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Xiao Lu

Publications and source records attributed to Xiao Lu.

At least 19 recordsLinked to original sources

Observational Evidence Revises Presumed Large Ozone Worsening from Nitrogen Oxides Cuts

Many air quality models indicate that rapid reductions in nitrogen oxides (NOx), without comparable controls on volatile organic compounds, have worsened summertime ozone pollution in urban China, producing a short-term strong ozone penalty. Other models, however, simulate the opposite response, suggesting that cutting down NOx has already helped mitigate ozone pollution. This contradiction obscures understanding of atmospheric chemistry and weakens guidance on control policy design. Here, we reconcile this disagreement and reveal the underestimated benefits of NOx emission reductions using a machine learning framework integrated with an observational constraint. We first constrain ozone responses under a 30% NOx reduction, comparable to the magnitude of NOx emission declines across major Chinese city clusters between 2015 and 2023. The constrained results indicate that ozone decreases prevail across urban China, with only small increases mainly in July 2015. This challenges the widespread ozone worsening that many models predict. We then extend the constraint across 10-60% NOx reductions, establishing its use for rapid ozone sensitivity diagnosis without exhaustive scenario modeling. This diagnosis shows that sustained NOx control increasingly favored ozone mitigation during 2015-2023, benefiting a growing share of China's population. These results underscore that continued NOx reductions can deliver larger ozone mitigation benefits than many models suggest.

physics.ao-ph

The $^{229}$Th Isomer: Nuclear Structure, Clocks, and Tests of Fundamental Physics

The $^{229}$Th nucleus possesses an isomeric state at an excitation energy of $\sim 8$ eV, the lowest known nuclear transition energy, placing its frequency in the vacuum-ultraviolet range and making it directly accessible to laser spectroscopy. In this review, we discuss the $^{229}$Th isomer from three connected perspectives: experimental spectroscopy and clock development, nuclear structure theory, and applications to precision tests of fundamental physics. We first trace the experimental progress from indirect $\gamma$-ray energy inference to resonant laser excitation, absolute frequency comparison with an atomic clock, and feedback-loop operation of a solid-state nuclear clock, and discuss trapped-ion, highly charged ion, and solid-state platforms together with mechanisms for nuclear-state manipulation and readout. We then review, from the nuclear-structure perspective, how the near-degeneracy of the $5/2^+[633]$ and $3/2^+[631]$ neutron Nilsson configurations, together with Coriolis mixing and octupole correlations, underlies the anomalously low transition energy and its electromagnetic properties. Comparisons among different phenomenological and microscopic models show that octupole correlations are a common structural ingredient, while magnetic moments and transition strengths remain sensitive tests of the calculated wave functions. Finally, we discuss how the near-cancellation of MeV-scale nuclear contributions into an eV-scale transition can enhance sensitivity to variations of fundamental constants, signatures of ultralight dark matter, CP-violating interactions, Lorentz-invariance violation, and possible nuclear quantum technologies.

nucl-th

A Context Augmented Multi-Play Multi-Armed Bandit Algorithm for Fast Channel Allocation in Opportunistic Spectrum Access

We study the restless contextual multi-play multi-armed bandit (MP-MAB) problem for channel allocation in the opportunity spectrum access (OSA) scenario. Most existing MP-MAB methods are impractical for real-world OSA systems as they assume many ideal conditions, incur a heavy computational cost, and most importantly, ignore the impact of channel noise which is directly related to the quality of service. In this study, we embody this impact by modeling channel noise as a perturbation of the arm's reward function in MP-MAB. As there is an implicit correlation between channel state information and channel noise, we take the former as a context for MP-MAB to present the perturbation caused by the latter. We investigate two types of correlation between the context and the perturbation -- linear and nonlinear, and derive two index policies, respectively. These policies learn the correlations through a linear model and a neural network, and use estimated noise value to adjust the upper confidence bound. Numerical experiments demonstrate that the proposed policies can achieve lower regret and select sub-optimal arms in a more reasonable way.

cs.LG

Deformed neutron halo nuclei and soft dipole excitations in the 40<A<90 mass region

We study deformed neutron halo nuclei in the mass region $40 < A < 90$ and their soft electric dipole ($E1$) excitations based on the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc). Three candidates, $^{43}$Si, $^{69}$Ti, and $^{75}$Cr, are selected for detailed analysis. Unique features are identified in the decoupled densities of possible $s$- and $p$-wave deformed halo nuclei in this mass region, which are influenced by large high-$l$ configurations. It is shown that the dipole response is a highly sensitive observable to detect the halo component of the single-particle wave function in deformed halo nucleus, and it helps identify the configuration and the magnitude of deformation for halo nuclei in the $40 < A < 90$ mass region. Experimental confirmation of the dipole strength in the low-energy region is highly desirable to explore possible deformed halo candidates in the medium-heavy mass region.

nucl-th

A Halo: The Trigger to a New Era of Nuclear Correlations

In this contribution to the Halo-40 Proceedings, we discuss two topics regarding halo phenomena: The first is the pairing anti-halo effect on the neutron radius of halo nuclei and its restoration due to the coupling to the continuum; the second is the soft dipole excitation of deformed halo nuclei. We demonstrate the importance of Hartree-Fock-Bogoliubov and the relativistic Hartree-Bogoliubov theory in continuum for properly taking into account the halo nature of extended wave functions in calculations of neutron radii, as well as the soft dipole excitations of halo nuclei. It was shown that the anti-halo effect is very sensitive to the continuum coupling induced by Bogoliubov-type quasi-particles, which largely cancels the anti-halo effect on the neutron radius. The soft dipole excitations of deformed halo nuclei Ne-31 and Mg-37 are discussed within the deformed Woods-Saxon model. We point out that the sharp peak just above the threshold in the dipole response is created by the halo effect, and its strength can be used to identify the magnitude of deformation and the halo configuration in the Nilsson level scheme.

nucl-th

Automating Crash Diagram Generation Using Vision-Language Models: A Case Study on Multi-Lane Roundabouts

Crash diagrams are essential tools in transportation safety analysis, yet their manual preparation remains time-consuming and prone to human variability. This study investigates the use of Vision-Language Models (VLMs) to automate crash diagram generation from police crash reports, focusing on multilane roundabouts as a challenging test case. A three-part structured prompt framework was developed to guide model reasoning through interpretation, extraction, and visual synthesis, while a 10-metric evaluation system was designed to assess diagram quality in terms of semantic accuracy, spatial fidelity, and visual clarity. Three popular models, including GPT-4o, Gemini-1.5-Flash, and Janus-4o, were tested on 79 crash reports. GPT-4o achieved the highest average performance (6.29 out of 10), followed by Gemini-1.5-Flash (5.28) and Janus-4o (3.64). The analysis revealed GPT-4o's superior spatial reasoning and alignment between extracted and visualized crash data. These results highlight both the promise and current limitations of VLMs in engineering visualization tasks. The study lays the groundwork for integrating generative AI into crash analysis workflows to improve efficiency, consistency, and interpretability.

cs.HC

Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation

We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which only 6.1 billion are active per token. This architecture enables highly efficient scaling (dramatically improving computational efficiency while significantly expanding model capacity) and empowers stronger unified multimodal intelligence across vision, speech, and language, representing a key step toward Artificial General Intelligence (AGI). Compared to its predecessor, the upgraded version exhibits substantial improvements across multimodal understanding and generation. Notably, it achieves strong performance on vision-language understanding benchmarks, with overall scores on par with Gemini 2.5 Pro, and enables seamless switching among multimodal tasks in multi-turn interactions. In speech, it achieves strong performance in contextual and dialect-aware ASR while enabling joint, continuous-generation of speech, sound, and music. In vision, it introduces generative semantic segmentation that achieves competitive standalone performance and enhances spatial control and editing consistency, alongside marked improvements in identity preservation, and high-fidelity in-image text rendering. Together, these capabilities demonstrate that a single unified model can serve as a practical foundation for general-purpose multimodal intelligence.

cs.CV

Performance Analysis of End-to-End LEO Satellite-Aided Shore-to-Ship Communications: A Stochastic Geometry Approach

Low Earth orbit (LEO) satellite networks have shown strategic superiority in maritime communications, assisting in establishing signal transmissions from shore to ship through space-based links. Traditional performance modeling based on multiple circular orbits is challenging to characterize large-scale LEO satellite constellations, thus requiring a tractable approach to accurately evaluate the network performance. In this paper, we propose a theoretical framework for an LEO satellite-aided shore-to-ship communication network (LEO-SSCN), where LEO satellites are distributed as a binomial point process (BPP) on a specific spherical surface. The framework aims to obtain the end-to-end transmission performance by considering signal transmissions through either a marine link or a space link subject to Rician or Shadowed Rician fading, respectively. Due to the indeterminate position of the serving satellite, accurately modeling the distance from the serving satellite to the destination ship becomes intractable. To address this issue, we propose a distance approximation approach. Then, by approximation and incorporating a threshold-based communication scheme, we leverage stochastic geometry to derive analytical expressions of end-to-end transmission success probability and average transmission rate capacity. Extensive numerical results verify the accuracy of the analysis and demonstrate the effect of key parameters on the performance of LEO-SSCN.

eess.SP

Octupole correlations in $^{220,222,224,226}$Rn

The octupole correlations in $^{220,222,224,226}$Rn are investigated by using multi-dimensionally constrained covariant density functional theory. The ground-state properties and potential energy surfaces are analyzed, revealing that octupole deformation appears in $^{222,224}$Rn, but not in $^{220,226}$Rn. The relationship between pairing correlations and octupole deformation is examined, showing that the neutron pairing energy decreases as octupole deformation develops, whereas the proton pairing energy shows the opposite behavior. The microscopic origin of octupole correlations in these radon isotopes are explored based on an examination of the single-particle levels near the Fermi surface and a schematic two-level model. Experiments have indicated that these isotopes undergo octupole vibrations and the present prediction of octupole deformation in $^{222,224}$Rn awaits further confirmation.

nucl-th

Ming-Omni: A Unified Multimodal Model for Perception and Generation

We propose Ming-Omni, a unified multimodal model capable of processing images, text, audio, and video, while demonstrating strong proficiency in both speech and image generation. Ming-Omni employs dedicated encoders to extract tokens from different modalities, which are then processed by Ling, an MoE architecture equipped with newly proposed modality-specific routers. This design enables a single model to efficiently process and fuse multimodal inputs within a unified framework, thereby facilitating diverse tasks without requiring separate models, task-specific fine-tuning, or structural redesign. Importantly, Ming-Omni extends beyond conventional multimodal models by supporting audio and image generation. This is achieved through the integration of an advanced audio decoder for natural-sounding speech and Ming-Lite-Uni for high-quality image generation, which also allow the model to engage in context-aware chatting, perform text-to-speech conversion, and conduct versatile image editing. Our experimental results showcase Ming-Omni offers a powerful solution for unified perception and generation across all modalities. Notably, our proposed Ming-Omni is the first open-source model we are aware of to match GPT-4o in modality support, and we release all code and model weights to encourage further research and development in the community.

cs.AI

Language-Driven Dual Style Mixing for Single-Domain Generalized Object Detection

Generalizing an object detector trained on a single domain to multiple unseen domains is a challenging task. Existing methods typically introduce image or feature augmentation to diversify the source domain to raise the robustness of the detector. Vision-Language Model (VLM)-based augmentation techniques have been proven to be effective, but they require that the detector's backbone has the same structure as the image encoder of VLM, limiting the detector framework selection. To address this problem, we propose Language-Driven Dual Style Mixing (LDDS) for single-domain generalization, which diversifies the source domain by fully utilizing the semantic information of the VLM. Specifically, we first construct prompts to transfer style semantics embedded in the VLM to an image translation network. This facilitates the generation of style diversified images with explicit semantic information. Then, we propose image-level style mixing between the diversified images and source domain images. This effectively mines the semantic information for image augmentation without relying on specific augmentation selections. Finally, we propose feature-level style mixing in a double-pipeline manner, allowing feature augmentation to be model-agnostic and can work seamlessly with the mainstream detector frameworks, including the one-stage, two-stage, and transformer-based detectors. Extensive experiments demonstrate the effectiveness of our approach across various benchmark datasets, including real to cartoon and normal to adverse weather tasks. The source code and pre-trained models will be publicly available at https://github.com/qinhongda8/LDDS.

cs.CV

Octupole correlations in superdeformed bands of $^{56}$Ni

The projected multi-dimensionally-constrained relativistic Hartree-Bogoliubov model was employed to calculate the potential energy surface of the high-spin states in $^{56}\text{Ni}$. It is pointed out for the first time that possible octupole deformations exist for the positive and negative parity superdeformed bands in $^{56}\text{Ni}$, with deformations $\beta_{30}\sim0.14$ and $\beta_{30}\sim0.24$, respectively, along with a large prolate deformation of $\beta_{20}\sim 0.42$. These octupole deformations are induced by the coupling between $2p_{3/2}$ and $1g_{9/2}$ orbits at the deformation $\beta_{20}\sim 0.4$. The calculated excitation energies of the two rotational bands are consistent with the observed superdeformed bands of $^{56}\text{Ni}$. In addition, two rotational bands are predicted, consisting of one superdeformed band with negative parity and one hyperdeformed bands with positive parity.

nucl-th

Dipole response of deformed halo nuclei $^{31}$Ne and $^{37}$Mg

We study the soft electric dipole ($E1$) response of deformed halo nuclei $^{31}$Ne and $^{37}$Mg using a deformed Woods-Saxon potential, with the potential depth adjusted to reproduce empirical separation energy of last neutron orbit, i.e., 150 keV for $^{31}$Ne and 220 keV for $^{37}$Mg. The configuration dependence of the $E1$ strength near the neutron threshold is pointed out. The halo configurations $[321]3/2$ at $\beta_2=0.5$ and $[330]1/2$ at $\beta_2=0.24$ in $^{31}$Ne contain large amplitudes of halo $p$-shell orbits, which significantly enhance the threshold strength by several times compared to the non-halo configuration $[202]5/2$ at $\beta_2=0.32$. In $^{37}$Mg, the last neutron configuration is assigned as $[321]1/2$ at a large deformation of $\beta_2=0.46$, which involves a halo $p$-shell configuration that significantly enhances the soft dipole strength. This enhancement is about 60\% larger than that of the $[321]3/2$ configuration in $^{31}$Ne because of large $p$-shell probability in $^{37}$Mg. Experimental confirmation of the soft dipole strength is highly desired to determine the deformation and the configuration of the last neutron orbits both in $^{31}$Ne and $^{37}$Mg.

nucl-th

Unlocking Multi-View Insights in Knowledge-Dense Retrieval-Augmented Generation

While Retrieval-Augmented Generation (RAG) plays a crucial role in the application of Large Language Models (LLMs), existing retrieval methods in knowledge-dense domains like law and medicine still suffer from a lack of multi-perspective views, which are essential for improving interpretability and reliability. Previous research on multi-view retrieval often focused solely on different semantic forms of queries, neglecting the expression of specific domain knowledge perspectives. This paper introduces a novel multi-view RAG framework, MVRAG, tailored for knowledge-dense domains that utilizes intention-aware query rewriting from multiple domain viewpoints to enhance retrieval precision, thereby improving the effectiveness of the final inference. Experiments conducted on legal and medical case retrieval demonstrate significant improvements in recall and precision rates with our framework. Our multi-perspective retrieval approach unleashes the potential of multi-view information enhancing RAG tasks, accelerating the further application of LLMs in knowledge-intensive fields.

cs.CL

Nuclear mass table in deformed relativistic Hartree-Bogoliubov theory in continuum, II: Even-$Z$ nuclei

The mass table in the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) with the PC-PK1 density functional has been established for even-$Z$ nuclei with $8\le Z\le120$, extended from the previous work for even-even nuclei [Zhang $\it{et.~al.}$ (DRHBc Mass Table Collaboration), At. Data Nucl. Data Tables 144, 101488 (2022)]. The calculated binding energies, two-nucleon and one-neutron separation energies, root-mean-square (rms) radii of neutron, proton, matter, and charge distributions, quadrupole deformations, and neutron and proton Fermi surfaces are tabulated and compared with available experimental data. A total of 4829 even-$Z$ nuclei are predicted to be bound, with an rms deviation of 1.477 MeV from the 1244 mass data. Good agreement with the available experimental odd-even mass differences, $\alpha$ decay energies, and charge radii is also achieved. The description accuracy for nuclear masses and nucleon separation energies as well as the prediction for drip lines is compared with the results obtained from other relativistic and nonrelativistic density functional. The comparison shows that the DRHBc theory with PC-PK1 provides an excellent microscopic description for the masses of even-$Z$ nuclei. The systematics of the nucleon separation energies, odd-even mass differences, pairing energies, two-nucleon gaps, $\alpha$ decay energies, rms radii, quadrupole deformations, potential energy curves, neutron density distributions, and neutron mean-field potentials are discussed.

nucl-th

Towards Source-free Domain Adaptive Semantic Segmentation via Importance-aware and Prototype-contrast Learning

Domain adaptive semantic segmentation enables robust pixel-wise understanding in real-world driving scenes. Source-free domain adaptation, as a more practical technique, addresses the concerns of data privacy and storage limitations in typical unsupervised domain adaptation methods, making it especially relevant in the context of intelligent vehicles. It utilizes a well-trained source model and unlabeled target data to achieve adaptation in the target domain. However, in the absence of source data and target labels, current solutions cannot sufficiently reduce the impact of domain shift and fully leverage the information from the target data. In this paper, we propose an end-to-end source-free domain adaptation semantic segmentation method via Importance-Aware and Prototype-Contrast (IAPC) learning. The proposed IAPC framework effectively extracts domain-invariant knowledge from the well-trained source model and learns domain-specific knowledge from the unlabeled target domain. Specifically, considering the problem of domain shift in the prediction of the target domain by the source model, we put forward an importance-aware mechanism for the biased target prediction probability distribution to extract domain-invariant knowledge from the source model. We further introduce a prototype-contrast strategy, which includes a prototype-symmetric cross-entropy loss and a prototype-enhanced cross-entropy loss, to learn target intra-domain knowledge without relying on labels. A comprehensive variety of experiments on two domain adaptive semantic segmentation benchmarks demonstrates that the proposed end-to-end IAPC solution outperforms existing state-of-the-art methods. The source code is publicly available at https://github.com/yihong-97/Source-free-IAPC.

cs.CV

Finding the best basis states for the variation after projection nuclear wave functions

The variation after projection (VAP) method is expected to be an efficient way of getting the optimized nuclear wave functions, so that they can be as close as possible to the exact shell model ones. However, we found there are two additional problems that may seriously affect the convergence of the VAP iteration. The first problem is, if a randomly selected projected basis state does not mix with a VAP wave function in the VAP calculation, then it is likely that this basis state will never mix with the VAP wave function even after the VAP iteration converges, which means such selected projected basis state is useless. The other problem is the poor orthonormality among the projected basis states that seriously affect the accuracy of the calculated VAP wave function. In the present work, solutions for these two problems are proposed and some examples are presented to test the validity. It turns out that, with the present solutions, the most important projected basis states can be reliably obtained and the fully optimized VAP wave functions can be accurately and efficiently calculated.

nucl-th

Removal of $K$-mixing in angular momentum projected nuclear wave functions

Angular momentum projection plays a key role in studying quantum many-body systems with rotational invariance such as atomic nuclei. At a given spin $J$, one can generate $2J+1$ angular momentum projected states labeled with $-J\leq K \leq J$ from a deformed Slater determinant. Usually, a nuclear wave function with $K$-mixing can be expressed as a superposition of all these $2J+1$ projected states, where the coefficients can be obtained by solving the generalized eigenvalue equation. In this Letter, we report a new fundamental feature that the frequently discussed $K$-mixing in the angular momentum projected nuclear wave function can be safely removed. Strikingly, we found that such nuclear wave function with $K$-mixing can always be equivalently replaced by a single projected state with any given $K$. Consequently, such nuclear wave function can be significantly simplified, especially for high-spin states. This also indicates that the $K$-mixing in the angular momentum projected nuclear wave functions, adopted by many present-day nuclear models, does not carry any physical meaning, and is essentially different from that $K$-mixing caused by the Coriolis force in the cranked shell model.

nucl-th