arXiv subjects

Yong Tang

Publications and source records attributed to Yong Tang.

At least 55 records · Page 3Linked to original sources

arXiv2023

Constraining deviations from spherical symmetry using $ γ$-metric

The $ γ$-spacetime metric is a static and axially symmetric vacuum solution of the Einstein equation. This spacetime represents a naked singularity and it has an extra parameter $ γ$ which signifies deviations from spherical symmetry. In this work, we study the possibility of constraining the deformation parameter with astrophysical observations. We start with gravitational lensing in the weak and strong-field limit and calculate the respective deflection angles to show that only strong-field lensing observations will be able to constrain $ γ$ independently. Later we study two other classical tests of gravity: Shapiro time delay and precession of perihelion. We show that, out of these two experiments, the deformation parameter affects the observables only in perihelion shift.

gr-qc↗

arXiv2023

Gravitational Waves from Preheating in Inflation with Weyl Symmetry

Inflation with Weyl scaling symmetry provides a viable scenario that can generate both the nearly scaling invariant primordial density fluctuation and a dark matter candidate. Here we point out that, in additional to the primordial gravitational waves (GWs) from quantum fluctuations, the production of high-frequency GWs from preheating in such inflation models can provide an another probe of the inflationary dynamics. We conduct both linear analytical analysis and nonlinear numerical lattice simulation in a typical model. We find that significant stochastic GWs can be produced and the frequency band is located around $10^8$ Hz $\sim$ $10^9$ Hz, which might be probed by future resonance-cavity experiments.

astro-ph.CO↗

arXiv2023

Joint Multi-view Unsupervised Feature Selection and Graph Learning

Despite significant progress, previous multi-view unsupervised feature selection methods mostly suffer from two limitations. First, they generally utilize either cluster structure or similarity structure to guide the feature selection, which neglect the possibility of a joint formulation with mutual benefits. Second, they often learn the similarity structure by either global structure learning or local structure learning, which lack the capability of graph learning with both global and local structural awareness. In light of this, this paper presents a joint multi-view unsupervised feature selection and graph learning (JMVFG) approach. Particularly, we formulate the multi-view feature selection with orthogonal decomposition, where each target matrix is decomposed into a view-specific basis matrix and a view-consistent cluster indicator. The cross-space locality preservation is incorporated to bridge the cluster structure learning in the projected space and the similarity learning (i.e., graph learning) in the original space. Further, a unified objective function is presented to enable the simultaneous learning of the cluster structure, the global and local similarity structures, and the multi-view consistency and inconsistency, upon which an alternating optimization algorithm is developed with theoretically proved convergence. Extensive experiments on a variety of real-world multi-view datasets demonstrate the superiority of our approach for both the multi-view feature selection and graph learning tasks. The code is available at https://github.com/huangdonghere/JMVFG.

cs.CV↗

arXiv2023

Sensitivity of Space-based Gravitational-Wave Interferometers to Ultralight Bosonic Fields and Dark Matter

Ultralight bosonic fields (ULBFs) are predicted by various theories beyond the standard model of particle physics and are viable candidates of cold dark matter. There have been increasing interests to search for the ULBFs in physical and astronomical experiments. In this paper, we investigate the sensitivity of several planned space-based gravitational-wave interferometers to ultralight scalar and vector fields. Using time-delay interferometry (TDI) to suppress the overwhelming laser frequency noise, we derive the averaged transfer functions of different TDI combinations to scalar and vector fields, and estimate the impacts of bosonic field's velocities. We obtain the sensitivity curves for LISA, Taiji and TianQin, and explore their projected constraints on the couplings between ULBFs and standard model particles, illustrating with the ULBFs as dark matter.

gr-qc↗

arXiv2023

Inflation in Weyl Scaling Invariant Gravity with $R^3$ Extensions

The cosmological observations of cosmic microwave background and large-scale structure indicate that our universe has a nearly scaling invariant power spectrum of the primordial perturbation. However, the exact origin for this primordial spectrum is still unclear. Here, we propose the Weyl scaling invariant $R^2+R^3$ gravity that gives rise to inflation that is responsible for the primordial perturbation in the early universe. We develop both analytic and numerical treatments on inflationary observables, and find this model gives a distinctive scalar potential that can support two different patterns of inflation. The first one is similar to that occurs in the pure $R^2$ model, but with a wide range of tensor-to-scalar ratio $r$ from $\mathcal O(10^{-4})$ to $\mathcal O(10^{-2})$. The other one is a new situation with not only slow-roll inflation but also a short stage of oscillation-induced accelerating expansion. Both patterns of inflation have viable parameter spaces that can be probed by future experiments on cosmic microwave background and primordial gravitational waves.

astro-ph.CO↗

arXiv2023

Efficient Multi-view Clustering via Unified and Discrete Bipartite Graph Learning

Although previous graph-based multi-view clustering algorithms have gained significant progress, most of them are still faced with three limitations. First, they often suffer from high computational complexity, which restricts their applications in large-scale scenarios. Second, they usually perform graph learning either at the single-view level or at the view-consensus level, but often neglect the possibility of the joint learning of single-view and consensus graphs. Third, many of them rely on the k-means for discretization of the spectral embeddings, which lack the ability to directly learn the graph with discrete cluster structure. In light of this, this paper presents an efficient multi-view clustering approach via unified and discrete bipartite graph learning (UDBGL). Specifically, the anchor-based subspace learning is incorporated to learn the view-specific bipartite graphs from multiple views, upon which the bipartite graph fusion is leveraged to learn a view-consensus bipartite graph with adaptive weight learning. Further, the Laplacian rank constraint is imposed to ensure that the fused bipartite graph has discrete cluster structures (with a specific number of connected components). By simultaneously formulating the view-specific bipartite graph learning, the view-consensus bipartite graph learning, and the discrete cluster structure learning into a unified objective function, an efficient minimization algorithm is then designed to tackle this optimization problem and directly achieve a discrete clustering solution without requiring additional partitioning, which notably has linear time complexity in data size. Experiments on a variety of multi-view datasets demonstrate the robustness and efficiency of our UDBGL approach. The code is available at https://github.com/huangdonghere/UDBGL.

cs.LG↗

arXiv2023

Weyl Scaling Invariant $R^2$ Gravity for Inflation and Dark Matter

Inflation in the early universe can generate the nearly conformal invariant fluctuation that leads to the structures we observe at the present. The simple viable Starobinsky $R^2$ inflation has an approximate global scale symmetry. We study the conformal symmetric Weyl $\hat{R}^2$ and general $F(\hat{R})$ theories and demonstrate their equivalence to Einstein gravity coupled with a scalar and a Weyl gauge field. The scalar field in Weyl $\hat{R}^2$ gravity can be responsible for inflation with Starobinsky model as the attractor, potentially distinguishable from the latter by future experiments. The intrinsic Weyl gauge boson becomes massive once the Einstein frame is fixed, and constitutes as a dark matter candidate with mass up to $\sim 5\times 10^{16}$GeV.

hep-ph↗

arXiv2023

Multi-MEC Cooperation Based VR Video Transmission and Cache using K-Shortest Paths Optimization

In recent network architectures, multi-MEC cooperative caching has been introduced to reduce the transmission latency of VR videos, in which MEC servers' computing and caching capability are utilized to optimize the transmission process. However, many solutions that use the computing capability of MEC servers ignore the additional arithmetic power consumed by the codec process, thus making them infeasible. Besides, the minimum cache unit is usually the entire VR video, which makes caching inefficient. To address these challenges, we split VR videos into tile files for caching based on the current popular network architecture and provide a reliable transmission mechanism and an effective caching strategy. Since the number of different tile files N is too large, the current cooperative caching algorithms do not cope with such large-scale input data. We further analyze the problem and propose an optimized k-shortest paths (OKSP) algorithm with an upper bound time complexity of O((K * M + N) * M * logN)), and suitable for shortest paths with restricted number of edges, where K is the total number of tiles that all M MEC servers can cache in the collaboration domain. And we prove the OKSP algorithm can compute the caching scheme with the lowest average latency in any case, which means the solution given is the exact solution. The simulation results show that the OKSP algorithm has excellent speed for solving large-scale data and consistently outperforms other caching algorithms in the experiments.

cs.NI↗

arXiv2023

Stochastic Gravitational Waves from Particle Origin

We propose that there may be a substantial stochastic gravitational wave background from particle origin, mainly from the gravitational three-body decay of the inflaton. The emitted gravitons could constitute a sizable contribution to dark radiation if the mass of inflaton is close to the Planck scale, which can be probed by future CMB experiments that have a sensitivity on the deviation of the effective number of neutrinos in the standard cosmology, $δN_{\textrm{eff}}\sim 0.02 - 0.03$. We have also illustrated the spectrum of the radiated gravitational waves, in comparison to the current and future experiments, and found that gravitational waves from particle origin could be the dominant contribution to the energy density at high-frequency domain, but beyond the sensitivity regions of various experiments.

hep-ph↗

arXiv2022

Contributions to the Muon $g-2$ from a Three-Form Field

We examine contributions to the muon dipole moment $g-2$ from a 3-form field $Ω$, which naturally arises from many fundamental theories, such as the string theory and the hyperunified field theory. In particular, by calculating the one-loop Feynman diagram, we have obtained the leading-order $Ω$-induced contribution to the muon $g-2$, which is found to be finite. Then we investigate the theoretical constraints from perturbativity and unitarity. Especially, the unitarity bounds are yielded by computing the tree-level $μ^+μ^-$ scattering amplitudes of various initial and final helicity configurations. As a result, despite the strong unitarity bounds imposed on this model of $Ω$, we have still found a substantial parameter space which can accommodates the muon $g-2$ data.

hep-ph↗

arXiv2022

Privileged Prior Information Distillation for Image Matting

Performance of trimap-free image matting methods is limited when trying to decouple the deterministic and undetermined regions, especially in the scenes where foregrounds are semantically ambiguous, chromaless, or high transmittance. In this paper, we propose a novel framework named Privileged Prior Information Distillation for Image Matting (PPID-IM) that can effectively transfer privileged prior environment-aware information to improve the performance of students in solving hard foregrounds. The prior information of trimap regulates only the teacher model during the training stage, while not being fed into the student network during actual inference. In order to achieve effective privileged cross-modality (i.e. trimap and RGB) information distillation, we introduce a Cross-Level Semantic Distillation (CLSD) module that reinforces the trimap-free students with more knowledgeable semantic representations and environment-aware information. We also propose an Attention-Guided Local Distillation module that efficiently transfers privileged local attributes from the trimap-based teacher to trimap-free students for the guidance of local-region optimization. Extensive experiments demonstrate the effectiveness and superiority of our PPID framework on the task of image matting. In addition, our trimap-free IndexNet-PPID surpasses the other competing state-of-the-art methods by a large margin, especially in scenarios with chromaless, weak texture, or irregular objects.

cs.CV↗

arXiv2022

Probing Dark Matter Spikes via Gravitational Waves of Extreme Mass Ratio Inspirals

The exact properties of dark matter remain largely unknown despite the accumulating evidence. If dark matter is composed of weakly interacting massive particles, it would be accreted by the black hole in the galactic center and form a dense, cuspy spike. Dynamical friction from this spike may have observable effects in a binary system. We consider extreme-mass-ratio inspiral (EMRI) binaries comprising massive black holes harbored in dark matter spikes and stellar mass objects in elliptic orbits. We find that the gravitational-wave waveforms in the frequency domain can be substantially modified. In particular, we show that dark matter can suppress the characteristic strain of a gravitational wave at low frequency but enhance it at a higher domain. These effects are more dramatic as the dark matter density increases. The results indicate that the signal-to-noise ratio of EMRIs can be strongly reduced near $10^{-3}\sim 0.3$~Hz but enhanced near $1.0$~Hz with a higher sensitivity, which can be probed via the future space-borne gravitational-wave (GW) detectors, LISA and TAIJI. The findings will have important impacts on the detection and parameter inference of EMRIs.

astro-ph.CO↗

arXiv2022

Dark Matter Production in Weyl $R^2$ Inflation

Dark matter and inflation are two key elements to understand the origin of cosmic structures in modern cosmology, and yet their exact physical models remain largely uncertain. The Weyl scaling invariant theory of gravity may provide a feasible scheme to solve these two puzzles jointly, which contains a massive gauge boson playing the role of dark matter candidate, and allows the quadratic scalar curvature term, namely $R^2$, to realize a viable inflationary mechanism in agreement with current observations. We ponder on the production of dark matters in the Weyl $R^2$ model, including the contribution from the non-perturbative production due to the quantum fluctuations from inflationary vacuum and perturbative ones from scattering. We demonstrate that there are generally three parameter ranges for viable dark matter production: (1) If the reheating temperature is larger than $10^3~\mathrm{GeV}$, the Weyl gauge boson as dark matter can be produced abundantly with mass larger than the inflation scale $\sim 10^{13}~\mathrm{GeV}$. (2) Small mass region with $3\times10^{-13}~\mathrm{GeV}$ for a higher reheating temperature. (3) Annihilation channel becomes important in the case of higher reheating temperature, which enables the Weyl gauge boson with mass up to $4\times10^{16}~\mathrm{GeV}$ to be produced through freeze-in.

hep-ph↗

arXiv2022

Situational Perception Guided Image Matting

Most automatic matting methods try to separate the salient foreground from the background. However, the insufficient quantity and subjective bias of the current existing matting datasets make it difficult to fully explore the semantic association between object-to-object and object-to-environment in a given image. In this paper, we propose a Situational Perception Guided Image Matting (SPG-IM) method that mitigates subjective bias of matting annotations and captures sufficient situational perception information for better global saliency distilled from the visual-to-textual task. SPG-IM can better associate inter-objects and object-to-environment saliency, and compensate the subjective nature of image matting and its expensive annotation. We also introduce a textual Semantic Transformation (TST) module that can effectively transform and integrate the semantic feature stream to guide the visual representations. In addition, an Adaptive Focal Transformation (AFT) Refinement Network is proposed to adaptively switch multi-scale receptive fields and focal points to enhance both global and local details. Extensive experiments demonstrate the effectiveness of situational perception guidance from the visual-to-textual tasks on image matting, and our model outperforms the state-of-the-art methods. We also analyze the significance of different components in our model. The code will be released soon.

cs.CV↗

arXiv2021

ExamGAN and Twin-ExamGAN for Exam Script Generation

Nowadays, the learning management system (LMS) has been widely used in different educational stages from primary to tertiary education for student administration, documentation, tracking, reporting, and delivery of educational courses, training programs, or learning and development programs. Towards effective learning outcome assessment, the exam script generation problem has attracted many attentions and been investigated recently. But the research in this field is still in its early stage. There are opportunities to further improve the quality of generated exam scripts in various aspects. In particular, two essential issues have been ignored largely by existing solutions. First, given a course, it is unknown yet how to generate an exam script which can result in a desirable distribution of student scores in a class (or across different classes). Second, while it is frequently encountered in practice, it is unknown so far how to generate a pair of high quality exam scripts which are equivalent in assessment (i.e., the student scores are comparable by taking either of them) but have significantly different sets of questions. To fill the gap, this paper proposes ExamGAN (Exam Script Generative Adversarial Network) to generate high quality exam scripts, and then extends ExamGAN to T-ExamGAN (Twin-ExamGAN) to generate a pair of high quality exam scripts. Based on extensive experiments on three benchmark datasets, it has verified the superiority of proposed solutions in various aspects against the state-of-the-art. Moreover, we have conducted a case study which demonstrated the effectiveness of proposed solution in a real teaching scenario.

cs.LG↗

arXiv2021

On Conformal Transformation with Multiple Scalar Fields and Geometric Property of Field Space with Einstein-like Solutions

Multiple scalar fields appear in vast modern particle physics and gravity models. When they couple to gravity non-minimally, conformal transformation is utilized to bring the theory into Einstein frame. However, the kinetic terms of scalar fields are usually not canonical, which makes analytic treatment difficult. Here we investigate under what conditions the theories can be transformed to the quasi-canonical form, in which case the effective metric tensor in field space is conformally flat. We solve the relevant nonlinear partial differential equations for arbitrary number of scalar fields and present several solutions that may be useful for future phenomenological model building, including the $σ$-model with a particular non-minimal coupling. We also find conformal flatness can always be achieved in some modified gravity theories, for example, Starobinsky model.

gr-qc↗

arXiv2021

Compliant Fins for Locomotion in Granular Media

In this paper, we present an approach to study the behavior of compliant plates in granular media and optimize the performance of a robot that utilizes this technique for mobility. From previous work and fundamental tests on thin plate force generation inside granular media, we introduce an origami-inspired mechanism with non-linear compliance in the joints that can be used in granular propulsion. This concept utilizes one-sided joint limits to create an asymmetric gait cycle that avoids more complicated alternatives often found in other swimming/digging robots. To analyze its locomotion as well as its shape and propulsive force, we utilize granular Resistive Force Theory (RFT) as a starting point. Adding compliance to this theory enables us to predict the time-based evolution of compliant plates when they are dragged and rotated. It also permits more rational design of swimming robots where fin design variables may be optimized against the characteristics of the granular medium. This is done using a Python-based dynamic simulation library to model the deformation of the plates and optimize aspects of the robot's gait. Finally, we prototype and test robot with a gait optimized using the modelling techniques mentioned above.

cs.RO↗

arXiv2021

Semi-annihilating $Z_3$ Dark Matter for XENON1T Excess

The recently reported result from XENON1T experiment indicates that there is an excess with $3.5σ$ significance in the electronic recoil events. Interpreted as new physics, new sources are needed to account for the electronic scattering. We show that a dark fermion $ψ$ with mass about $ \mathcal{O}\left(10\right)$ MeV from semi-annihilation of $Z_3$ dark matter $X$ and subsequent decay of a dark gauge boson $V_μ$ may be responsible for the excess. The relevant semi-annihilation process is $X+X\rightarrow \overline{X}+V_μ(\rightarrow ψ+ \overlineψ)$, in which the final $ψ$ has a box-shape energy spectrum. The fast-moving $ψ$ can scatter with electron through an additional gauge boson that mixes with photon kinetically. The shape of the signals in this model can be consistent with the observed excess. The additional interaction with proton makes this model testable in future searches for nucleus recoil as well. Because of the lightness of invisible particle introduced, this scenario requires non-standard cosmology to accommodate the additional radiation component.

hep-ph↗