arXiv subjects

Yuxiang Li

Publications and source records attributed to Yuxiang Li.

At least 19 recordsLinked to original sources

arXiv2026

A nuclear clock based on $^{229}$Th

Atomic clocks have made time and frequency the most precisely measured quantities in physics, progressing from microwave standards that realize the SI second to optical clocks that now reach unprecedented levels of precision. A nuclear clock would shift the frequency reference from an electronic transition to the uniquely low-lying, laser-accessible isomeric transition in the $^{229}$Th nucleus, offering a route to compact, robust timekeeping and sensitive tests of fundamental physics. However, turning recent advances in spectroscopy of the $^{229}$Th nuclear resonance into clock operation requires the nuclear transition to serve as a stable discriminator for steering a traceable oscillator. Here we demonstrate the operation of a $^{229}$Th nuclear clock by stabilizing a continuous-wave narrow-linewidth 148.4 nm vacuum-ultraviolet (VUV) laser to a resolved nuclear transition in a solid-state host. This clock operation is enabled by fast frequency discrimination based on phototube photocurrent readout of the transmitted VUV power. The 10 $\mu$W VUV laser, generated by four-wave mixing in cadmium vapour, provides a high-signal-to-noise absorption signal from a home-grown $^{229}$Th:CaF$_2$ crystal, allowing the laser to be locked to a weakly temperature-sensitive nuclear transition. The clock reaches a fractional frequency instability of $2\times10^{-12}/\sqrt{\tau/s} $, where $\tau$ is the averaging time. Remarkably, nuclear-clock frequencies measured with two distinct crystals agree at the $10^{-13}$ level, demonstrating the reproducibility of solid-state nuclear frequency references. By making a laser-addressed atomic nucleus an operational clock reference, this work extends quantum metrology from electronic to nuclear transitions, and opens a new platform for compact clocks, solid-state nuclear quantum sensors and precision tests of fundamental physics.

physics.atom-ph↗

arXiv2026

On the ends of Willmore surfaces with curvature decay

For a properly embedded Willmore surface $\Sigma$ in $\mathbb R^3$, we prove that if the scale-invariant second fundamental form is sufficiently small near infinity, the surface has finitely many ends. Moreover, if this scale-invariant quantity vanishes at infinity, or if there is only one end, the total $L^2$-norm of the second fundamental form is finite.

math.DG↗

arXiv2026

Decentralized Heterogeneous Multi-Robot Collaborative Exploration for Indoor and Outdoor 3D Environments

Heterogeneous multi-robot systems feature significant adaptability for complex environments. However, effective collaboration that fully exploits the robots' potential remains a core challenge. This paper proposes a decentralized collaborative framework for heterogeneous multi-robot systems to autonomously explore indoor and outdoor 3D environments. First, a basic perception map that integrates terrain and observation metrics is designed. Improved supervoxel segmentation is developed to simplify the map structure and form a high-level representation that supports lightweight communication. Second, the traversal and observation capabilities of heterogeneous robots are modeled to evaluate the requirements of task views derived from incomplete supervoxels. These task views are grouped by requirements and clustered to streamline assignment. Subsequently, the view-cluster assignment is formulated as a heterogeneous multi-depot multi-traveling salesman problem (HMDMTSP) that incorporates constraints between view-cluster requirements and robot capabilities. An improved genetic algorithm is developed to efficiently solve this problem while ensuring global consistency. Based on the assignments, redundant views within clusters are eliminated to refine exploration routes. Finally, conflicts between robots' motion paths are resolved. Simulations and field experiments in cluttered indoor and outdoor environments demonstrate that our approach effectively coordinates exploration tasks among heterogeneous robots, achieving superior exploration efficiency and communication savings compared to state-of-the-art approaches.

cs.RO↗

arXiv2026

Open World Knowledge Aided Single-Cell Foundation Model with Robust Cross-Modal Cell-Language Pre-training

Recent advancements in single-cell multi-omics, particularly RNA-seq, have provided profound insights into cellular heterogeneity and gene regulation. While pre-trained language model (PLM) paradigm based single-cell foundation models have shown promise, they remain constrained by insufficient integration of in-depth individual profiles and neglecting the influence of noise within multi-modal data. To address both issues, we propose an Open-world Language Knowledge-Aided Robust Single-Cell Foundation Model (OKR-CELL). It is built based on a cross-modal Cell-Language pre-training framework, which comprises two key innovations: (1) leveraging Large Language Models (LLMs) based workflow with retrieval-augmented generation (RAG) enriches cell textual descriptions using open-world knowledge; (2) devising a Cross-modal Robust Alignment (CRA) objective that incorporates sample reliability assessment, curriculum learning, and coupled momentum contrastive learning to strengthen the model's resistance to noisy data. After pretraining on 32M cell-text pairs, OKR-CELL obtains cutting-edge results across 6 evaluation tasks. Beyond standard benchmarks such as cell clustering, cell-type annotation, batch-effect correction, and few-shot annotation, the model also demonstrates superior performance in broader multi-modal applications, including zero-shot cell-type annotation and bidirectional cell-text retrieval.

q-bio.GN↗

arXiv2026

Boundedness in a two-dimensional doubly degenerate nutrient taxis system with logistic source

We are concerned with the following doubly degenerate nutrient taxis system \begin{align} \begin{cases}\tag{$\star$}\label{eq-0.1} u_t=\nabla\cdot(u v\nabla u)-\nabla\cdot(u^{2} v\nabla v)+u-u^2,\\[1mm] v_t=\Delta v-u v, \end{cases} \end{align} posed in a bounded smooth domain $\Omega\subset\mathbb{R}^2$ under homogeneous Neumann boundary conditions. This model was introduced to describe the aggregation patterns of colonies of \emph{Bacillus subtilis} observed on thin agar plates. Previous results have established global boundedness in one space dimension and, in two dimensions, under additional assumptions such as small initial data or convex domains (see, e.g., M. Winkler, \textit{Trans. Amer. Math. Soc.}, 2021; M. Winkler, \textit{J. Differ. Equ.}, 2024). In the presence of the quadratic degradation term in the logistic growth, which markedly enhances the dissipative structure of the system, and by employing a weighted energy method, we prove that for arbitrary smooth initial data the problem \eqref{eq-0.1} admits a global weak solution that remains uniformly bounded in time.

math.AP↗

arXiv2026

Critical blow-up lines in a two-species quasilinear chemotaxis system with two chemicals

In this study, we explore the quasilinear two-species chemotaxis system with two chemicals \begin{align}\tag{$\star$} \begin{cases} u_t = \nabla \cdot(D(u)\nabla u) - \nabla \cdot \left(S(u) \nabla v\right), & x \in \Omega, \ t > 0, \\ 0 = \Delta v - \mu_w + w, \quad \mu_w=\fint_{\Omega}w, & x \in \Omega, \ t > 0, \\ w_t = \Delta w - \nabla \cdot \left(w \nabla z\right), & x \in \Omega, \ t > 0, \\ 0 = \Delta z - \mu_u + u, \quad \mu_u=\fint_{\Omega}u, & x \in \Omega, \ t > 0, \\ \frac{\partial u}{\partial \nu} = \frac{\partial v}{\partial \nu} = \frac{\partial w}{\partial \nu} = \frac{\partial z}{\partial \nu} = 0, & x \in \partial \Omega, \ t > 0, \\ u(x, 0) = u_0(x), \quad w(x, 0) = w_0(x), & x \in \Omega, \end{cases} \end{align} where $\Omega \subset \mathbb{R}^n$ ($n \geq3$) is a smooth bounded domain. The functions $D(s)$ and $S(s)$ exhibit asymptotic behavior of the form \begin{align*} D(s) \simeq k_D s^p \ \text {and} \ S(s) \simeq k_S s^q, \quad s \gg 1 \end{align*} with $p,q \in \mathbb{R}$. We prove that \begin{itemize} \item when $\Omega$ is a ball, if $q-p>2-\frac{n}{2}$ and $q>1-\frac{n}{2}$, there exist radially symmetric initial data $u_0$ and $w_0$, such that the corresponding solutions blow up in finite time; \item for any general smooth bounded domain $\Omega \subset \mathbb{R}^n$, if $q-p<2-\frac{n}{2}$, all solutions are globally bounded; \item for any general smooth bounded domain $\Omega \subset \mathbb{R}^n$, if $q<1-\frac{n}{2}$, all solutions are global. \end{itemize} We point out that our results implies that the system ($\star$) possess two critical lines $ q-p=2-\frac{n}{2}$ and $q=1-\frac{n}{2}$ to classify three dynamics among global boundedness, finite-time blow-up, and global existence of solutions to system ($\star$).

math.AP↗

arXiv2026

Critical blow-up curve in a two-species chemotaxis system with two chemicals involving flux-limitation

We investigate the following two-species chemotaxis system with two chemicals involving flux-limitation \begin{align}\tag{$\star$} \begin{cases} u_t = \Delta u - \nabla \cdot \left(u(1+|\nabla v|^2)^{-\frac{p}{2}}\nabla v\right), & x \in \Omega, \ t > 0, \\ 0 = \Delta v - \mu_w + w, \quad \mu_{w}=f_{\Omega} w, & x \in \Omega, \ t > 0, \\ w_t = \Delta w - \nabla \cdot \left(w (1+|\nabla z|^2)^{-\frac{q}{2}} \nabla z\right), & x \in \Omega, \ t > 0, \\ 0 = \Delta z - \mu_u + u, \quad \mu_{u}=f_{\Omega} u, & x \in \Omega, \ t > 0, \\ \frac{\partial u}{\partial \nu} = \frac{\partial v}{\partial \nu} = \frac{\partial w}{\partial \nu} = \frac{\partial z}{\partial \nu} = 0, & x \in \partial \Omega, \ t > 0, \\ u(x, 0) = u_0(x), \quad w(x, 0) = w_0(x), & x \in \Omega, \end{cases} \end{align} where $p,q \in \mathbb{R}$ and $\Omega \subset \mathbb{R}^n$ is a smooth bounded domain. In this paper, we identify a critical blow-up curve for system ($\star$) with $n\geq 3$. If $p<\frac{n-2}{n-1}$ and $q<\frac{n-2}{n-1}$, and $\Omega=B_R(0) \subset \mathbb{R}^n$ with $n\geq 3$, there exist radially symmetric initial data such that the corresponding solution blows up in finite time; if either $p>\frac{n-2}{n-1}$ or $q>\frac{n-2}{n-1}$ with $n\geq 2$, then solutions exist globally and remain bounded.

math.AP↗

arXiv2026

Finite-time blow-up in a quasilinear two-species chemotaxis system with two chemicals

This paper investigates the finite-time blow-up phenomena to a quasilinear two-species chemotaxis system with two chemicals \begin{align}\tag{$\star$} \begin{cases} u_t = \nabla \cdot \left(D_1(u) \nabla u\right) - \nabla \cdot \left(u \nabla v\right), & x \in \Omega, \ t > 0, 0 = \Delta v - \mu_2 + w, \quad \mu_2=\fint_{\Omega}w, & x \in \Omega, \ t > 0, w_t = \nabla \cdot \left(D_2(w) \nabla w\right) - \nabla \cdot \left(w \nabla z\right), & x \in \Omega, \ t > 0, 0 = \Delta z - \mu_1 + u, \quad \mu_1=\fint_{\Omega}u, & x \in \Omega, \ t > 0, \frac{\partial u}{\partial \nu} = \frac{\partial v}{\partial \nu} = \frac{\partial w}{\partial \nu} = \frac{\partial z}{\partial \nu} = 0, & x \in \partial \Omega, \ t > 0, u(x, 0) = u_0(x), \quad w(x, 0) = w_0(x), & x \in \Omega, \end{cases} \end{align} where $\Omega \subset \mathbb{R}^n$ $(n \geqslant 3)$ is a smoothly bounded domain. The nonlinear diffusion functions $ D_1(s) $ and $ D_2(s) $ are of the following forms: \begin{align*} D_1(s)\simeq s^{m_1-1} \quad \text{and}\quad D_2(s) \simeq s^{m_2-1}, \quad m_1,m_2> 1 \end{align*} for $s\geqslant 1$. For the classical two-species chemotaxis system with two chemicals (i.e. the second and fourth equations are replaced by $0 = \Delta v - v + w$ and $0 = \Delta z - z + u$ ), Zhong [J. Math. Anal. Appl., 500 (2021), Paper No. 125130, pp. 22.] showed that the system possesses a globally bounded classical solution in the case that \[ m_1 + m_2 < \max\left\{m_1m_2 + \frac{2m_1}{ n},\ m_1m_2 + \frac{2m_2 }{ n}\right\}. \] Complementing the boundedness result, we prove that the system ($\star$) admits solutions that blow up in finite time, if \[ m_1 + m_2 > \max\left\{ m_1m_2 + \frac{2m_1}{ n},\ m_1m_2 + \frac{2m_2}{ n}\right\} \] with $n\geqslant 3$.

math.AP↗

arXiv2025

ARIMA_PLUS: Large-scale, Accurate, Automatic and Interpretable In-Database Time Series Forecasting and Anomaly Detection in Google BigQuery

Time series forecasting and anomaly detection are common tasks for practitioners in industries such as retail, manufacturing, advertising and energy. Two unique challenges stand out: (1) efficiently and accurately forecasting time series or detecting anomalies in large volumes automatically; and (2) ensuring interpretability of results to effectively incorporate business insights. We present ARIMA_PLUS, a novel framework to overcome these two challenges by a unique combination of (a) accurate and interpretable time series models and (b) scalable and fully managed system infrastructure. The model has a sequential and modular structure to handle different components of the time series, including holiday effects, seasonality, trend, and anomalies, which enables high interpretability of the results. Novel enhancements are made to each module, and a unified framework is established to address both forecasting and anomaly detection tasks simultaneously. In terms of accuracy, its comprehensive benchmark on the 42 public datasets in the Monash forecasting repository shows superior performance over not only well-established statistical alternatives (such as ETS, ARIMA, TBATS, Prophet) but also newer neural network models (such as DeepAR, N-BEATS, PatchTST, TimeMixer). In terms of infrastructure, it is directly built into the query engine of BigQuery in Google Cloud. It uses a simple SQL interface and automates tedious technicalities such as data cleaning and model selection. It automatically scales with managed cloud computational and storage resources, making it possible to forecast 100 million time series using only 1.5 hours with a throughput of more than 18000 time series per second. In terms of interpretability, we present several case studies to demonstrate time series insights it generates and customizability it offers.

cs.DC↗

arXiv2025

Quantum-Classical Hybrid Computation of Electron Transfer in a Cryptochrome Protein via VQE-PDFT and Multiscale Modeling

Accurate calculation of strongly correlated electronic systems requires proper treatment of both static and dynamic correlations, which remains challenging for conventional methods. To address this, we present VQE-PDFT,aquantum-classical hybrid framework that integrates variational quantum eigensolver with multiconfiguration pair-density functional theory (MC-PDFT). This framework strategically employs quantum circuits for multiconfigurational wavefunction representation while utilizing density functionals for correlation energy evaluation. The hybrid strategy maintains accurate treatment of static and dynamic correlations while reducing quantum resource requirements compared to highly expressive quantum algorithms. Benchmark validation, performed via noiseless quantum circuit simulator, on the Charge-Transfer dataset confirmed that VQE-PDFT achieved results comparable to conventional MC-PDFT. Building upon this, we developed shallow-depth hardware-efficient ansatz circuits and integrated them into a QM/MM multiscale architecture to enable applications in complex biological systems. This extended framework, when applied to electron transfer in the European robin cryptochrome protein ErCRY4 with noiseless simulations, yielded transfer rates that aligned well with experimental measurements. Finally, as a proof-of-concept hardware demonstration, we executed the reduced-density-matrix measurements for a single protein conformation on a 13-qubit superconducting device and showed the impact of noise through a comprehensive error analysis.

quant-ph↗

arXiv2025

Uniform Convergence of Metrics on Alexandrov Surfaces with Bounded Integral Curvature

We prove uniform convergence of metrics $g_k$ on a closed surface with bounded integral curvature (measure) in the sense of A.D. Alexandrov, under the assumption that the curvature measures $\mathbb{K}_{g_k}=μ^1_k-μ^2_k$, where $μ^1_k,μ^2_k$ are nonnegative Radon measures converging weakly to measures $μ^1,μ^2$ respectively, and $μ^1$ is less than $2π$ at each point (no cusps). This is the global version of Yu. G. Reshetnyak's well-known result on uniform convergence of metrics on a domain in $\mathbb{C}$, and answers affirmatively the open question on the metric convergence on a closed surface. We also give an analytic proof of the fact that a (singular) metric $g=e^{2u}g_0$ with bounded integral curvature on a closed Riemannian surface $(Σ,g_0)$ can be approximated by smooth metrics in the fixed conformal class $[g_0]$. % in terms of distance functions, curvature measures and conformal factors. Results on a closed surface with varying conformal classes and on complete noncompact surfaces are obtained as well.

math.DG↗

arXiv2025

ChiMed 2.0: Advancing Chinese Medical Dataset in Facilitating Large Language Modeling

Building high-quality data resources is crucial for advancing artificial intelligence research and applications in specific domains, particularly in the Chinese medical domain. Existing Chinese medical datasets are limited in size and narrow in domain coverage, falling short of the diverse corpora required for effective pre-training. Moreover, most datasets are designed solely for LLM fine-tuning and do not support pre-training and reinforcement learning from human feedback (RLHF). In this paper, we propose a Chinese medical dataset named ChiMed 2.0, which extends our previous work ChiMed, and covers data collected from Chinese medical online platforms and generated by LLMs. ChiMed 2.0 contains 204.4M Chinese characters covering both traditional Chinese medicine classics and modern general medical data, where there are 164.8K documents for pre-training, 351.6K question-answering pairs for supervised fine-tuning (SFT), and 41.7K preference data tuples for RLHF. To validate the effectiveness of our approach for training a Chinese medical LLM, we conduct further pre-training, SFT, and RLHF experiments on representative general domain LLMs and evaluate their performance on medical benchmark datasets. The results show performance gains across different model scales, validating the dataset's effectiveness and applicability.

cs.CL↗

arXiv2025

Integral gradient estimates on a closed surface

Let $(Σ, g)$ be a closed Riemann surface, and let $u$ be a weak solution to equation \[ - Δ_g u = μ, \] where $μ$ is a signed Radon measure. We aim to establish $L^p$ estimates for the gradient of $u$ that are independent of the choice of the metric $g$. This is particularly relevant when the complex structure approaches the boundary of the moduli space. To this end, we consider the metric $g' = e^{2u} g$ as a metric of bounded integral curvature. This metric satisfies a so-called quadratic area bound condition, which allows us to derive gradient estimates for $g'$ in local conformal coordinates. From these estimates, we obtain the desired estimates for the gradient of $u$.

math.DG↗

arXiv2025

Critical mass for finite-time chemotactic collapse in the critical dimension via comparison

We study the Neumann initial-boundary value problem for the parabolic-elliptic chemotaxis system, proposed by Jäger and Luckhaus (1992). We confirm that their comparison methods can be simplified and refined, applicable to seek the critical mass $8π$ concerning finite-time blowup in the unit disk. As an application, we deal with a parabolic-elliptic-parabolic chemotaxis model involving indirect signal production in the unit ball of $\mathbb R^4$, proposed by Tao and Winkler (2025). Within the framework of radially symmetric solutions, we prove that if initial mass is less than $64π^2$, then solution is globally bounded; for any $m$ exceeding $64π^2$, there exist nonnegative initial data with prescribed mass $m$ such that the corresponding classical solutions exhibit a formation of Dirac-delta type singularity in finite time, termed a chemotactic collapse.

math.AP↗

arXiv2025

Generative AI-Aided QoE Maximization for RIS-Assisted Digital Twin Interaction

In this paper, we investigate a quality of experience (QoE)-aware resource allocation problem for reconfigurable intelligent surface (RIS)-assisted digital twin (DT) interaction with uncertain evolution. In the considered system, mobile users are expected to interact with a DT model maintained on a DT server that is deployed on a base station, via effective uplink and downlink channels assisted by an RIS. Our goal is to maximize the sum of all mobile users' joint subjective and objective QoE in DT interactions across various DT scenes, by jointly optimizing phase shift matrix, receive/transmit beamforming matrix, rendering resolution configuration and computing resource allocation. While solving this problem is challenging mainly due to the uncertain evolution of the DT model, which leads to multiple scene-specific problems, and require us to constantly re-solve each of them whenever DT model evolves. To this end, leveraging the dynamic optimization capabilities of decision transformers and the generalization strengths of generative artificial intelligence (GAI), we propose a novel GAI-aided approach, called the prompt-guided decision transformer integrated with zero-forcing optimization (PG-ZFO). Simulations are conducted to evaluate the proposed PG-ZFO, demonstrating its effectiveness and superiority over counterparts.

cs.NI↗

arXiv2025

Distributionally Robust Optimization for Digital Twin Service Provisioning over Edge Computing

Digital Twin (DT) is a transformative technology poised to revolutionize a wide range of applications. This advancement has led to the emergence of digital twin as a service (DTaaS), enabling users to interact with DT models that accurately reflect the real-time status of their physical counterparts. Quality of DTaaS primarily depends on the freshness of DT data, which can be quantified by the age of information (AoI). The reliance on remote cloud servers solely for DTaaS provisioning presents significant challenges for latency-sensitive applications with strict AoI demands. Edge computing, as a promising paradigm, is expected to enable the AoI-aware provision of real-time DTaaS for users. In this paper, we study the joint optimization of DT model deployment and DT model selection for DTaaS provisioning over edge computing, with the objective of maximizing the quality of DTaaS. To address the uncertainties of DT interactions imposed on DTaaS provisioning, we propose a novel distributionally robust optimization (DRO)-based approach, called Wasserstein DRO (WDRO), where we first reformulate the original problem to a robust optimization problem, with the objective of maximizing the quality of DTaaS under the unforeseen extreme request conditions. Then, we leverage multi-level dual transformations based on Wasserstein distance to derive a robust solution. Simulations are conducted to evaluate the performance of the proposed WDRO, and the results demonstrate its superiority over counterparts.

cs.NI↗

arXiv2025

LeakGuard: Detecting Memory Leaks Accurately and Scalably

Memory leaks are prevalent in various real-world software projects, thereby leading to serious attacks like denial-of-service. Though prior methods for detecting memory leaks made significant advance, they often suffer from low accuracy and weak scalability for testing large and complex programs. In this paper we present LeakGuard, a memory leak detection tool which provides satisfactory balance of accuracy and scalability. For accuracy, LeakGuard analyzes the behaviors of library and developer-defined memory allocation and deallocation functions in a path-sensitive manner and generates function summaries for them in a bottom-up approach. Additionally, we develop a pointer escape analysis technique to model the transfer of pointer ownership. For scalability, LeakGuard examines each function of interest independently by using its function summary and under-constrained symbolic execution technique, which effectively mitigates path explosion problem. Our extensive evaluation on 18 real-world software projects and standard benchmark datasets demonstrates that LeakGuard achieves significant advancements in multiple aspects: it exhibits superior MAD function identification capability compared to Goshawk, outperforms five state-of-the-art methods in defect detection accuracy, and successfully identifies 129 previously undetected memory leak bugs, all of which have been independently verified and confirmed by the respective development teams.

cs.CR↗

arXiv2025

Finite-time blowup in a fully parabolic chemotaxis model involving indirect signal production

This paper is concerned with a parabolic-parabolic-parabolic chemotaxis system with indirect signal production, modelling the impact of phenotypic heterogeneity on population aggregation \begin{equation*} \begin{cases} u_t = Δu - \nabla\cdot(u\nabla v),\\ v_t = Δv - v + w,\\ w_t = Δw - w + u, \end{cases} \end{equation*} posed on a ball in $\mathbb R^n$ with $n\geq5$, subject to homogeneous Neumann boundary conditions. The system has a four-dimensional critical mass phenomenon concerning blowup in finite or infinite time according to the seminal works of Fujie and Senba [J. Differential Equations, 263 (2017), 88--148; 266 (2019), 942--976]. We prove that for any prescribed mass $m > 0$, there exist radially symmetric and nonnegative initial data $(u_0,v_0,w_0)\in C^0(\overlineΩ)\times C^2(\overlineΩ)\times C^2(\overlineΩ)$ with $\int_Ωu_0 = m$ such that the corresponding classical solutions blow up in finite time. The key ingredient is a novel integral inequality for the cross-term integral $\int_Ωuv$ constructed via a Lyapunov functional.

math.AP↗