A New Transfer Learning Ensemble Model with New Training Methods for Gear Wear Particle Recognition

Aiming at solving the acquisition problems of wear particle data of large-modulus gear teeth and few training datasets, an integrated model of LCNNE based on transfer learning is proposed in this paper. Firstly, the wear particles are diagnosed and classified by connecting a new joint loss function and two pretrained models VGG19 and GoogLeNet. Subsequently, the wear particles in gearbox lubricating oil are chosen as the experimental object to make a comparison. Compared with the other four models’ experimental results, the model superiority in wear particle identification and classification is verified. Taking five models as feature extractors and support vector machines as classifiers, the experimental results and comparative analysis reveal that the LCNNE model is better than the other four models because its feature expression ability is stronger than that of the other four models.

Status of the Design of an Annihilation Detector to Observe Neutron-Antineutron Conversions at the European Spallation Source

The goal of the HIBEAM/NNBAR program is to search for baryon number violation via the conversion or oscillation of neutrons into sterile neutrons and/or antineutrons at the European Spallation Source. A key experimental component of the program is the construction of an annihilation detector to directly observe the production of an antineutron following the oscillation. Design studies for the annihilation detector are presented. The predicted response of the detector models are studied using Geant4 simulations made with Monte Carlo simulations of the annihilation signal topology and cosmic ray backgrounds. Particle identification and sensitive discriminating observables, such as invariant mass and sphericity, are shown.

Surface Dyakonov–Cherenkov radiation

Recent advances in engineered material technologies (e.g., photonic crystals, metamaterials, plasmonics, etc.) provide valuable tools to control Cherenkov radiation. In all these approaches, however, the particle velocity is a key parameter to affect Cherenkov radiation in the designed material, while the influence of the particle trajectory is generally negligible. Here, we report on surface Dyakonov–Cherenkov radiation, i.e. the emission of directional Dyakonov surface waves from a swift charged particle moving atop a birefringent crystal. This new type of Cherenkov radiation is highly susceptible to both the particle velocity and trajectory, e.g. we observe a sharp radiation enhancement when the particle trajectory falls in the vicinity of a particular direction. Moreover, close to the Cherenkov threshold, such a radiation enhancement can be orders of magnitude higher than that obtained in traditional Cherenkov detectors. These distinct properties allow us to determine simultaneously the magnitude and direction of particle velocities on a compact platform. The surface Dyakonov–Cherenkov radiation studied in this work not only adds a new degree of freedom for particle identification, but also provides an all-dielectric route to construct compact Cherenkov detectors with enhanced sensitivity.

Method of Separating Cosmic-Ray Positrons from Electrons in the DAMPE Experiment

A method of identifying positron/electron species from the cosmic rays was studied in the DAMPE experiment. As there is no onboard magnet on the satellite, the different features imposed by the geomagnetic field on these two species were exploited for the particle identification. Application of this method to the simulation of on-orbit electrons/positrons/protons and the real flight data proves that separately measuring the CR positrons/electrons with DAMPE is feasible, though limited by the field of view for the present observation data. Further analysis on the positron flux with this method can be expected in the future.

A 4π time-of-flight detector for the ND280/T2K upgrade

ND280 is a near detector of the T2K experiment which is located in the J-PARC accelerator complex in Japan. After a decade of fruitful data-taking, ND280 is scheduled for upgrade. The time-of-flight (ToF) detector, which is described in this article, is one of three new detectors that will be installed in the basket of ND280. The ToF detector has a modular structure. Each module represents an array of 20 plastic scintillator bars which are stacked in a plane of 2.4 × 2.2 m2 area. Six modules of similar construction will be assembled in a cube, thus providing an almost 4π enclosure for an active neutrino target and two TPCs. The light emitted by scintillator is absorbed by arrays of large-area silicon photo-multipliers (SiPMs) which are attached to both ends of every bar. The readout of SiPMs, shaping and analog sum of individual SiPM signals within the array are performed by a discrete circuit amplifier. An average time resolution of about 0.14 ns is achieved for a single bar when measured with cosmic muons. The detector will be installed in the basket of ND280, where it will be used to veto particle originating outside the neutrino target, improve the particle identification and provide a cosmic trigger for calibration of detectors which are enclosed inside it.

Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC

The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 × 6 × 7.2 m3. The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP's successful operation between 2018 and 2020 demonstrates the effectiveness of the single-phase far detector design. This paper describes the design, construction, assembly and operation of the detector components.

Performance Monitoring of the Barrel Time-of-Flight Supermodule for the PANDA Experiment at FAIR

The PANDA experiment at FAIR in Darmstadt will use proton-antiproton collisions, with momenta ranging from 1.5 GeV/c to 15 GeV/c, on a fixed target to study open questions in hadron physics. The Barrel Time-of-Flight detector for this experiment is a scintillating tile hodoscope based on 16 identical and independent subdetectors called Super-Modules arranged in a cylindrical configuration. We have conducted performance studies on one such Super-Module to prove the feasibility of the Barrel Time-of-Flight detector design. Time resolution, signal delay and amplitude drop along the length of the detector were measured and analyzed as a function of the position on the individual scintillator tiles. A time resolution of about 50 ps has been achieved, which is very important for event timing and particle identification.

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in νμCC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.