arXiv subjects

Haitao Yang

Publications and source records attributed to Haitao Yang.

At least 19 recordsLinked to original sources

arXiv2026

Decoupled domain-texture switching from magnetic easy axis in kagome ferromagnet EuTi3Bi4

Magnetic anisotropy defines the easy axis of a magnetic material and governs the spatial arrangement of its domains. To date, anisotropy engineering has focused on reorienting the easy axis or tuning the anisotropy energy, both of which demand substantial energy input. Here, we demonstrate that magnetic domain textures can be switched without reorienting the easy axis, as observed in a kagome ferromagnet EuTi3Bi4 crystal. Using low-temperature magnetic force microscopy, we observe that the preferred orientation of magnetic domains switches from the a-axis to the b-axis upon temperature variation, and that this switching can also be triggered by an out-of-plane magnetic-field reset. Magnetization measurements and density functional theory calculations confirm a robust c-axis easy magnetization, ruling out a conventional spin-reorientation transition. Instead, the texture switching is governed by the temperature dependence of the in-plane variation of the Magnetic anisotropy energy landscape, which arises from two competing interactions with different decay rates: single-ion anisotropy favors a-oriented spin components, while nearest-neighbor anisotropic exchange favors b-oriented ones. Furthermore, the critical switching temperature is substantially elevated in a mechanically exfoliated EuTi3Bi4 flake. Our findings establish that macroscopic magnetic textures can be effectively manipulated by tuning the competition between in-plane anisotropic interactions, without the energy cost of reorienting the easy axis.

cond-mat.mtrl-sci↗

arXiv2026

Physics-guided residual correction of $\alpha$-decay half-lives based on the effective liquid drop model

To improve the prediction accuracy of $\alpha$-decay half-lives in heavy and superheavy nuclei, a physics-guided residual-correction framework combining the effective liquid drop model (ELDM) with machine-learning methods is proposed. The ELDM is first used as the macroscopic baseline for describing the barrier-penetration process, and XGBoost and TabPFN models are then employed to learn the residual deviations between ELDM predictions and experimental data. To incorporate microscopic nuclear-structure information, several physically motivated descriptors are constructed, including deformation-related quantities, Geiger--Nuttall-related features, and minimum orbital angular momentum. The results show that machine-learning residual correction significantly improves the predictive performance of the ELDM baseline. Among all models, TabPFN-term3 achieves the best accuracy, reducing the RMSE and MAE to 0.348 and 0.248, corresponding to improvements of 38.60\% and 40.46\%, respectively. Residual-distribution and feature-ablation analyses further indicate that the corrected predictions are closer to experimental values and that physically motivated descriptors play an important role in learning nonlinear residual structures. Overall, the proposed ELDM-based residual-correction framework can effectively compensate for missing microscopic nuclear-structure effects while preserving physical interpretability, providing a feasible strategy for high-precision $\alpha$-decay half-life prediction.

nucl-th↗

arXiv2026

Speculative Rollback Correction for Quality-Diverse Web Agent Imitation

Training interactive web agents through imitation learning from expert trajectories has emerged as a highly effective approach. However, determining the optimal timing for expert intervention presents a critical challenge in this context. Delayed intervention often leads to the accumulation of early-stage errors, pushing the page state into an irrecoverable regime. Conversely, premature or excessive intervention causes the agent to become overly reliant on expert policies, trapping the model in local optima characterized by a single, rigid trajectory. We propose Speculative Rollback Correction (SRC), a branch-level imitation framework for resettable agent environments. Instead of requesting teacher labels at every visited state or correcting only after a completed trajectory, SRC uses fixed-horizon branch review: the student executes a short speculative segment before teacher review, and the teacher localizes the first harmful deviation only when local progress breaks. Rollback preserves useful prefixes, while successful rollouts are filtered by a hard verifier and retained in a lightweight quality-diversity archive. The resulting data supports next-action supervised fine-tuning on both localized corrections and verifier-passing trajectories. On WebArena-Infinity, SRC collects 977 verifier-passing trajectories and 9,183 next-action examples; fixed-horizon review improves the recovery-versus-query tradeoff over step-level review while retaining verifier-passing solution variants. Code is available at https://github.com/LongkunHao/SRC_gui_agent.

cs.LG↗

arXiv2026

ARAPDiffusion: ARAP Regularization for Diffusion-Based Deformable Shape Space Learning

This paper introduces ARAPDiffusion, a latent diffusion model to learn the underlying continuous shape space of a deformation shape collection. The key innovation is in injecting the as-rigid-as-possible (ARAP) deformation model as regularization losses into latent diffusion (LD), releasing the requirement of having abundant 3D training data for learning generative models. In contrast to the standard LD, we show how the ARAP model can be used to improve both the encoder/decoder and the LD model. The training procedure alternates between using the synthetic distribution defined by the LD model to develop a regularization loss that enhances the shape encoder/decoder and using the shape decoder to develop a regularization loss to improve the LD model. We also show the benefit of the LD paradigm in combining a representation-free LD process and an implicit shape decoder that is applicable to unorganized point clouds. The experimental results of unconditional and conditional shape generation demonstrate the advantages of ARAPDiffusion over baseline approaches.

cs.CV↗

arXiv2026

WorldCoder-Bench: Benchmarking Physically Grounded 3D World Synthesis

Large language models (LLMs) are increasingly asked not only to write static interfaces, but to construct executable interactive worlds from natural language. Browser-native 3D, commonly built with Three.js, is a natural next frontier: generated programs must integrate assets, obey spatial and physical constraints, and keep user-facing controls synchronized with hidden runtime state. Existing web-generation benchmarks and evaluators, however, largely observe only pixels or DOM nodes, while the mechanics of a Three.js world unfold inside an opaque . We introduce WorldCoder-Bench, a benchmark for autonomous, physically grounded 3D world synthesis. WorldCoder-Bench contains 2,026 expert-curated tasks across Simulation, Rendering, and Application scenarios, with optional .glb assets and hidden behavioral contracts. We further propose StateProbe, an execution-based protocol that probes generated programs in a sandboxed browser and verifies hidden, mutation-hardened contracts over runtime states and transitions. Beyond verification coverage, we report Return on Automation and Time Efficiency Multiplier to measure correctness-adjusted cost and time savings. Across nine frontier models, the best system reaches only 27.8% verification coverage on WorldCoder-Core and 19.9% on WorldCoder-Robust, with failures dominated by state-schema drift and broken interaction chains rather than missing scene elements. Utility metrics further show that cheap or fast models can still provide substantial value on easier domains. WorldCoder-Bench is available at https://anonymous.4open.science/r/WorldCoder-Bench/.

cs.AI↗

arXiv2026

Modulation of charge density waves in a twisted vortex moire superlattice

Twisted moire superlattices in van-der-Waals heterostructures provide a powerful platform for engineering correlated states through moire-band reconstruction. However, whether globally coherent electronic orders can be continuously manipulated at the nanoscale remains largely unexplored. Reconstructed moire structures in small-angle and near-commensurate regime feature continuously varying local environments, offering new opportunities for nanoscale manipulation of correlated phases. Here, we report the modulation of charge density wave (CDW) states in a twisted vortex moire superlattice formed between monolayer VTe2 and superconducting NbSe2. Scanning tunneling microscopy/spectroscopy reveals that the intrinsic long-range CDW of monolayer VTe2 is reconstructed into inequivalent local phases with distinct stability and coherence within a single moire unit cell, including suppressed CDW order and enhanced short-range CDW correlations persisting to room temperature. First-principles calculations show that the reconstructed CDW landscape originates from strong local strain variation, where compressive strain substantially stabilizes the charge order. Furthermore, the modulated CDW states exhibit competing interplay with proximity-induced superconductivity. Our results establish vortex moire superlattices as a versatile platform for nanoscale manipulation of correlated electronic orders in low-dimensional quantum materials.

cond-mat.mtrl-sci↗

arXiv2026

Discovery of a nonsymmorphic superconductor with spontaneous rotational symmetry breaking and nontrivial zero modes

Topological superconductivity has attracted great interest due to its fundamental significance for realizing Majorana quasiparticles and fault-tolerant quantum computation. Nonsymmorphic superconductors, with symmetry-protected nontrivial electronic structures, offer a promising route to exotic topological superconducting states, yet experimental realizations remain scarce. Here we identify nonsymmorphic compound PtPb4 as a robust platform hosting superconductivity with spontaneous rotational symmetry breaking and nontrivial zero-energy modes. PtPb4 crystallizes in a frustrated Shastry-Sutherland lattice and exhibits nontrivial band topology. By combining in-plane and out-of-plane resistivity measurements, pronounced twofold anisotropy is observed in both the superconducting state and the upper critical field, evidencing spontaneous rotational symmetry breaking. Scanning tunneling microscopy/spectroscopy further reveal twofold-symmetric magnetic vortices, providing direct real-space evidence for the symmetry-broken superconducting state. Notably, a robust zero-energy vortex bound state emerges and persists without spatial splitting over extended distances, consistent with the characteristics expected for Majorana bound state. These findings uncover an exotic superconducting state in PtPb4 and establish a promising platform for exploring topological superconductivity and superconducting quantum devices.

cond-mat.supr-con↗

arXiv2026

Discovery of parity-violating chiral polar-nematic charge density wave and superconductivity in kagome metals

Nonmagnetic kagome metals and superconductors AV3Sb5 (A = K, Rb, Cs) host unconventional charge density wave (CDW) and superconducting (SC) phases accompanied by multiple electronic symmetry breaking. Due to the centrosymmetric crystal structure, inversion symmetry has generally been assumed to hold. Here, using scanning tunneling microscopy complemented by atomic force microscopy and optical second-harmonic generation, we directly reveal that inversion symmetry in the kagome plane is spontaneously broken in the CDW state. The mixed-parity CDW state exhibits ferroelectric dipolar and nematic quadrupolar ordered moments. The coexistence and coupling between the dipole and quadrupole favor noncollinear ferro-polar and nematic alignment that breaks all mirror symmetries and gives rise to robust electronic chirality in the 3Q CDW. The multipolar coupling to in-plane electric field enables electric field control and manipulation of the chiral polar-nematic CDW state, including its chirality. Below the SC transition, we observe parity-violating pair density modulations at both the original and the CDW lattice wavevectors. Our findings of parity-violating electronic chiral multipolar order provide microscopic insights into the magnetoelectric and nonreciprocal transport, loop current order, pairing density waves, and unconventional superconductivity in kagome metals and related quantum materials.

cond-mat.supr-con↗

arXiv2026

AngstromPro: A software platform for STM data management, visualization and analysis

Modern scanning tunneling microscopy (STM) experiments increasingly generate multidimensional datasets that require coordinated data management, visualization, and analysis. We present AngstromPro, an open-source Python-based software platform designed to support these activities within a common interactive environment. Its application architecture organizes inapplication data through independent module instances, each combining a Workspace with a common structure and module-specific visualization and interaction. Scientific processing methods are registered independently of individual modules and operate on explicitly selected inputs through common execution services. A unified I/O subsystem maps heterogeneous ondisk formats to supported in-application data types. The plugin subsystem can add new modules, processing methods, I/O handlers, and in-application data types without modifying the core package. Representative workflows demonstrate the integration of established methods. In the registration example, the normalized cross-correlation maximum increases from 0.855 to 0.966. AngstromPro therefore provides an integrated software architecture for organizing, visualizing, processing, and extending STM data-analysis workflows.

cond-mat.supr-con↗

arXiv2026

Identification and Structural Characterization of Twisted Atomically Thin Bilayer Materials by Deep Learning

Two-dimensional materials are expected to play an important role in next-generation electronics and optoelectronic devices. Recently, twisted bilayer graphene and transition metal dichalcogenides have attracted significant attention due to their unique physical properties and potential applications. In this study we describe the use of optical microscopy to collect the color space of chemical vapor deposition (CVD) molybdenum disulfide ($\mbox{MoS}_2$), and the application of a semantic segmentation convolutional neural network (CNN) to accurately and rapidly identify thicknesses of $\mbox{MoS}_2$ flakes. A second CNN model is trained to provide precise predictions on the twist angle of CVD-grown bilayer flakes. This model harnessed a dataset comprising over 10,000 synthetic images, encompassing geometries spanning from hexagonal to triangular shapes. Subsequent validation of the deep learning predictions on twist angles was executed through the second harmonic generation and Raman spectroscopy. Our results introduce a scalable methodology for automated inspection of twisted atomically thin CVD-grown bilayer.

cond-mat.mtrl-sci↗

arXiv2026

Controllable highly oriented skyrmion track array in Fe3GaTe2

Magnetic skyrmions are emerging as promising candidates for next-generation information technologies, while the realization of scalable skyrmion lattices with tailored configurations is essential for advancing fundamental skyrmion physics and developing future applications. Here we achieved the controllable generation and regulation of a large-area, highly oriented skyrmion track array (STA) in ferromagnetic Fe3GaTe2 using a vector magnetic field manipulation technique. The orientation and ordering of STA, along with the types and density of skyrmions, are precisely controlled by modulating parameters during the manipulation. The critical roles of in-plane magnetic fields and Dzyaloshinskii-Moriya interaction in STA generation is further confirmed by micromagnetic simulation. Our findings develop a strategy for engineering large-area and highly-oriented skyrmion configurations, offering a new pathway for the future application of next-generation spintronic and information technologies.

cond-mat.mtrl-sci↗

arXiv2026

Spin-mediated hysteretic switching of unidirectional charge density waves by rotating magnetic fields

Charge density waves (CDWs) are a widespread collective electronic order in quantum materials, furnishing key insights into symmetry breaking and competing phases. However, their dynamic control with external fields remains a pivotal challenge. Here, we report deterministic and hysteretic switching of unidirectional CDW orientation via in-plane magnetic field rotation in magnetic kagome metal GdTi3Bi4. Atomically resolved spectroscopy shows two types of 3a0*1a0 CDW domains, Q1 and Q2 oriented 60 degree apart along two distinct crystallographic directions and separated by atomically sharp domain walls. Rotating the magnetic field drives reversible transitions between these CDW configurations, exhibiting a robust C2-symmetric phase diagram with pronounced hysteresis. This hysteretic switching is mediated by a field-dependent reorientation of underlying antiferromagnetic spins, revealing a tunable energy landscape with stable and metastable states and modulates the electronic charge order via spin-lattice coupling. Our findings not only demonstrate the switching of CDW configurations by in-plane magnetic field but also reveal the mechanism of coupling between CDW and magnetic fields, offering new insights into CDW manipulation and versatile platform for developing a spin-mediated multistate spin-charge coupling memory and programmable quantum devices.

cond-mat.str-el↗

arXiv2026

Tunable bifurcation of magnetic anisotropy and bi-oriented antiferromagnetic order in kagome metal GdTi3Bi4

The novel kagome family RTi3Bi4 (R: rare-earth) offers a unique platform for exploring distinctive physical phenomena such as anisotropy, spin density wave, and anomalous Hall effect. In particular, the magnetic frustration and behavior of magnetic anisotropy in antiferromagnetic (AFM) kagome materials are of great interest for the fundamental studies and hold promise for next-generation device applications. Here, we report a tunable bifurcation of magnetic anisotropic and bi-oriented AFM order observed in the quasi-1D kagome antiferromagnet GdTi3Bi4. The magnetic domain evolutions during two plateau transition processes are directly visualized, unveiling a pronounced in-plane anisotropy along the a-axis. Temperature-dependent characterization reveals a bifurcation transition of anisotropy at approximately 2 K, where the a-axis anisotropy splits into two special orientations, revealing a hidden bi-oriented in-plane AFM order deviating from the high-symmetry direction by 7 degree. More intriguingly, the characteristics of the bifurcated anisotropy are clearly illustrated through vector magnetic field modulation, revealing three distinct in-plane domain phases in the transverse magnetic field phase diagram. Our results not only provide valuable insights into the tunable bifurcation of magnetic anisotropic in GdTi3Bi4, but also pave a novel pathway for AFM spintronics development.

cond-mat.str-el↗

arXiv2026

Cs$_4$Cr$_7$Te$_{10}$: Interwoven Reconstructed Archimedean and Kagome Lattices with a Possible Phase Transition near 130 K

Chromium-based materials with complex lattice geometries provide an important platform for investigating correlated electronic and magnetic states. However, Cr-based compounds with unusual crystal geometries are still rarely reported. Here, we report a new Cr-based compound, Cs$_4$Cr$_7$Te$_{10}$, featuring interwoven Cr and Te sublattices that can be viewed as reconstructed networks derived from Archimedean (3.4.6.4) tiling and the kagome lattice, respectively. Transport measurements reveal the semiconducting nature in Cs$_4$Cr$_7$Te$_{10}$. Magnetization measurements show a weak anisotropy between H//b and H//ac planes, and uncover an anomaly near 130 K that is insensitive to the applied magnetic fields. Specific-heat measurements further confirm this transition, indicating its bulk thermodynamic nature. The associated entropy change is as small as 0.41 J mol^-1 K^-1, ruling out a structural phase transition and pointing to a possible electronic and/or magnetic phase transition. These results provide a new route for designing complex crystal geometries and exploring their associated emergent phenomena.

cond-mat.mtrl-sci↗

arXiv2026

Building an Affordable Self-Driving Lab: Practical Machine Learning Experiments for Physics Education Using Internet-of-Things

Machine learning (ML) is transforming modern physics research, but practical, hands-on experience with ML techniques remains limited due to cost and complexity barriers. To address this gap, we introduce an affordable, autonomous, Internet-of-Things (IoT)-enabled experimental platform designed specifically for applied physics education. Utilizing an Arduino microcontroller, a customizable multi-wavelength light emitting diode (LED) array, and photosensors, our setup generates diverse, real-time optical datasets ideal for training and evaluating foundational ML algorithms, including traversal methods, Bayesian inference, and deep learning. The platform facilitates a closed-loop, self-driving experimental workflow, encompassing automated data collection, preprocessing, model training, and validation. Through systematic performance comparisons, we demonstrate the superior ability of deep learning to capture complex nonlinear relationships compared to traversal and Bayesian methods. At approximately $60, this open-source IoT platform provides an accessible, practical pathway for students to master advanced ML concepts, promoting deeper conceptual insights and essential technical skills required for the next generation of physicists and engineers.

physics.ed-ph↗

arXiv2026

$\mathrm{Cs_3V_9Te_{13}}$: A New Vanadium-Based Material with a Reuleaux-Triangle-Like Lattice and a Possible Phase Transition near 48 K

Exploring and synthesizing materials with new crystal structures provides an important route to discovering exotic quantum phenomena. However, materials with unconventional lattice geometries remain largely unexplored. Here, we report the discovery of a new vanadium-based material, $\mathrm{Cs_3V_9Te_{13}}$, featuring a Reuleaux-triangle-like lattice. Electrical transport and magnetic measurements consistently reveal an anomaly near 48 K, and this feature shows little sensitivity to the applied magnetic field. A corresponding anomaly is also observed in the Hall coefficient near 48 K, indicating a marked change in the carrier response. In addition, temperature-dependent x-ray diffraction results indicate no obvious structural change across 48 K. Taken together, these results suggest that the anomaly is not induced by the structural transition, but associated to a possible electronic and/or magnetic phase transition. High-pressure transport measurements and first-principles calculations further reveal a highly tunable electronic state in $\mathrm{Cs_3V_9Te_{13}}$, with the kagome-like electronic feature and pressure-suppressed antiferromagnetism. These results demonstrate this material, with its structurally novel Reuleaux-triangle-like lattice, as a new platform for exploring the interplay between nontrivial lattice geometry and emergent physical phenomena.

cond-mat.mtrl-sci↗

arXiv2026

DM0: An Embodied-Native Vision-Language-Action Model towards Physical AI

Moving beyond the traditional paradigm of adapting internet-pretrained models to physical tasks, we present DM0, an Embodied-Native Vision-Language-Action (VLA) framework designed for Physical AI. Unlike approaches that treat physical grounding as a fine-tuning afterthought, DM0 unifies embodied manipulation and navigation by learning from heterogeneous data sources from the onset. Our methodology follows a comprehensive three-stage pipeline: Pretraining, Mid-Training, and Post-Training. First, we conduct large-scale unified pretraining on the Vision-Language Model (VLM) using diverse corpora--seamlessly integrating web text, autonomous driving scenarios, and embodied interaction logs-to jointly acquire semantic knowledge and physical priors. Subsequently, we build a flow-matching action expert atop the VLM. To reconcile high-level reasoning with low-level control, DM0 employs a hybrid training strategy: for embodied data, gradients from the action expert are not backpropagated to the VLM to preserve generalized representations, while the VLM remains trainable on non-embodied data. Furthermore, we introduce an Embodied Spatial Scaffolding strategy to construct spatial Chain-of-Thought (CoT) reasoning, effectively constraining the action solution space. Experiments on the RoboChallenge benchmark demonstrate that DM0 achieves state-of-the-art performance in both Specialist and Generalist settings on Table30.

cs.RO↗

arXiv2026

Realization of a Wigner-Mott insulator in 6R-TaS$_2$ superconductor

Wigner-Mott insulating states represent a paradigmatic manifestation of strong electronic correlations, in which long-range Coulomb interactions drive spontaneous charge ordering and enable Mott localization at fractional electronic fillings. Such states have been theoretically proposed to arise from the cooperative interplay between onsite and inter-site Coulomb interactions. However, experimental realizations of the simultaneous microscopic observation of interaction-driven charge order and genuine Mott localization, which are the defining hallmarks of a Wigner-Mott insulator, have remained elusive. Here we report the observation of a Wigner-Mott insulating state in 6R-TaS$_2$ using scanning tunneling microscopy. By locally injecting electrons into the depleted 1T layer, we induce distinct Star-of-David charge-ordered superstructures and realize a cascade of insulating phases. In particular, a $\sqrt{3}\times \sqrt{3}$ charge-ordered superstructure at one-third filling hosts a robust Mott gap despite fractional filling. The spontaneous relaxation from excited states back to the ground state demonstrates that this Wigner-Mott phase is stabilized by the cooperative effects of onsite and inter-site Coulomb interactions. Our results provide direct microscopic evidence for a Wigner-Mott mechanism and establish 6R-TaS$_2$ as a platform for the controlled realization and investigation of Wigner-Mott insulating states.

cond-mat.str-el↗