arXiv subjects

Yao Ma

Publications and source records attributed to Yao Ma.

At least 55 records · Page 3Linked to original sources

arXiv2025

Singly heavy tetraquark resonant states with multiple strange quarks

We systematically investigate the S-wave singly heavy tetraquark systems containing two or three strange quarks, $Qs\bar{s}\bar{s}$, $Qn\bar{s}\bar{s}$ and $Qs\bar{s}\bar{n}\left( Q=c,b,n=u,d \right) $, within the constituent quark potential model. We solve the four-body Schrödinger equation using the Gaussian expansion method (GEM) and identify resonances via the complex scaling method (CSM). There are no bound states below the lowest two-meson thresholds. We obtain several compact resonances with $J^P=0^+,2^+$ in $Qs\bar{s}\bar{s}$, and $J^P=2^+$ in $Qn\bar{s}\bar{s}$ and $Qs\bar{s}\bar{n}$. The pole positions are mainly distributed around $7.0-7.2$ GeV (bottom) and $3.7-3.9$ GeV (charm), with widths from a few to several tens of MeV. These resonances decay into $D_sη^\prime ,{D_{(s)}^*}ϕ,{D_s}^*K^*$ and $D_s^*\bar{K}^*$ (and their bottom counterparts), providing targets for future experimental searches.

hep-ph↗

arXiv2025

Modeling Insider Filing Delays in Financial Markets with an Interpretable XGBoost Framework

Timely disclosure of insider transactions is a cornerstone of market transparency, yet delays in filing remain widespread and challenging to monitor at scale. This study introduces a comprehensive insider filing delay dataset spanning more than four million Form 4 transactions from 2002 to 2025, enriched with annotations on insider roles, governance attributes, and firm-level indicators. Building on these data, we present a hybrid framework that integrates a state-space encoder with an XGBoost classifier to capture temporal trading patterns while retaining interpretability essential for regulatory auditing. The framework consistently outperforms statistical models, deep sequence learners, and large language model baselines, achieving balanced gains in precision, recall, and F1-score. Feature ablation analyses highlight the predictive importance of insider history, spatiotemporal factors, and governance signals, shedding light on the behavioral drivers of both minor oversights and systematic violations. Beyond accuracy, the dataset and framework establish a reproducible benchmark for studying disclosure compliance, offering regulators and researchers transparent tools to strengthen market integrity.

cs.CE↗

arXiv2025

Peak of sound velocity, scale symmetry, and nuclear force in baryonic matter

The sound velocity in homogeneous matter has fundamental significance as it relates to the stiffness of the equation of state of compact star matter. In this work, we investigate the density evolution of the sound velocity in homogeneous {neutron matter at zero temperature} by using an effective field theory implemented with a conformal compensator -- the nonlinear realization of scale symmetry -- regarded as the source of the lightest scalar meson. We find that the peak of sound velocity emerges naturally in the intermediate density region, $(1-2.5)n_0$, without resorting to any transitions from hadron to exotic configurations or introducing new degrees of freedom. This phenomenon is not found in the Walecka-type models where the sigma meson is included in the linear-type approach, therefore it is an intrinsic character of the dilaton compensator approach through the matching of the QCD trace anomaly; a mechanism has not been found before, and it connects to the character of the lightest scalar meson. In addition, these observations shed light on how the hidden scale symmetry manifests in the nuclear medium from the unitarity limit in dilute matter to the dilaton limit in compact star matter.

nucl-th↗

arXiv2025

Tetraquark states in the quark model

We perform systematical investigations of heavy flavor tetraquark systems, including fully heavy $QQ\bar Q\bar Q$ ($Q=b,c$), doubly heavy $QQ^{(\prime)}\bar q\bar q$ ($q=u,d$), and singly heavy $Qs\bar q\bar q$ tetraquark systems, within the framework of quark potential model. We employ the Gaussian expansion method and complex scaling method to solve the four-body Hamiltonian and identify bound and resonant states. We further calculate the root mean square radii to study the spatial configurations of tetraquarks. Our calculations reveal a rich spectrum of tetraquark states exhibiting diverse spatial configurations. In particular, we find good candidates for experimental states $X(6900)$, $X(7200)$, $T_{cc}(3875)^+$, and $T_{\bar c\bar s0}^*(2870)$. The fully charmed tetraquark resonances $X(6900)$ and $X(7200)$ are compact teraquark states, while doubly charmed tetraquark bound state $T_{cc}(3875)^+$ and charm-strange tetraquark resonance $T_{\bar c\bar s0}^*(2870)$ are meson molecules. Additionally, more tetraquark bound and resonant states are predicted and may be searched for in future experiments.

hep-ph↗

arXiv2025

CryptGNN: Enabling Secure Inference for Graph Neural Networks

We present CryptGNN, a secure and effective inference solution for third-party graph neural network (GNN) models in the cloud, which are accessed by clients as ML as a service (MLaaS). The main novelty of CryptGNN is its secure message passing and feature transformation layers using distributed secure multi-party computation (SMPC) techniques. CryptGNN protects the client's input data and graph structure from the cloud provider and the third-party model owner, and it protects the model parameters from the cloud provider and the clients. CryptGNN works with any number of SMPC parties, does not require a trusted server, and is provably secure even if P-1 out of P parties in the cloud collude. Theoretical analysis and empirical experiments demonstrate the security and efficiency of CryptGNN.

cs.CR↗

arXiv2025

White Dwarf Structure and Binary Inspiral Gravitational Waves from Quantum Hadrodynamics

White dwarfs, one of the compact objects in the universe, play a crucial role in astrophysical research and provide a platform for exploring nuclear physics. In this work, we extend the relativistic mean field approach by using a Walecka-type quantum hadrodynamics model to capture the intricate structure of white dwarfs. We calculate nuclear properties, Coulomb energy, and photon energy within white dwarfs in a unified framework. By carefully calibrating the model parameters to align with nuclear matter properties, we successfully reproduce the structures of several elements in white dwarfs, such as the isotopes of $\rm C$ and $^{16}\rm O$, except for the unnaturally deeply bound state $^4$He. Furthermore, we predict the characteristics of white dwarfs composed of atom-like units and the gravitational waves stemming from binary white dwarf inspirals incorporating tidal deformability contributions up to the 2.5 post-Newtonian order. These results shed light on the structure of white dwarfs and provide valuable information for future gravitational wave detection. This methodological advancement allows for a cohesive analysis of white dwarfs, neutron stars, and the nuclear pasta within a unified theoretical framework.

nucl-th↗

arXiv2025

Heavy flavored hydrogen molecule systems

This study provides a comprehensive analysis of $S$-wave exotic hydrogen-like three-body systems ($ppμ^-$, $ppτ^-$, $μ^-μ^-p$, $τ^-τ^-p$, $pμ^-τ^-$) with spin-parity $J^P = 1/2^+$ and $3/2^+$, and four-body systems ($ppμ^-μ^-$, $ppτ^-τ^-$) with $J^P = 0^+$, $1^+$, and $2^+$. We use complex scaling and Gaussian expansion methods to solve the complex-scaled Schrödinger equation and obtain possible bound and quasi-bound states. The resulting binding energies range from $-33.8$~keV to $-340$~eV. Notably, we present the first theoretical estimation of the bound-state energy levels of $ppμ^-μ^-$ and $ppτ^-τ^-$, which is of significant importance for understanding exotic few-body Coulomb systems. We further analyze spin configurations and root-mean-square radii to elucidate the spatial structure of these bound and quasi-bound states. Our results reveal that $K$-type spatial configurations play a crucial role in accurately describing bound and quasi-bound states in the hydrogen-molecule-like systems $ppμ^-μ^-$ and $ppτ^-τ^-$. Incorporating $K$-type configurations significantly alters the mass spectra of these states. Future muon colliders and muon facilities may offer promising platforms for the possible copious production of such heavy flavored hydrogen molecules and molecular ions. For instance, scattering processes such as $2μ^- + \mathrm{H_2} \to \mathrm{H_{2μ}} + 2e^-$, $μ^- + \mathrm{H_2} \to \mathrm{H_{μe}} + e^-$, and $μ^- + \mathrm{H_2^+} \to \mathrm{H_{2μ}^+} + e^-$ could be utilized, facilitating detailed studies of intriguing states such as $\mathrm{H_{2μ}}$, $\mathrm{H_{μe}}$, and $\mathrm{H_{2μ}^+}$.

physics.atom-ph↗

arXiv2025

Quantum-Safe Identity Verification using Relativistic Zero-Knowledge Proof Systems

Identity verification is the process of confirming an individual's claimed identity, which is essential in sectors like finance, healthcare, and online services to ensure security and prevent fraud. However, current password/PIN-based identity solutions are susceptible to phishing or skimming attacks, where malicious intermediaries attempt to steal credentials using fake identification portals. Alikhani et al. [Nature, 2021] began exploring identity verification through graph coloring-based relativistic zero-knowledge proofs (RZKPs), a key cryptographic primitive that enables a prover to demonstrate knowledge of secret credentials to a verifier without disclosing any information about the secret. Our work advances this field and addresses unresolved issues: From an engineering perspective, we relax further the relativistic constraints from 60m to 30m, and significantly enhance the stability and scalability of the experimental demonstration of the 2-prover graph coloring-based RZKP protocol for near-term use cases. At the same time, for long-term security against entangled malicious provers, we propose a modified protocol with comparable computation and communication costs, we establish an upper bound on the soundness parameter for this modified protocol. On the other hand, we extend the two-prover, two-verifier setup to a three-prover configuration, demonstrating the security of such relativistic protocols against entangled malicious provers.

cs.CR↗

arXiv2025

Multi-Agent Reinforcement Learning for Dynamic Pricing in Supply Chains: Benchmarking Strategic Agent Behaviours under Realistically Simulated Market Conditions

This study investigates how Multi-Agent Reinforcement Learning (MARL) can improve dynamic pricing strategies in supply chains, particularly in contexts where traditional ERP systems rely on static, rule-based approaches that overlook strategic interactions among market actors. While recent research has applied reinforcement learning to pricing, most implementations remain single-agent and fail to model the interdependent nature of real-world supply chains. This study addresses that gap by evaluating the performance of three MARL algorithms: MADDPG, MADQN, and QMIX against static rule-based baselines, within a simulated environment informed by real e-commerce transaction data and a LightGBM demand prediction model. Results show that rule-based agents achieve near-perfect fairness (Jain's Index: 0.9896) and the highest price stability (volatility: 0.024), but they fully lack competitive dynamics. Among MARL agents, MADQN exhibits the most aggressive pricing behaviour, with the highest volatility and the lowest fairness (0.5844). MADDPG provides a more balanced approach, supporting market competition (share volatility: 9.5 pp) while maintaining relatively high fairness (0.8819) and stable pricing. These findings suggest that MARL introduces emergent strategic behaviour not captured by static pricing rules and may inform future developments in dynamic pricing.

cs.LG↗

arXiv2025

Exploring a Hybrid Deep Learning Approach for Anomaly Detection in Mental Healthcare Provider Billing: Addressing Label Scarcity through Semi-Supervised Anomaly Detection

The complexity of mental healthcare billing enables anomalies, including fraud. While machine learning methods have been applied to anomaly detection, they often struggle with class imbalance, label scarcity, and complex sequential patterns. This study explores a hybrid deep learning approach combining Long Short-Term Memory (LSTM) networks and Transformers, with pseudo-labeling via Isolation Forests (iForest) and Autoencoders (AE). Prior work has not evaluated such hybrid models trained on pseudo-labeled data in the context of healthcare billing. The approach is evaluated on two real-world billing datasets related to mental healthcare. The iForest LSTM baseline achieves the highest recall (0.963) on declaration-level data. On the operation-level data, the hybrid iForest-based model achieves the highest recall (0.744), though at the cost of lower precision. These findings highlight the potential of combining pseudo-labeling with hybrid deep learning in complex, imbalanced anomaly detection settings.

cs.LG↗

arXiv2025

Template-Based Schema Matching of Multi-Layout Tenancy Schedules:A Comparative Study of a Template-Based Hybrid Matcher and the ALITE Full Disjunction Model

The lack of standardized tabular formats for tenancy schedules across real estate firms creates significant inefficiencies in data integration. Existing automated integration methods, such as Full Disjunction (FD)-based models like ALITE, prioritize completeness but result in schema bloat, sparse attributes and limited business usability. We propose a novel hybrid, template-based schema matcher that aligns multi-layout tenancy schedules to a predefined target schema. The matcher combines schema (Jaccard, Levenshtein) and instance-based metrics (data types, distributions) with globally optimal assignments determined via the Hungarian Algorithm. Evaluation against a manually labeled ground truth demonstrates substantial improvements, with grid search optimization yielding a peak F1-score of 0.881 and an overall null percentage of 45.7%. On a separate ground truth of 20 semantically similar column sets, ALITE achieves an F1-score of 0.712 and 75.6% nulls. These results suggest that combining structured business knowledge with hybrid matching can yield more usable and business-aligned schema mappings. The approach assumes cleanly extracted tabular input, future work could explore extending the matcher to support complex, composite tables.

cs.DB↗

arXiv2025

The ${ϕNN,J/ψNN,η_c NN}$ systems based on HAL QCD interactions

We investigate the existence of bound states and resonances in the ${ϕNN, J/ψNN, η_c NN}$ systems using HAL QCD interactions for ${ϕN, J/ψN}$, and ${η_c N}$. We employ the Gaussian expansion method to solve the complex-scaled Schrödinger equation and find no resonances or bound states in the ${J/ψNN}$ and ${η_c NN}$ systems. We estimate the interaction between charmonium and nuclei, concluding that the $J/ψ$ or $η_c$ is likely to bind with ${}^3\mathrm{H}$, ${}^3\mathrm{He}$, ${}^4\mathrm{He}$, and heavier nuclei. For the $ϕNN$ system, the lattice QCD $ϕN\left({ }^2 S_{1 / 2}\right)$ interaction is absent. We combine the $ϕp$ correlation function analysis and HAL QCD results in Model A. We assume the spin-spin interactions for $J/ψN$ and $ϕN$ systems are inversely proportional to their masses in Model B. Model A predicts a stronger $ϕN({}^2 S_{1/2})$ interaction and permits a two-body bound state, whereas Model B suggests the interaction is attractive but too weak to form a bound state. Both models predict bound states for the $I(J^P) = 0(0^-)$ and $0(1^-)$ $ϕNN$ systems. In Model A, these states are deeply bound with binding energies exceeding 15 MeV and remain existent when considering parameter uncertainties. In contrast, these states are very loosely bound in Model B, with binding energies below 1 MeV and an existent probability of about 60\% when parameter uncertainties are considered. In both models, there exist very loosely bound $I(J^P) = 0(2^-)$ three-body states which resemble a $ϕ$-d atom with the $ϕ$ meson surrounding the deuteron, but their existences are sensitive to parameter uncertainties. No bound states or resonances are found in the isovector $I(J^P) = 1(1^-)$ $ϕNN$ system.

hep-ph↗

arXiv2025

Nuclear matter properties from chiral-scale effective theory including a dilatonic scalar meson

Chiral effective theory has become a powerful tool for studying the low-energy properties of QCD. In this work, we apply an extended chiral effective theory -- chiral-scale effective theory -- including a dilatonic scalar meson to study nuclear matter and find that the properties around saturation density can be well reproduced. Compared to the traditionally used Walecka-type models in nuclear matter studies, our approach improves the behavior of symmetry energy and the incompressibility coefficient in describing empirical data without introducing additional freedoms. Moreover, the predicted neutron star structures fall within the constraints of GW170817, PSR J0740+6620, and PSR J0030+0451, while the maximum neutron star mass can reach about $~3M_{\odot}$ with a pure hadronic phase. Additionally, we find that symmetry patterns of the effective theory significantly impact neutron star structures. %In chiral-scale effective theory, effective operators are well organized by chiral-scale orders and freedoms induced by QCD symmetry patterns. We believe that introducing this type of theory into nuclear matter studies can lead to a deeper understanding of QCD, nuclear matter, and compact astrophysical objects.

nucl-th↗

arXiv2025

A Graph Perspective to Probe Structural Patterns of Knowledge in Large Language Models

Large language models have been extensively studied as neural knowledge bases for their knowledge access, editability, reasoning, and explainability. However, few works focus on the structural patterns of their knowledge. Motivated by this gap, we investigate these structural patterns from a graph perspective. We quantify the knowledge of LLMs at both the triplet and entity levels, and analyze how it relates to graph structural properties such as node degree. Furthermore, we uncover the knowledge homophily, where topologically close entities exhibit similar levels of knowledgeability, which further motivates us to develop graph machine learning models to estimate entity knowledge based on its local neighbors. This model further enables valuable knowledge checking by selecting triplets less known to LLMs. Empirical results show that using selected triplets for fine-tuning leads to superior performance.

cs.CL↗

arXiv2025

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection

Unsupervised graph anomaly detection aims at identifying rare patterns that deviate from the majority in a graph without the aid of labels, which is important for a variety of real-world applications. Recent advances have utilized Graph Neural Networks (GNNs) to learn effective node representations by aggregating information from neighborhoods. This is motivated by the hypothesis that nodes in the graph tend to exhibit consistent behaviors with their neighborhoods. However, such consistency can be disrupted by graph anomalies in multiple ways. Most existing methods directly employ GNNs to learn representations, disregarding the negative impact of graph anomalies on GNNs, resulting in sub-optimal node representations and anomaly detection performance. While a few recent approaches have redesigned GNNs for graph anomaly detection under semi-supervised label guidance, how to address the adverse effects of graph anomalies on GNNs in unsupervised scenarios and learn effective representations for anomaly detection are still under-explored. To bridge this gap, in this paper, we propose a simple yet effective framework for Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection (G3AD). Specifically, G3AD first introduces two auxiliary networks along with correlation constraints to guard the GNNs against inconsistent information encoding. Furthermore, G3AD introduces an adaptive caching module to guard the GNNs from directly reconstructing the observed graph data that contains anomalies. Extensive experiments demonstrate that our G3AD can outperform twenty state-of-the-art methods on both synthetic and real-world graph anomaly datasets, with flexible generalization ability in different GNN backbones.

cs.LG↗

arXiv2025

Constraining the $DDD^*$ three-body bound state via the $Z_c(3900)$ pole

In this study, we propose using the $Z_c(3900)$ pole position to constrain the existence of the $DDD^*$ three-body bound state within the one-boson-exchange (OBE) model. The existence of the $DDD^*$ bound state remains uncertain due to significant variations in the OBE interaction, particularly in the strength of scalar-meson-exchange interactions, which can differ by a factor about 20 between two commonly used OBE models. This discrepancy renders the $DDD^*$ system highly model-dependent. To address this issue, we constrain the scalar-meson-exchange interaction using the $Z_c(3900)$ pole position, where the pseudoscalar-meson coupling is well-determined, and the $ρ$- and $ω$-exchange interactions nearly cancel each other out, leaving the coupling constant of the $σ$-exchange as the only unknown parameter. Our results indicate that the isospin-$\frac{1}{2}$ $DDD^*$ bound states exist when $Z_c(3900)$ is a virtual state of $D\bar{D}^*/\bar{D}D^*$ located within approximately $-15$ MeV of the threshold. However, the three-body bound state is gone when the $Z_c(3900)$ virtual state pole is more than $20$ MeV away from the threshold. Each experimental progress, either on the $DDD^*$ state or the $Z_c(3900)$, can shed light on the nature of the other state. Another significant outcome is a refined set of OBE model parameters calibrated using the pole positions of $X(3872)$, $T_{cc}(3875)$, and $Z_c(3900)$, rigorously addressing the cutoff dependence. These parameters provide a valuable resource for more accurate calculations of systems involving few-body $D$, $D^*$ and their antiparticles. Additionally, we find no evidence of the $DDD^*$ three-body resonances after extensive search using a combination of the Gaussian expansion method and the complex scaling method.

hep-ph↗

arXiv2025

Identifying regions for asymptotic expansions of amplitudes: fundamentals and recent advances

This review paper discusses the identification of regions, a crucial first step in applying the "method-of-regions" technique. A systematic approach based on Newton polytope geometry has proven successful and efficient for many cases. However, obtaining the correct list of regions becomes increasingly subtle with higher loop numbers or specific Feynman graph topologies. This paper explores the scenarios where such subtleties arise, outlines general strategies to address them, and reviews the current understanding of region structures in various asymptotic expansions of Feynman integrals.

hep-ph↗

arXiv2025

Trilepton and tetralepton bound and resonant states: the QED counterpart of multiquark states

This work presents the first prediction of tetralepton resonant states containing muons, extending beyond the simplest tetralepton system, dipositronium ($\mathrm{Ps}_2$). With the rapid advancements in experimental facilities, the production and study of these intriguing states may be within reach. We perform a comprehensive analysis of S-wave trilepton and tetralepton systems within the framework of a QED Coulomb potential. We employ the Gaussian expansion method to solve the three- or four-body Schrödinger equation and utilize the complex scaling method to identify resonant states. We uncover a series of bound and resonant states in the trilepton systems $e^+e^+e^-$, $μ^+μ^+μ^-$, $e^+e^+μ^-$, and $μ^+μ^+e^-$, as well as the tetralepton systems $e^+e^+e^-e^-$, $μ^+μ^+μ^-μ^-$, and $μ^+μ^+e^-e^-$. The energies of these states range from $-30$ eV to $-1$ eV below the total mass of three or four leptons, with their widths varying from less than $0.01$ eV to approximately $0.07$ eV. Additionally, we calculate the spin configurations and root mean square radii of these states, providing insight into their spatial structures. No bound or resonant states are found in the trilepton $e^+μ^+e^-$, $μ^+e^+μ^-$ systems, nor in the tetralepton $μ^+e^+μ^-e^-$ system. A comparison with fully heavy tetraquark systems reveals that the additional color degree of freedom in QCD results in the absence of low-energy bound and resonant states. However, this extra degree of freedom allows for a broader range of $J^{PC}$ quantum numbers to produce resonant states, highlighting the rich complexity of QCD systems.

hep-ph↗