arXiv subjects

Gang Yang

Publications and source records attributed to Gang Yang.

At least 73 records · Page 4Linked to original sources

arXiv2024

Pioneering Deterministic Scheduling and Network Structure Optimization for Time-Critical Computing Tasks in Industrial IoT

The Industrial Internet of Things (IIoT) has become a critical technology to accelerate the process of digital and intelligent transformation of industries. As the cooperative relationship between smart devices in IIoT becomes more complex, getting deterministic responses of IIoT periodic time-critical computing tasks becomes a crucial and nontrivial problem. However, few current works in cloud/edge/fog computing focus on this problem. This paper is a pioneer to explore the deterministic scheduling and network structural optimization problems for IIoT periodic time-critical computing tasks. We first formulate the two problems and derive theorems to help quickly identify computation and network resource sharing conflicts. Based on this, we propose a deterministic scheduling algorithm, \textit{IIoTBroker}, which realizes deterministic response for each IIoT task by optimizing the fine-grained computation and network resources allocations, and a network optimization algorithm, \textit{IIoTDeployer}, providing a cost-effective structural upgrade solution for existing IIoT networks. Our methods are illustrated to be cost-friendly, scalable, and deterministic response guaranteed with low computation cost from our simulation results.

cs.NI↗

arXiv2023

Joint Range-Velocity-Azimuth Estimation for OFDM-Based Integrated Sensing and Communication

Orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) is promising for future sixth-generation mobile communication systems. Existing works focus on the joint estimation of the targets' range and velocity for OFDM-based ISAC systems. In contrast, this paper studies the three-dimensional joint estimation (3DJE) of range, velocity, and azimuth for OFDM-based ISAC systems with multiple receive antennas. First, we establish the signal model and derive the Cramer-Rao bounds (CRBs) on the 3DJE. Furthermore, an auto-paired super-resolution 3DJE algorithm is proposed by exploiting the reconstructed observation sub-signal's translational invariance property in the time, frequency, and space domains. Finally, with the 5G New Radio parameter setup, simulation results show that the proposed algorithm achieves better estimation performance and its root mean square error is closer to the root of CRBs than existing methods.

eess.SP↗

arXiv2023

The $\mathbf{\bar{q}q\bar{s}Q}$ $\mathbf{(q=u,\,d;\,Q=c,\,b)}$ tetraquark system in a chiral quark model

Inspired by the experimentally reported $T_{c\bar{s}}(2900)$ exotic states, the $S$-wave $\bar{q}q\bar{s}Q$ $(q=u,\,d;\,Q=c,\,b)$ tetraquarks, with spin-parity $J^P=0^+$, $1^+$ and $2^+$, in both isoscalar and isovector sectors are systematically studied in a chiral quark model. The meson-meson, diquark-antidiquark and K-type arrangements of quarks, along with all possible color wave functions, are comprehensively considered. The four-body system is solved by means of a highly efficient computational approach, the Gaussian expansion method, along with a complex-scaling formulation of the problem to disentangle bound, resonance and scattering states. This theoretical framework has already been successfully applied in various tetra- and penta-quark systems. In the complete coupled-channel case, and within the complex-range formulation, several narrow resonances of $\bar{q}q\bar{s}c$ and $\bar{q}q\bar{s}b$ systems are obtained in each allowed $I(J^P)$-channels. Particularly, the $T_{c\bar{s}}(2900)$ is well identified as a $I(J^P)=1(0^+)$ $\bar{q}q\bar{s}c$ tetraquark state with a dominant molecular structure. Meanwhile, more resonances in $\bar{q}q\bar{s}c$ and $\bar{q}q\bar{s}b$ systems are also obtained within the energy regions $2.4-3.4$ GeV and $5.7-6.7$ GeV, respectively. The predicted exotic states, which are an indication of a richer color structure when going towards multiquark systems beyond mesons and baryons, are expected to be confirmed in future high-energy particle and nuclear experiments.

hep-ph↗

arXiv2023

Hidden-charm pentaquarks with strangeness in a chiral quark model

The LHCb collaboration has recently announced the discovery of two hidden-charm pentaquark states with also strange quark content, $P_{cs}(4338)$ and $P_{cs}(4459)$; its analysis points towards having both hadrons isospin equal to zero and spin-parity quantum numbers $\frac12^-$ and $\frac32^-$, respectively. We perform herein a systematical investigation of the $qqsc\bar{c}$ $(q=u,\,d)$ system by means of a chiral quark model, along with a highly accurate computational method, the Gaussian expansion approach combined with the complex-scaling technique. Baryon-meson configurations in both singlet- and hidden-color channels are considered. The $P_{cs}(4338)$ and $P_{cs}(4459)$ signals can be well identified as molecular bound states with dominant components $ΛJ/ψ$ $(60\%)$ and $Ξ_c D$ $(23\%)$ for the lowest-energy case and $Ξ_c D^*$ $(72\%)$ for the highest-energy one. Besides, it seems that some narrow resonances can be also found in each allowed $I(J^P)$-channel in the energy region of $4.6-5.5$ GeV, except for the $1(\frac12^-)$ where a shallow bound state with dominant $Ξ^*_c D^*$ structure is obtained at $4673$ MeV with binding energy $E_B=-3$ MeV. These exotic states are expected to be confirmed in future high energy experiments.

hep-ph↗

arXiv2023

Jade: A Differentiable Physics Engine for Articulated Rigid Bodies with Intersection-Free Frictional Contact

We present Jade, a differentiable physics engine for articulated rigid bodies. Jade models contacts as the Linear Complementarity Problem (LCP). Compared to existing differentiable simulations, Jade offers features including intersection-free collision simulation and stable LCP solutions for multiple frictional contacts. We use continuous collision detection to detect the time of impact and adopt the backtracking strategy to prevent intersection between bodies with complex geometry shapes. We derive the gradient calculation to ensure the whole simulation process is differentiable under the backtracking mechanism. We modify the popular Dantzig algorithm to get valid solutions under multiple frictional contacts. We conduct extensive experiments to demonstrate the effectiveness of our differentiable physics simulation over a variety of contact-rich tasks.

cs.RO↗

arXiv2023

Exploring the Potential of Integrated Optical Sensing and Communication (IOSAC) Systems with Si Waveguides for Future Networks

Advanced silicon photonic technologies enable integrated optical sensing and communication (IOSAC) in real time for the emerging application requirements of simultaneous sensing and communication for next-generation networks. Here, we propose and demonstrate the IOSAC system on the silicon nitride (SiN) photonics platform. The IOSAC devices based on microring resonators are capable of monitoring the variation of analytes, transmitting the information to the terminal along with the modulated optical signal in real-time, and replacing bulk optics in high-precision and high-speed applications. By directly integrating SiN ring resonators with optical communication networks, simultaneous sensing and optical communication are demonstrated by an optical signal transmission experimental system using especially filtering amplified spontaneous emission spectra. The refractive index (RI) sensing ring with a sensitivity of 172 nm/RIU, a figure of merit (FOM) of 1220, and a detection limit (DL) of 8.2*10-6 RIU is demonstrated. Simultaneously, the 1.25 Gbps optical on-off-keying (OOK) signal is transmitted at the concentration of different NaCl solutions, which indicates the bit-error-ratio (BER) decreases with the increase in concentration. The novel IOSAC technology shows the potential to realize high-performance simultaneous biosensing and communication in real time and further accelerate the development of IoT and 6G networks.

eess.SP↗

arXiv2023

PanFlowNet: A Flow-Based Deep Network for Pan-sharpening

Pan-sharpening aims to generate a high-resolution multispectral (HRMS) image by integrating the spectral information of a low-resolution multispectral (LRMS) image with the texture details of a high-resolution panchromatic (PAN) image. It essentially inherits the ill-posed nature of the super-resolution (SR) task that diverse HRMS images can degrade into an LRMS image. However, existing deep learning-based methods recover only one HRMS image from the LRMS image and PAN image using a deterministic mapping, thus ignoring the diversity of the HRMS image. In this paper, to alleviate this ill-posed issue, we propose a flow-based pan-sharpening network (PanFlowNet) to directly learn the conditional distribution of HRMS image given LRMS image and PAN image instead of learning a deterministic mapping. Specifically, we first transform this unknown conditional distribution into a given Gaussian distribution by an invertible network, and the conditional distribution can thus be explicitly defined. Then, we design an invertible Conditional Affine Coupling Block (CACB) and further build the architecture of PanFlowNet by stacking a series of CACBs. Finally, the PanFlowNet is trained by maximizing the log-likelihood of the conditional distribution given a training set and can then be used to predict diverse HRMS images. The experimental results verify that the proposed PanFlowNet can generate various HRMS images given an LRMS image and a PAN image. Additionally, the experimental results on different kinds of satellite datasets also demonstrate the superiority of our PanFlowNet compared with other state-of-the-art methods both visually and quantitatively.

cs.CV↗

arXiv2023

Gorenstein homological dimension and some invariants of groups

For any group $G$, the Gorenstein homological dimension ${\rm Ghd}_RG$ is defined to be the Gorenstein flat dimension of the coefficient ring $R$, which is considered as an $RG$-module with trivial group action. We prove that ${\rm Ghd}_RG < \infty$ if and only if the Gorenstein flat dimension of any $RG$-module is finite, if and only if there exists an $R$-pure $RG$-monic $R\rightarrow A$ with $A$ being $R$-flat and ${\rm Ghd}_RG = {\rm fd}_{RG}A$, where $R$ is a commutative ring with finite Gorenstein weak global dimension. As applications, properties of ${\rm Ghd}$ on subgroup, quotient group, extension of groups as well as Weyl group are investigated. Moreover, we compare the relations between some invariants such as ${\rm sfli}RG$, ${\rm silf}RG$, ${\rm spli}RG$, ${\rm silp}RG$, and Gorenstein projective, Gorenstein flat and PGF dimensions of $RG$-modules; a sufficient condition for Gorenstein projective-flat problem over group rings is given.

math.AC↗

arXiv2023

Charmoniumlike tetraquarks in a chiral quark model

The lowest-lying charmonium-like tetraquarks $c\bar{c}q\bar{q}$ $(q=u,\,d)$ and $c\bar{c}s\bar{s}$, with spin-parity $J^P=0^+$, $1^+$ and $2^+$, and isospin $I=0$ and $1$, are systematically investigated within the theoretical framework of complex-scaling range for a chiral quark model that has already been successfully applied in former studies of various tetra- and penta-quark systems. A four-body $S$-wave configuration which includes meson-meson, diquark-antidiquark and K-type arrangements of quarks, along with all possible color wave functions, is comprehensively considered. Several narrow resonances are obtained in each tetraquark channel when a fully coupled-channel computation is performed. We tentatively assign theoretical states to experimentally reported charmonium-like signals such as $X(3872)$, $Z_c(3900)$, $X(3960)$, $X(4350)$, $X(4685)$ and $X(4700)$. They can be well identified as hadronic molecules; however, other exotic components which involve, for instance, hidden-color channels or diquark-antidiquark structures play a considerable role. Meanwhile, two resonances are obtained at $4.04$ GeV and $4.14$ GeV which may be compatible with experimental data in the energy interval $4.0-4.2$ GeV. Furthermore, the $X(3940)$ and $X(4630)$ may be identified as color compact tetraquark resonances. Finally, we also find few resonance states in the energy interval from $4.5$ GeV to $5.0$ GeV, which would be awaiting for discovery in future experiments.

hep-ph↗

arXiv2023

Gluonic evanescent operators: two-loop anomalous dimensions

Evanescent operators are a special class of operators that vanish in four-dimensional spacetime but are non-zero in $d=4-2ε$ dimensions. In this paper, we continue our systematic study of the evanescent operators in the pure Yang-Mills theory and focus on their two-loop renormalization. We develop an efficient strategy to compute the two-loop divergences of form factors of high-dimensional and high-length operators by combining the $d$-dimensional unitarity method and the improved tensor reduction techniques. Two-loop anomalous dimensions are obtained for the mass-dimension-10 basis in the planar YM theory, for which both the $\overline{\text{MS}}$ scheme and the finite-renormalization scheme are used. We verify that the two-loop anomalous dimensions are the same in these two schemes at the Wilson-Fisher conformal fixed point. Our computation shows that the evanescent operators are indispensable in order to obtain the correct two-loop anomalous dimensions. This work provides a first computation of the two-loop anomalous dimensions of the complete set of dimension-10 operators. The method we use is also expected to provide an efficient strategy for the two-loop renormalization of general high-dimensional operators.

hep-th↗

arXiv2022

Double Copy of Form Factors and Higgs Amplitudes: A mechanism of turning spurious poles in Yang-Mills into physical poles in gravity

We extend the double copy picture of scattering amplitudes to a class of matrix elements (so-called form factors) that involve local gauge invariant operators. Both the Bern, Carrasco and Johansson (BCJ) and the Kawai, Lewellen and Tye (KLT) formalisms are considered and novel properties are observed. One remarkable feature is that through the double-copy construction, certain spurious poles hidden in the gauge form factors become physical propagators in gravity. This mechanism also reveals new hidden relations for form factors which can be understood as a generalization of the BCJ relations.

hep-th↗

arXiv2022

Segmentation-based Information Extraction and Amalgamation in Fundus Images for Glaucoma Detection

Glaucoma is a severe blinding disease, for which automatic detection methods are urgently needed to alleviate the scarcity of ophthalmologists. Many works have proposed to employ deep learning methods that involve the segmentation of optic disc and cup for glaucoma detection, in which the segmentation process is often considered merely as an upstream sub-task. The relationship between fundus images and segmentation masks in terms of joint decision-making in glaucoma assessment is rarely explored. We propose a novel segmentation-based information extraction and amalgamation method for the task of glaucoma detection, which leverages the robustness of segmentation masks without disregarding the rich information in the original fundus images. Experimental results on both private and public datasets demonstrate that our proposed method outperforms all models that utilize solely either fundus images or masks.

eess.IV↗

arXiv2022

Deciphering the Maximal Transcendentality Principle via Bootstrap

We prove the principle of maximal transcendentality for a class of form factors, including the general two-loop minimal form factors, the two-loop three-point form factor of ${\rm tr}(F^2)$, and the two-loop four-point form factor of ${\rm tr}(F^3)$. Our proof is based on a recently developed bootstrap method using the representation of master integral expansions, together with some unitarity cuts that are universal in general gauge theories. The maximally transcendental parts of the two-loop four-gluon form factor of $\mathrm{tr}(F^3)$ are obtained for the first time in both planar $\mathcal{N}=4$ SYM and pure YM theories. This form factor can be understood as the Higgs-plus-four-gluon amplitudes involving a dimension-seven operator in the Higgs effective theory. In this case, we find that the maximally transcendental part of the $\mathcal{N}=4$ SYM result is different from that of pure YM, and the discrepancy is due to the gluino-loop contributions in $\mathcal{N}=4$ SYM. In contrast, the scalar-loop contributions have no maximally transcendental parts. Thus, the maximal transcendentality principle still holds for the form factor results in $\mathcal{N}=4$ SYM and QCD, after a proper identification of the fundamental quarks and adjoint gluinos as $n_f \rightarrow 4N_c$. This seems to be the first example of the maximally transcendental principle that involves fermion-loop contributions. As another intriguing observation, we find that the four-point form factor of the half-BPS $\mathrm{tr}(ϕ^3)$ operator is precisely a building block in the form factor of $\mathrm{tr}(F^3)$.

hep-th↗

arXiv2022

Model-Guided Multi-Contrast Deep Unfolding Network for MRI Super-resolution Reconstruction

Magnetic resonance imaging (MRI) with high resolution (HR) provides more detailed information for accurate diagnosis and quantitative image analysis. Despite the significant advances, most existing super-resolution (SR) reconstruction network for medical images has two flaws: 1) All of them are designed in a black-box principle, thus lacking sufficient interpretability and further limiting their practical applications. Interpretable neural network models are of significant interest since they enhance the trustworthiness required in clinical practice when dealing with medical images. 2) most existing SR reconstruction approaches only use a single contrast or use a simple multi-contrast fusion mechanism, neglecting the complex relationships between different contrasts that are critical for SR improvement. To deal with these issues, in this paper, a novel Model-Guided interpretable Deep Unfolding Network (MGDUN) for medical image SR reconstruction is proposed. The Model-Guided image SR reconstruction approach solves manually designed objective functions to reconstruct HR MRI. We show how to unfold an iterative MGDUN algorithm into a novel model-guided deep unfolding network by taking the MRI observation matrix and explicit multi-contrast relationship matrix into account during the end-to-end optimization. Extensive experiments on the multi-contrast IXI dataset and BraTs 2019 dataset demonstrate the superiority of our proposed model.

eess.IV↗

arXiv2022

TANet: Transformer-based Asymmetric Network for RGB-D Salient Object Detection

Existing RGB-D SOD methods mainly rely on a symmetric two-stream CNN-based network to extract RGB and depth channel features separately. However, there are two problems with the symmetric conventional network structure: first, the ability of CNN in learning global contexts is limited; second, the symmetric two-stream structure ignores the inherent differences between modalities. In this paper, we propose a Transformer-based asymmetric network (TANet) to tackle the issues mentioned above. We employ the powerful feature extraction capability of Transformer (PVTv2) to extract global semantic information from RGB data and design a lightweight CNN backbone (LWDepthNet) to extract spatial structure information from depth data without pre-training. The asymmetric hybrid encoder (AHE) effectively reduces the number of parameters in the model while increasing speed without sacrificing performance. Then, we design a cross-modal feature fusion module (CMFFM), which enhances and fuses RGB and depth features with each other. Finally, we add edge prediction as an auxiliary task and propose an edge enhancement module (EEM) to generate sharper contours. Extensive experiments demonstrate that our method achieves superior performance over 14 state-of-the-art RGB-D methods on six public datasets. Our code will be released at https://github.com/lc012463/TANet.

cs.CV↗

arXiv2022

Fully-charm and -bottom pentaquarks in a Lattice-QCD inspired quark model

The fully-charm and -bottom pentaquarks, \emph{i.e.} $cccc\bar{c}$ and $bbbb\bar{b}$, with spin-parity quantum numbers $J^P=\frac{1}{2}^-$, $\frac{3}{2}^-$ and $\frac{5}{2}^-$, are investigated within a Lattice-QCD inspired quark model, which has already successfully described the recently announced fully-charm tetraquark candidate $X(6900)$, and has also predicted several other fully-heavy tetraquarks. A powerful computational technique, based on the Gaussian expansion method combined with a complex-scaling range approach, is employed to predict, and distinguish, bound, resonance and scattering states of the mentioned five-body system. Both baryon-meson and diquark-diquark-antiquark configurations, along with all of their possible color channels are comprehensively considered. Narrow resonances are obtained in each spin-parity channel for the fully-charm and -bottom systems. Moreover, most of them seems to be compact multiquarks whose wave-functions are dominated by either hidden-color baryon-meson or diquark-diquark-antiquark structure, or by the coupling between them.

hep-ph↗

arXiv2022

Gluonic evanescent operators: classification and one-loop renormalization

Evanescent operators are a special class of operators that vanish classically in four-dimensional spacetime, while in general dimensions they are non-zero and are expected to have non-trivial physical effects at the quantum loop level in dimensional regularization. In this paper we initiate the study of evanescent operators in pure Yang-Mills theory. We develop a systematic method for classifying and constructing the $d$-dimensional Lorentz invariant evanescent operators, which start to appear at mass dimension ten. We also compute one-loop form factors for the dimension-ten operators via the $d$-dimensional unitarity method and obtain their one-loop anomalous dimensions. These operators are necessary ingredients in the study of high dimensional operators in effective field theories involving a Yang-Mills sector.

hep-th↗

arXiv2022

Inverse design of nano-photonic wavelength demultiplexer with a deep neural network approach

In this paper, we propose a pre-trained-combined neural network (PTCN) as a comprehensive solution to the inverse design of an integrated photonic circuit. By utilizing both the initially pre-trained inverse and forward model with a joint training process, our PTCN model shows remarkable tolerance to the quantity and quality of the training data. As a proof of concept demonstration, the inverse design of a wavelength demultiplexer is used to verify the effectiveness of the PTCN model. The correlation coefficient of the prediction by the presented PTCN model remains greater than 0.974 even when the size of training data is decreased to 17%. The experimental results show a good agreement with predictions, and demonstrate a wavelength demultiplexer with an ultra-compact footprint, a high transmission efficiency with a transmission loss of -2dB, a low reflection of -10dB, and low crosstalk around -7dB simultaneously.

physics.optics↗