arXiv subjects

Yupeng Wang

Publications and source records attributed to Yupeng Wang.

At least 37 records · Page 2Linked to original sources

arXiv2025

An integrable Anderson-impurity problem embedded in the one-dimensional Hubbard model

An exactly solvable one-dimensional Hubbard model with a single Anderson impurity embedded at the boundary is constructed in the framework of the quantum inverse scattering method. The model is solved exactly by the nested Bethe ansatz method. We identify the boundary bound states and determine the ground state phase diagram. By deriving the impurity contribution to the magnetic susceptibility, we show that in the dilute electron limit, a nearly free local moment forms at the impurity site, while at finite electron densities, the impurity spin is screened by the host electrons, consistent with Kondo physics.

math-ph↗

arXiv2025

Unlocking Mixed Reality for Medical Education: A See-Through Perspective on Head Anatomy

Extended reality (XR), encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), is emerging as a transformative platform for medical education. Traditional methods such as textbooks, physical models, and cadaveric dissections often lack interactivity and fail to convey complex spatial relationships effectively. The emerging MR technology addresses these limitations by providing immersive environments that blend virtual elements with real-world contexts. This study presents an MR application for head anatomy education, enabling learners to intuitively interact with see-through 3D anatomical structures via hand gestures and controllers. Our hierarchical information design supports progressive learning, guiding users from basic anatomical labels to detailed structural insights. Additionally, the system incorporates an automatic calibration module that aligns virtual anatomical models with a real human head, thereby facilitating realistic human-model interactions. Experiments show that the system can effectively match the anatomical model with real-time scenes, thus enhancing the interactivity and immersion of medical education, providing an innovative tool for teaching anatomy.

cs.HC↗

arXiv2025

Pressure-Driven Moiré Potential Enhancement and Tertiary Gap Opening in Graphene/h-BN Heterostructure

Moiré superlattices enable engineering of correlated quantum states through tunable periodic potentials, where twist angle controls periodicity but dynamic potential strength modulation remains challenging. Here, we develop a high-pressure quantum transport technique for van der Waals heterostructures, achieving the ultimate pressure limit (~9 GPa) in encapsulated moiré devices. In aligned graphene/h-BN, we demonstrate that pressure induces a substantial enhancement of the moiré potential strength, evidenced by the suppression of the first valence bandwidth and the near-doubling of the primary band gap. Moreover, we report the first observation of a tertiary gap emerging above 6.4 GPa, verifying theoretical predictions. Our results establish hydrostatic pressure as a universal parameter to reshape moiré band structures. By enabling quantum transport studies at previously inaccessible pressure regimes, this Letter expands the accessible parameter space for exploring correlated phases in moiré systems.

cond-mat.str-el↗

arXiv2025

CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning

Self-supervised topological deep learning (TDL) represents a nascent but underexplored area with significant potential for modeling higher-order interactions in simplicial complexes and cellular complexes to derive representations of unlabeled graphs. Compared to simplicial complexes, cellular complexes exhibit greater expressive power. However, the advancement in self-supervised learning for cellular TDL is largely hindered by two core challenges: \textit{extrinsic structural constraints} inherent to cellular complexes, and intrinsic semantic redundancy in cellular representations. The first challenge highlights that traditional graph augmentation techniques may compromise the integrity of higher-order cellular interactions, while the second underscores that topological redundancy in cellular complexes potentially diminish task-relevant information. To address these issues, we introduce Cellular Complex Contrastive Learning with Adaptive Trimming (CellCLAT), a twofold framework designed to adhere to the combinatorial constraints of cellular complexes while mitigating informational redundancy. Specifically, we propose a parameter perturbation-based augmentation method that injects controlled noise into cellular interactions without altering the underlying cellular structures, thereby preserving cellular topology during contrastive learning. Additionally, a cellular trimming scheduler is employed to mask gradient contributions from task-irrelevant cells through a bi-level meta-learning approach, effectively removing redundant topological elements while maintaining critical higher-order semantics. We provide theoretical justification and empirical validation to demonstrate that CellCLAT achieves substantial improvements over existing self-supervised graph learning methods, marking a significant attempt in this domain.

cs.LG↗

arXiv2025

EndoVLA: Dual-Phase Vision-Language-Action Model for Autonomous Tracking in Endoscopy

In endoscopic procedures, autonomous tracking of abnormal regions and following circumferential cutting markers can significantly reduce the cognitive burden on endoscopists. However, conventional model-based pipelines are fragile for each component (e.g., detection, motion planning) requires manual tuning and struggles to incorporate high-level endoscopic intent, leading to poor generalization across diverse scenes. Vision-Language-Action (VLA) models, which integrate visual perception, language grounding, and motion planning within an end-to-end framework, offer a promising alternative by semantically adapting to surgeon prompts without manual recalibration. Despite their potential, applying VLA models to robotic endoscopy presents unique challenges due to the complex and dynamic anatomical environments of the gastrointestinal (GI) tract. To address this, we introduce EndoVLA, designed specifically for continuum robots in GI interventions. Given endoscopic images and surgeon-issued tracking prompts, EndoVLA performs three core tasks: (1) polyp tracking, (2) delineation and following of abnormal mucosal regions, and (3) adherence to circular markers during circumferential cutting. To tackle data scarcity and domain shifts, we propose a dual-phase strategy comprising supervised fine-tuning on our EndoVLA-Motion dataset and reinforcement fine-tuning with task-aware rewards. Our approach significantly improves tracking performance in endoscopy and enables zero-shot generalization in diverse scenes and complex sequential tasks.

cs.RO↗

arXiv2025

Artificially creating emergent interfacial antiferromagnetism and its manipulation in a magnetic van-der-Waals heterostructure

Van der Waals (vdW) magnets, with their two-dimensional (2D) atomic structures, provide a unique platform for exploring magnetism at the nanoscale. Although there have been numerous reports on their diverse quantum properties, the emergent interfacial magnetism--artificially created at the interface between two layered magnets--remains largely unexplored. This work presents observations of such emergent interfacial magnetism at the ferromagnet/antiferromagnet interface in a vdW heterostructure. We report the discovery of an intermediate Hall resistance plateau in the anomalous Hall loop, indicative of emergent interfacial antiferromagnetism fostered by the heterointerface. This plateau can be stabilized and further manipulated under varying pressures but collapses under high pressures over 10 GPa. Our theoretical calculations reveal that charge transfer at the interface is pivotal in establishing the interlayer antiferromagnetic spin-exchange interaction. This work illuminates the previously unexplored emergent interfacial magnetism at a vdW interface comprised of a ferromagnetic metal and an antiferromagnetic insulator, and highlights its gradual evolution under increasing pressure. These findings enrich the portfolio of emergent interfacial magnetism and support further investigations on vdW magnetic interfaces and the development of next-generation spintronic devices.

cond-mat.mtrl-sci↗

arXiv2025

Directional Transport in Rydberg Atom Arrays via Kinetic Constraints and Temporal Modulation

We propose an experimentally feasible scheme to achieve directional transport of Rydberg excitations and entangled states in atomic arrays with unequal spacings. By leveraging distance-dependent Rydberg-Rydberg interactions and temporally modulated laser detunings, our method directs excitation flow without requiring local addressing. Numerical simulations demonstrate robust and coherent transport under experimentally realistic conditions. Additionally, we show that this scheme enables controlled transport of Bell pairs and preserves entanglement during propagation. The approach provides a versatile platform for programmable directional transport, with potential applications in quantum simulation, entanglement distribution, and the design of scalable quantum processors and networks.

quant-ph↗

arXiv2025

Some New Convergence Analysis and Applications of POD-Greedy Algorithms

In this article, we derive a novel convergence estimate for the weak POD-Greedy method with multiple POD modes and variable greedy thresholds in terms of the entropy numbers of the parametric solution manifold. Combining the POD with the Empirical Interpolation Method (EIM), we also propose an EIM-POD-Greedy method with entropy-based convergence analysis for simultaneously approximating parametrized target functions by separable approximants. Several numerical experiments are presented to demonstrate the effectiveness of the proposed algorithm compared to traditional methods.

math.NA↗

arXiv2024

Exact solution of a quantum integrable system associated with the $G_2$ exceptional Lie algebra

A quantum integrable spin chain model associated with the $G_2$ exceptional Lie algebra is studied. By using the fusion technique, the closed recursive relations among the fused transfer matrices are obtained. These identities allow us to derive the exact energy spectrum and Bethe ansatz equations of the system based on polynomial analysis. The present method provides a unified treatment to investigate the Bethe ansatz solutions for both periodic and non-diagonal open boundary conditions associated with exceptional Lie algebras.

math-ph↗

arXiv2024

Prismatic crystals and $p$-adic Riemann--Hilbert correspondence

We systematically study relative and absolute $Δ_{\mathrm{dR}}^+$-crystals on the (log-) prismatic site of a smooth (resp.~ semi-stable) formal scheme. Using explicit computation of stratifications, we classify (local) relative crystals by certain nilpotent connections, and classify (local) absolute crystals by certain enhanced connections. By using a $p$-adic Riemann--Hilbert functor and an infinite dimensional Sen theory over the Kummer tower, we globalize the results on absolute crystals and further classify them by certain small (global) $\mathbb{B}_{\mathrm{dR}}^+$-local systems.

math.NT↗

arXiv2024

Exact physical quantities of the XYZ spin chain in the thermodynamic limit

The thermodynamic limits of the XYZ spin chain with periodic or twisted boundary conditions are studied. By using the technique of characterizing the eigenvalue of the transfer matrix by the $T-Q$ relation and by the zeros of the associated polynomial, we obtain the constraints of the Bethe roots and the zeros for the eigenvalues. With the help of structure of Bethe roots, we obtain the distribution patterns of zeros. Based on them, the physical quantities such as the surface energy and excitation energy are calculated. We find that both of them depend on the parity of sites number due to the topological long-range Neel order on the Mobius manifold in the spin space. We also check our results with those obtaining by the density matrix renormalization group. The method provided in this paper can be applied to study the thermodynamic properties at the thermal equilibrium state with finite temperature.

math-ph↗

arXiv2024

Web-based Augmented Reality with Auto-Scaling and Real-Time Head Tracking towards Markerless Neurointerventional Preoperative Planning and Training of Head-mounted Robotic Needle Insertion

Neurosurgery requires exceptional precision and comprehensive preoperative planning to ensure optimal patient outcomes. Despite technological advancements, there remains a need for intuitive, accessible tools to enhance surgical preparation and medical education in this field. Traditional methods often lack the immersive experience necessary for surgeons to visualize complex procedures and critical neurovascular structures, while existing advanced solutions may be cost-prohibitive or require specialized hardware. This research presents a novel markerless web-based augmented reality (AR) application designed to address these challenges in neurointerventional preoperative planning and education. Utilizing MediaPipe for precise facial localization and segmentation, and React Three Fiber for immersive 3D visualization, the application offers an intuitive platform for complex preoperative procedures. A virtual 2-RPS parallel positioner or Skull-Bot model is projected onto the user's face in real-time, simulating surgical tool control with high precision. Key features include the ability to import and auto-scale head anatomy to the user's dimensions and real-time auto-tracking of head movements once aligned. The web-based nature enables simultaneous access by multiple users, facilitating collaboration during surgeries and allowing medical students to observe live procedures. A pilot study involving three participants evaluated the application's auto-scaling and auto-tracking capabilities through various head rotation exercises. This research contributes to the field by offering a cost-effective, accessible, and collaborative tool for improving neurosurgical planning and education, potentially leading to better surgical outcomes and more comprehensive training for medical professionals. The source code of our application is publicly available at https://github.com/Hillllllllton/skullbot_web_ar.

cs.RO↗

arXiv2024

The small $p$-adic Simpson correspondence in the semi-stable reduction case

We generalize several known results on small Simpson correspondence for smooth formal schemes over $\calO_C$ to the case for semi-stable formal schemes. More precisely, for a liftable semi-stable formal scheme $\frakX$ over $\calO_C$ with generic fiber $X$, we establish (1) an equivalence between the category of Hitchin-small integral $v$-bundles on $X_{v}$ and the category of Hitchin-small Higgs bundles on $\frakX_{\et}$, generalizing the previous work of Min--Wang, and (2) an equivalence between the moduli stack of $v$-bundles on $X_{v}$ and the moduli stack of rational Higgs bundles on $\frakX_{\et}$ (equivalently, moduli stack of Higgs bundles on $X_{\et}$), generalizing the previous work of Anschütz--Heuer--Le Bras.

math.AG↗

arXiv2024

Electric field control for experiments with atoms in Rydberg states

Atoms excited to Rydberg states have recently emerged as a valuable resource in neutral atom platforms for quantum computation, quantum simulation, and quantum information processing. Atoms in Rydberg states have large polarizabilities, making them highly sensitive to electric fields. Therefore, stray electric fields can decohere these atoms, in addition to compromising the fidelity of engineered interactions between them. It is therefore essential to cancel these stray electric fields. Here we present a novel, simple, and highly-compact electrode assembly, implemented in a glass cell-based vacuum chamber design, for stray electric field cancellation. The electrode assembly allows for full 3D control of the electric field in the vicinity of the atoms while blocking almost no optical access. We experimentally demonstrate the cancellation of stray electric fields to better than 10 mV/cm using this electrode assembly.

physics.atom-ph↗

arXiv2024

Integral $p$-adic non-abelian Hodge theory for small representations

Let $\frakX$ be a smooth $p$-adic formal scheme over $\calO_C$ with rigid generic fiber $X$. In this paper, we construct a new period sheaf $\calO\widehat \bC_{\pd}^+$ on $X_{\proet}$ and use it to establish an integral $p$-adic Simspon correspondence for small $\OXp$-representations on $X_{\proet}$ and small Higgs bundles on $\frakX_{\et}$ which is compatible with the works on rational level. In particular, for a small $\OXp$-representations $\calL$ with induced Higgs bundle $(\calH,θ_{\calH})$, we provide a canonical morphism $\HIG(\calH,θ_{\calH})\to\rRν_*\calL$ with a uniformly bounded $p^{\infty}$-torsion cofiber. Finally, we shall use this canonical map to study an analogue of Deligne--Illusie decomposition with coefficients in small $\OXp$-representations.

math.AG↗

arXiv2024

P-adic Simpson correpondence via prismatic crystals

Let $\frakX$ be a smooth $p$-adic formal scheme over $\calO_K$ with adic generic fiber $X$. We obtain a global equivalence between the category $\Vect((\frakX)_{\Prism},\overline\calO_{\Prism}[\frac{1}{p}])$ of rational Hodge--Tate crystals on the absolute prismatic site $(\frakX)_{\Prism}$ and the category $\HIG^{\nil}_*(X)$ of enhanced Higgs bundles on $X$. Along the way, we construct an inverse Simpson functor from $\HIG^{\nil}_*(X)$ to the category $\Vect(X_{\proet},\widehat\calO_X)$ of generalised representations on $X$, which turns out to be fully faithful.

math.AG↗

arXiv2024

Exact solution of a two-parameter extended Bariev model

An exactly solvable strongly correlated electron model with two independent parameters is constructed in the frame of the quantum inverse scattering method, which can be seen as a generalization of the Bariev model. Through the Bethe ansatz method, a set of Bethe ansatz equations is derived. In the thermodynamic limit, to study the ground state of the model, we obtain the integral equations for the density of Bethe roots. Numerical validation are done to confirm the accuracy of our analytic results.

cond-mat.str-el↗

arXiv2024

Revisiting Spurious Correlation in Domain Generalization

Without loss of generality, existing machine learning techniques may learn spurious correlation dependent on the domain, which exacerbates the generalization of models in out-of-distribution (OOD) scenarios. To address this issue, recent works build a structural causal model (SCM) to describe the causality within data generation process, thereby motivating methods to avoid the learning of spurious correlation by models. However, from the machine learning viewpoint, such a theoretical analysis omits the nuanced difference between the data generation process and representation learning process, resulting in that the causal analysis based on the former cannot well adapt to the latter. To this end, we explore to build a SCM for representation learning process and further conduct a thorough analysis of the mechanisms underlying spurious correlation. We underscore that adjusting erroneous covariates introduces bias, thus necessitating the correct selection of spurious correlation mechanisms based on practical application scenarios. In this regard, we substantiate the correctness of the proposed SCM and further propose to control confounding bias in OOD generalization by introducing a propensity score weighted estimator, which can be integrated into any existing OOD method as a plug-and-play module. The empirical results comprehensively demonstrate the effectiveness of our method on synthetic and large-scale real OOD datasets.

cs.LG↗