arXiv subjects

Le Wang

Publications and source records attributed to Le Wang.

At least 109 records · Page 6Linked to original sources

arXiv2022

Intrinsic Magnetic Topological Materials

Topological states of matter possess bulk electronic structures categorized by topological invariants and edge/surface states due to the bulk-boundary correspondence. Topological materials hold great potential in the development of dissipationless spintronics, information storage, and quantum computation, particularly if combined with magnetic order intrinsically or extrinsically. Here, we review the recent progress in the exploration of intrinsic magnetic topological materials, including but not limited to magnetic topological insulators, magnetic topological metals, and magnetic Weyl semimetals. We pay special attention to their characteristic band features such as the gap of topological surface state, gapped Dirac cone induced by magnetization (either bulk or surface), Weyl nodal point/line, and Fermi arc, as well as the exotic transport responses resulting from such band features. We conclude with a brief envision for experimental explorations of new physics or effects by incorporating other orders in intrinsic magnetic topological materials.

cond-mat.mes-hall↗

arXiv2022

Exploring Discrete Diffusion Models for Image Captioning

The image captioning task is typically realized by an auto-regressive method that decodes the text tokens one by one. We present a diffusion-based captioning model, dubbed the name DDCap, to allow more decoding flexibility. Unlike image generation, where the output is continuous and redundant with a fixed length, texts in image captions are categorical and short with varied lengths. Therefore, naively applying the discrete diffusion model to text decoding does not work well, as shown in our experiments. To address the performance gap, we propose several key techniques including best-first inference, concentrated attention mask, text length prediction, and image-free training. On COCO without additional caption pre-training, it achieves a CIDEr score of 117.8, which is +5.0 higher than the auto-regressive baseline with the same architecture in the controlled setting. It also performs +26.8 higher CIDEr score than the auto-regressive baseline (230.3 v.s.203.5) on a caption infilling task. With 4M vision-language pre-training images and the base-sized model, we reach a CIDEr score of 125.1 on COCO, which is competitive to the best well-developed auto-regressive frameworks. The code is available at https://github.com/buxiangzhiren/DDCap.

cs.CV↗

arXiv2022

Realization of Practical Eightfold Fermions and Fourfold van Hove Singularity in TaCo$_2$Te$_2$

Space groups describing the symmetry of lattice structure allow the emergence of fermionic quasiparticles with various degeneracy in the band structure. Theoretical efforts have predicted many materials hosting fermions with the highest degeneracy, i.e., eightfold fermions, yet lacking experimental realization. Here, we explore the band degeneracies in TaCo$_2$Te$_2$ crystals. Through systematic experimental and theoretical analyses, we establish TaCo$_2$Te$_2$ as a nonsymmorphic crystal with negligible spin-orbit coupling (SOC) and long-range magnetic order. These critical properties guarantee the first realization of practical eightfold fermions and fourfold van Hove singularity, as directly observed by photoemission spectroscopy. TaCo$_2$Te$_2$ serves as a topological quantum critical platform, which can be tuned into various magnetic, topologically trivial, and nontrivial phases by adding strain, magnetic field, or SOC. The latter is demonstrated by our first-principles calculations, which show that enhancing SOC in TaCo$_2$Te$_2$ will promote the experimental observation of bulk hourglass fermions. Our results establish TaCo$_2$Te$_2$ as a unique platform to explore states of matter intertwining magnetism, correlation, symmetry, and band topology.

cond-mat.str-el↗

arXiv2022

Physical Logic Enhanced Network for Small-Sample Bi-Layer Metallic Tubes Bending Springback Prediction

Bi-layer metallic tube (BMT) plays an extremely crucial role in engineering applications, with rotary draw bending (RDB) the high-precision bending processing can be achieved, however, the product will further springback. Due to the complex structure of BMT and the high cost of dataset acquisi-tion, the existing methods based on mechanism research and machine learn-ing cannot meet the engineering requirements of springback prediction. Based on the preliminary mechanism analysis, a physical logic enhanced network (PE-NET) is proposed. The architecture includes ES-NET which equivalent the BMT to the single-layer tube, and SP-NET for the final predic-tion of springback with sufficient single-layer tube samples. Specifically, in the first stage, with the theory-driven pre-exploration and the data-driven pretraining, the ES-NET and SP-NET are constructed, respectively. In the second stage, under the physical logic, the PE-NET is assembled by ES-NET and SP-NET and then fine-tuned with the small sample BMT dataset and composite loss function. The validity and stability of the proposed method are verified by the FE simulation dataset, the small-sample dataset BMT springback angle prediction is achieved, and the method potential in inter-pretability and engineering applications are demonstrated.

cs.LG↗

arXiv2022

Resolving diverse oxygen transport pathways across Sr-doped lanthanum ferrite and metal-perovskite heterostructures

Perovskite structured transition metal oxides are important technological materials for catalysis and solid oxide fuel cell applications. Their functionality often depends on oxygen diffusivity and mobility through complex oxide heterostructures, which can be significantly impacted by structural and chemical modifications, such as doping. Further, when utilized within electrochemical cells, interfacial reactions with other components (e.g. Ni- and Cr-based alloy electrodes and interconnects) can influence the perovskite's reactivity and ion transport, leading to complex dependencies that are difficult to control in real-world environments. Here we use isotopic tracers and atom probe tomography to directly visualize oxygen diffusion and transport pathways across perovskite and metal-perovskite heterostructures, i.e. (Ni-Cr coated) Sr-doped lanthanum ferrite (LSFO). Annealing in 18O2(g) results in elemental and isotopic redistributions through oxygen exchange (OE) in the LSFO while Ni-Cr undergoes oxidation via multiple mechanisms and transport pathways. Complementary density functional theory (DFT) calculations at experimental conditions provide rationale for OE reaction mechanisms and reveal a complex interplay of different thermodynamic and kinetic drivers. Our results shed light on the fundamental coupling of defects and oxygen transport in an important class of catalytic materials.

cond-mat.mtrl-sci↗

arXiv2022

Strain tunability of perpendicular magnetic anisotropy in van der Waals ferromagnets VI3

Layered ferromagnets with high coercivity have special applications in nanoscale memory elements in electronic circuits, such as data storage. Therefore, searching for new hard ferromagnets and effectively tuning or enhancing the coercivity are the hottest topics in layered magnets today. Here, we report a strain tunability of perpendicular magnetic anisotropy in van der Waals (vdW) ferromagnets VI3 using magnetic circular dichroism measurements. For an unstrained flake, the M-H curve shows a rectangular-shaped hysteresis loop with perpendicular magnetic anisotropy and a large coercivity (up to 1.775 T at 10 K). Furthermore, the coercivity can be enhanced to a maximum of 2.6 T at 10 K under a 2.9% in-plane tensile strain. Our DFT calculations show that the magnetic anisotropy energy (MAE) can be dramatically increased after applying an in-plain tensile strain, which contributes to the enhancement of coercivity in the VI3 flake. Meanwhile, the strain tunability on the coercivity of CrI3, with a similar crystal structure, is limited. The main reason is the strong spin-orbital coupling in V3+ in VI6 octahedra in comparison with that in Cr3+. The strain tunability of coercivity in VI3 flakes highlights its potential for integration into vdW heterostructures, paving the way toward nanoscale spintronic devices and applications in the future.

cond-mat.mtrl-sci↗

arXiv2022

Learning to Refactor Action and Co-occurrence Features for Temporal Action Localization

The main challenge of Temporal Action Localization is to retrieve subtle human actions from various co-occurring ingredients, e.g., context and background, in an untrimmed video. While prior approaches have achieved substantial progress through devising advanced action detectors, they still suffer from these co-occurring ingredients which often dominate the actual action content in videos. In this paper, we explore two orthogonal but complementary aspects of a video snippet, i.e., the action features and the co-occurrence features. Especially, we develop a novel auxiliary task by decoupling these two types of features within a video snippet and recombining them to generate a new feature representation with more salient action information for accurate action localization. We term our method RefactorNet, which first explicitly factorizes the action content and regularizes its co-occurrence features, and then synthesizes a new action-dominated video representation. Extensive experimental results and ablation studies on THUMOS14 and ActivityNet v1.3 demonstrate that our new representation, combined with a simple action detector, can significantly improve the action localization performance.

cs.CV↗

arXiv2022

Uniaxial stress effect on the quasi-one-dimensional Kondo lattice CeCo$_2$Ga$_8$

Quantum critical phenomena in the quasi-one-dimensional limit remains an open issue. We report the uniaxial stress effect on the quasi-one-dimensional Kondo lattice CeCo$_2$Ga$_8$ by electric transport and AC heat capacity measurements. CeCo$_2$Ga$_8$ is speculated to sit in close vicinity but on the quantum-disordered side of a quantum critical point. Upon compressing the ${c}$ axis, parallel to the Ce-Ce chain, the onset of coherent Kondo effect is enhanced. In contrast, the electronic specific heat diverges more rapidly at low temperature when the intra-chain distance is elongated by compressions along {a} or {b} axes. These results suggest that a tensile intra-chain strain ($\varepsilon_c >0$) pushes CeCo$_2$Ga$_8$ closer to a quantum critical point, while a compressive intra-chain strain ($\varepsilon_c <0$) likely causes departure. Our work provides a rare paradigm of manipulation near a quantum critical point in a quasi-1D Kondo lattice by uniaxial stress, and paves the way for further investigations on the unique feature of quantum criticality in the quasi-1D limit.

cond-mat.str-el↗

arXiv2022

Pressure-induced superconductivity in flat-band Kagome compounds Pd$_3$P$_2$(S$_{1-x}$Se$_x$)$_8$

We performed high-pressure transport studies on the flat-band Kagome compounds, Pd$_3$P$_2$(S$_{1-x}$Se$_x$)$_8$ ($x$ = 0, 0.25), with a diamond anvil cell. For both compounds, the resistivity exhibits an insulating behavior with pressure up to 17 GPa. With pressure above 20 GPa, a metallic behavior is observed at high temperatures in Pd$_3$P$_2$S$_8$, and superconductivity emerges at low temperatures. The onset temperature of superconducting transition $T_{\rm C}$ rises monotonically from 2 K to 4.8 K and does not saturate with pressure up to 43 GPa. For the Se-doped compound Pd$_3$P$_2$(S$_{0.75}$Se$_{0.25}$)$_8$, the $T_{\rm C}$ is about 1.5 K higher than that of the undoped one over the whole pressure range, and reaches 6.4 K at 43 GPa. The upper critical field with field applied along the $c$ axis at typical pressures is about 50$\%$ of the Pauli limit, suggesting a 3D superconductivity. The Hall coefficient in the metallic phase is low and exhibits a peaked behavior at about 30 K, which suggests either a multi-band electronic structure or an electron correlation effect in the system.

cond-mat.supr-con↗

arXiv2022

Social Interpretable Tree for Pedestrian Trajectory Prediction

Understanding the multiple socially-acceptable future behaviors is an essential task for many vision applications. In this paper, we propose a tree-based method, termed as Social Interpretable Tree (SIT), to address this multi-modal prediction task, where a hand-crafted tree is built depending on the prior information of observed trajectory to model multiple future trajectories. Specifically, a path in the tree from the root to leaf represents an individual possible future trajectory. SIT employs a coarse-to-fine optimization strategy, in which the tree is first built by high-order velocity to balance the complexity and coverage of the tree and then optimized greedily to encourage multimodality. Finally, a teacher-forcing refining operation is used to predict the final fine trajectory. Compared with prior methods which leverage implicit latent variables to represent possible future trajectories, the path in the tree can explicitly explain the rough moving behaviors (e.g., go straight and then turn right), and thus provides better interpretability. Despite the hand-crafted tree, the experimental results on ETH-UCY and Stanford Drone datasets demonstrate that our method is capable of matching or exceeding the performance of state-of-the-art methods. Interestingly, the experiments show that the raw built tree without training outperforms many prior deep neural network based approaches. Meanwhile, our method presents sufficient flexibility in long-term prediction and different best-of-$K$ predictions.

cs.CV↗

arXiv2022

Improving robustness of language models from a geometry-aware perspective

Recent studies have found that removing the norm-bounded projection and increasing search steps in adversarial training can significantly improve robustness. However, we observe that a too large number of search steps can hurt accuracy. We aim to obtain strong robustness efficiently using fewer steps. Through a toy experiment, we find that perturbing the clean data to the decision boundary but not crossing it does not degrade the test accuracy. Inspired by this, we propose friendly adversarial data augmentation (FADA) to generate friendly adversarial data. On top of FADA, we propose geometry-aware adversarial training (GAT) to perform adversarial training on friendly adversarial data so that we can save a large number of search steps. Comprehensive experiments across two widely used datasets and three pre-trained language models demonstrate that GAT can obtain stronger robustness via fewer steps. In addition, we provide extensive empirical results and in-depth analyses on robustness to facilitate future studies.

cs.CL↗

arXiv2022

Two-Stream Consensus Network: Submission to HACS Challenge 2021 Weakly-Supervised Learning Track

This technical report presents our solution to the HACS Temporal Action Localization Challenge 2021, Weakly-Supervised Learning Track. The goal of weakly-supervised temporal action localization is to temporally locate and classify action of interest in untrimmed videos given only video-level labels. We adopt the two-stream consensus network (TSCN) as the main framework in this challenge. The TSCN consists of a two-stream base model training procedure and a pseudo ground truth learning procedure. The base model training encourages the model to predict reliable predictions based on single modality (i.e., RGB or optical flow), based on the fusion of which a pseudo ground truth is generated and in turn used as supervision to train the base models. On the HACS v1.1.1 dataset, without fine-tuning the feature-extraction I3D models, our method achieves 22.20% on the validation set and 21.68% on the testing set in terms of average mAP. Our solution ranked the 2nd in this challenge, and we hope our method can serve as a baseline for future academic research.

cs.CV↗

arXiv2022

Comparison of skyrmion phases between poly and single-crystal MnSi by composite magnetoelectric method

We have explored the skyrmion phases and phase diagram of poly and single-crystal MnSi by the measurements of the magnetoelectric coefficient alfaE and ac magnetic susceptibility of the MnSi/PMN-PT composite. We found that the regular skyrmion lattice phase in single crystal sample has been averaged in the MnSi polycrystal due to random grain orientations which results in an extended skyrmion lattice-conical mixture phase down to 25 K. The magnitude of the out-of-phase component in alfaE of the polycrystal, not single crystal, decreases gradually with decreasing frequency. With the changing of the driven ac field, it reveals a depinning threshold behavior in both samples. The depinning field is stronger in the polycrystal than that in single crystal and maybe responsible for the diminishing of dissipative behavior at lower frequency due to grain boundaries and defects. The composite magnetoelectric method provides a unique approach to probe topological phase dynamics.

cond-mat.mtrl-sci↗

arXiv2022

Type-II Dirac Nodal Lines in double-kagome-layered CsV$_8$Sb$_{12}$

Lorentz-violating type-II Dirac nodal line semimetals (DNLSs), hosting curves of band degeneracy formed by two dispersion branches with the same sign of slope, represent a novel states of matter. While being studied extensively in theory, convincing experimental evidences of type-II DNLSs remain elusive. Recently, Vanadium-based kagome materials have emerged as a fertile ground to study the interplay between lattice symmetry and band topology. In this work, we study the low-energy band structure of double-kagome-layered CsV$_8$Sb$_{12}$ and identify it as a scarce type-II DNLS protected by mirror symmetry. We have observed multiple DNLs consisting of type-II Dirac cones close to or almost at the Fermi level via angle-resolved photoemission spectroscopy (ARPES). First-principle analyses show that spin-orbit coupling only opens a small gap, resulting effectively gapless ARPES spectra, yet generating large spin Berry curvature. These type-II DNLs, together with the interaction between a low-energy van Hove singularity and quasi-1D band as we observed in the same material, suggest CsV$_8$Sb$_{12}$ as an ideal platform for exploring novel transport properties such as chiral anomaly, the Klein tunneling and fractional quantum Hall effect.

cond-mat.str-el↗

arXiv2022

Diffractive deep neural network based adaptive optics scheme for vortex beam in oceanic turbulence

Vortex beam carrying orbital angular momentum (OAM) is disturbed by oceanic turbulence (OT) when propagating in underwater wireless optical communication (UWOC) system. Adaptive optics (AO) is used to compensate for distortion and improve the performance of the UWOC system. In this work, we propose a diffractive deep neural network (DDNN) based AO scheme to compensate for the distortion caused by OT, where the DDNN is trained to obtain the mapping between the distortion intensity distribution of the vortex beam and its corresponding phase screen representating OT. The intensity pattern of the distorted vortex beam obtained in the experiment is input to the DDNN model, and the predicted phase screen can be used to compensate the distortion in real time. The experiment results show that the proposed scheme can extract quickly the characteristics of the intensity pattern of the distorted vortex beam, and output accurately the predicted phase screen. The mode purity of the compensated vortex beam is significantly improved, even with a strong OT. Our scheme may provide a new avenue for AO techniques, and is expected to promote the communication quality of UWOC system.

eess.IV↗

arXiv2021

Room-temperature ferromagnetism at an oxide/nitride interface

Heterointerfaces have led to the discovery of novel electronic and magnetic states because of their strongly entangled electronic degrees of freedom. Single-phase chromium compounds always exhibit antiferromagnetism following the prediction of Goodenough-Kanamori rules. So far, exchange coupling between chromium ions via hetero-anions has not been explored and the associated quantum states is unknown. Here we report the successful epitaxial synthesis and characterizations of chromium oxide (Cr2O3)-chromium nitride (CrN) superlattices. Room-temperature ferromagnetic spin ordering is achieved at the interfaces between these two antiferromagnets, and the magnitude of the effect decays with increasing layer thickness. First-principles calculations indicate that robust ferromagnetic spin interaction between Cr3+ ions via anion-hybridizations across the interface yields the lowest total energy. This work opens the door to fundamental understanding of the unexpected and exceptional properties of oxide-nitride interfaces and provides access to hidden phases at low-dimensional quantum heterostructures.

cond-mat.mtrl-sci↗

arXiv2021

Density-aware Haze Image Synthesis by Self-Supervised Content-Style Disentanglement

The key procedure of haze image translation through adversarial training lies in the disentanglement between the feature only involved in haze synthesis, i.e.style feature, and the feature representing the invariant semantic content, i.e. content feature. Previous methods separate content feature apart by utilizing it to classify haze image during the training process. However, in this paper we recognize the incompleteness of the content-style disentanglement in such technical routine. The flawed style feature entangled with content information inevitably leads the ill-rendering of the haze images. To address, we propose a self-supervised style regression via stochastic linear interpolation to reduce the content information in style feature. The ablative experiments demonstrate the disentangling completeness and its superiority in level-aware haze image synthesis. Moreover, the generated haze data are applied in the testing generalization of vehicle detectors. Further study between haze-level and detection performance shows that haze has obvious impact on the generalization of the vehicle detectors and such performance degrading level is linearly correlated to the haze-level, which, in turn, validates the effectiveness of the proposed method.

cs.CV↗

arXiv2021

Layer-controlled Ferromagnetism in Atomically Thin CrSiTe$_3$ Flakes

The research on two-dimensional (2D) van der Waals (vdW) ferromagnets has promoted the development of ultrahigh-density and nanoscale data storage. However, intrinsic ferromagnetism in layered magnets is always subject to many factors, such as stacking orders, interlayer couplings, and the number of layers. Here, we report a magnetic transition from soft to hard ferromagnetic behaviors as the thickness of CrSiTe$_3$ flakes decreases down to several nanometers. Phenomenally, in contrast to the negligible hysteresis loop in the bulk counterparts, atomically thin CrSiTe$_3$ shows a rectangular loop with finite magnetization and coercivity as thickness decreases down to ~8 nm, indicative of a single-domain and out-of-plane ferromagnetic order. We find that the stray field is weakened with decreasing thickness, which suppresses the formation of the domain wall. In addition, thickness-dependent ferromagnetic properties also reveal a crossover from 3 dimensional to 2 dimensional Ising ferromagnets at a ~7 nm thickness of CrSiTe$_3$, accompanied by a drop of the Curie temperature from 33 K for bulk to ~17 K for 4 nm sample.

cond-mat.mtrl-sci↗