An in-situ tender X-ray absorption spectroscopy (XAS) technique was developed to enhance the characterization of key light elements, including P, S, Cl, K, etc., which are indispensable for studies in new energy materials, environmental pollutant monitoring, and biological toxins analysis. A quick-scanning XAS (QXAS) technique was established for the tender X-ray energy range (2–5 keV), improving temporal resolution from tens of minutes to a few seconds. Effective noise suppression was achieved via incorporating an analog low-pass filter for QXAS acquisition. In addition, a digital Butterworth filter was applied for comparison. Quick-scanning at the maximum speed enabled the acquisition of XAS spectra for S, Cl, and K elements in less than 18s, 12s, and 7s, respectively. The resulting data exhibited good consistency with conventional measurements, confirming the reliability of the QXAS system. As a proof-of-concept, in-situ QXAS monitoring of the sulfur K-edge during lithium–sulfur battery (LSB) discharge demonstrated the system’s capability for observing dynamic electrochemical processes. An integrated QXAS system for the tender X-ray regime has been developed, achieving second-scale time resolution through rapid and periodic monochromator scanning. The analog low-pass filter effectively suppresses noise under quick-scanning conditions. This system shows strong potential for advancing the mechanistic understanding of complex dynamic processes.
Introducing convolutional neural networks (CNN) into positron emission tomography (PET) signal processing enhances detector performance. Most existing work focuses on developing and executing CNN models on back-end computers. When in practical use, it requires heavy data transfer and storage demands. Recently developed front-end inference methods rely on field programmable gate array (FPGA), which requires custom logic implementation of model operations, limiting practical use to simple multilayer perceptron (MLP) models and offering little support for CNNs suited to image-based processing tasks. In this study, we propose a front-end CNN inference method based on multi-processor system on chip (MPSoC) platform for PET detector depth of interaction (DOI) classification. This method addresses the high data transfer overhead associated with executing CNN models on a back-end computer, and reduces implementation complexity required for deploying CNN models on a front-end FPGA. A CNN-based DOI classifier is trained on data from a two-layer lutetium yttrium oxyorthosilicate (LYSO) detector, quantized to int8, and deployed on an AMD Xilinx UltraScale+ MPSoC via Vitis AI toolchain, enabling inference on the integrated deep learning processing unit (DPU) accelerator without manual register-transfer level design. Compared to the floating-point model deployed on back-end computer, the proposed solution achieves DOI classification accuracy of 99.05
Photomultiplier tubes (PMTs) are the core light sensors of liquid xenon dark matter detectors. The PandaX-4T experiment selected Hamamatsu 3-inch R11410-23 PMTs for their ultra-low radioactivity, high quantum efficiency and potential long-term stability at cryogenic temperatures. Each PMT was thoroughly tested in a dedicated vacuum chamber before detector installation. We measured the main performance characteristics including gain, dark count rate and after-pulse probability, and performed cryogenic tests to simulate the actual operating conditions of the detector. The parameter distributions of all qualified PMTs are presented. Long-term performance monitoring during the PandaX-4T commissioning run shows that most PMTs operated reliably and stably throughout the period. All installed PMTs meet the experimental requirements. The test results provide a solid foundation for the physics data taking of PandaX-4T and valuable reference for future liquid xenon detector designs.
This paper briefly describes the data acquisition software of the updated SAXS/XRD/XAFS station at beamline 1W2B of Beijing Synchrotron Radiation Facility (BSRF), so as to facilitate users to choose a more suitable experimental mode and configure the data acquisition parameters of the combined measurements. Based on the equipment control and data acquisition network system, routine or anomalous small-angle X-ray scattering (SAXS, ASAXS) data, routine or anomalous X-ray diffraction (XRD, AXRD) data, as well as X-ray absorption fine structure (XAFS) data can be simultaneously or separately acquired without the need for mechanical switching. Multiple experimental modes, including routine XAFS measurements, routine SAXS/XRD combined measurements, quick or slow SAXS/XRD/XAFS combined measurements, as well as ASAXS/AXRD combined measurements are available. With the BSRF upgrade, the updated experimental station at beamline 1W2B focuses more on SAXS/XRD/XAFS combined technique and anomalous X-ray scattering technique. The updated station has an intrinsic seconds-level time resolution, and a variety of experimental modes are available. Combined with in situ sample environment system, atomic local structure, nanoscale structure, long-range ordered structure, and element-specific distribution can be detected simultaneously under in situ conditions. Choosing the appropriate data acquisition software, correctly configuring the data acquisition parameters, and performing necessary data preprocessing are the prerequisites for successfully obtaining effective combined data.
To investigate the impact of temperature and humidity, neutron radiation fields, shielding factors, and mixed radionuclides on the imaging performance of tellurium-zinc-cadmium Compton scattering γ cameras under specific complex environmental conditions. Experimental tests were conducted to evaluate the imaging effectiveness of tellurium-zinc-cadmium Compton scattering γ cameras under varying temperature-humidity conditions, 252Cf neutron radiation fields, shielded scattering scenarios, and mixed radionuclide environments. The experiments demonstrated that prolonged imaging time and slight shape distortion occurred under high-temperature/high-humidity conditions. The 252Cf neutron radiation field had no significant impact on imaging quality. Shielded scattering caused elevation of the Compton flateau in γ energy spectra, which adversely affected imaging of radionuclides emitting low-energy γ rays. This study elucidates the specific influence mechanisms of temperature-humidity variations, neutron radiation fields, shielding scattering, and mixed radionuclides on tellurium-zinc-cadmium Compton scattering γ camera imaging performance, providing data support for expanding its application in complex environmental environments.
The high-energy photon source (HEPS) is a fourth-generation synchrotron light source, which is designed to be one of the world’s brightest synchrotron light sources. HEPS imposes higher requirements for the beamline experimental methods, demanding enhancements in experimental efficiency, minimized radiation damage and time-resolved capabilities. In this paper, we present a high-dynamic motion control system for HEPS beamline, which is designed to achieve high-dynamic and high-stability position control of mechatronic equipment, and realize the synchronization based on time-triggering or position-triggering. The hardware of high-dynamic motion control system is based on EtherCAT fieldbus, which can support voice coil motor (VCM) and permanent magnet synchronous motor (PMSM). The software is designed under the experimental physics and industrial control system (EPICS), where the motion axes and controller script buffers are mapped to EPICS PVs, respectively. A frequency-domain-based dynamic model identification approach and robust control algorithm based on mixed sensitivity optimization were proposed, in order to realize high-bandwidth performance and robust stability of the mechatronic system. In this paper, the flexibility and effectiveness of this system and control method were demonstrated by two representative cases, including beamline fast shutter and imaging sample stage. The fast shutter can achieve the 6 mm aperture within 37 ms, and this system realized the timing-synchronization between the motion control and detector. The high-dynamic motion control system was successfully applied in imaging sample stage, which achieves the position synchronization with PandaBox in fly-scan applications. The experiment results were shown to demonstrate the advantages of this system for the time-resolved performance of the in situ experiments and the high-dynamic scanning performance of fly-scan applications. This proposed control system can satisfy the requirements of HEPS, which will play a vital role in HEPS with the development of novel experimental method.
High-precision accelerators require stringent beam stability, which can be affected by cooling-water-induced vibrations. However, effective quantitative analysis methods for such vibrations remain limited. This study aims to establish a methodological framework for analyzing flow-induced vibrations in high-precision accelerator cooling-water systems. Transient simulations of representative cooling-water piping structures were conducted using Large Eddy Simulation (LES). Continuous Wavelet Transform (CWT) was applied to the simulated velocity signals to extract time–frequency characteristics and identify flow-induced vibration frequencies. Comparative vibration measurements with cooling water on and off were performed on a QD2 quadrupole magnet at HEPS to validate the LES-CWT framework. The measured signals were analyzed using CWT, power spectral density (PSD), and root-mean-square (RMS) methods. The LES-CWT analysis identified characteristic frequencies associated with cooling-water flow in representative piping structures. Experimentally, CWT results showed broadband energy enhancement under the cooling-water-on condition. Auxiliary PSD analysis identified characteristic components around 56 Hz, 65 Hz, and 71 Hz, which were consistent with the dominant frequencies obtained from the LES-CWT analysis. The RMS results indicated that cooling water contributed approximately 0.62 nm to the magnet’s transverse vibration. This study demonstrates that the LES-CWT framework can effectively identify the frequency characteristics of cooling-water-induced vibrations. The combined experimental CWT, PSD, and RMS analyses support its applicability for vibration assessment and mitigation design in high-precision accelerator cooling-water systems.
The High-energy Proton Beam Experimental Station (HPES) trigger system imposes stringent time-resolution requirements on its front-end detectors. This study aims to systematically evaluate the temporal performance of the Fast Large Area Starting Signal Hub (FLASH) detector, which is designed for high-precision beam monitoring and event start-signal generation. The FLASH detector prototype was fabricated using plastic scintillator fibers and ultra-fast photomultiplier tubes (FPMTs). To comprehensively characterize its temporal performance without the complexities of initial beam tests, a multi-source calibration approach was adopted. Specifically, picosecond lasers, a ^90 Sr radioactive source, cosmic rays acting as minimum ionizing particles (MIPs), were utilized to evaluate the intrinsic timing response. Experiments show that this type of FLASH readout chain achieves an intrinsic time resolution of 15 ps. Under cosmic-ray muon irradiation, the overall system-level time resolution is better than 400 ps, fully satisfying the HPES trigger design goals. The FLASH detector exhibits excellent temporal performance, meeting HPES trigger requirements and providing critical experimental evidence for its deployment in high-precision beam monitoring and start-signal triggering.
Purpose Cosmic ray muons, characterized by their high energy and penetrative capabilities, provide significant advantages for non-destructive imaging applications, including security inspection, geological exploration, and archaeology. As the muon tomography continues to advance, there is growing demand for precise and efficient muon imaging algorithms. This study aims to enhance muon track reconstruction accuracy, improve the quality of muon scattering imaging, and increase track utilization quality. Methods This paper proposes a neural network-based method utilizing Multi-Wire Drift Chambers (MWDCs), to improve muon track reconstruction performance. Additionally, to address the limitations of the conventional Point-of-Closest Approach (PoCA) algorithm in imaging accuracy and track utilization efficiency, an improved PoCA-based imaging method is proposed and its imaging performance is evaluated. Results The proposed neural network-based track reconstruction method achieved a spatial resolution 351 μ m . Furthermore, the improved PoCA algorithm significantly improved imaging resolution and reconstruction performance, while enhancing muon track utilization efficiency. Conslusions The MWDC-based neural network track reconstruction method improves muon track reconstruction performance, while the improved PoCA algorithm enhances imaging quality and track utilization efficiency. The combination of these methods provides an effective solution for muon scattering tomography
The Beijing Electron–Positron Collider (BEPC) is a circular accelerator operating in the τ-charm energy region, which has been operational since 1988. The facility comprises a linear accelerator (Linac), two transport lines, and two collider rings. Originally, the Linac operated at an energy of 1.3 GeV at BEPC; this was increased to 1.89 GeV at BEPCII. To meet evolving physics requirements, a recent upgrade has further raised the Linac energy to 2.35 GeV, with the capability of accelerating beams up to 2.8 GeV. The microwave system is essential for the stable operation of the Linac. It comprises four subsystems: the microwave excitation system, the radio frequency (RF) distribution system, the sub-harmonic buncher system, and the low-level RF system. Designed to support long-term, stable operation for electron–positron collision experiments, the system also meets the technical requirements for wakefield acceleration verification experiments. Beam energy requirements are fulfilled by incorporating a pulse compressor and two klystrons—referred as an energy enhancement. Additional operational demands are addressed by improving system stability and replacing equipment with degraded performance. The former involves upgrades to the microwave excitation and low-level RF systems, while the latter includes the replacement of sub-harmonic bunchers and pulse compressors. The outcomes of the energy enhancement and system upgrade are in accordance with the expected requirements. The upgraded microwave system is capable of meeting the latest operational requirements and maintaining long-term stable operation.
This paper presents a distributed monitoring and control system for the Cylindrical Gas Electron Multiplier (CGEM) inner tracker at the Beijing Spectrometer III (BESIII). Built on a LabVIEW-based framework, the system provides real-time data acquisition, data archiving, alarm handling, and operator interfaces. A state-machine-based high-voltage (HV) control mechanism enforces deterministic power-up sequences tailored to detector requirements. A multi-level safety interlock integrates status information from detector subsystems and BESIII global safety signals to trigger graded protection actions, including alarms, controlled HV ramp-down, and emergency shutdown. The design emphasizes reliability, scalability, and maintainability. The HV control is implemented using a finite-state machine with decoupled core logic and configurable operational sequences. The interlock architecture consists of unit-level, system-level, and global-level protection layers. Commissioning tests, integration verification, and long-term operational validation were performed to assess system performance and reliability. The system continuously supervises approximately 1100 parameters. HV operations and interlock responses are completed within 1 s. Over more than one year of routine operation, interlock performance was evaluated using statistics from recorded detector events. No missed actuation was observed in the recorded events, and the automated HV protection and recovery logic successfully handled routine trip events, reducing operator workload and improving data-taking efficiency. The validated control logic and scalable architecture satisfy the operational requirements of the CGEM detector. The framework is also reusable for detector control systems in large-scale high-energy physics experiments.
PGNAA is a well-known method for analyzing the composition of rock samples. In this work, LaBr_3 is used as a gamma detector. For correct operation of the elemental analysis, it is necessary to calibrate by the registration efficiency of the available method over a wide range of energies from 50 keV to 15 MeV. Traditionally, such calibration requires a particle accelerator or reactor in this work, a practical, alternative is proposed. A combination of standard gamma-ray sources, thermal neutron capture reactions on ^35Cl (n,γ)^36Cl using a DT neutron generator, and simulations in Geant4 was employed to determine the full-energy peak efficiency of the LaBr_3 detector. This approach fully compensates for the absence of a reactor while still providing a wide energy range. The full-energy peak efficiency of detector LaBr_3 (Ce) with dimensions Ø7.6 × 7.6 cm was determined in energy region from 50 keV to 15 MeV. The results show that the experiments are in good agreement with the simulation in Geant4, and the full-energy peak efficiency curves are consistent. Thus, a practical solution for wide-energy calibration in PGNAA applications is offered.
Beam tuning at the high-intensity heavy-ion accelerator facility (HIAF) remains heavily reliant on operator experience. This study proposes a multi-task Transformer ensemble method to predict detector operation sequences and provide real-time recommendations for the next operation during beam tuning, with the aim of supporting future automated operation and maintenance. Bit-level state-change detection of HIAF machine protection system (MPS) programmable logic controller (PLC) data yielded 2108 operation events spanning ten patterns, which were validated by unsupervised clustering. A multi-task Transformer with 247-dimensional multi-level features jointly predicts the next device, device type, location region, operation pattern, and anomaly status. Rare-class merging, embedding-layer Mixup, and a weighted Transformer ensemble were employed to mitigate data sparsity, class imbalance, and overfitting, and sequence-wise grouped cross-validation was used to prevent sliding-window leakage. Using sequence-wise grouped fivefold cross-validation, in which all sliding-window samples generated from the same original operation sequence were assigned to the same fold, the deployed seven-model Mixup ensemble achieved Top-5 accuracy of 82.3
The BEPCII upgrade project necessitates two new final focus superconducting magnets on both sides of interaction point to achieve a high luminosity at higher beam energy. Each superconducting magnet consists of a quadrupole magnet for final focusing the beam and an anti-solenoid for canceling the magnetic field of Detector solenoid. Compared with the BEPCII magnet, the magnetic field gradient of new superconducting quadrupole (SCQ) increases from 18.7 to 25 T/m. The field harmonics of SCQ are required to be less than 3 × 10–4. Use line current approximation and field simulation by OPERA, the magnetic design of serpentine coil of SCQ is determined, and the calculated field harmonics are less than 0.5 × 10–4. According to the theoretical trajectory of each turn conductor, the SCQ coil is wound layer by layer using direct winding technology. Room temperature magnetic field measurement and cryogenic vertical test at 4.2 K are used to check the field quality and validate the magnet fabrication process. Cryogenic horizontal test at 4.5 K shows that the magnetic field performance of SCQ and anti-solenoid of the two magnets meets the design requirements. The measured field harmonics of SCQ are less than 2 × 10–4 corresponding to the nominal field gradient 25 T/m. The measured magnetic field distribution of anti-solenoid is consistent with field simulation result. Two new final focus superconducting magnets have been successfully developed for BEPCII upgrade project. They were installed in upgraded BEPCII interaction region at the end of 2024, and have maintained stable operation under the Detector solenoid field without any quench since May 2025.
For the particle detection when large area coverage is needed and wide surface must be instrumented, the gaseous detectors represent the only possible choice. Using GEM-type structures in the presence of proper quenching gas, it is possible to follow optically the charge particle tracks in gaseous position-sensitive detectors. Depending on the geometric parameters in these structures, this method can consider as an applied method for the detection of alpha particle tracks with specific accuracy. In this work, a Double EMA is presented as a new configuration of an Electron Multiplier Assembly (EMA), and the geometrical quenching factor concerning the electric field arrangement in the EMA through-holes is introduced as an effective parameter for the appearance of visible streamers in the space between EMA plates when they are employed as multiplication regions within a gaseous detector. In EMA arrays, in the presence of P10 gas at the threshold applied voltages, the light strips constantly emerge in the EMA through-holes exposed to radioactive source. In Double EMA, the formation of the regular electric field arrangement in the space of exterior EMA plates decreases the threshold applied voltage, thus enhancement the electron multiplication efficiency in the amplification region. With simulation of the electric field in the multiplication region, there is demonstrated the convergence of the electric field lines in the center of each hole as well as their divergence in the vicinity of the EMA electrodes can play the key role in the creating self-sustaining plasma regions in the EMA wall-less holes.
Accurately identifying radioactive nuclides is essential for environmental monitoring and nuclear security.This study aims to develop a deep learning-based methodology within tomographic gamma scanning (TGS) to distinguish 137 Cs 110mand Ag, as their misidentifi cation poses signifi cant safety risks in nuclear waste management. A bidirectional long short-term memory (Bi-LSTM) network was employed as the baseline classifi er, withhyperparameter optimization performed to enhance discrimination capability. A Monte Carlo model was constructedaccording to actual nuclear waste drum dimensions, incorporating detector response and environmental radioactivebackground contributions. The Bi-LSTM model was trained and evaluated using simulated spectroscopic data undervarying 137Cs/ 110m ⁰ᵐAg activity ratios. The optimized Bi-LSTM model achieved an average identifi cation accuracy exceeding 97
To initiate machine learning (ML)-based drift chamber track reconstruction, for which no dedicated dataset currently exists, we present DCTracks-v1.0—a Monte Carlo (MC) dataset comprising single- and two-track events, with the latter including both conventional and close-by topologies. To enable standardized evaluation, we adopt a set of track reconstruction evaluation metrics, with which we benchmark both traditional and graph neural network (GNN)-based methods on this dataset. Our results show that while the GNN-based approach performs comparably to traditional methods on single and conventional two-track events, its performance degrades on close-by two-track events, highlighting both the potential and current limitations of GNN-based tracking. By providing baseline results on this dataset, this work validates the reliability of the dataset and establishes a foundation for systematic, reproducible validation and fair comparison in future research.
Water Cherenkov detectors play a fundamental role in neutrino physics and cosmic-ray research. The water attenuation length (WAL, also called water transparency) is the parameter serving as an indicator of water quality within the detector. This paper presents the design, implementation, and performance of a dedicated monitoring system developed to measure the WAL in situ in the water Cherenkov (Veto) detector of the Jiangmen Underground Neutrino Observatory (JUNO). The system incorporates five 20-inch PMTs with light guides, a stable LED light source and a calibration LED light source with optical fibers, and deployed at the bottom of the JUNO water pool. The system provides the capability to continuously monitor water transparency throughout the water filling and commissioning phases in JUNO. Long-term monitoring data demonstrate a systematic improvement in water quality. The measured WAL increased from an initial value of 23 m at the beginning of filling operations to a stable value of about 60 m during detector commissioning. With the ongoing operation of the water purification and recirculation system, the attenuation length has further improved, currently reaching about 75 m. The system operates stably, monitor detector performance and validating water circulation in JUNO water Cherenkov detector.
This paper presents the design and development of a comprehensive Personal Protection System (PPS) for the Compact Laser Plasma Accelerator for Proton Radiotherapy (CLAPA-II) at Peking University. High-gradient laser accelerators operate based on the special mechanism of femtosecond pulsed laser–plasma interaction, featuring frequent mode switching and complex operating conditions. Meanwhile, the generated pulsed proton beams are characterized by short pulse durations and high dose rates, posing significant challenges for radiation protection and personnel safety. To address these issues, the proposed PPS develops dedicated interlock mechanisms tailored for laser accelerators and differentiated safety solutions for both laser areas and laser–plasma interaction regions. The core interlock logic and safety actions are executed by redundant programmable logic controllers (PLCs), ensuring fail-safe operation and high reliability. Through integration with the Experimental Physics and Industrial Control System (EPICS) framework, the PPS achieves seamless coordination with multiple subsystems across the accelerator facility, enabling distributed monitoring and data archiving. Additionally, the system incorporates deep learning techniques for anti-tailgating detection, enhancing safety monitoring capabilities. The intelligent and reliable PPS has been operating stably for over one year, providing effective protection for experimental personnel against radiation hazards at laser-driven accelerator facilities. The proposed PPS demonstrates high reliability, intelligent monitoring capability, and strong adaptability for radiation safety protection in advanced laser-driven accelerator facilities.
