arXiv subjects

Haijun Yang

Publications and source records attributed to Haijun Yang.

At least 19 recordsLinked to original sources

arXiv2026

Prospective study of light dark matter search in positron beam mode with DarkSHINE experiment initiative

We perform the prospective study on searching for invisibly decayed dark photons ($A^{\prime}$) in positron-on-fixed-target (POT) scheme with the DarkSHINE experiment simulation setup. In the positron-on-fixed-target scheme, two additional production channels of dark photons via annihilation with extranuclear electrons are present: non-resonant t-channel ($e^+e^-N \to \gamma A^{\prime}N$) and resonant s-channel ($e^+e^-N \to A^{\prime}N$), alongside bremsstrahlung emission similar to electron-on-fixed-target scheme. Based on a Geant4 full detector simulation of an 8 GeV positron beam with $3 \times 10^{14}$ POT events, we developed an analysis strategy using missing energy and momentum signatures across three orthogonal signal regions optimized for these channels. Our results indicate that the additional annihilation channels of dark photon production improve the dark photon invisible decay search sensitivity, improving the exclusion limits by approximately two orders of magnitude compared to existing constraints in the electron-on-fixed target (EOT) scheme, particularly near the center-of-mass energy threshold.

hep-ex↗

arXiv2026

Assessing Parameter Redundancy in Transformers for Jet Tagging

Transformer-based jet taggers, such as the Particle Transformer (ParT) and the More-Interaction Particle Transformer (MIParT), achieve excellent discrimination by exploiting correlations among jet constituents, but often require more trainable parameters than earlier deep-learning taggers. In this paper, we investigate whether comparable discriminating power can be achieved with substantially fewer parameters. We introduce an hourglass structure that replaces the feed-forward networks (FFNs) in the attention blocks while leaving the particle-interaction attention unchanged. We also introduce a lightweight particle-embedding layer to replace the original dense embedding network. Applying both modifications to ParT and MIParT yields the hourglass (HG) variants ParT-HG and MIParT-HG, respectively. We evaluate both models on benchmark datasets for top tagging and quark-gluon discrimination. Both variants retain comparable tagging performance, including background rejection at fixed signal efficiencies, while using only approximately 48% and 39.7% of the parameters of their respective baselines. On the larger JetClass dataset, accuracy and AUC decrease by less than 1%, and background rejection also decreases for several signal classes. Overall, our approach provides an alternative way to reduce the parameter count of Transformer jet taggers while largely retaining their tagging performance.

hep-ph↗

arXiv2026

SiPM non-linearity studies in beam tests with scintillating crystals

High-granularity homogeneous electromagnetic calorimeters based on scintillating crystals and silicon photomultipliers (SiPMs) are a promising option for future $e^{+}e^{-}$ Higgs factories, where both excellent energy resolution and a very large dynamic range are required. In this work, the non-linear response of high-pixel-density SiPMs with pixel pitches of 6--10~$\mu$m coupled to BGO and BSO crystals is studied under realistic beam conditions. A dual-end readout scheme with an attenuated reference SiPM was employed to precisely calibrate the deposited energy and the corresponding number of photoelectrons over a wide dynamic range. Beam tests were carried out at the CERN SPS H2 beamline using high-energy electrons, with a tungsten pre-shower and variable incident angles to enhance energy deposition. The measurements directly quantify the non-linear response of SiPMs to scintillation light over an extended dynamic range. For BGO-coupled Hamamatsu SiPMs, deviations from linearity of about 20\% are observed at $5\times10^{5}$ photoelectrons, while larger deviations are measured for the tested NDL devices and for configurations with faster BSO scintillation.

physics.ins-det↗

arXiv2026

Conceptual Design of a Novel Highly Granular Crystal Electromagnetic Calorimeter for Future Higgs Factories

Next-generation high-energy electron-positron colliders, operating as Higgs factories, require an unprecedented jet energy resolution for precision measurements of Higgs and Z/W bosons. To address this challenge, a conceptual design is presented for a novel high-granularity crystal electromagnetic calorimeter that combines the superior intrinsic energy resolution of a homogeneous calorimeter with the fine segmentation required for particle-flow reconstruction. The crystal electromagnetic calorimeter design is based on orthogonally arranged long scintillating crystal bars read out by silicon photomultipliers (SiPMs) at both ends. Key design specifications were established through comprehensive simulation studies. Critical technical considerations, including crystal choices, photosensors, electronics, mechanical support, and radiation damage, are discussed. A dedicated digitisation framework was developed to realistically model effects from the crystal, SiPMs, and readout electronics. The performance of a single calorimeter module was evaluated using simulated electron showers. Simulation results for a single module demonstrate an excellent electromagnetic energy resolution of $1.12\%/\sqrt{E(\mathrm{GeV})}\oplus0.22\%$ and an energy linearity within $\pm0.5\%$ for electrons from 3 GeV to 100 GeV. The performance significantly exceeds the design requirement of $\leq 3\%/\sqrt{E(\mathrm{GeV})}\oplus1\%$. The results establish the feasibility of the proposed high-granularity crystal calorimeter concept and point to a promising pathway toward the precision calorimetry required for future high-energy electron-positron collider experiments.

physics.ins-det↗

arXiv2025

Deep-learning jet flavor tagging for precision hadronic Higgs measurements at future $e^+e^-$ Higgs factories

Precise measurements of Higgs decays into quarks and gluons are essential for probing the Yukawa couplings of the Higgs boson and testing the flavor structure of the Standard Model. We investigate the process $e^+e^- \to ZH$ at $\sqrt{s}=240~\mathrm{GeV}$ at a future $e^+e^-$ Higgs factory, taking the CEPC design as a benchmark. The analysis focuses on events with $Z\to\nu\bar{\nu}$ and hadronic Higgs decays $H\to b\bar{b}$, $c\bar{c}$, $s\bar{s}$ and $gg$. Jet flavor is identified using state-of-the-art particle-level deep neural network taggers (ParticleNet, Particle Transformer and More-Interaction Particle Transformer), whose per-jet outputs are combined with global event observables in a two-stage analysis employing XGBoost classifiers to separate the four Higgs decay modes from the dominant two- and four-fermion Standard Model backgrounds. Assuming an integrated luminosity of $20~\mathrm{ab}^{-1}$, we obtain projected relative precision on $\sigma(ZH)\times\mathrm{Br}(H\to X)$ of 0.17% for $X=b\bar{b}$, 1.06% for $c\bar{c}$, 0.50% for $gg$ and 68% for $s\bar{s}$. Compared with the CEPC published results, the precisions for $H\to c\bar{c}$ and $H\to gg$ are improved by about 43% and 29%, respectively. For $H\to s\bar{s}$ we present a quantitative sensitivity estimation corresponding to a statistical significance of about $1.5\sigma$. These results highlight the potential of deep-learning-based jet flavor tagging for precision studies of Higgs decays at future $e^+e^-$ Higgs factories.

hep-ph↗

arXiv2025

Higgs Boson CP Properties and Effective Field Theory Measurements from the ATLAS Experiment at the LHC

This proceedings presents a concise overview of the Higgs boson's charge-conjugation and parity (CP) properties and constraints on Effective Field Theory (EFT) operators, derived from the ATLAS experiment at the Large Hadron Collider (LHC). Using proton$\textendash$proton collision data with integrated luminosities of up to 140 fb$^{-1}$ at $\sqrt{s} = 13$ TeV, the ATLAS collaboration systematically probe the CP nature of the Higgs boson's couplings to fermions ($\tau$ leptons, bottom quarks, and top quarks) and bosons ($W$, $Z$, and $\gamma$) across diverse decay final states. The EFT framework is used to parameterize Beyond the Standard Model (BSM) effects via dimension-6 operators, enabling model-independent constraints on CP violation and new physics scales. The main focus is comparison of measurement characteristics and sensitivity across different final states: (1) $H \to \tau\tau$ (semileptonic/hadronic decays) for light fermion couplings; (2) $H \to \gamma\gamma$ and $H \to bb$ in $t\bar{t}H/tH$ processes for heavy fermion couplings; (3) $H \to WW^* \to l\nu l\nu$, $H \to ZZ^* \to 4l$, and vector boson fusion (VBF) $H \to \tau\tau/\gamma\gamma$ for boson couplings; and (4) double Higgs ($HH$) production for self-couplings. All measurements are consistent with the Standard Model (SM) prediction of a CP-even Higgs boson ($J^{CP} = 0^{++}$), with no evidence of CP violation. The most stringent constraint on the CP-odd EFT parameter $c_{H\tilde{W}}$ is obtained from VBF $H \to \tau\tau$ ($c_{H\tilde{W}} \in [-0.23, 0.70]$ at 95\% CL), highlighting the unique sensitivity of this channel. Complementary constraints from other final states reinforce the robustness of SM consistency and provide a foundation for future searches.

hep-ex↗

arXiv2025

DarkSHINE: Search for Light Dark Matter at the SHINE Facility in Shanghai

DarkSHINE is an electron fixed target experiment under proposal that aims to probe light dark matter in the MeV-GeV mass range via the invisible decay of dark photons, leveraging the High repetition rate 8 GeV electron beam from the Shanghai High repetition-rate XFEL and Extreme Light Facility. This proceeding presents the core detector design of the experiment, the simulation framework, and the prospects of the physics. The detector system integrates an AC-coupled Low Gain Avalanche Diode silicon tracker, a LYSO crystal electromagnetic calorimeter, and a scintillator-based hadronic calorimeter, all optimized for SHINE high-radiation, high-rate environment. The prototype tests at DESY and CERN have validated key performance metrics, including a spatial resolution of 6.5-8.2 microns for silicon strip sensor, an electromagnetic calorimeter energy resolution of 1.8%. Based on MC simulations and 9E14 EOT, the DarkSHINE experiment is expected to rule out most of the sensitive regions predicted by popular dark photon models.

hep-ex↗

arXiv2025

Development of the CEPC analog hadron calorimeter prototype

The Circular Electron Positron Collider (CEPC) is a next-generation electron$-$positron collider proposed for the precise measurement of the properties of the Higgs boson. To emphasize boson separation and jet reconstruction, the baseline design of the CEPC detector was guided by the particle flow algorithm (PFA) concept. As one of the calorimeter options, the analogue hadron calorimeter (AHCAL) was proposed. The CEPC AHCAL comprises a 40-layer sandwich structure using steel plates as absorbers and scintillator tiles coupled with silicon photomultipliers (SiPM) as sensitive units. To validate the feasibility of the AHCAL option, a series of studies were conducted to develop a prototype. This AHCAL prototype underwent an electronic test and a cosmic ray test to assess its performance and ensure it was ready for three beam tests performed in 2022 and 2023. The test beam data is currently under analysis, and the results are expected to deepen our understanding of hadron showers, validate the concept of Particle Flow Algorithm (PFA), and ultimately refine the design of the CEPC detector.

physics.ins-det↗

arXiv2025

FedSDWC: Federated Synergistic Dual-Representation Weak Causal Learning for OOD

Amid growing demands for data privacy and advances in computational infrastructure, federated learning (FL) has emerged as a prominent distributed learning paradigm. Nevertheless, differences in data distribution (such as covariate and semantic shifts) severely affect its reliability in real-world deployments. To address this issue, we propose FedSDWC, a causal inference method that integrates both invariant and variant features. FedSDWC infers causal semantic representations by modeling the weak causal influence between invariant and variant features, effectively overcoming the limitations of existing invariant learning methods in accurately capturing invariant features and directly constructing causal representations. This approach significantly enhances FL's ability to generalize and detect OOD data. Theoretically, we derive FedSDWC's generalization error bound under specific conditions and, for the first time, establish its relationship with client prior distributions. Moreover, extensive experiments conducted on multiple benchmark datasets validate the superior performance of FedSDWC in handling covariate and semantic shifts. For example, FedSDWC outperforms FedICON, the next best baseline, by an average of 3.04% on CIFAR-10 and 8.11% on CIFAR-100.

cs.LG↗

arXiv2025

Particle-level transformers for 95 GeV Higgs boson searches at future $e^+e^-$ Higgs factories

Motivated by several mild excesses around 95~GeV, we investigate the prospects for a light scalar $S$ produced via Higgsstrahlung, $e^+e^- \to Z(\mu^+\mu^-)S$, at future $e^+e^-$ Higgs factories. We take the CEPC as a benchmark, with a center-of-mass energy of $\sqrt{s}=240$ GeV and an integrated luminosity of $L=20~\mathrm{ab}^{-1}$. We focus on the decay modes $S\to\tau^+\tau^-$ and $S\to b\bar b$. To maximize sensitivity, we employ the particle-level transformer networks Particle Transformer (ParT) and its more-interactive variant MIParT, which exploit the features of all reconstructed objects and their correlations. For a representative signal benchmark, this approach improves the expected statistical precision on the signal strength by factors of 2.3 in the $\tau^+\tau^-$ channel and 1.4 in the $b\bar b$ channel compared to a cut-based analysis. Within the flipped Next-to-Two-Higgs-Doublet Model (N2HDM-F), the CEPC can measure the signal strength with a statistical precision down to 1.0% in the $\tau^+\tau^-$ channel and 0.69% in the $b\bar b$ channel using MIParT. It can achieve a $5\sigma$ discovery for $\mu_{\tau\tau}^{ZS}>1.6\times10^{-2}$ or $\mu_{bb}^{ZS}>5.0\times10^{-3}$, and reach 1% precision for $\mu_{\tau\tau}^{ZS}>0.93$ or $\mu_{bb}^{ZS}>0.14$. These gains are expected to qualitatively carry over to other future lepton colliders such as FCC-ee and the ILC. Our results demonstrate the potential of particle-level machine-learning techniques to strengthen light Higgs searches at future $e^+e^-$ Higgs factories.

hep-ph↗

arXiv2025

Emergence of Homophily under Contextual Mechanisms

This paper introduces a tractable model to study incentive-compatible homophily under both external environments--such as exogenous shocks or policy constraints--and internal micromotives based on interactive attributes. We propose a set of invariants that capture main features of homophily and the well-defined partition dynamics leading to perfect global homophily. The criteria for homophily formation are characterized via isomorphism. Within this framework, we demonstrate the emergence of macro-complementarity coupled with micro-substitution, where local individuals' utility function is nonlinear and submodular. We discuss two types of financial networks and their differences: hierarchical structure emerges from short-term liquidity transactions, whereas core-periphery structure is based on a stock-based perspective.

econ.TH↗

arXiv2025

Optimisation of the vertex detector and measurement of Higgs decays to second-generation quarks at the CEPC

The vertex detector is crucial for precision measurements of the Higgs boson at the electron-positron Higgs factory. Benchmarked with $H \to c\bar{c}$ and $H \to s\bar{s}$ measurements in the $\nu\bar{\nu}H$ channel, we perform an optimisation study on the inner radius and spatial resolution of the vertex detector using the Jet Origin Identification (JOI) framework, which determines the parton flavor of jets using advanced Artificial Intelligence (AI) algorithm. We observe that, compared to the reference detector configuration, halving the inner radius and spatial resolution improves the transverse and longitudinal impact parameter resolution approximately by a factor of two, while increasing the accuracy and significance of the $H \to c\bar{c}/s\bar{s}$ measurement by 4\% and 8\%, respectively. Conversely, doubling these parameters results in comparable degradation, with variations in the inner radius being the dominant factor. Our results provide guidance for detector design and highlight promising prospects for identifying the $H \to s\bar{s}$ decay mode at future Higgs factories.

hep-ex↗

arXiv2025

Testing a 95 GeV Scalar at the CEPC with Machine Learning

Several possible excesses around 95 GeV hint at an additional light scalar beyond the Standard Model. We examine the capability of the CEPC to test this hypothesis in the Higgsstrahlung channel $e^{+}e^{-} \to ZS$ with $Z \to\mu^{+}\mu^{-}$ and $S\to\tau^{+}\tau^{-}$. Full detector simulation shows that the optimal center-of-mass energy to study the 95 GeV light scalar is 210 GeV. A deep neural network classifier reduces the luminosity required for discovery by half. At $L = 20~\mathrm{ab}^{-1}$, the CEPC's $5\sigma$ sensitivity to the signal strength $\mu_{\tau\tau}^{ZS}$ reaches 0.016 and 0.020 for $\sqrt{s} =$ 210 GeV and 240 GeV, respectively. The corresponding thresholds for a 5% precision measurement are $\mu_{\tau\tau}^{ZS} > 0.10$ and $>0.12$. At $\sqrt{s}=$ 210 GeV (240 GeV), $5\sigma$ coverage of all N2HDM-Flipped samples with $\chi^2_{h_{95}}<7.82$ requires $L=800\ \mathrm{fb}^{-1}$ (1.22 $\mathrm{ab}^{-1}$). These results establish a 210 GeV run, augmented by machine-learning selection, as the most efficient strategy to confirm or refute the 95 GeV excess at future lepton colliders.

hep-ph↗

arXiv2024

Design of High-speed readout electronics for the DarkSHINE electromagnetic calorimeter

The DarkSHINE experiment aims to search for dark photons by measuring the energy loss of the electrons recoiled from fixed-target. Its electromagnetic calorimeter is primarily responsible for accurately reconstructing the energy of the recoil electrons and bremsstrahlung photons. The performance of the electromagnetic calorimeter is crucial, as its energy measurement precision directly determines the sensitivity to the search for dark photons. The DarkSHINE electromagnetic calorimeter uses LYSO crystals to form a fully absorptive electromagnetic calorimeter. It utilizes SiPMs to detect scintillation light in the crystals, and its readout electronics system deduces the deposited energy in the crystals by measuring the number of photoelectric signals generated by the SiPMs. The DarkSHINE electromagnetic calorimeter aims to operate at an event rate of 1-10 MHz, detecting energies ranging from 1 MeV to 1 GeV. To meet the requirements of high energy measurement precision, high event rate, and large dynamic range, we have researched and designed a readout electronics system based on dual-channel high-speed ADCs and a customized DAQ. The front-end amplification part of this system uses low-noise trans-impedance amplifiers to achieve high-precision waveform amplification. It successfully achieves a dynamic range up to a thousandfold through a double-gain readout scheme. The digital part uses 1 GSPS high-speed ADCs to achieve non-dead-time, high-precision waveform digitization. The DAQ part uses JESD204B high-speed serial protocol to read out the signal from ADC, and transmit it to PC software for processing and storage. Test results show a signal-to-noise ratio greater than 66 dBFS and an ENOB greater than 10.6 bits. Energy spectra measurements have been conducted using LYSO crystals and SiPMs, and an energy resolution of 5.96% at the 2.6 MeV gamma peak of Th-232 has been achieved.

physics.ins-det↗

arXiv2024

Design of a LYSO Crystal Electromagnetic Calorimeter for DarkSHINE Experiment

This paper presents the design and optimization of a LYSO crystal electromagnetic calorimeter (ECAL) for the DarkSHINE experiment, which aims to search for dark photons as potential mediators of dark forces. The ECAL design was evaluated through comprehensive simulations, focusing on optimizing dimensions, material selection, energy distribution, and energy resolution. The ECAL configuration consists of 21$\times$21$\times$11 LYSO crystals, each measuring 2.5$\times$2.5$\times$4 cm$^3$, arranged in a staggered layout to improve signal detection efficiency. A 4 GeV energy dynamic range was established to ensure accurate energy measurements without saturation, which is essential for background rejection and signal identification. A detailed digitization model was developed to simulate the scintillation, SiPM, and ADC behaviors, providing a more realistic representation of detector performance. Additionally, the study assessed radiation damage in the ECAL region, highlighting the necessity of radiation-resistant scintillators and silicon sensors.

physics.ins-det↗

arXiv2024

Reconstructing Close Human Interactions from Multiple Views

This paper addresses the challenging task of reconstructing the poses of multiple individuals engaged in close interactions, captured by multiple calibrated cameras. The difficulty arises from the noisy or false 2D keypoint detections due to inter-person occlusion, the heavy ambiguity in associating keypoints to individuals due to the close interactions, and the scarcity of training data as collecting and annotating motion data in crowded scenes is resource-intensive. We introduce a novel system to address these challenges. Our system integrates a learning-based pose estimation component and its corresponding training and inference strategies. The pose estimation component takes multi-view 2D keypoint heatmaps as input and reconstructs the pose of each individual using a 3D conditional volumetric network. As the network doesn't need images as input, we can leverage known camera parameters from test scenes and a large quantity of existing motion capture data to synthesize massive training data that mimics the real data distribution in test scenes. Extensive experiments demonstrate that our approach significantly surpasses previous approaches in terms of pose accuracy and is generalizable across various camera setups and population sizes. The code is available on our project page: https://github.com/zju3dv/CloseMoCap.

cs.CV↗

arXiv2023

A Design of Hadronic Calorimeter for DarkSHINE Experiment

The sensitivity of the dark photon search through invisible decay final states in low background experiments significantly relies on the neutron and muon veto efficiency, which depends on the amount of material used and the design of detector geometry. This paper presents an optimized design of a hadronic calorimeter (HCAL) used for the DarkSHINE experiment, which is studied using a GEANT4-based simulation framework. The geometry is optimized by comparing a traditional design with uniform absorbers to one that uses different thicknesses at different locations of the detector, which enhances the efficiency of vetoing low-energy neutrons at the sub-GeV level. The overall size and total amount of material used in HCAL are optimized to be lower due to the load and budget requirements, while the overall performance is studied to meet the physical objectives.

physics.ins-det↗

arXiv2023

A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models

The springing up of Large Language Models (LLMs) has shifted the community from single-task-orientated natural language processing (NLP) research to a holistic end-to-end multi-task learning paradigm. Along this line of research endeavors in the area, LLM-based prompting methods have attracted much attention, partially due to the technological advantages brought by prompt engineering (PE) as well as the underlying NLP principles disclosed by various prompting methods. Traditional supervised learning usually requires training a model based on labeled data and then making predictions. In contrast, PE methods directly use the powerful capabilities of existing LLMs (i.e., GPT-3 and GPT-4) via composing appropriate prompts, especially under few-shot or zero-shot scenarios. Facing the abundance of studies related to the prompting and the ever-evolving nature of this field, this article aims to (i) illustrate a novel perspective to review existing PE methods, within the well-established communication theory framework; (ii) facilitate a better/deeper understanding of developing trends of existing PE methods used in four typical tasks; (iii) shed light on promising research directions for future PE methods.

cs.CL↗