arXiv subjects

Xiaobo Lu

Publications and source records attributed to Xiaobo Lu.

At least 19 recordsLinked to original sources

arXiv2026

Emergent trans-moir\'e orbitals and topology in rhombohedral graphene

The fractional quantum anomalous Hall effect (FQAHE) exhibited in fractional Chern insulators has recently been demonstrated in twisted MoTe2 and rhombohedral graphene/hBN moir\'e superlattices, promising new routes toward topological quantum computation. Central to realizing this promise is the understanding of the underlying microscopic mechanism. This, however, remains elusive in the case of rhombohedral graphene, with the crux being its two seemingly paradoxical conditions: a pronounced small-twist-angle ({\theta}) moir\'e interface, yet only when electrons are kept distant from it. Here, by scanning tunnelling microscopic imaging with both conditions fulfilled, we capture dramatic electronic structure reshaping in rhombohedral hexalayer graphene by unforeseen 'trans-moir\'e orbitals', which emerge on the other, distant side of the moir\'e interface but nevertheless enforce the moir\'e periodicity at all measured fillings. We visualize a hierarchy of spatially and energetically distinct trans-moir\'e orbitals which doped electrons must sequentially occupy--the lowest-energy orbital, expectedly responsible for the FQAHE at small fillings, carries a hollow-cage-like shape. Remarkably, these trans-moir\'e orbitals vanish at {\theta} {\gtrsim} 1{\deg}, and so do QAHE plateaus in similar devices. Simulations reveal an interaction-driven charge-redistribution mechanism which shapes the trans-moir\'e orbitals and corresponding Chern minibands. With our findings providing the missing microscopic link, the paradoxical conditions find a natural explanation: electrons are not simply kept distant from a small-{\theta} moir\'e interface; they are forced into topological trans-moir\'e orbitals, forged precisely under such conditions. Our microscopic diagnostics unlocks a wide range of possible 'synthetic' FQAHE platforms.

cond-mat.mes-hall↗

arXiv2026

Cross-View Feature Matching: Survey, Benchmarking, and Foundation-Model Perspectives

Cross-view feature matching aims to establish reliable correspondences across images with large viewpoint variations. Over the past decade, the field has evolved from task-specific models toward increasingly unified and generalizable correspondence models, with recent progress further driven by the emergence of vision foundation models (VFMs). Despite these advances, existing studies remain highly diverse in their problem formulations, model architectures, training paradigms, and evaluation protocols, making it difficult to obtain a unified understanding of the field. In this survey, we present a unified review of cross-view feature matching. We first introduce a structured taxonomy covering feature extraction, single-type feature matcher, multi-type feature matcher, VFMs based methods, training strategy and robust estimation, providing a coherent framework for analysis and comparison. We further examine recent advances, distilling key design principles and highlighting the shift toward unified and generalizable correspondence models. We also provide a unified experimental benchmarking of representative state-of-the-art methods under consistent protocols, enabling fair and comprehensive performance comparisons. In addition, we discuss open challenges and future directions, including efficiency, robustness under extreme conditions, and cross-domain generalization. This survey aims to provide a comprehensive and structured reference for understanding the evolution, current landscape, and future development of cross-view feature matching in the era of vision foundation models.

cs.LG↗

arXiv2026

COAL: Counterfactual and Observation-Enhanced Alignment Learning for Discriminative Referring Multi-Object Tracking

Referring Multi-Object Tracking (RMOT) faces a fundamental structural contradiction between the high-discriminability demand and the sparse semantic supervision. This mismatch is particularly acute in highly homogeneous scenarios that require fine-grained discrimination over complex compositional semantics. However, under sparse supervision, models overfit to salient yet insufficient cues, thereby encouraging shortcut learning and semantic collapse. To resolve this, we propose COAL (Counterfactual and Observation-enhanced Alignment Learning), a framework that advances RMOT beyond isolated structural optimization through knowledge regularization. First, we introduce Explicit Semantic Injection (ESI) via a VLM to densify the observation space and enhance instance discriminability. Second, leveraging LLM reasoning, we propose Counterfactual Learning (CFL) to augment supervision, enforcing strict attribute verification for robust compositional recognition. These strategies are unified within a Hierarchical Multi-Stream Integration (HMSI) architecture, which distills external knowledge into domain-specific discriminative representations. Experiments on Refer-KITTI and Refer-KITTI-V2 benchmarks validate COAL's efficacy. Notably, it surpasses the state-of-the-art by 7.28% HOTA on the highly challenging Refer-KITTI-V2. These results demonstrate the effectiveness of knowledge regularization for resolving the sparsity-discriminability paradox in RMOT.

cs.CV↗

arXiv2026

SceneGlue: Scene-Aware Transformer for Feature Matching without Scene-Level Annotation

Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained by the inherent local nature of feature descriptors, limiting their ability to capture non-local scene information that is essential for accurate cross-view correspondence. In this paper, we introduce SceneGlue, a scene-aware feature matching framework designed to overcome these limitations. SceneGlue leverages a hybridizable matching paradigm that integrates implicit parallel attention and explicit cross-view visibility estimation. The parallel attention mechanism simultaneously exchanges information among local descriptors within and across images, enhancing the scene's global context. To further enrich the scene awareness, we propose the Visibility Transformer, which explicitly categorizes features into visible and invisible regions, providing an understanding of cross-view scene visibility. By combining explicit and implicit scene-level awareness, SceneGlue effectively compensates for the local descriptor constraints. Notably, SceneGlue is trained using only local feature matches, without requiring scene-level groundtruth annotations. This scene-aware approach not only improves accuracy and robustness but also enhances interpretability compared to traditional methods. Extensive experiments on applications such as homography estimation, pose estimation, image matching, and visual localization validate SceneGlue's superior performance. The source code is available at https://github.com/songlin-du/SceneGlue.

cs.CV↗

arXiv2026

Observation of a Reconstructed Chern Insulator in Twisted Bilayer MoTe2

Twisted bilayer MoTe2 is a prototypical moire material in which long-wavelength superlattices amplify electron correlations, enabling a wealth of emergent quantum phases. To date, experimental efforts have focused primarily on small twist angles (typically smaller than 4deg ), whereas the larger-angle regime-where moire bands become more dispersive and correlations are reduced-has remained largely unexplored. Here we chart the topological phase space of tMoTe2 at a relatively large twist angle of approximately 4.54deg, accessing a moderately correlated regime with enhanced bandwidth. In contrast to small-angle devices that predominantly host fractional quantum anomalous Hall or spin Hall responses, we uncover multiple Chern-insulating states with C = 1 at moire fillings v = -1, -0.53 and -1/2. Strikingly, at v = -2/3 a magnetic field induces a fractional Chern insulator accompanied by an insulator-metal transition. Our results broaden the topological phase diagram of tMoTe2 and establish large-angle moire superlattices as a versatile platform for engineering robust topological states beyond the strong-correlation limit.

cond-mat.mes-hall↗

arXiv2026

FocusTrack: One-Stage Focus-and-Suppress Framework for 3D Point Cloud Object Tracking

In 3D point cloud object tracking, the motion-centric methods have emerged as a promising avenue due to its superior performance in modeling inter-frame motion. However, existing two-stage motion-based approaches suffer from fundamental limitations: (1) error accumulation due to decoupled optimization caused by explicit foreground segmentation prior to motion estimation, and (2) computational bottlenecks from sequential processing. To address these challenges, we propose FocusTrack, a novel one-stage paradigms tracking framework that unifies motion-semantics co-modeling through two core innovations: Inter-frame Motion Modeling (IMM) and Focus-and-Suppress Attention. The IMM module employs a temp-oral-difference siamese encoder to capture global motion patterns between adjacent frames. The Focus-and-Suppress attention that enhance the foreground semantics via motion-salient feature gating and suppress the background noise based on the temporal-aware motion context from IMM without explicit segmentation. Based on above two designs, FocusTrack enables end-to-end training with compact one-stage pipeline. Extensive experiments on prominent 3D tracking benchmarks, such as KITTI, nuScenes, and Waymo, demonstrate that the FocusTrack achieves new SOTA performance while running at a high speed with 105 FPS.

cs.CV↗

arXiv2025

Magnetic-Field-Driven Insulator-Superconductor Transition in Rhombohedral Graphene

Recent studies of rhombohedral multilayer graphene (RMG) have revealed a variety of superconducting states that can be induced or enhanced by magnetic fields, reinforcing RMG as a powerful platform for investigating novel superconductivity. Here we report an insulator-superconductor transition driven by in-plane magnetic fields B|| in rhombohedral hexalayer graphene. The upper critical in-plane field of 2T violates the Pauli limit, and an analysis based on isospin symmetry breaking supports a spin-polarized superconductor. At in-plane B = 0, such spin-polarized superconductor transitions into an insulator, exhibiting a thermally activated gap of 0.1 meV. In addition, we observe four superconducting states in the hole-doped regime, as well as phases with orbital multiferroicity near charge neutrality point. These findings substantially enrich the phase diagram of rhombohedral graphene and provide new insight into the microscopic mechanisms of superconductivity

cond-mat.supr-con↗

arXiv2025

Entangled Moire Chern Insulator in Rhombohedral Graphene

Graphene-based moire superlattices exhibit novel quantum phenomena driven by pronounced interactions, leading to topological corrected states like orbital Chern insulators exhibiting quantum anomalous Hall effect (QAHE). Typically, intrinsic Chern insulators are stabilized at odd moir\'e fillings, as even fillings often result in valley-balanced, topologically trivial states at zero magnetic field. In our work, we report the observation of an intrinsic Chern insulator with C = 1 state at moire filling v = 2 in rhombohedral octalayer graphene (R8G)/hBN moire superlattice. Observing such Chern insulators in particular with C = 1 at v = 2 is intriguing, as each moir\'e band carries Chern number C = 1 or -1. We further demonstrate such a state can originate from the entanglement between the low-energy moire flat bands and high-energy remote bands according to the Hartree-Fock calculation. Our findings extend the known topological phase diagram of rhombohedral multilayer graphene (RMG) moire systems and establish this platform as highly promising for investigating strong electron correlations and multiband hybridized transport.

cond-mat.mes-hall↗

arXiv2025

Fractional High-Chern Insulator in Twisted Rhombohedral Graphene

The realization of fractional Chern insulators opens up the possibility of exploring fractionally charged excitations and anyonic statistics in the absence of a magnetic field. A central question is whether lattice-based systems can give rise to radically new states, distinct from those observed in traditional fractional quantum Hall systems. In this work, we investigate a new type of moir\'e flat band system composed of Bernal bilayer graphene and rhombohedral tetralayer graphene. We discover an unprecedented richness of quantum anomalous Hall insulators with Chern numbers from C = 1 to C = 7 at v = 1 and around v = 3. Remarkably, we observe an exotic fractional Chern insulator with C = 7/3 around v = 2/3 which is beyond all known fractional Chern insulators described by either the Jain sequence or current high Chern theory. Our work expands the understanding of fractionally charged excitations beyond the Landau level basis and offers a new moire platform for exploring anyons.

cond-mat.mes-hall↗

arXiv2025

CompTrack: Information Bottleneck-Guided Low-Rank Dynamic Token Compression for Point Cloud Tracking

3D single object tracking (SOT) in LiDAR point clouds is a critical task in computer vision and autonomous driving. Despite great success having been achieved, the inherent sparsity of point clouds introduces a dual-redundancy challenge that limits existing trackers: (1) vast spatial redundancy from background noise impairs accuracy, and (2) informational redundancy within the foreground hinders efficiency. To tackle these issues, we propose CompTrack, a novel end-to-end framework that systematically eliminates both forms of redundancy in point clouds. First, CompTrack incorporates a Spatial Foreground Predictor (SFP) module to filter out irrelevant background noise based on information entropy, addressing spatial redundancy. Subsequently, its core is an Information Bottleneck-guided Dynamic Token Compression (IB-DTC) module that eliminates the informational redundancy within the foreground. Theoretically grounded in low-rank approximation, this module leverages an online SVD analysis to adaptively compress the redundant foreground into a compact and highly informative set of proxy tokens. Extensive experiments on KITTI, nuScenes and Waymo datasets demonstrate that CompTrack achieves top-performing tracking performance with superior efficiency, running at a real-time 90 FPS on a single RTX 3090 GPU.

cs.CV↗

arXiv2025

Does Moire Matter? Critical Moire Dependence with Quantum Fluctuations in Graphene Based Integer and Fractional Chern Insulators

Rhombohedral multilayer graphene has emerged as a powerful platform for investigating flat-band-driven correlated phenomena, yet most aspects remain not understood. In this work, we systematically study the moire-dependent band topology in rhombohedral hexalayer graphene. For the first time we demonstrate that the moire twist angle plays a crucial role in the formation of the moire Chern insulators in rhombohedral hexalayer graphene/hexagonal boron nitride (RHG/hBN) moire superlattices. In the moire-distant regime at filling factor v = 1, only systems with a twist angle {\theta} < 1.1{\deg} exhibit an integer moire Chern insulator, while the fractional Chern insulator at v = 2/3 requires smaller twist angle to be stabilized. Our theoretical modelling, which includes quantum fluctuations and exact diagonalization results, suggests that mean-field theory, which has been widely adopted, does not explain the twist-angle dependence of the v = 1 phase diagram, and that correlation effects are crucial. Moreover, we realize two distinct stacking configurations ( /Xi=0 and /Xi=1) between graphene and hBN, and find that both cases can yield a Chern insulator at v = 1. Our experimental work upends the current mean-field paradigm, illuminates how quantum fluctuations and moir\'e effects shape the RHG/hBN phase diagram, and paves the way for future understanding and engineering of topological correlated states in rhombohedral graphene moire systems.

cond-mat.mes-hall↗

arXiv2025

SOI is the Root of All Evil: Quantifying and Breaking Similar Object Interference in Single Object Tracking

In this paper, we present the first systematic investigation and quantification of Similar Object Interference (SOI), a long-overlooked yet critical bottleneck in Single Object Tracking (SOT). Through controlled Online Interference Masking (OIM) experiments, we quantitatively demonstrate that eliminating interference sources leads to substantial performance improvements (AUC gains up to 4.35) across all SOTA trackers, directly validating SOI as a primary constraint for robust tracking and highlighting the feasibility of external cognitive guidance. Building upon these insights, we adopt natural language as a practical form of external guidance, and construct SOIBench-the first semantic cognitive guidance benchmark specifically targeting SOI challenges. It automatically mines SOI frames through multi-tracker collective judgment and introduces a multi-level annotation protocol to generate precise semantic guidance texts. Systematic evaluation on SOIBench reveals a striking finding: existing vision-language tracking (VLT) methods fail to effectively exploit semantic cognitive guidance, achieving only marginal improvements or even performance degradation (AUC changes of -0.26 to +0.71). In contrast, we propose a novel paradigm employing large-scale vision-language models (VLM) as external cognitive engines that can be seamlessly integrated into arbitrary RGB trackers. This approach demonstrates substantial improvements under semantic cognitive guidance (AUC gains up to 0.93), representing a significant advancement over existing VLT methods. We hope SOIBench will serve as a standardized evaluation platform to advance semantic cognitive tracking research and contribute new insights to the tracking research community.

cs.CV↗

arXiv2025

Programmable Quantum Anomalous Hall Insulator in Twisted Crystalline Flatbands

The isospin flavors in condensed matters can be continuously broken, forming various symmetry-broken quantum states. In moir\'e crystals, the competition between different isospin configurations can be effectively tuned by the twist angles and staciking orders. Here we report twisted double rhombohedral-trilayer-gaphene as a new twisted crystalline flatbands system showing rich moir\'e dependent topological phenomena. In devices with small twist angles, programmable Chern insulators with Chern number C = 3 at integer moir\'e filling v = 1 have been observed. We have further revealed an exotic hidden order which can quench the Chern insulator as well as multiple first-order transitions between different symmetry-broken phases. Interestly, in the device with a slightly larger twist angle, multiple Chern insulators with C = 1 at fractional moir\'e fillings including v = 1/4, 1/3 and 1/2 have been observed, whereas the Chern insulator at v = 1 is abscent. Our study demonstrated the twisted flatbands form rhombohedral-multilayer-graphene as a new platform to study tunable high Chern insulators as well as new devices for quantum storage and computation.

cond-mat.mes-hall↗

arXiv2025

Evidence of Mott Insulator with Thermally Induced Melting Behavior in Kagome Compound Nb3Cl8

The kagome lattice provides a playground to explore novel correlated quantum states due to the presence of flat bands in its electronic structure. Recently discovered layered kagome compound Nb3Cl8 has been proposed as a Mott insulator coming from the half-filled flat band. Here we have carried out systematic transport study to uncover the evidence of Mott insulator in Nb3Cl8 thin flakes. Bipolar semiconducting property with Fermi level close to conduction band has been revealed. We have further probed the chemical potential of Nb3Cl8 by tracing the charge neutrality point of the monolayer graphene proximate to Nb3Cl8. The gap of Nb3Cl8 flakes is approximately 1.10 eV at 100 K and shows pronounced temperature dependence, decreasing substantially with increasing temperature to ~0.63 eV at 300 K. The melting behavior of the gapped state is in consistent with theoretically proposed Mott insulator in Nb3Cl8. Our work has demonstrated Nb3Cl8 as a promising platform to study strongly correlated physics at relatively high temperature.

cond-mat.str-el↗

arXiv2025

Unconventional Orbital Magnetism in Graphene-based Fractional Chern Insulators

Orbital magnetism in graphene originates from correlation-driven spontaneous valley symmetry breaking1-7. It can lead to various anomalous transport phenomena such as integer and fractional quantum anomalous Hall effects8-11. In general, the in-plane magnetic field B|| primarily couples to the spin degrees of freedom in graphene and has long been presumed to have a negligible effect on orbital magnetism due to the ultra-weak spin-orbit coupling12-18. In this work, we report multiple unconventional orbital magnetic phenomena that are highly sensitive to the B|| field in graphene/hBN superlattices hosting both integer and fractional Chern insulators (FCIs). We observed chirality-switching behaviors of the Chern insulator at moir\'e filling factor {\nu} = 1 under a finite B_par, demonstrating that both the C = +-1 states are permissible ground states at zero perpendicular magnetic field B_per. For the FCI at {\nu} = 2/3, we observed topological phase transitions between two states characterized by Hall resistivity \r{ho}xy = +-3h/2e2 under both B_per and B_par fields. In-plane B|| field can effectively suppress the FCI state at zero B_per field and enhance the FCI state with the opposite chirality, as resolved in Landau fan diagrams. Moreover, we observed rich phase transitions at 1 < {\nu} < 2, accompanied by intervalley coherence and anomalous Hall effects (AHE) that can be triggered by sweeping either B_per or B_par. Our work has unveiled new properties of orbital magnetism, providing a new knob for engineering various AHE in graphene.

cond-mat.mes-hall↗

arXiv2025

Tunable Fractional Chern Insulators in Rhombohedral Graphene Superlattices

Fractional Chern insulators (FCIs) showing a transport effect with fractionally quantized Hall plateaus emerging under zero magnetic field, provide a radically new opportunity to engineer topological quantum electronics. By construction of topological flat band with moire engineering, intrinsic FCIs have been observed in twisted MoTe2 system and rhombohedral pentalayer graphene/hBN moire superlattices with anomalous Hall resistivity quantization number C <= 2/3 including the gapless composite Fermi-liquid state with C = 1/2. Here, we experimentally demonstrate a new system of rhombohedral hexalayer graphene (RHG)/hBN moire superlattices, which exhibit both integer and fractional quantum anomalous Hall effects with rich tunability including electric displacement field, perpendicular magnetic field and in-plane magnetic field. By tuning the electrical and magnetic fields at 0 < v < 1, we have observed a quantum phase transition showing a sign reversal of the Hall resistivity at finite magnetic fields. Surprisingly, the FCI state at v = 2/3 survives in the phase transitions, exhibiting a robust quantized Hall resistivity across both phases. Finally we have further demonstrated the indispensable role moire potential plays in the formation of the flat Chern band from a theoretical perspective. Our work has established RHG/hBN moire superlattices as a promising platform for exploring quasi-particles with fractional charge and non-Abelian anyons at zero magnetic field.

cond-mat.mes-hall↗

arXiv2025

Flat Band and Many-body Gap in Chirally Twisted Triple Bilayer Graphene

We experimentally investigate the band structures of chirally twisted triple bilayer graphene. The new kind of moiré structure, formed by three pieces of helically stacked Bernal bilayer graphene, has flat bands at charge neutral point based on the continuum approximation. We experimentally confirm the existence of flat bands and directly acquire the gap in-between flat bands as well as between the flat bands and dispersive bands from the capacitance measurements. We discover a finite gap even at zero perpendicular electric field, possibly induced by the Coulomb interaction and ferromagnetism. Our quantitative study not only provides solid evidence for the flat-band and interesting physics, but also introduces a quantitative approach to explore phenomena of similar moiré systems.

cond-mat.mes-hall↗

arXiv2024

Collective Pinning and Vortex Dynamics in type 2 superconducting thin films with Varying Magnetic Field

A perpendicular magnetic field penetrating a thin type-II superconductor slab produces vortices, with one vortex per flux quantum, h/2e. The vortices interact repulsively and form an ordered array (Abrikosov lattice) in clean systems, while strong disorder changes the lattice into a vortex glass. Here we investigate type-II superconducting films (PdBi2 and NbSe2) with surface acoustic waves (SAWs) at mK temperature. When sweeping the magnetic field at an extremely slow rate, we observe a series of spikes in the attenuation and velocity of the SAW, on average separated in field by approximately Hc1. We suspect the following scenario: The vortex-free region at the edges of the film produces an edge barrier across which the vortices can enter or leave. When the applied field changes, the induced supercurrents flowing along this edge region lowers this barrier until there is an instability. At that point, vortices avalanche into (or out of) the bulk and change the vortex crystal, suggested by the sharp jump in each such spike. The vortices then gradually relax to a new stable pinned configuration, leading to a ~30s relaxation after the jump. Our observation enriches the limited experimental evidence on the important topic of real-time vortex dynamics in superconductors.

cond-mat.supr-con↗