arXiv subjects

Yue Meng

Publications and source records attributed to Yue Meng.

At least 19 recordsLinked to original sources

arXiv2026

Search for neutrinoless quadruple beta decay of $^{136}$Xe in PandaX-4T detector

The observation of neutrinoless quadruple beta decay (0$\nu$4$\beta$) in the absence of neutrinoless double beta decay (0$\nu$2$\beta$) has been argued to provide a strong indication that neutrinos are Dirac particles. We report a search for 0$\nu$4$\beta$ decay of $^{136}\text{Xe}$ using a total $^{136}\text{Xe}$ exposure of 148.4 kg$\cdot$yr, collected during the commissioning and the first science runs of the PandaX-4T experiment. No significant excess of events over the background is observed. A lower limit on the 0$\nu$4$\beta$ decay half-life of $^{136}\text{Xe}$ is set at 6.01 x $10^{24}$ yr at the 90% confidence level. This result establishes the most stringent constraint on this process in xenon, demonstrating the unique capability of the PandaX-4T detector in probing lepton number violation and shedding light on the fundamental nature of neutrinos.

nucl-ex↗

arXiv2026

Irreducible $\mathbb{Z}_+$-modules over some $\mathbb{Z}_+$-rings

Let $d_1,\ldots,d_r$ be pairwise relatively prime positive square-free integers, with $d_j\geq2$ for all $1\leq j\leq r$. Using elementary matrices and combinatorial mathematics, we give a complete classification of the irreducible $\mathbb{Z}_+$-modules over the domain $\mathbb{Z}[d^{\frac{1}{N_1}}_1,d^{\frac{1}{N_2}}_2,\dots,d^{\frac{1}{N_r}}_r]$, where $N_i \geq2$ for all $ 1\leq i \leq r$. Furthermore, we explicitly construct all of these irreducible $\mathbb{Z}_+$-modules.

math.RA↗

arXiv2026

The Radioactive Background of the JUNO Calibration System

The Jiangmen Underground Neutrino Observatory (JUNO) experiment is a reactor antineutrino detector employing 20 kton of ultra-pure liquid scintillator to determine the neutrino mass ordering and to precisely measure oscillation parameters. The total singles background rate from radioactivity is required to be below 10 Hz in the energy range of 0.7-12 MeV within the fiducial volume for reactor neutrino analysis. The calibration system is designed to characterize the detector energy and position responses, while several of its components are located close to the target and may contribute to the background budget. Therefore, extensive material screening and selection are required to construct a low-background calibration system and to ensure that its contribution remains within the design requirements. In this work, a comprehensive study of the radioactive background induced by the calibration system is presented, including material radioactivity measurements using high-purity germanium detectors and neutron activation analysis techniques, detailed Monte Carlo simulations to evaluate the background, and comparisons with in-situ detector data to validate the predictions. In this data analysis, dedicated spatial selection methods are developed to isolate calibration-related contributions and to suppress the liquid scintillator background. The total radioactivity contribution from the calibration system is estimated to be less than 76 mHz, which satisfies the requirement of 200 mHz (2% of the total background budget). The results from in-situ data are found to be consistent with the expectations based on material assay and simulation within uncertainties. These results demonstrate that the calibration-induced background is well understood, in agreement between data and simulation, and negligible for reactor antineutrino measurements in JUNO.

physics.ins-det↗

arXiv2026

Classification of some $\mathbb{Z}/2\mathbb{Z}\times \mathbb{Z}/2\mathbb{Z}$-quadratic fusion categories of rank 6

A fusion category $\mathcal{C}$ is said to be $\mathbb{Z}/2\mathbb{Z}\times \mathbb{Z}/2\mathbb{Z}$-quadratic if the group $G(\mathcal{C})$ of invertible objects is isomorphic to $\mathbb{Z}/2\mathbb{Z}\times \mathbb{Z}/2\mathbb{Z}$, and the remaining simple objects form an orbit under the action of $G(\mathcal{C})$. In this paper, we give a partial classification of $\mathbb{Z}/2\mathbb{Z}\times \mathbb{Z}/2\mathbb{Z}$-quadratic fusion categories of rank six. More precisely, we show that its Grothendieck ring $\mathcal{K}_0(\mathcal{C})$ must be one of nine fusion rings if the fusion rule multiplicities are less than $20$, and the categorifications of five of them are previously known. We prove that one of the last four fusion rings can be realized as de-equivariantization of a near-group fusion category of type $\mathbb{Z}/2\mathbb{Z}\times \mathbb{Z}/4\mathbb{Z}+8$.

math.QA↗

arXiv2026

High-accuracy ultrasonic positioning of calibration sources in the Jiangmen Underground Neutrino Observatory

Precise source positioning is essential for detector calibration in large liquid scintillator detectors such as JUNO, particularly in regions where purely mechanical control is insufficient. An ultrasonic positioning system has been developed to reconstruct the three-dimensional coordinates of a calibration source without interfering with photon collection or contaminating the liquid scintillator. The method combines a sound-speed modeling based on dedicated laboratory measurements and in-detector temperature profiles, waveform-based arrival-time reconstruction, and an in-situ calibration of the effective receiver geometry using central-axis deployments. With six active receivers, central-axis positioning yields a mean error of 1.23 cm relative to the known deployment reference. For off-axis operation in the Cable Loop System calibration plane, a detector-realistic simulation that includes timing resolution, sound-speed variation, and receiver-coordinate smearing predicts a positioning uncertainty of 2.40 cm. These results demonstrate that ultrasonic positioning can provide centimetre-level source accuracy for large liquid scintillator detectors and can support off-axis calibration in JUNO-like experiments.

physics.ins-det↗

arXiv2026

Measurement of solar $pp$ neutrino flux with the new PandaX-4T data

We report a new measurement of the solar proton--proton ($pp$) neutrino flux via neutrino--electron elastic scattering using the PandaX-4T Run 2 data set collected between 2024 and 2026, corresponding to an exposure of 1.9 tonne$\cdot$yr. Before Run 2 data taking, the detector underwent a series of upgrades to improve its response and background conditions. Time variations of radioactive noble-gas impurities are constrained using the physics data themselves, complemented by measurements from the gas-assay system. The analysis introduced improvements in the data processing chain, detector response characterization, and background models. A blind spectral analysis was then performed on the electronic-recoil data across a wide energy range from 20 to 1000 keV. In combination with the Run 0 data published earlier, the fitted $pp$ flux is $(8.5 \pm 3.5)\times 10^{10}$ $\mathrm{cm^{-2}s^{-1}}$, consistent with the prediction of the Standard Solar Model. With a statistical significance of $2.2\sigma$ above background, this marks the first positive indication of solar $pp$ neutrino--electron scattering below an electronic-recoil energy of 165 keV.

hep-ex↗

arXiv2026

SFFNet: Synergistic Feature Fusion Network With Dual-Domain Edge Enhancement for UAV Image Object Detection

Object detection in unmanned aerial vehicle (UAV) images remains a highly challenging task, primarily caused by the complexity of background noise and the imbalance of target scales. Traditional methods easily struggle to effectively separate objects from intricate backgrounds and fail to fully leverage the rich multi-scale information contained within images. To address these issues, we have developed a synergistic feature fusion network (SFFNet) with dual-domain edge enhancement specifically tailored for object detection in UAV images. Firstly, the multi-scale dynamic dual-domain coupling (MDDC) module is designed. This component introduces a dual-driven edge extraction architecture that operates in both the frequency and spatial domains, enabling effective decoupling of multi-scale object edges from background noise. Secondly, to further enhance the representation capability of the model's neck in terms of both geometric and semantic information, a synergistic feature pyramid network (SFPN) is proposed. SFPN leverages linear deformable convolutions to adaptively capture irregular object shapes and establishes long-range contextual associations around targets through the designed wide-area perception module (WPM). Moreover, to adapt to the various applications or resource-constrained scenarios, six detectors of different scales (N/S/M/B/L/X) are designed. Experiments on two challenging aerial datasets (VisDrone and UAVDT) demonstrate the outstanding performance of SFFNet-X, achieving 36.8 AP and 20.6 AP, respectively. The lightweight models (N/S) also maintain a balance between detection accuracy and parameter efficiency. The code will be available at https://github.com/CQNU-ZhangLab/SFFNet.

cs.CV↗

arXiv2025

Design, simulation and performance of the resistive-anode PICOSEC Micromegas detector

The PICOSEC Micromegas detector is a Micro-Pattern Gaseous Detector concept developed to achieve tens of picosecond timing resolution for charged particle detection by combining a Cherenkov radiator with a two-stage Micromegas amplification structure. To improve operational robustness, a resistive anode has been implemented using a DLC layer deposited on a Kapton substrate. While this design enhances detector stability, the resistive layer may influence rate capability, signal formation, and detector capacitance, altering timing performance. This work presents a comprehensive study of a resistive design, including an analytical model and finite-element simulations to quantify rate-dependent gain reduction due to ohmic voltage drop on the resistive layer. An analytical solution for the voltage across a finite-size resistive layer is derived, and a numerical model is developed to evaluate gain suppression under intense particle fluxes. The impact of the resistive layer on signal formation is investigated using time-dependent weighting fields and the Garfield++ simulation framework. The contribution of signal components induced by the resistive layer is quantified, and preservation of the signal leading edge is found for surface resistivities above 100 kohm per square. Single-channel resistive-anode prototypes were designed, constructed, and experimentally characterized. Laboratory measurements using single photoelectrons and power spectral density analysis show the predicted reduction in signal amplitude while preserving the leading edge. Muon beam tests with CsI and DLC photocathodes demonstrate a time resolution of 11.5 ps for CsI, comparable to 11.9 ps for the metallic-anode device, showing the suitability of the resistive design for precision timing applications.

physics.ins-det↗

arXiv2025

Precise $^{136}$Xe Double Beta Decay Measurement in PandaX-4T with Implications on the Nuclear Matrix Elements and Majorons

The continuous spectrum of double beta decay ($\beta\beta$) provides a sensitive probe to test the predictions of the standard model and to search for signatures of new physics beyond it. We present a comprehensive analysis of the $^{136}$Xe $\beta\beta$ spectrum utilizing $39.1 \pm 0.7~\textrm{kg}\cdot\textrm{yr}$ of $^{136}$Xe exposure from the PandaX-4T experiment. The analysis yields the most precise measurement to date of the $^{136}$Xe two-neutrino double beta decay ($2\nu\beta\beta$) half-life, $(2.14 \pm 0.05) \times 10^{21}$ years, the uncertainty of which is reduced by a factor of 2 compared to our previous result. We measure the parameter $\xi_{31}^{2\nu}$, defined as the ratio between the subleading and leading components of the $^{136}$Xe $2\nu\beta\beta$ nuclear matrix element, to be $0.59^{+0.41}_{-0.38}$, which is consistent with theoretical predictions. We also search for Majoron-emitting modes of $^{136}$Xe $\beta\beta$, establishing the most stringent limit for the spectral index $n=7$.

nucl-ex↗

arXiv2025

GPS-Synchronized Monitoring of Core-collapse Supernova Bursts with PandaX-4T via Coherent Elastic Neutrino Nuclear Scattering

The landmark detection of neutrinos from SN1987A marked the dawn of neutrino astrophysics. The neutrino burst provided essential insights into fundamental properties of neutrinos, and served as key probes of stellar evolution and supernova dynamics. The recent advancement in coherent elastic neutrino-nucleus scattering enables the detection of core-collapse supernova burst neutrinos using tonne-scale liquid xenon detectors originally designed for dark matter direct detection. Leveraging this capability, we developed and deployed an online supernova monitoring system for the PandaX-4T experiment. This system features a GPS module with millisecond-level timing precision, a low false-alarm rate, and high sensitivity to galactic core-collapse supernova explosion events. The methodology is robust, directly scalable, and planned for implementation in the next-generation PandaX-20T experiment.

hep-ex↗

arXiv2025

Probing scalar-neutrino and scalar-dark-matter interactions with PandaX-4T

Scalar-mediated interactions may exist among neutrinos, dark matter particles, or between the two. Double $\beta$-decay experiments provide a powerful tool to probe such exotic interactions. Using $^{136}$Xe double $\beta$-decay data from PandaX-4T, we perform the first direct spectral search in the energy range of 20 to 2800~keV, setting the most stringent limits to date on scalar-mediated neutrino self-interactions for mediator masses below 2~MeV$/c^2$. These results place significant constraints on models invoking such interactions to alleviate the Hubble Tension. Assuming the same scalar also mediates dark matter self-interactions, constraints on the dark matter-scalar interactions can be placed in conjunction with cosmological constraints.

hep-ex↗

arXiv2025

Tomographic beta-gamma spectroscopy of nuclear beta decay

Nuclear $\beta$ decay, a sensitive probe of nuclear structure and weak interactions, has become a precision test bed for physics beyond the Standard Model, driven by recent advances in spectrometric techniques. Here we introduce tomographic $\beta$-$\gamma$ spectroscopy (TBGS) of nuclear $\beta$ decay, a method that detects the energies of $\beta$, $\gamma$, and internal conversion electrons while simultaneously reconstructing the energy deposition vertices. Using the PandaX-4T detector operated as a TBGS, we obtain a precise and unbiased decay scheme of $^{214}$Pb, a key background isotope in searches for dark matter and Majorana neutrinos. For the first time, transitions of $^{214}$Pb to both the ground and excited states of $^{214}$Bi are measured concurrently, revealing discrepancies in branching ratios of up to 4.7$\sigma$ relative to previous evaluations. Combined with state-of-the-art theoretical spectral-shape calculations, these results establish a new benchmark for background modelling in rare-event searches and highlight the potential of TBGS as a versatile tool for fundamental physics and nuclear applications.

nucl-ex↗

arXiv2025

TGPO: Temporal Grounded Policy Optimization for Signal Temporal Logic Tasks

Learning control policies for complex, long-horizon tasks is a central challenge in robotics and autonomous systems. Signal Temporal Logic (STL) offers a powerful and expressive language for specifying such tasks, but its non-Markovian nature and inherent sparse reward make it difficult to be solved via standard Reinforcement Learning (RL) algorithms. Prior RL approaches focus only on limited STL fragments or use STL robustness scores as sparse terminal rewards. In this paper, we propose TGPO, Temporal Grounded Policy Optimization, to solve general STL tasks. TGPO decomposes STL into timed subgoals and invariant constraints and provides a hierarchical framework to tackle the problem. The high-level component of TGPO proposes concrete time allocations for these subgoals, and the low-level time-conditioned policy learns to achieve the sequenced subgoals using a dense, stage-wise reward signal. During inference, we sample various time allocations and select the most promising assignment for the policy network to rollout the solution trajectory. To foster efficient policy learning for complex STL with multiple subgoals, we leverage the learned critic to guide the high-level temporal search via Metropolis-Hastings sampling, focusing exploration on temporally feasible solutions. We conduct experiments on five environments, ranging from low-dimensional navigation to manipulation, drone, and quadrupedal locomotion. Under a wide range of STL tasks, TGPO significantly outperforms state-of-the-art baselines (especially for high-dimensional and long-horizon cases), with an average of 31.6% improvement in task success rate compared to the best baseline. The code will be available at https://github.com/mengyuest/TGPO

cs.RO↗

arXiv2025

Search for Light Inelastic Dark Matter with Low-Energy Ionization Signatures in PandaX-4T

Direct detection of light dark matter (DM) is generally difficult due to its small recoil energy. The inelastic scattering of DM can produce unique signatures in the DM direct detection experiments. Using the low-energy unpaired ionization data from PandaX-4T, we newly analyze the probe of the exothermic inelastic dark matter (ineDM). We demonstrate that PandaX-4T can probe the ineDM mass-splitting down to 0.05 keV and probe the ineDM mass to the sub-GeV range. For the ineDM with a dark photon mediator, we use the PandaX-4T data to impose stringent bounds on the mixing parameter between the dark photon and photon.

hep-ph↗

arXiv2025

Precise Measurement of $^{216}$Po Half-life with Exact Parent-daughter Pairing in PandaX-4T

We report a precise measurement of $^{216}\rm Po$ half-life using the PandaX-4T liquid xenon time projection chamber (TPC). $^{220}\rm Rn $, emanating from a $^{228}\rm Th $ calibration source, is injected to the detector and undergoes successive $\alpha$ decays, first to $^{216}\rm Po$ and then to $^{212}\rm Pb$. PandaX-4T detector measures the 5-dimensional (5D) information of each decay, including time, energy, and 3-dimensional positions. Therefore, we can identify the $^{220}\rm Rn $ and $^{216}\rm Po$ decay events and pair them exactly to extract the lifetime of each $^{216}\rm Po$. With a large data set and high-precision $^{220}\rm $Rn-$^{216}\rm $Po pairing technique, we measure the $^{216}\rm Po$ half-life to be $143.7\pm0.5$ ms, which is the most precise result to date and agrees with previously published values. The leading precision of this measurement demonstrates the power of 5D calorimeter and the potential of exact parent-daughter pairing in the xenon TPC.

nucl-ex↗

arXiv2025

Search for Light Dark Matter with 259-day data in PandaX-4T

We present a search for light dark matter particles through their interactions with atomic electrons and nucleons, utilizing PandaX-4T data with an effective exposure of 1.04 tonne$\cdot$year for ionization-only data and 1.20 tonne$\cdot$year for paired data. Our analysis focuses on the energy range (efficiency$>$0.01) of approximately 0.33 to 3 keV for nuclear recoils, and from 0.04 to 0.39 keV for electronic recoils. We establish the most stringent constraints on spin-independent dark matter-nucleon interactions within a mass range of 2.5 to 5.0 GeV/$c^2$, spin-dependent neutron-only interactions within 2.0 to 5.3 GeV/$c^2$, and spin-dependent proton-only interactions within 2.0 to 3.8 GeV/$c^2$. Their corresponding limits at 3\,GeV/$c^2$ are $1.1 \times 10^{-43}$, $1.6 \times 10^{-38}$, and $5.6 \times 10^{-37}$\,cm$^2$, respectively. Additionally, our results improve the upper limits on the dark matter-electron scattering cross-section by a factor of 1.5 and 9.3 for heavy and light mediator scenarios respectively within 50 MeV/$c^2$ to 10 GeV/$c^2$, compared with previous best results.

hep-ex↗

arXiv2025

User Long-Term Multi-Interest Retrieval Model for Recommendation

User behavior sequence modeling, which captures user interest from rich historical interactions, is pivotal for industrial recommendation systems. Despite breakthroughs in ranking-stage models capable of leveraging ultra-long behavior sequences with length scaling up to thousands, existing retrieval models remain constrained to sequences of hundreds of behaviors due to two main challenges. One is strict latency budget imposed by real-time service over large-scale candidate pool. The other is the absence of target-aware mechanisms and cross-interaction architectures, which prevent utilizing ranking-like techniques to simplify long sequence modeling. To address these limitations, we propose a new framework named User Long-term Multi-Interest Retrieval Model(ULIM), which enables thousand-scale behavior modeling in retrieval stages. ULIM includes two novel components: 1)Category-Aware Hierarchical Dual-Interest Learning partitions long behavior sequences into multiple category-aware subsequences representing multi-interest and jointly optimizes long-term and short-term interests within specific interest cluster. 2)Pointer-Enhanced Cascaded Category-to-Item Retrieval introduces Pointer-Generator Interest Network(PGIN) for next-category prediction, followed by next-item retrieval upon the top-K predicted categories. Comprehensive experiments on Taobao dataset show that ULIM achieves substantial improvement over state-of-the-art methods, and brings 5.54% clicks, 11.01% orders and 4.03% GMV lift for Taobaomiaosha, a notable mini-app of Taobao.

cs.IR↗

arXiv2025

A Generative Re-ranking Model for List-level Multi-objective Optimization at Taobao

E-commerce recommendation systems aim to generate ordered lists of items for customers, optimizing multiple business objectives, such as clicks, conversions and Gross Merchandise Volume (GMV). Traditional multi-objective optimization methods like formulas or Learning-to-rank (LTR) models take effect at item-level, neglecting dynamic user intent and contextual item interactions. List-level multi-objective optimization in the re-ranking stage can overcome this limitation, but most current re-ranking models focus more on accuracy improvement with context. In addition, re-ranking is faced with the challenges of time complexity and diversity. In light of this, we propose a novel end-to-end generative re-ranking model named Sequential Ordered Regression Transformer-Generator (SORT-Gen) for the less-studied list-level multi-objective optimization problem. Specifically, SORT-Gen is divided into two parts: 1)Sequential Ordered Regression Transformer innovatively uses Transformer and ordered regression to accurately estimate multi-objective values for variable-length sub-lists. 2)Mask-Driven Fast Generation Algorithm combines multi-objective candidate queues, efficient item selection and diversity mechanism into model inference, providing a fast online list generation method. Comprehensive online experiments demonstrate that SORT-Gen brings +4.13% CLCK and +8.10% GMV for Baiyibutie, a notable Mini-app of Taobao. Currently, SORT-Gen has been successfully deployed in multiple scenarios of Taobao App, serving for a vast number of users.

cs.IR↗