arXiv subjects

Wen Yin

Publications and source records attributed to Wen Yin.

At least 37 records · Page 2Linked to original sources

arXiv2026

Resolving the QCD Axion Domain Wall Problem with a Light Axion

We propose two novel solutions to the domain wall problem of the QCD axion by introducing a massless or light axion that also couples to gluons. The first solution applies when the new axion forms strings after inflation. Due to its mixing with the QCD axion, domain walls of the QCD axion are bounded by these strings and confined into cosmologically safe string bundles. This scenario predicts the existence of such string bundles, which may survive until today and leave observable signatures, such as gravitational waves, cosmic birefringence, and CMB anisotropies. The simultaneous detection of the QCD axion and any of these cosmological signatures would serve as a smoking-gun signal. The second solution assumes a homogeneous initial condition for the new axion. If it is sufficiently light, its potential temporarily induces a bias in the QCD axion potential before the onset of oscillations, rendering the domain walls unstable. In both scenarios, the Peccei-Quinn mechanism remains effective, and the strong CP problem is not reintroduced. We identify the viable parameter regions and discuss the resulting dark matter abundance.

hep-ph↗

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

The Impact of Response Latency and Task Type on Human-LLM Interaction and Perception

Responsiveness in large language model (LLM) applications is widely assumed to be critical, yet the impact of latency on user behavior and perception of output quality has not been systematically explored. We report a controlled experiment varying time-to-first-token latency (2, 9, 20 seconds) across two taxonomy-driven knowledge task types (Creation and Advice). Log analyses reveal that user interaction behaviors were robust to latency, yet varied by task type: Creation tasks elicited more frequent prompting than Advice tasks. In contrast, participants who experienced 2-second latencies rated the LLM's outputs less thoughtful and useful than those who experienced 9- or 20-second latencies. Participants attributed delays to AI deliberation, though long waits occasionally shifted this interpretation toward frustration or concerns about reliability. Overall, this work demonstrates that latency is not simply a cost to reduce but a tunable design variable with ethical implications. We offer design strategies for enhancing human-LLM interaction.

cs.HC↗

arXiv2026

Robust Reversible Watermarking in Encrypted Images Based on Dual-MSBs Spiral Embedding

Robust reversible watermarking in encrypted images (RRWEI) faces an inherent challenge in simultaneously achieving robustness, reversibility, and content privacy under severely constrained embedding capacity. Existing RRWEI schemes often exhibit limited robustness against noise, lossy compression, and cropping attacks due to insufficient redundancy in the encrypted domain. To address this challenge, this paper proposes a novel RRWEI framework that couples dual most significant bit-plane (dual-MSBs) embedding with spatial redundancy and error-correcting coding. By compressing prediction-error bit-planes, sufficient embedding space and auxiliary information for lossless reconstruction are reserved. The dual-MSBs are further reorganized using a spiral embedding strategy to distribute multiple redundant watermark copies across spatially dispersed regions, enhancing robustness against both noise and spatial loss.Experimental results on standard test images demonstrate that the proposed method consistently outperforms under evaluated settings robustness against Gaussian noise, JPEG compression, and diverse cropping attacks, while maintaining perfect reversibility and high embedding capacity. Compared with state-of-the-art RRWEI schemes, the proposed framework achieves substantially lower bit-error rates and more stable performance under a wide range of attack scenarios.

cs.CR↗

arXiv2025

Relativistic Axion with Nonrelativistic Momenta: A Robust Bound on Minimal ALP Dark Matter

The axion-like particle (ALP), a pseudo Nambu-Goldstone boson that couples to two photons, has been studied extensively in recent years as a dark matter candidate. For initial field configurations in a minimal ALP model explaining the observed dark matter abundance, we need the potential height to exceed the ALP energy density at redshift $z\approx 5.5\times 10^{6}$ leading to: $$ f_ϕ\gtrsim4\times10^{13}\,{GeV}\,\biggl(\frac{10^{-18}\,eV}{m_ϕ}\biggr), $$ where $m_ϕ$ and $f_ϕ$ denote the ALP mass and decay constant, respectively. This bound is known for the ALP dark matter dominated by the homogeneous zero-momentum mode, under the requirement that coherent oscillations begin early enough to satisfy the late-forming dark matter constraint. One loop hole to evade this limit may be to introduce a large amount of the non-relativistic modes of the ALP with non-vanishing momenta. Here we show that the same limit remains valid even if nonzero-momentum modes dominate. Interestingly, when $nonrelativistic$ gradient modes prevail, the ALP behaves $relativistic$ radiation rather than matter, if it violates the limit. Moreover, if the typical momentum is sufficiently small, Baumkuchen-like domain walls form, which play an important role in understanding the transition.

hep-ph↗

arXiv2025

Superheavy dark matter from the natural inflation in light of the highest-energy astroparticle events

Superheavy dark matter has been attractive as a candidate of particle dark matter. We propose a ``natural" particle model, in which the dark matter serves as the inflaton in natural inflation, while decaying to high-energy particles at energies of $10^{9}-10^{13} \, \text{GeV}$ from the prediction of the inflation. A scalar field responsible for diluting the dark matter abundance revives the natural inflation either with or without the recent data from the Atacama Cosmology Telescope (ACT) and baryon acoustic oscillation results from Dark Energy Spectroscopic Instrument. Since the dark matter must be a spin-zero scalar, we carefully study the galactic dark matter 3-body decay into fermions and two body decays into a gluon pair, and point out relevant multi-messenger bounds that constrain these decay modes. Interestingly, the predicted energy scale may coincide with the AMATERASU event and/or the KM3NeT neutrino event, KM3-230213A. We also point out particle models with dark baryon to further alleviate $γ$-ray bounds. This scenario yields several testable predictions for the UHECR observations, including the highest-energy neutrons that are unaffected by magnetic fields, the tensor-to-scalar ratio, the running of spectral indices, $α_s\gtrsim\mathcal{O}(0.001)$, and the existence of light new colored particles that could be accessible at future collider experiments. Further measurements of high-energy cosmic rays, including their components and detailed directions, may provide insight into not only the origin of the cosmic rays but also inflation.

hep-ph↗

arXiv2025

Axion Cosmology with Multi-Branch Yang-Mills

It is known that Yang-Mills theories, especially in the large-$N$ limit, exhibit a $θ$-vacuum structure with a multi-branched vacuum energy. In this work, we demonstrate that this multi-branch structure can play a crucial role in axion cosmology when the axion acquires its mass from the Yang-Mills sector, even when that sector is never reheated by the inflaton. The key observation is that the axion potential is directly tied to the tunneling rate between adjacent branches. We find qualitatively new phenomena, including a new class of first-order phase transitions, bouncing bubbles, and nested "bubbles-within-bubbles." When the axion has a decay constant around the Planck scale, as motivated by the string Axiverse, the axion can be driven near the hilltop by inflationary dynamics, allowing the phase transition to be triggered. The associated energy release can be large enough to generate a significant stochastic gravitational-wave background, produce primordial black holes, or populate the Yang-Mills sector with particles. These phenomena represent novel predictions of the Axiverse and should be taken into account when assessing the cosmological impact of axions or axion-like particles. To recover conventional axion cosmology, one must suppress or avoid the dynamics discussed in this work.

hep-ph↗

arXiv2025

TiCAL:Typicality-Based Consistency-Aware Learning for Multimodal Emotion Recognition

Multimodal Emotion Recognition (MER) aims to accurately identify human emotional states by integrating heterogeneous modalities such as visual, auditory, and textual data. Existing approaches predominantly rely on unified emotion labels to supervise model training, often overlooking a critical challenge: inter-modal emotion conflicts, wherein different modalities within the same sample may express divergent emotional tendencies. In this work, we address this overlooked issue by proposing a novel framework, Typicality-based Consistent-aware Multimodal Emotion Recognition (TiCAL), inspired by the stage-wise nature of human emotion perception. TiCAL dynamically assesses the consistency of each training sample by leveraging pseudo unimodal emotion labels alongside a typicality estimation. To further enhance emotion representation, we embed features in a hyperbolic space, enabling the capture of fine-grained distinctions among emotional categories. By incorporating consistency estimates into the learning process, our method improves model performance, particularly on samples exhibiting high modality inconsistency. Extensive experiments on benchmark datasets, e.g, CMU-MOSEI and MER2023, validate the effectiveness of TiCAL in mitigating inter-modal emotional conflicts and enhancing overall recognition accuracy, e.g., with about 2.6% improvements over the state-of-the-art DMD.

cs.CV↗

arXiv2025

Revisiting axion dark matter with nonlinear transitions

Recently, two of the present authors showed that even when the axion momentum is much smaller than its mass, the axion can still behave like radiation if its energy density greatly exceeds the maximum potential energy set by the cosine-type potential. As the energy density redshifts down to the potential scale, a nonlinear transition occurs, during which the axion's adiabatic invariant is not conserved. In this paper, we revisit the analysis of axion dark matter by incorporating the effects of this nonlinear transition through a precise study of the axion spectrum. We demonstrate that in the parameter region with a relatively small decay constant, often favored in axion search experiments, special care is required when estimating the axion abundance and spectrum. We also highlight a scenario in which axions are produced through the stimulated decay of a modulus, a situation that may naturally arise in the string axiverse, where the nonlinear transition occurs across a wide parameter region. Furthermore, we discuss related phenomena, including QCD axion dark matter, the formation of axion clumps such as miniclusters and axion stars, gravitational wave production, and formation of primordial black holes as dark matter.

hep-ph↗

arXiv2025

Isotropic cosmic birefringence from string axion domain walls without cosmic strings, and DESI results

Recently, results from the Atacama Cosmology Telescope (ACT) DR6 have shown a preference for isotropic cosmic birefringence, consistent with previous analyses based on Planck and WMAP data. Separately, the Dark Energy Spectroscopic Instrument (DESI) DR2 results suggest that dark energy evolves over cosmic history, pointing to new physics in the late-time universe. In this paper, we propose that domain walls associated with the string axion can naturally explain the isotropic cosmic birefringence, focusing on the case in which the axion starts near a hilltop. Interestingly, to avoid the domain wall problem, these walls must form well after recombination. The predicted rotation angle, $β\approx 0.21\,c_γ$ degrees (with anomaly coefficient $c_γ\approx 1$), is in excellent agreement with observations. This scenario can be further tested by probing anisotropic birefringence of photons emitted long after recombination, as well as gravitational waves. Moreover, starting the axion oscillation from a hilltop naturally enhances its abundance via anharmonic effects, thus contributing to the dark energy component. We discuss how this hilltop axion scenario may connect with the DESI results.

hep-ph↗

arXiv2025

Mineral Detection of Neutrinos and Dark Matter 2025 Proceedings

The third ``Mineral Detection of Neutrinos and Dark Matter'' (MD$ν$DM'25) meeting was held May 20-23, 2025 in Yokohama, Japan, hosted by the Yokohama Institute for Earth Sciences, Japan Agency for Marine-Earth Science and Technology (JAMSTEC). These proceedings compile contributions from the workshop and update the progress of mineral detector research. MD$ν$DM'25 was the third such meeting, following the first in October of 2022 held at the IFPU in Trieste, Italy and the second in January of 2024 hosted by the Center for Neutrino Physics at Virginia Tech in Arlington, USA. Mineral detectors record and retain damage induced by nuclear recoils in synthetic or natural mineral samples. The damage features can then be read out by a variety of nano- and micro-scale imaging techniques. Applications of mineral detectors on timescales relevant for laboratory experiments include reactor neutrino monitoring and dark matter detection, with the potential to measure the directions as well as the energies of the induced nuclear recoils. For natural mineral detectors which record nuclear recoils over geological timescales, reading out even small mineral samples could be sensitive to rare interactions induced by astrophysical neutrinos, cosmic rays, dark matter and heavy exotic particles. A series of mineral detectors of different ages could measure the time evolution of these fluxes, offering a unique window into the history of our solar system and the Milky Way. Mineral detector research is highly multidisciplinary, incorporating aspects of high energy physics, condensed matter physics, materials science, geoscience, and AI/ML for data analysis. Although realizing the scientific potential of mineral detectors poses many challenges, the MD$ν$DM community looks forward to the continued development of mineral detector experiments and the possible discoveries that mineral detectors could reveal.

physics.ins-det↗

arXiv2025

Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys

Refractory high-entropy alloys (RHEAs) have emerged as promising candidates for extreme high-temperature applications, for example, in next-generation turbines and nuclear reactors. In such applications, atomic diffusion critically governs essential properties including creep resistance and microstructural stability. The present study systematically investigates impurity diffusion of Co, Mn, and Zn in single phase (BCC solid solution) HfTiZrNbTa and HfTiZrNbV RHEAs applying the radiotracer technique. A neutron total scattering technique is used to evaluate the pair distribution functions and element-specific lattice distortions in these alloys. \textit{Ab initio}-based calculations give access to lattice distortions and solubilities of the impurities under investigation, including the impact of short-range order. The diffusion results are discussed in relation to calculated substitutional and interstitial solution energies, local lattice distortions, and short-range order effects. Co diffusion is found to be dominated by the interstitial mechanism, exhibiting fast diffusion. These findings reveal important structure-property relationships between local atomic environments and diffusion kinetics in BCC RHEAs, providing critical insights for designing alloys with enhanced high-temperature performance through targeted control of impurity diffusion processes.

cond-mat.mtrl-sci↗

arXiv2025

Novel Limits on Dark Photon Mixing from Radiation Safety

I propose a novel laboratory search for dark photons based on radiation-safety monitoring at synchrotron radiation facilities, including NanoTerasu, SPring-8, KEK-PF, and ESRF. Dark photons can be produced parasitically in undulators or via photon-mirror interactions, and subsequently traverse optical systems and shielding. Taking into account quantum effects and the internal structure of undulators, mirrors, and detectors, I show that even a simple Geiger-Müller counter, routinely used for radiation-safety monitoring, can detect such dark photons outside the shielding and set competitive limits on the kinetic mixing parameter down to $χ\lesssim 5\times 10^{-6}$ in the eV mass range, providing some of the strongest bounds among laboratory searches. Because radiation safety is strictly regulated, the resulting limits can be regarded as robust and realistic constraints.

hep-ph↗

arXiv2025

A Survey on Post-training of Large Language Models

The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational systems to scientific exploration. However, their pre-trained architectures often reveal limitations in specialized contexts, including restricted reasoning capacities, ethical uncertainties, and suboptimal domain-specific performance. These challenges necessitate advanced post-training language models (PoLMs) to address these shortcomings, such as OpenAI-o1/o3 and DeepSeek-R1 (collectively known as Large Reasoning Models, or LRMs). This paper presents the first comprehensive survey of PoLMs, systematically tracing their evolution across five core paradigms: Fine-tuning, which enhances task-specific accuracy; Alignment, which ensures ethical coherence and alignment with human preferences; Reasoning, which advances multi-step inference despite challenges in reward design; Efficiency, which optimizes resource utilization amidst increasing complexity; Integration and Adaptation, which extend capabilities across diverse modalities while addressing coherence issues. Charting progress from ChatGPT's alignment strategies to DeepSeek-R1's innovative reasoning advancements, we illustrate how PoLMs leverage datasets to mitigate biases, deepen reasoning capabilities, and enhance domain adaptability. Our contributions include a pioneering synthesis of PoLM evolution, a structured taxonomy categorizing techniques and datasets, and a strategic agenda emphasizing the role of LRMs in improving reasoning proficiency and domain flexibility. As the first survey of its scope, this work consolidates recent PoLM advancements and establishes a rigorous intellectual framework for future research, fostering the development of LLMs that excel in precision, ethical robustness, and versatility across scientific and societal applications.

cs.CL↗

arXiv2025

Orthorhombic nitride perovskite CeTaN3-δ with switchable and robust ferroelectric polarization

Perovskite-type ternary nitrides with predicted exciting ferroelectricity and many other outstanding properties hold great promise to be an emerging class of advanced ferroelectrics for manufacturing diverse technologically important devices. However, such nitride ferroelectrics have not yet been experimentally identified, mainly due to the challenging sample synthesis by traditional methods at ambient pressure. Here we report the successful high-pressure synthesis of a high-quality ferroelectric nitride perovskite of CeTaN3-δ with nitrogen deficiency, adopting an orthorhombic Pmn21 polar structure. This material is electrically insulating and exhibits switchable and robust electric polarization for producing ferroelectricity. Furthermore, a number of other extraordinary properties are also revealed in this nitride such as excellent mechanical properties and chemical inertness, which would make it practically useful for many device-relevant applications and fundamentally important for the study of condensed-matter physics.

cond-mat.mtrl-sci↗

arXiv2025

Quantum and Material Effects in Undulator-Based LSW Searches for Dark Photons

The dark photon is one of the simplest extensions of the Standard Model and provides a minimal laboratory for quantum-mechanical phenomena. Light-shining-through-a-wall (LSW) searches often adopt the dark photon-photon oscillation formula as if the sensitivity were independent of the light source, the wall, and the surrounding medium. In this paper, I revisit an LSW experiment whose light source is an undulator and systematically include various quantum effects: finite wave packets, kinematical suppression due to the microscopic structure of the source, and mixing suppression/enhancement in the wall and the air. We find that the resulting sensitivities deviate significantly from those obtained with the naïve oscillation formula, especially depending on the mass of the dark photon, relevant to reflective index of the medium or walls, there can be resonance effects enhancing the sensitivity significantly. Accounting for these effects, we show that placing a photon detector outside the shielding along the beamline of a synchrotron facility enables an economical, parasitic LSW search for dark photons.

hep-ph↗

arXiv2025

Stability of domain walls with inflationary fluctuations under potential bias, and gravitational wave signatures

A recent study has shown that domain walls with inflationary initial fluctuations exhibit remarkable stability against population bias due to long-range correlations, challenging the claims of prior research. In this paper, we study the dynamics of these domain walls in the presence of potential bias and show that they collapse with a lifetime several times longer than that due to thermal fluctuations. This is interpreted as a difference in the average distance between domain walls, leading us to derive a new formula for the domain wall lifetime which depends on the area parameter in a qualitatively different way from previous studies. In addition, we compute the spectrum of gravitational waves generated by such domain walls and find that both the peak frequency and the peak abundance are lowered in a manner that depends on the area parameter. Based on these findings, we also determine the necessary degree of vacuum degeneracy for axion domain walls to explain the isotropic cosmic birefringence.

hep-ph↗

arXiv2025

Knowledge-Aligned Counterfactual-Enhancement Diffusion Perception for Unsupervised Cross-Domain Visual Emotion Recognition

Visual Emotion Recognition (VER) is a critical yet challenging task aimed at inferring emotional states of individuals based on visual cues. However, existing works focus on single domains, e.g., realistic images or stickers, limiting VER models' cross-domain generalizability. To fill this gap, we introduce an Unsupervised Cross-Domain Visual Emotion Recognition (UCDVER) task, which aims to generalize visual emotion recognition from the source domain (e.g., realistic images) to the low-resource target domain (e.g., stickers) in an unsupervised manner. Compared to the conventional unsupervised domain adaptation problems, UCDVER presents two key challenges: a significant emotional expression variability and an affective distribution shift. To mitigate these issues, we propose the Knowledge-aligned Counterfactual-enhancement Diffusion Perception (KCDP) framework. Specifically, KCDP leverages a VLM to align emotional representations in a shared knowledge space and guides diffusion models for improved visual affective perception. Furthermore, a Counterfactual-Enhanced Language-image Emotional Alignment (CLIEA) method generates high-quality pseudo-labels for the target domain. Extensive experiments demonstrate that our model surpasses SOTA models in both perceptibility and generalization, e.g., gaining 12% improvements over the SOTA VER model TGCA-PVT. The project page is at https://yinwen2019.github.io/ucdver.

cs.CV↗