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Bin Wu

Publications and source records attributed to Bin Wu.

At least 37 records · Page 2Linked to original sources
arXiv2026

Geometric formulation for the relativistic kinetic theory of photons

We provide a geometric foundation for the kinetic theory of photons. Although the induced metric $\hat h$ on the light cone bundle $Γ_0^+$ is degenerate, which causes the corresponding volume element to vanish, we can still use a method similar to the Hodge dual to construct a volume element $η_{Γ_0^+}$ for the light cone bundle. Based on this geometric structure $(Γ^+_0,η_{Γ_0^+},\hat h)$, we establish the fully covariant Boltzmann equation for photons. More importantly, the volume element and the induced metric are linked in a nontrivial way, which allows the physical distributions to be defined consistently. This yields the corresponding hydrodynamic quantities and their divergences, which take the same form as in the case of massive particles.

gr-qc↗
arXiv2026

Resummed azimuthal decorrelation and transverse momentum imbalance of dijets at the LHC

We present a theoretical study of the azimuthal decorrelation $δϕ$ and transverse momentum imbalance $q_T$ in dijet production at the LHC, offering intriguing insights into the dynamics of quantum chromodynamics. We define the jet axes using the recoil-free winner-take-all (WTA) recombination scheme. For the azimuthal decorrelation $δϕ$, this axis choice eliminates non-global logarithms (NGLs) entirely. For the transverse momentum imbalance $q_T$, NGLs emerge specifically in the small jet radius limit ($R \ll 1$). In this regime, the WTA scheme simplifies the theoretical framework by restricting jet radius logarithms to the soft sector. We derive factorization formulae for both observables within soft-collinear effective theory. To address the small-$R$ NGLs in the $q_T$ distribution, we refactorize the soft function into global soft, collinear-soft, and ultra-collinear-soft modes. We perform the resummation of global large logarithms $\ln(δϕ)$ and $\ln(q_T/Q)$ up to next-to-next-to-leading logarithmic accuracy. For the $q_T$ distribution, this is combined with a leading-logarithmic resummation of the non-global $\ln R$ terms. We match our predictions to leading fixed-order $O(α_s^3)$ calculations. We also numerically investigate the structure of the first subleading power corrections. Comparisons with PYTHIA8 simulations demonstrate that the observables we consider are robust against non-perturbative multi-parton interactions and hadronization effects.

hep-ph↗
arXiv2026

Stochastic Liouville-transport theory of light-atom interaction noise in thermal atomic vapors

Atom-light interaction noise can limit thermal-vapor sensing. Existing theories often treat internal-state dynamics, finite-mode atomic motion, and stochastic renewal separately, obscuring their coupled contributions to measured noise. We develop a general stochastic Liouville-transport theory, tested against polarization-resolved resonant Cs D$_2$ spectra. Joint experiment-theory analysis identifies atom-light noise below approximately 100 kHz as transit-dominated. Ballistic motion through the finite Gaussian mode modulates both the coupling-weighted effective atom number and trajectory-dependent Rabi coupling, producing predominantly common-mode noise. Boundary renewal introduces atoms with independently sampled ground-state sublevels, generating differential population fluctuations with opposite effects on the circular channels. Under an applied longitudinal magnetic field, experiment and theory show the same qualitative nonmonotonic change in common-mode suppression, supporting Zeeman redistribution of the channel responses. The framework can analyze noise in other thermal-atom sensors, including Rydberg-atom electric-field measurements.

quant-ph↗
arXiv2026

Mitigating Context Interference for Reliable and Efficient Search Agents

Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the contexts of multi-turn search agents are lengthy and complex. For example, the retrieved set of documents in each turn would inevitably introduce irrelevant information that distracts LLMs, referring to \textit{context interference}, potentially hindering the reliability and efficiency of search agents. Therefore, we conduct a systematic study on context interference in multi-turn search agents, focusing on investigating i) which parts of the context of search agents will contribute to the context interference, ii) how to refine the contexts of search agents to mitigate the interference, and iii) can incorporating context refinement into search agent training yield further improvements. We reveal that interference primarily arises from the latest retrieved documents. Based on the explored findings, we then introduce a distill-based context refiner to dynamically mitigate context interference for multi-turn search agents. Finally, we validate that incorporating context refinement into RL training pipelines of search agents can significantly enhance both reliability and efficiency. This study highlights the importance of mitigating context interference of search agents, inspiring a novel paradigm of ``refine context and then generate'' for AI agents.

cs.CL↗
arXiv2026

Particle Production, Equilibration, and Quantum Recurrences from Classical Fields

We investigate particle production from classical fields, a phenomenon central to the pre-equilibrium dynamics of relativistic heavy-ion collisions and the reheating epoch of the early Universe. Using lattice $λϕ^4$ theory as a proof of principle, we show that this problem is naturally amenable to quantum computation, providing a first-principles framework for nonequilibrium quantum-field dynamics beyond existing approximations. We perform simulations on small spatial lattices, exhausting our available classical computational resources while maintaining a direct mapping to future quantum-computing implementations. We find that particle production is accompanied by equilibration of observables, including the field expectation value, occupation-number distribution, and pressure. The observed equilibration persists for timescales several times longer than the initial equilibration time before the observables resume oscillatory behavior associated with quantum Poincaré recurrences. Our results establish a route toward first-principles studies of equilibration in nonequilibrium quantum field theory and provide insight into the search for the smallest possible locally equilibrated quark-gluon systems at hadron colliders.

hep-ph↗
arXiv2026

Fine-grained Semantics Integration for Large Language Model-based Recommendation

Recent advances in Large Language Models (LLMs) have driven a shift in recommender systems from the discriminative paradigm to the LLM-based generative paradigm, where the recommender autoregressively generates sequences of semantic identifiers (SIDs) for target items conditioned on historical interaction. While prevalent LLM-based recommenders have demonstrated performance gains by aligning pretrained LLMs between the language space and the SID space, modeling the SID space still faces two fundamental challenges: (i) Semantically Meaningless Initialization: SID tokens are initialized by random sampling without incorporating token-specific semantics, leaving them without explicit semantic correspondence to the pretrained language space; and (ii) Coarse-grained Alignment: existing SFT-based alignment tasks primarily focus on item-level optimization while overlooking the semantics of individual tokens within SID sequences. To address these challenges, we propose TS-Rec, which can integrate Token-level Semantics into LLM-based Recommenders. Specifically, TS-Rec comprises two key components: (1) Semantic-Aware Embedding Initialization (SA-Init), which initializes SID token embeddings by applying mean pooling to the pretrained embeddings of keywords extracted by a teacher model; and (2) Token-level Semantic Alignment (TS-Align), which aligns individual tokens within the SID sequence with the shared semantics of the corresponding item clusters. Extensive experiments on three real-world benchmarks demonstrate that TS-Rec consistently outperforms traditional and generative baselines across all standard metrics. These findings confirm the effectiveness of incorporating fine-grained semantic information into LLM-based generative recommenders. The implementation is available at https://anonymous.4open.science/r/TS-Rec-Review-8F99/.

cs.IR↗
arXiv2026

Domain Decoupling Attack: Exploiting the Validation Gap Between Protective DNS and Shared Edge Routing

Network attackers often conceal malicious communication within legitimate Internet traffic. Existing CDN-based evasion techniques rely on SNI--Host inconsistency, insufficient domain ownership verification, or provider-specific routing rewrites, which limit their applicability in modern CDN environments. We identify a validation gap in DNS-based authorization, where permission derived from an allowed domain applies to a shared IP and can be reused to reach another tenant in both CDN and non-CDN shared-hosting environments. This paper presents the Domain Decoupling Attack (DDA), which resolves an allowed domain to obtain permission for a shared edge IP and subsequently connects to the same address while presenting the hidden domain consistently in both TLS SNI and HTTP Host. Measurements of 1,069,048 domains across six continents produce 18,025,068 successful probes and identify exposure rates of 95.8% overall, 99.26% for CDN domains, 92.75% for non-CDN domains, and 97.7% for non-CDN cross-tenant IPs, while laboratory experiments reveal a structural limitation of DNS-bound access control on shared addresses. These results clarify the security risks of DNS-derived IP authorization and support the evaluation and improvement of access-control mechanisms in CDN and non-CDN shared-hosting environments.

cs.CR↗
arXiv2026

IMFuse: Instance-Aware Multi-Layer Fusion for LLM-Enhanced Sequential Recommendation

Recent advancements in Large Language Models (LLMs) have significantly enhanced sequential recommendation by encoding rich item textual information into semantic representations. However, existing methods typically rely on the final-layer hidden states of LLMs, overlooking potentially useful semantic signals encoded in other layers. Through empirical analysis, we reveal the limitations of this practice: final-layer representations often suffer from dimensional collapse, whereas intermediate layers preserve complementary, coarse-to-fine semantic knowledge. Furthermore, we observe that different items exhibit heterogeneous layer-wise representation evolution, making a uniform layer selection sub-optimal. To bridge this gap, we propose IMFuse, an instance-aware multi-layer fusion strategy designed for LLM-enhanced recommendation. Instead of relying on a single layer, IMFuse adaptively aggregates multi-layer semantic information by learning global dimension-wise layer preferences to capture general semantic contributions. To address item-level heterogeneity, IMFuse introduces an instance-aware expert modulation mechanism that dynamically adjusts these global preferences, generating personalized, item-specific semantic representations. Extensive experiments across four real-world datasets demonstrate the effectiveness of IMFuse. It consistently outperforms state-of-the-art baselines with an average relative improvement of 6.72%, while introducing limited parameter and computational overhead.

cs.IR↗
arXiv2026

Aggregation of Evolutionary Game Dynamics on Large-Scale Weighted Networks

Networked evolutionary games, which integrate network topology and game dynamics, serve as a powerful framework for complex systems. Evolutionary games on large-scale networks, however, have been analytically challenging due to the curse of dimensionality arising from large network size. This paper proposes an aggregation method based on backward equivalence, such that agents within the same equivalence class behave exactly the same over time. We give a necessary and sufficient condition under which the weighted networked evolutionary games (WNEG) are reduced to an equivalent system with low dimension. The aggregation is shown to reduce the computational burden ranging from strategy consensus, strategy optimization, controllability, to optimal control of the WNEG. Examples are provided. Our work opens an avenue to solve the curse of dimensionality on networked evolutionary game systems with mathematical rigor.

eess.SY↗
arXiv2026

Strange Quark Electric Dipole Moment withTopological Anomalies

We introduce an anomaly-based framework to probe quark electric dipole moments in exclusive hadronic final states produced in $e^+e^-$ annihilation. Chern-Simons-induced anomalous couplings yield a clean T-odd asymmetry $A_T$ from interference between the Standard-Model amplitude and dipole-moment contributions. As an application, $γ^\ast\to K^+K^-π^0$ provides direct sensitivity to the strange-quark EDM $d_s$ in the chiral limit. The precision on $d_s$ can reach $\mathcal{O}(10^{-16})\,e\cdot\mathrm{cm}$ with existing CMD--3 data and $\mathcal{O}(10^{-18})\,e\cdot\mathrm{cm}$ using current $J/ψ$ samples at BESIII, improving the current direct constraint from hyperon EDM by two to three orders.

hep-ph↗
arXiv2026

From Centrality Discounts to Centrality Premia: Interoperability and Platform Competition in Social Networks

We study how interoperability reshapes competitive price discrimination when consumers are embedded in a social network. Two differentiated platforms set personalized prices; consumers benefit from neighbors' consumption of the same platform and, under interoperability, of the rival. Equilibrium prices obtain in closed form for arbitrary networks and contain a network-position term, proportional to Katz-Bonacich centrality, whose sign is determined by whether interoperability exceeds product substitutability. Below this threshold, platforms contest central consumers and grant centrality discounts; above it, central consumers become gateways to a shared cross-platform network and pay premia; at the threshold, prices are independent of network position. Interoperability softens price competition, can make platforms favor denser consumer networks, and reverses which side of the market gains from price discrimination.

econ.TH↗
arXiv2026

Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory

Recent LLM-based mathematical reasoning agents have begun to tackle research-level problems and, in several cases, have contributed to the resolution of open problems. However, scaling and orchestrating such agents effectively remains challenging, due to the difficulty of coordinating parallel proof search while keeping intermediate claims organized and reliable. In this paper, we propose Danus, an orchestration system for research-level mathematical reasoning centered on a shared fact graph as a global memory-management mechanism. Danus consists of a main agent that performs planning and coordination, multiple worker agents that carry out proof search in parallel, and a stateless verifier that checks proposed mathematical claims before they are admitted into the fact graph. Each verified fact is stored together with its proof and logical dependencies, allowing the system to build long arguments incrementally while keeping the shared proof state organized. The main agent periodically summarizes the evolving proof state, redirects workers across promising directions, and supports interaction with human mathematicians through progress reports. We evaluate Danus through six research-level case studies in algebraic geometry, singularity theory, and combinatorics, illustrating how the fact-graph memory mechanism enables Danus to construct long, detailed mathematical proofs. Our results suggest that fact-graph-based orchestration provides an effective route toward scaling mathematical reasoning agents for long-horizon research problems. Danus is open source at https://github.com/frenzymath/Danus.

cs.AI↗
arXiv2026

Azimuthal momentum isotropization in the Quark-Gluon Plasma thermalization

Azimuthal anisotropies coming from the initial state of a heavy-ion collision have been historically disregarded in the study of thermalization because they are expected to be rapidly washed out due to final-state interactions. However, they may be important when one attempts to describe azimuthal correlations observed in the collisions of small systems. In this work, we study how these initial anisotropies relax in the context of the Boltzmann Equation in Diffusion Approximation (BEDA). We find a clear hierarchy in the relaxation time of the anisotropies in terms of each harmonic coefficient. We also explore the evolution of the $p_T$-dependent harmonic coefficients in time, finding a shift in the initial peak towards higher momenta that mimics the experimental data when we perform a phenomenologically motivated simulation.

hep-ph↗
arXiv2026

Positive and Negative Determinant Strategies in Repeated Games with Behavior-Value Inconsistency

Direct reciprocity, based on the repeated interactions, is a fundamental mechanism to promote cooperation. Zero-determinant (ZD) strategies have opened an avenue for unilateral payoff control. However, previous studies neglect internal costs provided what agents do differ from what agents think, which is crucial for decision making of intelligent agents. Motivated by this, we establish a game theoretical framework by assuming that an individual pays the internal cost if the behavior is inconsistent with the internal thought. We prove that ZD strategy does not exist if the cost via behavior-value inconsistency is present. Instead, we find a new class of repeated strategies that enforce a unilateral payoff control, which is termed as positive/negative determinant strategy. The found strategy allows an individual to enforce an affine combination of two individuals' average payoffs above/below zero. Consequently, a focal individual is able to unilaterally control the opponent's payoff below a given value via negative determinant strategy, and a focal individual is able to get more payoff than the opponent via positive determinant strategy. We also find that the control ability of positive/negative determinant strategies is better off than that of ZD strategies. Our work highlights the importance of inconsistency between the behavior and value on payoff control, which is typically absent in classic ZD strategies.

cs.GT↗
arXiv2026

$Λ\bar Λ$ spin correlations in high-energy collisions from quantum channels: an open quantum system view of hadronization

We construct a quantum information-centered approach to describe the experimentally observed behavior of hyperon spin-pair correlations in high-energy collider experiments. The evolution of the spin density matrix of the hyperon pair is treated in the language of quantum channels, accounting both for the spin dynamics in $\mathbb{C}^2\otimes\mathbb{C}^2$ and for the pair's angular separation $ΔR$. We show that the experimental data are consistent with an evolution under a two-qubit depolarizing channel, from which a Lindblad master equation is derived. This provides an open quantum system picture of spin dynamics during the hadronization transition, which is not naturally captured by other quantum channels, and we discuss its microscopic origins. These results show that quantum information science can offer new insights into confinement dynamics beyond the classification of entanglement in the final particle states.

hep-ph↗
arXiv2026

PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation

World foundation models (WFMs) are powerful simulators, yet they predominantly operate in a single-view setting and lack the multi-view 3D consistency required for robotic manipulation. While robotic systems rely on multiple cameras (egocentric, eye-to-hand, and wrist-mounted) for policy learning, current multi-view world models simply concatenate view tokens without explicit geometric reasoning. This causes cross-view object drift, depth inconsistency, and texture misalignment. We trace these failures to two deficiencies: the absence of an explicit inter-view communication mechanism and the lack of a 3D geometric prior. We argue that resolving both simultaneously is necessary and sufficient. To address this, we present PAIWorld, a framework that augments diffusion-transformer world models via three core components: (1) Geometry-Aware Cross-View Attention blocks that establish an explicit pathway across views, (2) Geometric Rotary Position Embedding that encodes camera ray directions and extrinsic poses into the attention mechanism, and (3) Latent 3D-REPA, which distills 3D-aware features from frozen 3D foundation models to ensure 3D consistency. Built upon a DiT-based world foundation model, PAIWorld achieves state-of-the-art multi-view 3D consistency on robotic manipulation benchmarks, ranking 1st on the WorldArena leaderboard and 2nd on the AgiBot-Challenge2026 leaderboard, while enabling downstream applications such as model-based planning, world action models, and multi-view policy post-training.

cs.RO↗
arXiv2026

Analysis of the semileptonic decays $Σ_b\toΣ_cl\barν_l$, $Ξ'_b\toΞ'_cl\barν_l$ and $Ω_b\toΩ_cl\barν_l$ in QCD sum rules

In this article, the electroweak transition form factors of $Σ_b\toΣ_c$, $Ξ'_b\toΞ'_c$ and $Ω_b\toΩ_c$ are analyzed within the framework of three-point QCD sum rules. In phenomenological side, all possible couplings of interpolating current to hadronic states are considered, and the Dirac structure dependence on the form factors is systematically eliminated. In QCD side, our calculation incorporates both the perturbative part and the contributions from vacuum condensates up to dimension 8. This systematic inclusion of higher-dimensional terms accounts for a broader set of Feynman diagrams, thereby enhancing the comprehensiveness and reliability of the operator product expansion. Using the obtained form factors, we study the partial widths of semileptonic decays $Σ_b\toΣ_cl\barν_l$, $Ξ'_b\toΞ'_cl\barν_l$ and $Ω_b\toΩ_cl\barν_l$ ($l=e$, $μ$ and $τ$). The results indicate that these decay widths approximately satisfy SU(3) flavor symmetry. Next, we calculate the branching ratios for the decay process $Ω_b\toΩ_cl\barν_l$ and compare them with the results from other collaborations. Furthermore, the lepton universality ratios and some asymmetry parameters of these decay processes are also analyzed, which provide information for the study of new physics. We hope that these results will serve as a useful reference for future theoretical and experimental studies of weak decays involving heavy flavor baryons.

hep-ph↗
arXiv2026

Inverse Source Problems for a Class of Fractional Elliptic Equations with Singular Coefficients

An inverse source problem for a class of fractional elliptic equations with singular coefficients is investigated in this paper. For the corresponding direct problem, a formal solution is derived and the well-posedness of the solution is established. For the inverse problem, a Hölder-type conditional stability estimate is obtained in a Hilbert scale associated with exponential operators. Based on this stability framework, two regularization methods are proposed for reconstructing the unknown source term: the exponential-type Tikhonov regularization method and the exponential quasi-boundary value regularization method. Convergence estimates for the regularized solutions are derived under both a priori and a posteriori choices of the regularization parameter. In addition, finite-dimensional spectral approximation results show that the proposed methods are also applicable to general square-integrable source terms, without requiring the exact source to satisfy an exponential-type source condition. Numerical experiments demonstrate that the proposed methods provide stable and accurate reconstructions for both smooth and piecewise smooth sources even under low signal-to-noise ratio conditions.

math.NA↗