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Xiaoyan Li

Publications and source records attributed to Xiaoyan Li.

At least 37 records · Page 2Linked to original sources
arXiv2024

Unraveling p-type and n-type interfaces in Superconducting Infinite-Layer Nickelate thin films

After decades of research, superconductivity was finally found in nickel-based analogs of superconducting cuprates, with infinite-layer (IL) structure. These results are so far restricted to thin films in the case of IL-nickelates. Therefore, the nature of the interface with the substrate, and how it couples with the thin film properties is still an open question. Here, using scanning transmission electron microscopy (STEM)- electron energy loss spectroscopy (EELS) and four-dimensional (4D)-STEM, a novel chemically sharp p-type interface is observed in a series of superconducting IL-praseodymium nickelate samples, and a comparative study is carried out with the previously reported n-type interface obtained in other samples. Both interfaces have strong differences, with the p-type interface being highly polar. In combination with ab-initio calculations, we find that the influence of the interface on the electronic structure is local, and does not extend beyond 2-3 unit cells into the thin film. This decouples the direct influence of the interface in driving the superconductivity, and indicates that the IL-nickelate thin films do not have a universal interface model. Insights into the spatial hole-distribution in SC samples, provided by monochromated EELS and total reflection-hard x-ray photoemission spectroscopy, suggest that this particular distribution might be directly influencing superconductivity.

cond-mat.supr-con↗
arXiv2024

Selective probing of longitudinal and transverse plasmon modes with electron phase-matching

The optical properties of metallic nanoparticles are dominated by localized surface plasmons (LSPs). Their properties only depend on the constituting material, the size and shape of the nano-object as well as its surrounding medium. In anisotropic structures, such as metallic nanorods, two families of modes generally exist, transverse and longitudinal. Their spectral and spatial overlaps usually impede their separate measurements in electron energy loss spectroscopy (EELS). In this work, we propose three different strategies enabling to overcome this difficulty and selectively probe longitudinal and transverse modes. The first strategy is numeric and relies on morphing of nano-structures, rooted in the geometrical nature of LSPs. The two other strategies exploit the relativistic and wave nature of the electrons in an EELS experiment. The first one is the phase-matching between the electron and the plasmon excitation to enhance their coupling by either tilting the sample and modifying the electron kinetic energy. The second one - polarized EELS (pEELS) - exploits the wave nature of electrons to mimic selection rules analogous to the one existing in light spectroscopies. The above-mentioned strategies are exemplified - either experimentally or numerically - on a canonical plasmonic toy model: the nano-rod. The goal of the paper is to bring together the state-of-the-art concepts of EELS for plasmonics to tackle a pedestrian problem in this field.

physics.optics↗
arXiv2024

FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View

In autonomous driving, 3D occupancy prediction outputs voxel-wise status and semantic labels for more comprehensive understandings of 3D scenes compared with traditional perception tasks, such as 3D object detection and bird's-eye view (BEV) semantic segmentation. Recent researchers have extensively explored various aspects of this task, including view transformation techniques, ground-truth label generation, and elaborate network design, aiming to achieve superior performance. However, the inference speed, crucial for running on an autonomous vehicle, is neglected. To this end, a new method, dubbed FastOcc, is proposed. By carefully analyzing the network effect and latency from four parts, including the input image resolution, image backbone, view transformation, and occupancy prediction head, it is found that the occupancy prediction head holds considerable potential for accelerating the model while keeping its accuracy. Targeted at improving this component, the time-consuming 3D convolution network is replaced with a novel residual-like architecture, where features are mainly digested by a lightweight 2D BEV convolution network and compensated by integrating the 3D voxel features interpolated from the original image features. Experiments on the Occ3D-nuScenes benchmark demonstrate that our FastOcc achieves state-of-the-art results with a fast inference speed.

cs.CV↗
arXiv2024

Reducing two-level system dissipations in 3D superconducting Niobium resonators by atomic layer deposition and high temperature heat treatment

Superconducting qubits have arisen as a leading technology platform for quantum computing which is on the verge of revolutionizing the world's calculation capacities. Nonetheless, the fabrication of computationally reliable qubit circuits requires increasing the quantum coherence lifetimes, which are predominantly limited by the dissipations of two-level system (TLS) defects present in the thin superconducting film and the adjacent dielectric regions. In this paper, we demonstrate the reduction of two-level system losses in three-dimensional superconducting radio frequency (SRF) niobium resonators by atomic layer deposition (ALD) of a 10 nm aluminum oxide Al2O3 thin films followed by a high vacuum (HV) heat treatment at 650 °C for few hours. By probing the effect of several heat treatments on Al2O3-coated niobium samples by X-ray photoelectron spectroscopy (XPS) plus scanning and conventional high resolution transmission electron microscopy (STEM/HRTEM) coupled with electron energy loss spectroscopy (EELS) and (EDX) , we witness a dissolution of niobium native oxides and the modification of the Al2O3-Nb interface, which correlates with the enhancement of the quality factor at low fields of two 1.3 GHz niobium cavities coated with 10 nm of Al2O3.

physics.app-ph↗
arXiv2023

Center Focusing Network for Real-Time LiDAR Panoptic Segmentation

LiDAR panoptic segmentation facilitates an autonomous vehicle to comprehensively understand the surrounding objects and scenes and is required to run in real time. The recent proposal-free methods accelerate the algorithm, but their effectiveness and efficiency are still limited owing to the difficulty of modeling non-existent instance centers and the costly center-based clustering modules. To achieve accurate and real-time LiDAR panoptic segmentation, a novel center focusing network (CFNet) is introduced. Specifically, the center focusing feature encoding (CFFE) is proposed to explicitly understand the relationships between the original LiDAR points and virtual instance centers by shifting the LiDAR points and filling in the center points. Moreover, to leverage the redundantly detected centers, a fast center deduplication module (CDM) is proposed to select only one center for each instance. Experiments on the SemanticKITTI and nuScenes panoptic segmentation benchmarks demonstrate that our CFNet outperforms all existing methods by a large margin and is 1.6 times faster than the most efficient method. The code is available at https://github.com/GangZhang842/CFNet.

cs.CV↗
arXiv2023

Optimal $L^2$-growth of the generalized Rosenau equation

We report that the quantity measured in the $L^2$ norm of the solution itself of the generalized Rosenau equation, which was completely unknown in this equation, grows in the proper order at time infinity. It is also immediately apparent that this growth aspect does not occur in three or more spatial dimensions, so we will apply the results obtained in this study to provide another proof that Hardy-type inequalities do not hold in the case of one or two spatial dimensions.

math.AP↗
arXiv2023

Reduced-Complexity Verification for K-Step and Infinite-Step Opacity in Discrete Event Systems

Opacity is a property that captures security concerns in cyber-physical systems and its verification plays a significant role. This paper investigates the verifications of K-step and infinite-step weak and strong opacity for partially observed nondeterministic finite state automata. K-step weak opacity is checked by constructing, for some states in the observer, appropriate state-trees, to propose a necessary and sufficient condition. Based on the relation between K-step weak and infinite-step weak opacity, a condition that determines when a system is not infinite-step weak opaque is presented. Regarding K-step and infinite-step strong opacity, we develop a secret-involved projected automaton, based on which we construct secret-unvisited state trees to derive a necessary and sufficient condition for K-step strong opacity. Furthermore, an algorithm is reported to compute a verifier that can be used to obtain a necessary and sufficient condition for infinite-step strong opacity. It is argued that, in some particular cases, the proposed methods achieve reduced complexity compared with the state of the art.

cs.FL↗
arXiv2023

Emergent electronic landscapes in a novel valence-ordered nickelate with tri-component nickel coordination

The metal-hydride-based topochemical reduction process has produced novel thermodynamically unstable phases across various transition metal oxide series with unusual crystal structures and non-trivial ground states. Here, by such an oxygen (de-) intercalation method we synthesis a novel samarium nickelate with ordered nickel valences associated with tri-component coordination configurations. This structure, with a formula of Sm$_{9}$Ni$_{9}$O$_{22}$ as revealed by four-dimensional scanning transmission electron microscopy, emerges from the intricate planes of {303}$_{\text{pc}}$ ordered apical oxygen vacancies. X-ray spectroscopy measurements and ab-initio calculations show the coexistence of square-planar, pyramidal and octahedral Ni sites with mono-, bi- and tri-valences. It leads to an intense orbital polarization, charge-ordering, and a ground state with a strong electron localization marked by the disappearance of ligand-hole configuration at low-temperature. This new nickelate compound provides another example of previously inaccessible materials enabled by topotactic transformations and presents a unique platform where mixed Ni valence can give rise to exotic phenomena.

cond-mat.mtrl-sci↗
arXiv2023

Compositional Modeling with Stock and Flow Diagrams

Stock and flow diagrams are widely used in epidemiology to model the dynamics of populations. Although tools already exist for building these diagrams and simulating the systems they describe, we have created a new package called StockFlow, part of the AlgebraicJulia ecosystem, which uses ideas from category theory to overcome notable limitations of existing software. Compositionality is provided by the theory of decorated cospans: stock and flow diagrams can be composed to form larger ones in an intuitive way formalized by the operad of undirected wiring diagrams. Our approach also cleanly separates the syntax of stock and flow diagrams from the semantics they can be assigned. We consider semantics in ordinary differential equations, although others are possible. As an example, we explain code in StockFlow that implements a simplified version of a COVID-19 model used in Canada.

cs.LO↗
arXiv2023

$L^2$-growth property for wave equations with higher derivative terms

We consider the Cauchy problems in the whole space for wave equations with higher derivative terms. We derive sharp growth estimates of the $L^2$-norm of the solution itself in the case of the space 1, 2 dimensions. By imposing the weighted $L^1$-initial velocity, we can get the lower and upper bound estimates of the solution itself. In three or more dimensions, we observe that the $L^2$-growth behavior of the solution never occurs in the ($L^2 \cap L^1$)-framework of the initial data.

math.AP↗
arXiv2023

Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit

Name disambiguation -- a fundamental problem in online academic systems -- is now facing greater challenges with the increasing growth of research papers. For example, on AMiner, an online academic search platform, about 10% of names own more than 100 authors. Such real-world challenging cases have not been effectively addressed by existing researches due to the small-scale or low-quality datasets that they have used. The development of effective algorithms is further hampered by a variety of tasks and evaluation protocols designed on top of diverse datasets. To this end, we present WhoIsWho owning, a large-scale benchmark with over 1,000,000 papers built using an interactive annotation process, a regular leaderboard with comprehensive tasks, and an easy-to-use toolkit encapsulating the entire pipeline as well as the most powerful features and baseline models for tackling the tasks. Our developed strong baseline has already been deployed online in the AMiner system to enable daily arXiv paper assignments. The public leaderboard is available at http://whoiswho.biendata.xyz/. The toolkit is at https://github.com/THUDM/WhoIsWho. The online demo of daily arXiv paper assignments is at https://na-demo.aminer.cn/arxivpaper.

cs.IR↗
arXiv2023

Hierarchical and Upstream-Downstream Composition of Stock and Flow Models

The growing complexity of decision-making in public health and health care has motivated an increasing use of mathematical modeling. An important line of health modeling is based on stock & flow diagrams. Such modeling elevates transparency across the interdisciplinary teams responsible for most impactful models, but existing tools suffer from a number of shortcomings when used at scale. Recent research has sought to address such limitations by establishing a categorical foundation for stock & flow modeling, including the capacity to compose a pair of models through identification of common stocks and sum variables. This work supplements such efforts by contributing two new forms of composition for stock & flow diagrams. We first describe a hierarchical means of diagram composition, in which a single existing stock is replaced by a diagram featuring compatible flow structure. Our composition method offers extra flexibility by allowing a single flow in the stock being replaced to split into several flows totalling to the same overall flow rate. Secondly, to address the common need of docking a stock & flow diagram with another "upstream" diagram depicting antecedent factors, we contribute a composition approach that allows a flow out of an upstream stock in one diagram to be connected to a downstream stock in another diagram. Both of these approaches are enabled by performing colimit decomposition of stock & flow diagrams into single-stock corollas and unit flows.

cs.LO↗
arXiv2023

Energy decay for wave equations with a potential and a localized damping

We consider the total energy decay together with L^2-bound of the solution itself of the Cauchy problem for wave equations with a localized damping and a short-range potential. We treat it in the one dimensional Euclidean space R. We adopt a simple multiplier method to study them. In this case, it is essential that the compactness of the support of the initial data is not assumed. Since this problem is treated in the whole space, the Poincare and Hardy inequalities are not available as is developed in the exterior domain case. For compensating such a lack of useful tools, the potential plays an effective role. As an application, the global existence of small data solution for a semilinear problem is provided.

math.AP↗
arXiv2023

Data Release of the AST3-2 Automatic Survey from Dome A, Antarctica

AST3-2 is the second of the three Antarctic Survey Telescopes, aimed at wide-field time-domain optical astronomy. It is located at Dome A, Antarctica, which is by many measures the best optical astronomy site on the Earth's surface. Here we present the data from the AST3-2 automatic survey in 2016 and the photometry results. The median 5$σ$ limiting magnitude in $i$-band is 17.8 mag and the light curve precision is 4 mmag for bright stars. The data release includes photometry for over 7~million stars, from which over 3,500 variable stars were detected, with 70 of them newly discovered. We classify these new variables into different types by combining their light curve features with stellar properties from surveys such as StarHorse.

astro-ph.SR↗
arXiv2023

A Categorical Framework for Modeling with Stock and Flow Diagrams

Stock and flow diagrams are already an important tool in epidemiology, but category theory lets us go further and treat these diagrams as mathematical entities in their own right. In this chapter we use communicable disease models created with our software, StockFlow.jl, to explain the benefits of the categorical approach. We first explain the category of stock-flow diagrams and note the clear separation between the syntax of these diagrams and their semantics, demonstrating three examples of semantics already implemented in the software: ODEs, causal loop diagrams, and system structure diagrams. We then turn to two methods for building large stock-flow diagrams from smaller ones in a modular fashion: composition and stratification. Finally, we introduce the open-source ModelCollab software for diagram-based collaborative modeling. The graphical user interface of this web-based software lets modelers take advantage of the ideas discussed here without any knowledge of their categorical foundations.

cs.LO↗
arXiv2022

$μ$eV electron spectromicroscopy using free-space light

The synergy between free electrons and light has recently been leveraged to reach an impressive degree of simultaneous spatial and spectral resolution, enabling applications in microscopy and quantum optics. However, the required combination of electron optics and light injection into the spectrally narrow modes of arbitrary specimens remains a challenge. Here, we demonstrate microelectronvolt spectral resolution in the nanoscale mapping of photonic modes with quality factors as high as 10$^4$. We rely on mode-matching of a tightly focused laser beam to whispering gallery modes to achieve a 10$^8$-fold increase in light-electron coupling efficiency. By adapting the shape and size of free-space optical beams to address specific physical questions, our approach allows us to interrogate any type of photonic structure with unprecedented spectral and spatial detail

cond-mat.mes-hall↗
arXiv2022

EBHI-Seg: A Novel Enteroscope Biopsy Histopathological Haematoxylin and Eosin Image Dataset for Image Segmentation Tasks

Background and Purpose: Colorectal cancer is a common fatal malignancy, the fourth most common cancer in men, and the third most common cancer in women worldwide. Timely detection of cancer in its early stages is essential for treating the disease. Currently, there is a lack of datasets for histopathological image segmentation of rectal cancer, which often hampers the assessment accuracy when computer technology is used to aid in diagnosis. Methods: This present study provided a new publicly available Enteroscope Biopsy Histopathological Hematoxylin and Eosin Image Dataset for Image Segmentation Tasks (EBHI-Seg). To demonstrate the validity and extensiveness of EBHI-Seg, the experimental results for EBHI-Seg are evaluated using classical machine learning methods and deep learning methods. Results: The experimental results showed that deep learning methods had a better image segmentation performance when utilizing EBHI-Seg. The maximum accuracy of the Dice evaluation metric for the classical machine learning method is 0.948, while the Dice evaluation metric for the deep learning method is 0.965. Conclusion: This publicly available dataset contained 5,170 images of six types of tumor differentiation stages and the corresponding ground truth images. The dataset can provide researchers with new segmentation algorithms for medical diagnosis of colorectal cancer, which can be used in the clinical setting to help doctors and patients.

eess.IV↗