arXiv subjects

Wanbing He

Publications and source records attributed to Wanbing He.

10 recordsLinked to original sources

arXiv2026

Time performance of USTC-IME LGAD under synchrotron light source focused X-ray

The time performance of Low Gain Avalanche Diodes (LGADs), designed by the University of Science and Technology of China (USTC) and fabricated by the Institute of Microelectronics of Chinese Academy of Sciences (IME), was characterized at the Shanghai Synchrotron Radiation Facility (SSRF). The experiment was conducted at the BL16B1 beamline, which delivers a focused X-ray beam with a diameter of 500 {\mu}m, a repetition period of 2 ns, and a photon energy of 10 keV. Using a fast oscilloscope, waveforms containing continuous signal pulses were recorded within a 50 ns time window. The LGAD under test successfully resolved the 2 ns period of the SSRF. To mitigate pile-up effects and extract pulse-by-pulse information from the acquired waveforms, a waveform-level global template fitting method was employed. The time resolution was then estimated using a combined profile likelihood approach, yielding a value of 126.6 ps. The effect of random photon absorption depth on the time resolution of LGADs was studied through dedicated simulations.

physics.ins-det↗

arXiv2026

Heavy-Flavor Electron Classification Using Hadronic Environment as Point Cloud

Electrons from semi-leptonic decays of charm (D) and bottom (B) hadrons are important probes in high-energy collisions, while their separation remains challenging due to the similarity of the underlying decay topologies. In this work, we represent the hadronic environment as a point cloud and investigate a hadron-based approach for distinguishing charm- and bottom-origin electrons using several set-based machine learning architectures, including Transformer models. Comparable performance is observed across different architectures, indicating that the dominant limitation originates from the intrinsic similarity between charm- and bottom-related hadronic structures rather than model expressivity. At an experimentally relevant working point corresponding to approximately 40% efficiency, the classifier achieves a purity close to 80% on the test dataset and significantly improves the classification performance relative to a hand-crafted observable BDT baseline. By studying the relation between the model response and physics-motivated observables, together with feature perturbation tests, we find that the learned representation is primarily sensitive to geometric and topological properties of the hadronic environment. Comparisons with high-level observables further suggest that the learned representation captures nontrivial discriminating information beyond a small set of manually constructed variables.

hep-ex↗

arXiv2026

Hyperon-Nucleon Spectrometer

Chirality lies at the heart of low-energy QCD, governing the symmetry structure that shapes hadron masses and strong interaction dynamics. Among the most compelling open questions tied to chiral dynamics and spontaneous chiral symmetry breaking is the longstanding $\Lambda$ polarization puzzle, in which $\Lambda$ hyperons produced in unpolarized hadronic collisions exhibit a surprisingly large transverse polarization that remains theoretically unexplained. This whitepaper presents the proposal for the Hyperon-Nucleon Spectrometer (H-NS) at the High-Intensity heavy-ion Accelerator Facility (HIAF). Leveraging the high energy and high intensity of HIAF's proton and heavy-ion beams, the H-NS experiment will perform systematic studies of hyperon polarization phenomena and their underlying mechanisms in proton-proton ($pp$), proton-nucleus ($pA$), and nucleus-nucleus ($AA$) collisions in the fixed target mode. A wide-range beam energy scan, including proton beams from 3 GeV up to 9.3 GeV (HIAF) and up to 32 GeV (upgraded HIAF), will be conducted to examine the dependence of polarization on collision energy. The spectrometer is designed with specialized detectors capable of high-precision reconstruction of final-state baryon polarizations. Among its many interesting and important measurements, H-NS will simultaneously measure hyperon and proton spin observables to explore the polarization mechanism in hadronic interactions and the spin structure of baryons. Furthermore, the use of $pA$ and $AA$ collisions will enable detailed investigations of cold and hot nuclear matter effects on spin polarization. Its physics program and detector development will significantly benefit the future Electron-ion Collider in China.

physics.ins-det↗

arXiv2024

Multifractal Dimension Spectrum Analysis for Nuclear Density Distribution

We present an integral density method for calculating the multifractal dimension spectrum for the nucleon distribution in atomic nuclei. This method is then applied to analyze the non-uniformity of the density distribution in several typical types of nuclear matter distributions, including the Woods-Saxon distribution, the halo structure and the tetrahedral $\alpha$ clustering. The subsequent discussion provides a comprehensive and detailed exploration of the results obtained. The multifractal dimension spectrum shows remarkable sensitivity to the density distribution, establishing it as an effective tool for studying the distribution of nucleons in nuclear multibody systems.

nucl-th↗

arXiv2023

Design and test for the CEPC muon subdetector based on extruded scintillator and SiPM

A combination of scintillator, wavelength shifting (WLS) fiber, and silicon photomultiplier (SiPM) shows an excellent performance in the `$K_{L}$ and $\mu$ detector (KLM)' of the Belle II experiment. In this study, we present the R&D efforts for a similar detection technology utilizing a new scintillator and SiPM. This technology can be applied to a muon detector for the proposed CEPC experiment. The R&D encompasses the investigation of the performance of a new 150 cm-long scintillator, the NDL SiPM with a sensitive surface of $\times$ 3 mm, or the Hamamatsu MPPC with a sensitive surface of 1.3 mm $\times$ 1.3 mm. Additionally, it includes the construction of a detector strip and the methods employed to achieve excellent light collection. Cosmic ray tests reveal efficient photon collections by NDL SiPM or MPPC, with efficiencies well above 90% using a threshold of 8 p.e.. The time resolutions for hits at the far end of a scintillator strip are better than 1.7 ns. The observed performance lays the foundation for advancing R&D including prototype modules aiming for reference Technical Design Report of CEPC detector recently.

physics.ins-det↗

arXiv2023

Machine learning method for $^{12}$C event classification and reconstruction in the active target time-projection chamber

Active target time projection chambers are important tools in low energy radioactive ion beams or gamma rays related researches. In this work, we present the application of machine learning methods to the analysis of data obtained from an active target time projection chamber. Specifically, we investigate the effectiveness of Visual Geometry Group (VGG) and the Residual neural Network (ResNet) models for event classification and reconstruction in decays from the excited $2^+_2$ state in $^{12}$C Hoyle rotation band. The results show that machine learning methods are effective in identifying $^{12}$C events from the background noise, with ResNet-34 achieving an impressive precision of 0.99 on simulation data, and the best performing event reconstruction model ResNet-18 providing an energy resolution of $\sigma_E<77$ keV and an angular reconstruction deviation of $\sigma_{\theta}<0.1$ rad. The promising results suggest that the ResNet model trained on Monte Carlo samples could be used for future classifying and predicting experimental data in active target time projection chambers related experiments.

physics.ins-det↗

arXiv2023

Machine learning in nuclear physics at low and intermediate energies

Machine learning is becoming a new paradigm for scientific research in various research fields due to its exciting and powerful capability of modeling tools used for big-data processing task. In this mini-review, we first briefly introduce different methodologies of the machine learning algorithms and techniques. As a snapshot of many applications by machine learning, some selected applications are presented especially for low and intermediate energy nuclear physics, which include topics on theoretical applications in nuclear structure, nuclear reactions, properties of nuclear matter as well as experimental applications in event identification/reconstruction, complex system control and firmware performance. Finally, we also give a brief summary and outlook on the possible directions of using machine learning in low-intermediate energy nuclear physics and possible improvements in ML algorithms.

nucl-th↗

arXiv2022

Manipulation of Nuclear Isomers with Lasers: Mechanisms and Prospects

Over one hundred years have passed since the nuclear isomer was first introduced, in analogy with chemical isomers to describe long-lived excited nuclear states. In 1921, Otto Hahn discovered the first nuclear isomer $^{234m}$Pa. After that, step by step, it was realized that different types of nuclear isomers exist, including spin isomer, K isomer, seniority isomers, and ``shape and fission'' isomer. The spin isomer occurs when the spin change $\Delta I$ of a transition is very large. The larger $\Delta I$, the lower the electromagnetic transition rates, the longer the half-lives. The K-isomer exists due to the significant change in K, where K is the projection of the total angular momentum on the symmetry axis. The seniority isomers arise due to a very small transition probability in seniority conserving transitions around semi-magic nuclei, where the seniority, which corresponds to the number of unpaired nucleons, is a reasonably pure quantum number. For a so-called shape isomer, the inhibition of the decay transition comes from the associated shape changes. It is caused by that a nucleus is trapped in a deformed shape which is its secondary minimum and is hard to decay back to its ground state.

nucl-ex↗

arXiv2019

The STAR Event Plane Detector

The Event Plane Detector (EPD) is an upgrade detector to the STAR experiment at RHIC, designed to measure the pattern of forward-going charged particles emitted in a high-energy collision between heavy nuclei. It consists of two highly-segmented disks of 1.2-cm-thick scintillator embedded with wavelength-shifting fiber, coupled to silicon photomultipliers and custom electronics. We describe the general design of the device, its construction, and performance on the bench and in the experiment.

physics.ins-det↗

arXiv2019

Background evaluations for the chiral magnetic effect with normalized correlators using a multiphase transport model

The chiral magnetic effect (CME) induces an electric charge separation in a chiral medium along the magnetic field that is mostly produced by spectator protons in heavy-ion collisions. The experimental searches for the CME, based on the charge-dependent angular correlations ($\gamma$), however, have remained inconclusive, because the non-CME background contributions are not well understood. Experimentally, the $\gamma$ correlators have been measured with respect to the second-order ($\Psi_{2}$) and the third-order ($\Psi_{3}$) symmetry planes, defined as $\gamma_{112}$ and $\gamma_{123}$, respectively. The expectation was that with a proper normalization, $\gamma_{123}$ would provide a data-driven estimate for the background contributions in $\gamma_{112}$. In this work, we calculate different harmonics of the $\gamma$ correlators using a charge-conserving version of a multiphase transport (AMPT) model to examine the validity of the said assumption. We find that the pure-background AMPT simulations do not yield an equality in the normalized $\gamma_{112}$ and $\gamma_{123}$, quantified by $\kappa_{112}$ and $\kappa_{123}$, respectively. Furthermore, we test another correlator, $\gamma_{132}$, within AMPT, and discuss the relation between different $\gamma$ correlators.

hep-ph↗