (NOvA and T2K). This opportunity is possible thanks to a powerful synergy boosting the overall sensitivity where the sub-percent precision of $\Delta m^2_{32}$ by LB$\nu$B experiments is found to be the leading order term for the MO earliest discovery. We also found that the comparison between matter and vacuum driven oscillation results enables unique discovery potential for physics beyond the Standard Model.

hep-ph↗

arXiv2020

Augmented Signal Processing in Liquid Argon Time Projection Chambers with a Deep Neural Network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

physics.ins-det↗