arXiv subjects

Tao Xiong

Publications and source records attributed to Tao Xiong.

At least 37 records · Page 2Linked to original sources

arXiv2024

Bound-preserving OEDG schemes for Aw-Rascle-Zhang traffic models on networks

Physical solutions to the widely used Aw-Rascle-Zhang (ARZ) traffic model and the adapted pressure (AP) ARZ model should satisfy the positivity of density, the minimum and maximum principles with respect to the velocity $v$ and other Riemann invariants. Many numerical schemes suffer from instabilities caused by violating these bounds, and the only existing bound-preserving (BP) numerical scheme (for ARZ model) is random, only first-order accurate, and not strictly conservative. This paper introduces arbitrarily high-order provably BP DG schemes for these two models, preserving all the aforementioned bounds except the maximum principle of $v$, which has been rigorously proven to conflict with the consistency and conservation of numerical schemes. Although the maximum principle of $v$ is not directly enforced, we find that the strictly preserved maximum principle of another Riemann invariant $w$ actually enforces an alternative upper bound on $v$. At the core of this work, analyzing and rigorously proving the BP property is a particularly nontrivial task: the Lax-Friedrichs (LF) splitting property, usually expected for hyperbolic conservation laws and employed to construct BP schemes, does not hold for these two models. To overcome this challenge, we formulate a generalized version of the LF splitting property, and prove it via the geometric quasilinearization (GQL) approach [Kailiang Wu and Chi-Wang Shu, SIAM Review, 65: 1031-1073, 2023]. To suppress spurious oscillations in the DG solutions, we employ the oscillation-eliminating (OE) technique, recently proposed in [Manting Peng, Zheng Sun, and Kailiang Wu, Mathematics of Computation, in press], which is based on the solution operator of a novel damping equation. Several numerical examples are included to demonstrate the effectiveness, accuracy, and BP properties of our schemes, with applications to traffic simulations on road networks.

math.NA↗

arXiv2024

Large-Scale Metric Computation in Online Controlled Experiment Platform

Online controlled experiment (also called A/B test or experiment) is the most important tool for decision-making at a wide range of data-driven companies like Microsoft, Google, Meta, etc. Metric computation is the core procedure for reaching a conclusion during an experiment. With the growth of experiments and metrics in an experiment platform, computing metrics efficiently at scale becomes a non-trivial challenge. This work shows how metric computation in WeChat experiment platform can be done efficiently using bit-sliced index (BSI) arithmetic. This approach has been implemented in a real world system and the performance results are presented, showing that the BSI arithmetic approach is very suitable for large-scale metric computation scenarios.

cs.DC↗

arXiv2024

High order conservative LDG-IMEX methods for the degenerate nonlinear non-equilibrium radiation diffusion problems

In this paper, we develop a class of high-order conservative methods for simulating non-equilibrium radiation diffusion problems. Numerically, this system poses significant challenges due to strong nonlinearity within the stiff source terms and the degeneracy of nonlinear diffusion terms. Explicit methods require impractically small time steps, while implicit methods, which offer stability, come with the challenge to guarantee the convergence of nonlinear iterative solvers. To overcome these challenges, we propose a predictor-corrector approach and design proper implicit-explicit time discretizations. In the predictor step, the system is reformulated into a nonconservative form and linear diffusion terms are introduced as a penalization to mitigate strong nonlinearities. We then employ a Picard iteration to secure convergence in handling the nonlinear aspects. The corrector step guarantees the conservation of total energy, which is vital for accurately simulating the speeds of propagating sharp fronts in this system. For spatial approximations, we utilize local discontinuous Galerkin finite element methods, coupled with positive-preserving and TVB limiters. We validate the orders of accuracy, conservation properties, and suitability of using large time steps for our proposed methods, through numerical experiments conducted on one- and two-dimensional spatial problems. In both homogeneous and heterogeneous non-equilibrium radiation diffusion problems, we attain a time stability condition comparable to that of a fully implicit time discretization. Such an approach is also applicable to many other reaction-diffusion systems.

math.NA↗

arXiv2023

High order asymptotic preserving and well-balanced schemes for the shallow water equations with source terms

In this study, we investigate the Shallow Water Equations incorporating source terms accounting for Manning friction and a non-flat bottom topology. Our primary focus is on developing and validating numerical schemes that serve a dual purpose: firstly, preserving all steady states within the model, and secondly, maintaining the late-time asymptotic behavior of solutions, which is governed by a diffusion equation and coincides with a long time and stiff friction limit. Our proposed approach draws inspiration from a penalization technique adopted in {\it{[Boscarino et. al, SIAM Journal on Scientific Computing, 2014]}}. By employing an additive implicit-explicit Runge-Kutta method, the scheme can ensure a correct asymptotic behavior for the limiting diffusion equation, without suffering from a parabolic-type time step restriction which often afflicts multiscale problems in the diffusive limit. Numerical experiments are performed to illustrate high order accuracy, asymptotic preserving, and asymptotically accurate properties of the designed schemes.

math.NA↗

arXiv2023

Cyber Physical System Information Collection: Robot Location and Navigation Method Based on QR Code

In this paper, we propose a method to estimate the exact location of a camera in a cyber-physical system using the exact geographic coordinates of four feature points stored in QR codes(Quick response codes) and the pixel coordinates of four feature points analyzed from the QR code images taken by the camera. Firstly, the P4P(Perspective 4 Points) algorithm is designed to uniquely determine the initial pose estimation value of the QR coordinate system relative to the camera coordinate system by using the four feature points of the selected QR code. In the second step, the manifold gradient optimization algorithm is designed. The rotation matrix and displacement vector are taken as the initial values of iteration, and the iterative optimization is carried out to improve the positioning accuracy and obtain the rotation matrix and displacement vector with higher accuracy. The third step is to convert the pose of the QR coordinate system with respect to the camera coordinate system to the pose of the AGV(Automated Guided Vehicle) with respect to the world coordinate system. Finally, the performance of manifold gradient optimization algorithm and P4P analytical algorithm are simulated and compared under the same conditions.One can see that the performance of the manifold gradient optimization algorithm proposed in this paper is much better than that of the P4P analytic algorithm when the signal-to-noise ratio is small.With the increase of the signal-to-noise ratio,the performance of the P4P analytic algorithm approaches that of the manifold gradient optimization algorithm.when the noise is same,the performance of manifold gradient optimization algorithm is better when there are more feature points.

cs.RO↗

arXiv2023

Distinguishing the importance of different charge trapping centers in CaF2-based 2D material MOSFETs

Crystalline CaF2 is drawing huge attentions due to its great potential of being the gate dielectric of two-dimensional (2D) material MOSFETs. It is deemed to be much superior than boron nitride and traditional SiO2 because of its larger dielectric constant, wider band gap, and lower defect density. Nevertheless, the CaF2-based MOSFETs fabricated in experiment still present notable reliability issues, and the underlying reason remains unclear. Here we studied the various intrinsic defects and adsorbates in CaF2/MoS2 and CaF2/MoSi2N4 interface systems to reveal the most active charge trapping centers in CaF2-based 2D material MOSFETs. An elaborate Table that comparing the importance of different defects in both n-type and p-type device is provided. Most impressively, the oxygen molecules adsorbed at the interface or surface, which are inevitable in experiments, are as active as the intrinsic defects in channel materials, and they can even change the MoSi2N4 to p-type spontaneously. These results mean that it is necessary to develop high vacuum packaging process as well as preparing high-quality 2D materials for better device performance.

cond-mat.mtrl-sci↗

arXiv2022

High order asymptotic preserving well-balanced finite difference WENO schemes for all Mach full Euler equations with gravity

In this paper, we propose a high order semi-implicit well-balanced finite difference scheme for all Mach Euler equations with a gravitational source term. To obtain the asymptotic preserving property, we start from the conservative form of full compressible Euler equations and add the evolution equation of the perturbation of potential temperature. The resulting system is then split into a (non-stiff) nonlinear low dynamic material wave to be treated explicitly, and (stiff) fast acoustic and gravity waves to be treated implicitly. With the aid of explicit time evolution for the perturbation of potential temperature, we design a novel well-balanced finite difference WENO scheme for the conservative variables, which can be proven to be both asymptotic preserving and asymptotically accurate in the incompressible limit. Extensive numerical experiments were provided to validate these properties.

math.NA↗

arXiv2022

High order asymptotic preserving finite difference WENO schemes with constrained transport for MHD equations in all sonic Mach numbers

In this paper, a high-order semi-implicit (SI) asymptotic preserving (AP) and divergence-free finite difference weighted essentially nonoscillatory (WENO) scheme is proposed for magnetohydrodynamic (MHD) equations. We consider the sonic Mach number $\varepsilon$ ranging from $0$ to $\mathcal{O}(1)$. High-order accuracy in time is obtained by SI implicit-explicit Runge-Kutta (IMEX-RK) time discretization. High-order accuracy in space is achieved by finite difference WENO schemes with characteristic-wise reconstructions. A constrained transport method is applied to maintain a discrete divergence-free condition. We formally prove that the scheme is AP. Asymptotic accuracy (AA) in the incompressible MHD limit is obtained if the implicit part of the SI IMEX-RK scheme is stiffly accurate. Numerical experiments are provided to validate the AP, AA, and divergence-free properties of our proposed approach. Besides, the scheme can well capture discontinuities such as shocks in an essentially non-oscillatory fashion in the compressible regime, while it is also a good incompressible solver with uniform large-time step conditions in the low sonic Mach limit.

math.NA↗

arXiv2022

Asymptotic preserving and uniformly unconditionally stable finite difference schemes for kinetic transport equations

In this paper, uniformly unconditionally stable first and second order finite difference schemes are developed for kinetic transport equations in the diffusive scaling. We first derive an approximate evolution equation for the macroscopic density, from the formal solution of the distribution function, which is then discretized by following characteristics for the transport part with a backward finite difference semi-Lagrangian approach, while the diffusive part is discretized implicitly. After the macroscopic density is available, the distribution function can be efficiently solved even with a fully implicit time discretization, since all discrete velocities are decoupled, resulting in a low-dimensional linear system from spatial discretizations at each discrete velocity. Both first and second order discretizations in space and in time are considered. The resulting schemes can be shown to be asymptotic preserving (AP) in the diffusive limit. Uniformly unconditional stabilities are verified from a Fourier analysis based on eigenvalues of corresponding amplification matrices. Numerical experiments, including high dimensional problems, have demonstrated the corresponding orders of accuracy both in space and in time, uniform stability, AP property, and good performances of our proposed approach.

math.NA↗

arXiv2022

sqSGD: Locally Private and Communication Efficient Federated Learning

Federated learning (FL) is a technique that trains machine learning models from decentralized data sources. We study FL under local notions of privacy constraints, which provides strong protection against sensitive data disclosures via obfuscating the data before leaving the client. We identify two major concerns in designing practical privacy-preserving FL algorithms: communication efficiency and high-dimensional compatibility. We then develop a gradient-based learning algorithm called \emph{sqSGD} (selective quantized stochastic gradient descent) that addresses both concerns. The proposed algorithm is based on a novel privacy-preserving quantization scheme that uses a constant number of bits per dimension per client. Then we improve the base algorithm in three ways: first, we apply a gradient subsampling strategy that simultaneously offers better training performance and smaller communication costs under a fixed privacy budget. Secondly, we utilize randomized rotation as a preprocessing step to reduce quantization error. Thirdly, an adaptive gradient norm upper bound shrinkage strategy is adopted to improve accuracy and stabilize training. Finally, the practicality of the proposed framework is demonstrated on benchmark datasets. Experiment results show that sqSGD successfully learns large models like LeNet and ResNet with local privacy constraints. In addition, with fixed privacy and communication level, the performance of sqSGD significantly dominates that of various baseline algorithms.

cs.LG↗

arXiv2021

Nanoconfinement of Tetraphenylethylene in Zeolitic Metal-Organic Framework for Turn-on Mechanofluorochromic Stress Sensing

Mechanofluorochromic materials are of great significance for the fabrication of innovative sensors and optoelectronics. However, efficient mechanofluorochromic materials are rarely explored due to the deficiency of existing design strategies. Here, we demonstrate the incarceration of aggregation-induced emission (AIE) materials within metal-organic framework (MOF) single crystals to construct a composite system with turn-on mechanofluorochromism. A new type of AIE@MOF material was designed: integrating a zeolitic MOF (ZIF-71) and tetraphenylethylene (TPE, a topical AIE material) to generate a TPE@ZIF-71 system with exceptional turn-on type mechanofluorochromism. Using terahertz vibrational spectroscopy, we show the unique fluorochromism emanates from the enhanced nanoconfinement effect exerted by ZIF-71 host on TPE guest under pressure and its permanent fluorescence after stress release. Compared with pure TPE, we demonstrate the nanoconfinement in AIE@MOF not only changes the TPE's turn-off type sensing behavior to a turn-on type, but boosts the original sensitivity markedly by tenfold. Significantly, because ZIF-71 prevents the spontaneous recrystallization of TPE upon unloading, this allows TPE@ZIF-71 to record the stress history. This is the first demonstration of the Guest@MOF system combining the concepts of AIE and MOF; its promising properties and potential engineering applications will stimulate new directions pertaining to luminescent stress sensors and smart optics.

physics.app-ph↗

arXiv2021

High Order Semi-implicit WENO Schemes for All Mach Full Euler System of Gas Dynamics

In this paper, we propose a new high order semi-implicit scheme for the all Mach full Euler equations of gas dynamics. Material waves are treated explicitly, while acoustic waves are treated implicitly, thus avoiding severe CFL restrictions for low Mach flows. High order accuracy in time is obtained by semi-implicit temporal integrator based on the IMEX Runge-Kutta (IMEX-RK) framework. High order in space is achieved by finite difference WENO schemes with characteristic-wise reconstructions adapted to the semi-implicit IMEX-RK time discretization. Type A IMEX schemes are constructed to handle not well-prepared initial conditions. Besides, these schemes are proven to be asymptotic preserving and asymptotically accurate as the Mach number vanishes for well-prepared initial conditions. Divergence-free property of the time-discrete schemes is proved. The proposed scheme can also well capture discontinuous solutions in the compressible regime, especially for two dimensional Riemann problems. Numerical tests in one and two space dimensions will illustrate the effectiveness of the proposed schemes.

math.NA↗

arXiv2021

Tunable Fluorescein-Encapsulated Zeolitic Imidazolate Framework-8 Nanoparticles for Solid-State Lighting

A series of fluorescein-encapsulated zeolitic imidazolate framework-8 (fluorescein@ZIF-8) luminescent nanoparticles with a scalable guest loading has been fabricated and characterized. The successful encapsulation of the organic dye (fluorescein) is supported by both experimental evidence and theoretical simulations. The measured optical band gap is found to be comparable with the computed values of a hypothetical guest-host system. Isolated monomers and aggregates species of fluorescein confined in ZIF-8 nanocrystals have been systematically investigated through fluorescence lifetime spectroscopy. The quantum yield (QY) of the obtained solid-state materials is particularly high (QY~98%), especially when the concentration of the fluorescein guest is low. Combining a blue LED chip and a thin photoactive film of fluorescein@ZIF-8, we demonstrate a device with good optical tunability for multicolor and white light emissions. Additionally, we show that the fluorescein@ZIF-8 nanoparticles exhibit an improved photostability due to the shielding effect conferred by the nanoconfinement of host framework, making them promising candidates for practical applications such as solid-state lighting, photonics, and optical communications.

cond-mat.mtrl-sci↗

arXiv2021

High order well-balanced asymptotic preserving finite difference WENO schemes for the shallow water equations in all Froude numbers

In this paper, high order semi-implicit well-balanced and asymptotic preserving finite difference WENO schemes are proposed for the shallow water equations with a non-flat bottom topography. We consider the Froude number ranging from O(1) to 0, which in the zero Froude limit becomes the "lake equations" for balanced flow without gravity waves. We apply a well-balanced finite difference WENO reconstruction, coupled with a stiffly accurate implicit-explicit (IMEX) Runge-Kutta time discretization. The resulting semi-implicit scheme can be shown to be well-balanced, asymptotic preserving (AP) and asymptotically accurate (AA) at the same time. Both one- and two-dimensional numerical results are provided to demonstrate the high order accuracy, AP property and good performance of the proposed methods in capturing small perturbations of steady state solutions.

math.NA↗

arXiv2021

Covariance Estimation and its Application in Large-Scale Online Controlled Experiments

During the last few decades, online controlled experiments (also known as A/B tests) have been adopted as a golden standard for measuring business improvements in industry. In our company, there are more than a billion users participating in thousands of experiments simultaneously, and with statistical inference and estimations conducted to thousands of online metrics in those experiments routinely, computational costs would become a large concern. In this paper we propose a novel algorithm for estimating the covariance of online metrics, which introduces more flexibility to the trade-off between computational costs and precision in covariance estimation. This covariance estimation method reduces computational cost of metric calculation in large-scale setting, which facilitates further application in both online controlled experiments and adaptive experiments scenarios like variance reduction, continuous monitoring, Bayesian optimization, etc., and it can be easily implemented in engineering practice.

stat.AP↗

arXiv2021

SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing

Deep learning provides a promising way to extract effective representations from raw data in an end-to-end fashion and has proven its effectiveness in various domains such as computer vision, natural language processing, etc. However, in domains such as content/product recommendation and risk management, where sequence of event data is the most used raw data form and experts derived features are more commonly used, deep learning models struggle to dominate the game. In this paper, we propose a symbolic testing framework that helps to answer the question of what kinds of expert-derived features could be learned by a neural network. Inspired by this testing framework, we introduce an efficient architecture named SHORING, which contains two components: \textit{event network} and \textit{sequence network}. The \textit{event} network learns arbitrarily yet efficiently high-order \textit{event-level} embeddings via a provable reparameterization trick, the \textit{sequence} network aggregates from sequence of \textit{event-level} embeddings. We argue that SHORING is capable of learning certain standard symbolic expressions which the standard multi-head self-attention network fails to learn, and conduct comprehensive experiments and ablation studies on four synthetic datasets and three real-world datasets. The results show that SHORING empirically outperforms the state-of-the-art methods.

cs.LG↗

arXiv2020

High order asymptotic preserving discontinuous Galerkin methods for gray radiative transfer equations

In this paper, we will develop a class of high order asymptotic preserving (AP) discontinuous Galerkin (DG) methods for nonlinear time-dependent gray radiative transfer equations (GRTEs). Inspired by the work \cite{Peng2020stability}, in which stability enhanced high order AP DG methods are proposed for linear transport equations, we propose to pernalize the nonlinear GRTEs under the micro-macro decomposition framework by adding a weighted linear diffusive term. In the diffusive limit, a hyperbolic, namely $Δt=\mathcal{O}(h)$ where $Δt$ and $h$ are the time step and mesh size respectively, instead of parabolic $Δt=\mathcal{O}(h^2)$ time step restriction is obtained, which is also free from the photon mean free path. The main new ingredient is that we further employ a Picard iteration with a predictor-corrector procedure, to decouple the resulting global nonlinear system to a linear system with local nonlinear algebraic equations from an outer iterative loop. Our scheme is shown to be asymptotic preserving and asymptotically accurate. Numerical tests for one and two spatial dimensional problems are performed to demonstrate that our scheme is of high order, effective and efficient.

math.NA↗

arXiv2020

Conservative discontinuous Galerkin/Hermite Spectral Method for the Vlasov-Poisson System

We propose a class of conservative discontinuous Galerkin methods for the Vlasov-Poisson system written as a hyperbolic system using Hermite polynomials in the velocity variable. These schemes are designed to be systematically as accurate as one wants with provable conservation of mass and possibly total energy. Such properties in general are hard to achieve within other numerical method frameworks for simulating the Vlasov-Poisson system. The proposed scheme employs discontinuous Galerkin discretization for both the Vlasov and the Poisson equations, resulting in a consistent description of the distribution function and electric field. Numerical simulations are performed to verify the order of accuracy and conservation properties.

math.NA↗