arXiv subjects

Kun Xu

Publications and source records attributed to Kun Xu.

At least 199 records · Page 11Linked to original sources

arXiv2022

$Λ/{\bar Λ}$ Polarization and Splitting Induced by Rotation and Magnetic Field

The global polarization of $Λ/{\bar Λ}$ and the splitting of ${\bar Λ}-Λ$ polarization induced by rotation and magnetic field has been investigated in a dynamical quark model by taking into account the axial vector interaction and the anomalous magnetic moment of quarks. It is found that the rotation leads to the spin polarization of quarks and anti-quarks with the same sign, while the magnetic field to opposite sign, which corresponds to the ${\bar Λ}-Λ$ polarization splitting. The combination of the two effects leads to perfect agreement with experiment data. Quantitatively, the axial vector spin polarization contributes 30$\%$ of the global polarization and the anomalous magnetic moment of quarks contributes 40$\%$ to the splitting of ${\bar Λ}-Λ$ polarization. However, at $\sqrt{s_{NN}} \leq 7.7 \text{GeV}$, it still remains a challenge to reach enough magnitude of the magnetic field at freeze-out.

hep-ph↗

arXiv2022

A high-order compact gas-kinetic scheme in a rotating coordinate frame and on sliding mesh

This paper extends the high-order compact gas-kinetic scheme (CGKS) to compressible flow simulations on a rotating coordinate frame. The kinetic equation with the inclusion of centrifugal and Coriolis acceleration is used in the construction of the scheme. With the updates of both cell averaged conservative variables and their gradients in the rotating and stationary domains, a third-order compact reconstruction is developed with sliding interface between them. To properly capture shock wave and complicated wave interaction, the HWENO-type non-linear reconstruction and gradient compression factors are incorporated in the scheme. For achieving high-order time accuracy, based on the flux function and its time derivative the multi-stage multi-derivative (MSMD) time stepping method is implemented in the scheme for the fourth-order accuracy with two stages. The CGKS is validated by many test cases from subsonic acoustic wave propagation to the high Mach number shock interaction in a rotating frame. The compact scheme achieves high-order accuracy and remarkable robustness.

physics.comp-ph↗

arXiv2022

Neural Color Operators for Sequential Image Retouching

We propose a novel image retouching method by modeling the retouching process as performing a sequence of newly introduced trainable neural color operators. The neural color operator mimics the behavior of traditional color operators and learns pixelwise color transformation while its strength is controlled by a scalar. To reflect the homomorphism property of color operators, we employ equivariant mapping and adopt an encoder-decoder structure which maps the non-linear color transformation to a much simpler transformation (i.e., translation) in a high dimensional space. The scalar strength of each neural color operator is predicted using CNN based strength predictors by analyzing global image statistics. Overall, our method is rather lightweight and offers flexible controls. Experiments and user studies on public datasets show that our method consistently achieves the best results compared with SOTA methods in both quantitative measures and visual qualities. The code and pretrained models are provided at https://github.com/amberwangyili/neurop

cs.CV↗

arXiv2022

Learning a Grammar Inducer from Massive Uncurated Instructional Videos

Video-aided grammar induction aims to leverage video information for finding more accurate syntactic grammars for accompanying text. While previous work focuses on building systems for inducing grammars on text that are well-aligned with video content, we investigate the scenario, in which text and video are only in loose correspondence. Such data can be found in abundance online, and the weak correspondence is similar to the indeterminacy problem studied in language acquisition. Furthermore, we build a new model that can better learn video-span correlation without manually designed features adopted by previous work. Experiments show that our model trained only on large-scale YouTube data with no text-video alignment reports strong and robust performances across three unseen datasets, despite domain shift and noisy label issues. Furthermore our model yields higher F1 scores than the previous state-of-the-art systems trained on in-domain data.

cs.CL↗

arXiv2022

Modeling and simulation in supersonic three-temperature carbon dioxide turbulent channel flow

This paper pioneers the direct numerical simulation (DNS) and physical analysis in supersonic three-temperature carbon dioxide (CO2) turbulent channel flow. CO2 is a linear and symmetric triatomic molecular, with the thermal non-equilibrium three-temperature effects arising from the interactions among translational, rotational and vibrational modes under room temperature. Thus, the rotational and vibrational modes of CO2 are addressed. Thermal non-equilibrium effect of CO2 has been modeled in an extended three-temperature BGK-type model, with the calibrated translational, rotational and vibrational relaxation time. To solve the extended BGK-type equation accurately and robustly, non-equilibrium high-accuracy gas-kinetic scheme is proposed within the well-established two-stage fourth-order framework. Compared with the one-temperature supersonic turbulent channel flow, supersonic three-temperature CO2 turbulence enlarges the ensemble heat transfer of the wall by approximate 20%, and slightly decreases the ensemble frictional force. The ensemble density and temperature fields are greatly affected, and there is little change in Van Driest transformation of streamwise velocity. The thermal non-equilibrium three-temperature effects of CO2 also suppress the peak of normalized root-mean-square of density and temperature, normalized turbulent intensities and Reynolds stress. The vibrational modes of CO2 behave quite differently with rotational and translational modes. Compared with the vibrational temperature fields, the rotational temperature fields have the higher similarity with translational temperature fields, especially in temperature amplitude. Current thermal non-equilibrium models, high-accuracy DNS and physical analysis in supersonic CO2 turbulent flow can act as the benchmark for the long-term applicability of compressible CO2 turbulence.

physics.flu-dyn↗

arXiv2022

Repeating Fast Radio Bursts with High Burst Rates by Plate Collisions in Neutron Star Crusts

Some repeating fast radio burst (FRB) sources show high burst rates, and the physical origin is still unknown. Outstandingly, the first repeater FRB 121102 appears extremely high burst rate with the maximum value reaching $122\,\mathrm{h^{-1}}$ or even higher. In this work, we propose that the high burst rate of an FRB repeater may be due to plate collisions in the crust of young neutron stars (NSs). In the crust of an NS, vortex lines are pinned to the lattice nuclei. When the relative angular velocity between the superfluid neutrons and the NS lattices is nonzero, a pinned force will act on the vortex lines, which will cause the lattice displacement and the strain on the NS crust growing. With the spin evolution, the crustal strain reaches a critical value, then the crust may crack into plates, and each of plates will collide with its adjacent ones. The Aflvén wave could be launched by the plate collisions and further produce FRBs. In this scenario, the predicted burst rate can reach $\sim 770\,\mathrm{h}^{-1}$ for an NS with the magnetic field of $10^{13}\,\rm{G}$ and the spin period of $0.01\,\rm{s}$. We further apply this model to FRB 121102, and predict the waiting time and energy distribution to be $P(t_{\mathrm{w}}) \propto t_{\text{w}}^{α_{t_{\text{w}}}}$ with $α_{t_{\text{w}}} \simeq -1.75$ and $N(E)\text{d}E \propto E^{α_{E}}\text{d}E$ with $α_{E} \simeq -1.67$, respectively. These properties are consistent with the observations of FRB 121102.

astro-ph.HE↗

arXiv2022

Neuromorphic computing using wavelength-division multiplexing

Optical neural networks (ONNs), or optical neuromorphic hardware accelerators, have the potential to dramatically enhance the computing power and energy efficiency of mainstream electronic processors, due to their ultralarge bandwidths of up to 10s of terahertz together with their analog architecture that avoids the need for reading and writing data back and forth. Different multiplexing techniques have been employed to demonstrate ONNs, amongst which wavelength division multiplexing (WDM) techniques make sufficient use of the unique advantages of optics in terms of broad bandwidths. Here, we review recent advances in WDM based ONNs, focusing on methods that use integrated microcombs to implement ONNs. We present results for human image processing using an optical convolution accelerator operating at 11 Tera operations per second. The open challenges and limitations of ONNs that need to be addressed for future applications are also discussed.

physics.optics↗

arXiv2022

High-order Gas-kinetic Schemes with Non-compact and Compact Reconstruction for Implicit Large Eddy Simulation

High-order gas-kinetic scheme (HGKS) with 5th-order non-compact reconstruction has been well implemented for implicit large eddy simulation (ILES) in nearly incompressible turbulent channel flows. In this study, the HGKS with higher-order non-compact reconstruction and compact reconstruction will be validated in turbulence simulation. For higher-order non-compact reconstruction, 7th-order normal reconstruction and tangential reconstruction are implemented. In terms of compact reconstruction, 5th-order normal reconstruction is adopted. Current work aims to show the benefits of high-order non-compact reconstruction and compact reconstruction for ILES. The accuracy of HGKS is verified by numerical simulation of three-dimensional advection of density perturbation. For the non-compact 7th-order scheme, 16 Gaussian points are required on the cell interface to preserve the order of accuracy. Then, HGKS with non-compact and compact reconstruction is used in the three-dimensional Taylor-Green vortex (TGV) problem and turbulent channel flows. Accurate ILES solutions have been obtained from HGKS. In terms of the physical modeling underlying the numerical algorithms, the compact reconstruction has the consistent physical and numerical domains of dependence without employing additional information from cells which have no any direct physical connection with the targeted cell. The compact GKS shows a favorable performance for turbulence simulation in resolving the multi-scale structures.

physics.flu-dyn↗

arXiv2022

High-order Compact Gas-kinetic Schemes for Three-dimensional Flow Simulation on Tetrahedral Mesh

A general framework for the development of high-order compact schemes has been proposed recently. The core steps of the schemes are composed of the following. 1). Based on a kinetic model equation, from a generalized initial distribution of flow variables construct a time-accurate evolution solution of gas distribution function at a cell interface ; 2). Introduce the WENO-type weighting functions into the time-derivative of the cell interface flux function in the multistage multi-derivative time stepping scheme to cope with the possible impingement of a shock wave on a cell interface within a time step; 3). Take moments of interface gas distribution function to obtain the time-accurate flow variables and the corresponding fluxes at the cell interface, and update the cell-averaged flow variables and their gradients inside each control volume; 4). Within the physical domain of dependence of the reconstructed cell, based on the cell-averaged flow variables and their gradients develop compact initial data reconstruction to get initial flow distributions at the beginning of next time step. A compact gas-kinetic scheme (GKS) up to sixth-order accuracy in space and fourth-order in time has been constructed on 2D unstructured mesh before. In this paper, the compact GKS up to fourth-order accuracy on 3D tetrahedral mesh will be further constructed with the focus on the WENO-type initial data reconstruction. Nonlinear weights are designed to achieve high-order accuracy for the smooth Navier-Stokes solution and keep super robustness in 3D computation with strong shock interactions. The fourth-order compact GKS can use a large time step with CFL number $0.6$ in the simulations from subsonic to hypersonic flow. A series of test cases are used to validate the scheme. The high-order compact GKS is ready for 3D applications with complex geometry.

physics.flu-dyn↗

arXiv2022

60-nm-span wavelength-tunable vortex fiber laser with intracavity plasmon metasurfaces

Wavelength-tunable vortex fiber lasers that could generate beams carrying orbital angular momentum (OAM) hold great interest in large-capacity optical communications. The wavelength tunability of conventional vortex fiber lasers is however limited by the range of 35 nm due to narrow bandwidth and/or insertion loss of mode conversion components. Optical metasurfaces apart from being compact planar components can flexibly manipulate light with high efficiency in a broad wavelength range. Here, we propose and demonstrate for the first time, to the best of our knowledge, a metasurface-assisted vortex fiber laser that can directly generate OAM beams with changeable topological charges. Due to the designed broadband gap-surface plasmon metasurface, combined with an intracavity tunable filter, the laser enables OAM beam with center wavelength continuously tunable from 1015 nm to 1075 nm, nearly twice of other vortex fiber lasers ever reported. The metasurface can be designed at will to satisfy requirements for either low pump threshold or high slope efficiency of the laser. Furthermore, the cavity-metasurface configuration can be extended to generate higher-order OAM beams or more complex structured beams in different wavelength regions, which greatly broadens the possibilities for developing low-cost and high-quality structured-beam laser sources.

physics.optics↗

arXiv2022

UGKWP for three-dimensional simulation of gas-particle fluidized bed

The gas-solid particle two-phase flow in a fluidized bed shows complex physics. Following our previous work, the multi-scale framework based on gas-kinetic scheme (GKS) and unified gas-kinetic wave-particle method (UGKWP) for the gas-particle system is firstly extended to the three-dimensional simulation of the fluidized bed. For the solid particle evolution, different from the widely-used Eulerian and Lagrangian approaches, the UGKWP unifies the wave (dense particle region) and discrete particle (dilute particle region) formulation seamlessly according to a continuous variation of particle cell's Kundsen number ($Kn$). The GKS-UGKWP for the coupled gas-particle evolution system can automatically become an Eulerian-Eulerian (EE) method in the high particle collision regime and Eulerian-Lagrangian (EL) formulation in the collisionless particle regime. In the transition regime, the UGKWP can achieve a smooth transition between the Eulerian and Lagrangian limiting formulation. More importantly, the weights of mass distributions from analytical wave and discrete particle are related to the local $Kn$ by $\exp(-1/Kn)$ for wave and $(1-\exp(-1/Kn))$ for discrete particle. As a result, the UGKWP provides an optimal modeling for capturing the particle phase in terms of physical accuracy and numerical efficiency. In the numerical simulation, the UGKWP does not need any prior division of dilute/dense regions, which makes it suitable for the fluidized bed problem, where the dilute/transition/dense regions instantaneously coexist and are dynamically interconvertible. In this paper, based on the GKS-UGKWP formulation two lab-scale fluidization cases are simulated in 3D and the simulation results are compared with the experimental measurements. The typical heterogeneous flow features of the fluidized bed are well captured and the statistics are in good agreement with experiment data.

physics.comp-ph↗

arXiv2022

Satellite galaxies' drag on field stars in the Milky Way

With Gaia EDR3 data, velocity dispersion of Milky Way field stars around satellite galaxies have been investigated. We have fitted velocity dispersion against distance to satellite galaxy and found the gradient of velocity dispersion is related to the mass of satellite galaxy. With order-of-magnitude approximations, a linear correlation has been fitted between the mass of satellite galaxy and gradient of velocity dispersion caused by its gravitational drag. Though our result is an observational qualitative result, it shows better relation could be obtained with more observations in the future.

astro-ph.GA↗

arXiv2022

DyLex: Incorporating Dynamic Lexicons into BERT for Sequence Labeling

Incorporating lexical knowledge into deep learning models has been proved to be very effective for sequence labeling tasks. However, previous works commonly have difficulty dealing with large-scale dynamic lexicons which often cause excessive matching noise and problems of frequent updates. In this paper, we propose DyLex, a plug-in lexicon incorporation approach for BERT based sequence labeling tasks. Instead of leveraging embeddings of words in the lexicon as in conventional methods, we adopt word-agnostic tag embeddings to avoid re-training the representation while updating the lexicon. Moreover, we employ an effective supervised lexical knowledge denoising method to smooth out matching noise. Finally, we introduce a col-wise attention based knowledge fusion mechanism to guarantee the pluggability of the proposed framework. Experiments on ten datasets of three tasks show that the proposed framework achieves new SOTA, even with very large scale lexicons.

cs.CL↗

arXiv2022

FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood Aggregation

Graph contrastive learning (GCL), as a popular approach to graph self-supervised learning, has recently achieved a non-negligible effect. To achieve superior performance, the majority of existing GCL methods elaborate on graph data augmentation to construct appropriate contrastive pairs. However, existing methods place more emphasis on the complex graph data augmentation which requires extra time overhead, and pay less attention to developing contrastive schemes specific to encoder characteristics. We argue that a better contrastive scheme should be tailored to the characteristics of graph neural networks (e.g., neighborhood aggregation) and propose a simple yet effective method named FastGCL. Specifically, by constructing weighted-aggregated and non-aggregated neighborhood information as positive and negative samples respectively, FastGCL identifies the potential semantic information of data without disturbing the graph topology and node attributes, resulting in faster training and convergence speeds. Extensive experiments have been conducted on node classification and graph classification tasks, showing that FastGCL has competitive classification performance and significant training speedup compared to existing state-of-the-art methods.

cs.LG↗

arXiv2022

Distant finetuning with discourse relations for stance classification

Approaches for the stance classification task, an important task for understanding argumentation in debates and detecting fake news, have been relying on models which deal with individual debate topics. In this paper, in order to train a system independent from topics, we propose a new method to extract data with silver labels from raw text to finetune a model for stance classification. The extraction relies on specific discourse relation information, which is shown as a reliable and accurate source for providing stance information. We also propose a 3-stage training framework where the noisy level in the data used for finetuning decreases over different stages going from the most noisy to the least noisy. Detailed experiments show that the automatically annotated dataset as well as the 3-stage training help improve model performance in stance classification. Our approach ranks 1st among 26 competing teams in the stance classification track of the NLPCC 2021 shared task Argumentative Text Understanding for AI Debater, which confirms the effectiveness of our approach.

cs.CL↗

arXiv2022

High-order Unified Gas-kinetic Scheme

In this paper, we present a high-order unified gas-kinetic scheme (UGKS) using the weighted essentially non-oscillatory with adaptive-order (WENO-AO) method for spatial reconstruction and the two-stage fourth-order scheme for time evolution. Since the UGKS updates both the macroscopic flow variables and microscopic distribution function, and provides an adaptive flux function by combining the equilibrium and non-equilibrium parts, it is possible to take separate treatment of the equilibrium and non-equilibrium calculation in the UGKS for the development of high-order scheme. Considering the fact that high-order techniques are commonly required for continuum flow with complex structures, and the rarefied flow structure are relatively simple and smooth in the physical space, we apply the high-order techniques in the equilibrium part of the UGKS for the capturing of macroscopic flow evolution, and retain the calculation of distribution function as a second-order method, so that a balance of computational cost and numerical accuracy could be well achieved. The high-order UGKS has been validated by several numerical test cases, including sine-wave accuracy test, sod-shock tube, Couette, oscillating Couette, lid-driven cavity and oscillating cavity flow. It is shown that the current method preserves the multiscale property of the original UGKS and obtains more accurate solutions in several cases.

physics.comp-ph↗

arXiv2022

Three-dimensional third-order gas-kinetic scheme on hybrid unstructured meshes for Euler and Navier-Stokes equations

In this paper, a third order gas kinetic scheme is developed on the three dimensional hybrid unstructured meshes for the numerical simulation of compressible inviscid and viscous flows. A third-order WENO reconstruction is developed on the hybrid unstructured meshes, including tetrahedron, pyramid, prism and hexahedron. A simple strategy is adopted for the selection of big stencil and sub-stencils. Incorporate with the two-stage fourth-order temporal discretization and lower-upper symmetric Gauss-Seidel methods, both explicit and implicit high-order gas-kinetic schemes are developed. A variety of numerical examples, from the subsonic to supersonic flows, are presented to validate the accuracy and robustness for both inviscid and viscous flows.

math.NA↗

arXiv2022

Zero-shot Cross-lingual Conversational Semantic Role Labeling

While conversational semantic role labeling (CSRL) has shown its usefulness on Chinese conversational tasks, it is still under-explored in non-Chinese languages due to the lack of multilingual CSRL annotations for the parser training. To avoid expensive data collection and error-propagation of translation-based methods, we present a simple but effective approach to perform zero-shot cross-lingual CSRL. Our model implicitly learns language-agnostic, conversational structure-aware and semantically rich representations with the hierarchical encoders and elaborately designed pre-training objectives. Experimental results show that our model outperforms all baselines by large margins on two newly collected English CSRL test sets. More importantly, we confirm the usefulness of CSRL to non-Chinese conversational tasks such as the question-in-context rewriting task in English and the multi-turn dialogue response generation tasks in English, German and Japanese by incorporating the CSRL information into the downstream conversation-based models. We believe this finding is significant and will facilitate the research of non-Chinese dialogue tasks which suffer the problems of ellipsis and anaphora.

cs.CL↗