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Wen Yin

Publications and source records attributed to Wen Yin.

At least 19 recordsLinked to original sources
arXiv2026

Earth-scale searches for displaced vertices: KM3NeT meets the LHC

At high-energy colliders, enormous numbers of feebly interacting particles beyond the Standard Model can be produced with negligible missing-energy signatures in the main detectors. These particles can travel macroscopic distances and decay inside a distant large-volume detector, leaving visible signals. In this sense, we may not need new detectors to search for very long-lived particles. In this paper, we show that long-lived dark particles produced in rare meson decays in proton-proton collisions during LHC Run 3 and at the HL-LHC can leave observable imprints in KM3NeT detectors such as ORCA. If no anomalous signal has been observed in ORCA to date, our projected sensitivity for LHC Run 3 will correspond to one of the strongest limits on kaon decays into light long-lived particles.

hep-ph↗
arXiv2026

A PQ-Symmetric High-Scale SUSY Interpretation of the LZ High-Energy Recoil

The 248-keV nuclear-recoil-like event reported by LZ can be interpreted as near-threshold upscattering of 1.08-TeV thermal Higgsino dark matter. A neutral-Higgsino splitting of order $0.3$--$0.35$ MeV places the fixed weak-interaction cross section close to the observed LZ interval and implies electroweak gauginos at ${O}(10^7)$ GeV. This spectrum is compatible with gravity-mediated high-scale supersymmetry and a Kim--Nilles Peccei--Quinn sector. Although the GUT scale is predicted to be lower than the conventional one, proton decay is suppressed due to the high SUSY scale which also solves the conventional CP, flavor, gravitino and moduli problems. Indeed, proton decay may be probed in the future. The PQ symmetry lowers the Higgsino mass below the SUSY scale and also yields a QCD axion that solves the strong-$CP$ problem. If the axion and Higgsino constitute mixed dark matter, the halo-profile-dependent H.E.S.S. limit can be relaxed.

hep-ph↗
arXiv2026

$\mu$DM: a new mechanism for the baryon-dark matter coincidence

For a relativistically decoupled thermal relic, the dark-matter energy-to-entropy ratio scales as $\rho_{\rm DM}/s\sim 10^{-3}m_{\rm DM}$. This is the familiar hot-dark-matter abundance relation. Immediately after weak-sphaleron freeze-out, the baryon asymmetry can be parametrized as $\rho_{\rm baryon}/s\sim 10^{-4}|\mu_B|$. Here $\mu_B$ is the baryon-number chemical potential. We propose a new class of models, called chemical-potential-matched dark matter ($\mu$DM), in which $|\mu_B|\sim m_{\rm DM}$, thereby providing a new route to the baryon-dark matter coincidence. As a concrete example of $\mu$DM, we consider an Affleck-Dine field whose excitations constitute dark matter. We also briefly discuss spontaneous electroweak baryogenesis associated with axion-like-particle walls. In the absence of entropy dilution, this coincidence mechanism generically points to dark matter in the eV-keV mass range. Its momentum distribution can nevertheless be cold if thermal production is dominated by Bose-enhanced stimulated emission. Alternatively, entropy dilution after both the dark-matter and baryon yields are fixed allows masses up to the MeV scale.

hep-ph↗
arXiv2026

Diversity of Galaxy Centers from Small-Scale Isocurvature

The observed diversity of galaxy centers motivates the possibility that the local dark matter composition may vary among galaxies. In conventional multicomponent dark matter scenarios, however, large stochastic variations in the relative abundances are not generically expected, with the cold component typically remaining dominant. We perform $N$-body simulations with a subdominant ultralight dark matter component carrying significant large-amplitude small-scale isocurvature perturbations. We find that although nonlinear evolution largely homogenizes its fraction on galactic scales,ultralight dark matter can still be enhanced and even dominate the centers of small halos because large initial ultralight dark matter fluctuations seed early potential wells that later form halo centers. The ultralight-dominated region can extend beyond $0.01R_{\rm vir}$ and account for more than half of the central dark matter density, even for a cosmological ultralight dark matter fraction below $O(10\%)$. This central segregation provides a possible route to stochastic cusp--core diversity, potentially explaining the observed diversity of galaxy centers.

astro-ph.CO↗
arXiv2026

Axion Isocurvature Perturbations Survive the Scaling Evolution of Axion Domain Walls

We revisit the evolution of axion domain walls seeded by inflationary fluctuations. In our previous work, we showed that such domain-wall networks retain superhorizon correlations even after entering the scaling regime. We extend our previous analysis to the case with large initial fluctuations, where many minima of the axion potential are already populated when the axion starts to oscillate. Although the conventional misalignment contribution can have suppressed long-wavelength isocurvature perturbations when many vacua are averaged over, axions produced by domain-wall collapse provide an additional contribution that can dominate when the walls enter the scaling regime before annihilation. In particular, the biased vacuum energy released during wall annihilation inherits the superhorizon correlations of the inflationary fluctuations and transfers them to the axion energy density. We find that sizable isocurvature perturbations can therefore survive even after the walls annihilate. We also discuss generic isocurvature constraints on dark matter produced by domain-wall collapse.

hep-ph↗
arXiv2026

What to Remove, What to Preserve: Dual-Ambiguity Rectification for All-in-One Image Restoration

All-in-one image restoration aims to handle diverse degradations within a unified framework. Existing methods commonly encode heterogeneous degradation conditions in a shared latent space, where degradation-related cues and scene content can remain entangled. We characterize the resulting challenge as dual ambiguity: semantic ambiguity in channel-wise modulation and spatial ambiguity in restoration responses, which can lead to content corruption and residual artifacts. To mitigate this issue, we propose DAR-Net, a Dual-Ambiguity Rectification Network for all-in-one image restoration. DAR-Net first introduces a Degradation Archetype Representation (DAR) module to construct a structured degradation state through simplex-constrained archetype mixture modeling. Based on this state, a Semantic Ambiguity Rectification (SeAR) module generates degradation-aware prompts to improve channel-wise conditioning in the decoder. A Spatial Ambiguity Rectification (SpAR) module further regularizes degradation-aware and complementary features toward orthogonal response subspaces, reducing spatial interference between removal and preservation cues. Extensive experiments on standard all-in-one restoration benchmarks show that DAR-Net achieves the best overall performance under both three-degradation and five-degradation settings, improving the average PSNR over the strongest competitor by 0.14 dB and 0.34 dB, respectively; it additionally shows superior performance on CDD-11 and WeatherBench.

cs.CV↗
arXiv2026

Why 4D? Spontaneous Dimensional Selection from Gauge Criticality

Noting that the Yang--Mills coupling is relevant below four dimensions, marginal in four dimensions, and irrelevant above four dimensions, I propose that this criticality can lead to the selection of four macroscopic dimensions. As a proof of principle, I present a concrete racetrack model of the type commonly studied in extra-dimensional scenarios, but without assuming a noncompact 4D spacetime. I find, within a well-controlled model without specifying the 4D, that 4D spacetime is spontaneously realized through radion stabilization via gauge-criticality-induced supersymmetry breaking and supergravity effects.

hep-ph↗
arXiv2026

MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction

High-throughput experimentation and self-driving laboratories are drastically accelerating materials discovery, yet automated interpretation of X-ray powder diffraction (XRPD) data remains a critical rate-limiting step. Conventional search-match workflows rely heavily on expert manual intervention, while pure data-driven machine learning approaches suffer from limited generalizability across chemical systems and lack rigorous crystallographic interpretability. Here we present MatDiffract, a material-informed automated analysis platform for high-throughput XRPD characterization. Built on a first-principles density functional theory (DFT)-derived inorganic crystal structure database, Atomly, MatDiffract constructs a perturbation-augmented simulated diffraction database, embeds multi-scale diffraction features into indexable vectors, and integrates hierarchical vector retrieval with full-pattern fitting Rietveld refinement and quantitative phase fitting. Benchmarked on 875 single-phase experimental patterns, the platform achieves 91.3% Top-1 and 97.2% Top-10 identification accuracy after automated refinement. For binary and ternary multiphase mixtures, it delivers 85.0% and 70.0% Top-1 accuracy with mass fraction mean absolute errors as low as 1.2% and 1.8%, respectively. Beyond mere phase labeling, MatDiffract outputs full crystallographic results including refined structural models, fitted profiles, and quantitative compositions within tens of seconds per sample. Its modular vector-based architecture supports seamless incremental expansion to new material systems, providing an end-to-end solution to close the characterization throughput gap for autonomous materials discovery and high-throughput materials development.

cond-mat.mtrl-sci↗
arXiv2026

Constant Scaling Fails for Global Monopole Networks

Global monopoles, which can also be understood as the zero-gauge-coupling limit of gauged monopoles, can form in the early Universe and evolve following a scaling network, as do other topological defects. However, only a limited number of numerical studies have investigated their scaling behavior. In this Letter, we show that the monopole number density parameter, $\xi$, does not follow the commonly assumed constant scaling. Instead, it exhibits a logarithmic-like evolution, despite the fact that the energy of an isolated global monopole grows linearly, rather than logarithmically, with the infrared cutoff. This behavior is found using the fat-monopole prescription and is supported by a conventional fixed-core simulation. We characterize the deviation by the fractional response $\gamma\equiv d\log \xi/d\log(m_r/H)$, and find $\gamma\sim 0.5$ for blue-tilted initial spectra. These results suggest that analytic studies based on the assumption of constant scaling should be revisited. They are also relevant to cosmological scenarios involving monopole dark matter, axion and dark-photon dark matter produced by monopole networks, monopole-induced primordial black holes, and gravitational-wave production from monopole dynamics.

hep-ph↗
arXiv2026

PBHs and GWs from Scaling Monopoles

Monopoles with sufficiently weak gauge couplings, or from global symmetries, can form scaling networks in the early Universe whose average energy density tracks the cosmological background. In this work, we find, by performing classical lattice simulations to estimate the overdensities, that primordial black holes (PBHs) with a broad mass spectrum can be produced during this evolution if the Higgs expectation value $v$ satisfies $v\gtrsim 0.1 M_{\rm pl}$. The formation is driven by the stochastic realization of the monopole number in Hubble patches causing the overdensities. We also show that gravitational waves (GWs) generated by the scaling dynamics are produced at the same epoch, with spectra correlated with the PBH spectra and with amplitudes testable in future observations. Interestingly, if the scaling regime is terminated by the gauge boson mass for the gauged monopole, a non-negligible fraction of the PBHs can carry magnetic charge, and the resulting magnetic Coulomb force between such charged PBHs is predicted to be comparable to the gravitational force. Together with the PBH and GW signals, this provides a smoking-gun signature of the scenario. We also point out simple cosmological scenarios, which may also apply to PBH formation from scaling cosmic strings, that allow PBHs to constitute dominant dark matter.

hep-ph↗
arXiv2026

Spontaneous Baryogenesis from Axions on Induced Electroweak Walls

We propose a baryogenesis mechanism in which an electroweak phase boundary is induced by a wall-like configuration of a scalar field, such as a domain wall or a shock wave, coupled to the Higgs field. If the Higgs mass parameter depends on the scalar field value, the wall locally separates the electroweak-symmetric and broken phases, thereby providing an induced electroweak wall. We focus on the case where the scalar field is an axion-like particle coupled to the SU(2) Chern--Simons density. The motion of the wall then generates a local effective chemical potential for B+L, realizing a spontaneous baryogenesis mechanism. In the presence of unsuppressed sphaleron transitions in front of the wall, this biases the plasma and leads to baryon asymmetry generation. We discuss the parametric conditions for the induced wall, cosmological realizations based on domain walls and shock waves, and the associated implications for baryon inhomogeneities and gravitational waves. The axion coupling is predicted to be sufficiently weak to evade current experimental and observational bounds.

hep-ph↗
arXiv2026

Can We Build Scene Graphs, Not Classify Them? FlowSG: Progressive Image-Conditioned Scene Graph Generation with Flow Matching

Scene Graph Generation (SGG) unifies object localization and visual relationship reasoning by predicting boxes and subject-predicate-object triples. Yet most pipelines treat SGG as a one-shot, deterministic classification problem rather than a genuinely progressive, generative task. We propose FlowSG, which recasts SGG as continuous-time transport on a hybrid discrete-continuous state: starting from a noised graph, the model progressively grows an image-conditioned scene graph through constraint-aware refinements that jointly synthesize nodes (objects) and edges (predicates). Specifically, we first leverage a VQ-VAE to quantize a scene graph (e.g., continuous visual features) into compact, predictable tokens; a graph Transformer then (i) predicts a conditional velocity field to transport continuous geometry (boxes) and (ii) updates discrete posteriors for categorical tokens (object features and predicate labels), coupling semantics and geometry via flow-conditioned message aggregation. Training combines flow-matching losses for geometry with a discrete-flow objective for tokens, yielding few-step inference and plug-and-play compatibility with standard detectors and segmenters. Extensive experiments on VG and PSG under closed- and open-vocabulary protocols show consistent gains in predicate R/mR and graph-level metrics, validating the mixed discrete-continuous generative formulation over one-shot classification baselines, with an average improvement of about 3 points over the state-of-the-art USG-Par.

cs.CV↗
arXiv2026

One Model, Two Minds: Task-Conditioned Reasoning for Unified Image Quality and Aesthetic Assessment

Unifying Image Quality Assessment (IQA) and Image Aesthetic Assessment (IAA) in a single multimodal large language model is appealing, yet existing methods adopt a task-agnostic recipe that applies the same reasoning strategy and reward to both tasks. We show this is fundamentally misaligned: IQA relies on low-level, objective perceptual cues and benefits from concise distortion-focused reasoning, whereas IAA requires deliberative semantic judgment and is poorly served by point-wise score regression. We identify these as a reasoning mismatch and an optimization mismatch, and provide empirical evidence for both through controlled probes. Motivated by these findings, we propose TATAR (Task-Aware Thinking with Asymmetric Rewards), a unified framework that shares the visual-language backbone while conditioning post-training on each task's nature. TATAR combines three components: fast--slow task-specific reasoning construction that pairs IQA with concise perceptual rationales and IAA with deliberative aesthetic narratives; two-stage SFT+GRPO learning that establishes task-aware behavioral priors before reward-driven refinement; and asymmetric rewards that apply Gaussian score shaping for IQA and Thurstone-style completion ranking for IAA. Extensive experiments across eight benchmarks demonstrate that TATAR consistently outperforms prior unified baselines on both tasks under in-domain and cross-domain settings, remains competitive with task-specific specialized models, and yields more stable training dynamics for aesthetic assessment. Our results establish task-conditioned post-training as a principled paradigm for unified perceptual scoring. Our code is publicly available at https://github.com/yinwen2019/TATAR.

cs.CV↗
arXiv2026

Modelling instrumental response for neutron scattering experiments at CSNS

Thermal neutron total scattering experiments of light and heavy water were reproduced using the CSNS in-house Monte Carlo thermal neutron transport code, Prompt, with a focus on the instrumental detector response and the accurate derivation of thermal neutron scattering cross-sections. In this work, a data reduction method is developed to process both the measured and simulated detector events for estimating angular, wavelength distributions, as well as angular differential cross sections. The reduction results of simulations and experiments show a high degree of consistency. The prominent inelasticity signatures observed in the experiments can be accurately reproduced in simulations. We discuss the cause of the inelasticity effects, and demonstrate the elimination of such effects when the inelastic scattering process is taken into account in simulations. In addition, multiple scattering in samples is analysed and discussed.

physics.ins-det↗
arXiv2026

Beyond thresholds: reconstructing UV physics from IR expansions

We show that ultraviolet information can be extracted from low-energy expansion coefficients, assuming analyticity and the absence of massless singularities. By reorganizing the low-energy expansion through an inverse Laplace transform and a controlled coarse-graining procedure, we make ultraviolet behavior accessible beyond the cutoff of the effective field theory. In particular, we determine the sign of the beta function and the associated dynamical scale directly from the low-energy expansion of a physical observable below the mass thresholds in QED and QCD-like theories.

hep-th↗
arXiv2026

AlignVAR: Towards Globally Consistent Visual Autoregression for Image Super-Resolution

Visual autoregressive (VAR) models have recently emerged as a promising alternative for image generation, offering stable training, non-iterative inference, and high-fidelity synthesis through next-scale prediction. This encourages the exploration of VAR for image super-resolution (ISR), yet its application remains underexplored and faces two critical challenges: locality-biased attention, which fragments spatial structures, and residual-only supervision, which accumulates errors across scales, severely compromises global consistency of reconstructed images. To address these issues, we propose AlignVAR, a globally consistent visual autoregressive framework tailored for ISR, featuring two key components: (1) Spatial Consistency Autoregression (SCA), which applies an adaptive mask to reweight attention toward structurally correlated regions, thereby mitigating excessive locality and enhancing long-range dependencies; and (2) Hierarchical Consistency Constraint (HCC), which augments residual learning with full reconstruction supervision at each scale, exposing accumulated deviations early and stabilizing the coarse-to-fine refinement process. Extensive experiments demonstrate that AlignVAR consistently enhances structural coherence and perceptual fidelity over existing generative methods, while delivering over 10x faster inference with nearly 50% fewer parameters than leading diffusion-based approaches, establishing a new paradigm for efficient ISR.

cs.CV↗
arXiv2026

Hubble-Scale Tachyonic Shocks from Low-Scale Inflation -- A New Gravitational-Wave Window on Inflation

Current bounds on the tensor-to-scalar ratio imply that the energy scale of inflation may lie below the grand-unified scale. In this paper, we show that in a broad class of single-field inflation models with sufficiently small energy scales, an extremely efficient tachyonic instability develops at the end of inflation. This instability rapidly drives the system into a nonlinear regime before coherent oscillations can be established, leading to a first-order phase-transition--like phenomenon without tunneling or barrier crossing. The resulting ultra-relativistic shock fronts surrounding the bubble interiors expand to near the Hubble scale, corresponding to the most strongly enhanced tachyonic modes, and collide with one another, producing energetic inflaton particles and gravitational waves. As a result, the post-inflationary dynamics can differ significantly from the conventional high-scale inflationary scenario. Interestingly, inflation at MeV--EeV energy scales can be probed via gravitational-wave observations, including pulsar timing arrays, ground-based detectors, and future space-based experiments. Recent limits from the LIGO--KAGRA--Virgo collaboration already constrain EeV-scale inflation, while pulsar timing array results may be interpreted as evidence for gravitational waves generated by GeV-scale inflation. We also briefly discuss further implications of the resulting tachyonic shocks.

hep-ph↗
arXiv2026

WISPedia -- the WISPs Encyclopedia

The Weakly-Interacting Slim Particle encyclopedia (WISPedia) is a comprehensive reference work dedicated to the systematic compilation of theoretical models, Effective Field Theories, and frameworks involving Weakly Interacting Slim Particles (WISPs): a broad class of light, feebly coupled particles proposed in extensions of the Standard Model. In current times, where the number of models largely surpasses the number of new physics signals, this encyclopedia aims to provide a concise reference of their landscape. The goal is to provide a useful tool to the community to navigate among them. It does not aim to review all the models in detail, but to define their essential characteristics, and point the reader to useful and minimal material such as the original sources, review articles, tools and general compilations of bounds. Hence, the format of this reference resembles the direct style of a model encyclopedia of WISPs.

hep-ph↗