arXiv subjects

Chao Zhang

Publications and source records attributed to Chao Zhang.

At least 847 records · Page 47Linked to original sources

arXiv2022

Gravitational axial perturbations of Schwarzschild-like black holes in dark matter halos

Gravitational waves emitted by distorted black holes, such as those arising from the coalescence of binary black holes, or a falling compact star into a supermassive black hole, carry not only information about the corresponding spacetime but also information about the environment surrounding the black holes. In this paper, we study the effects of the dark matter halos with three different density profiles on the gravitational axial perturbations of a Schwarzschild-like black hole. For this purpose, we first consider modified Schwarzschild black holes with three different dark matter profiles and derive the equation of motion of the axial perturbations of the modified Schwarzschild metric. It is shown that by ignoring the dark matter perturbations, a Regge-Wheeler-like master equation with a modified potential for the axial perturbation can be obtained explicitly. Then we calculate the complex frequencies of the quasi-normal modes of the Schwarzschild-like black hole in the dark matter halos by applying the sixth-order WKB method. The corresponding gravitational wave spectra with the effects of the dark matter halos have also been discussed.

gr-qc↗

arXiv2022

PACSan: Enforcing Memory Safety Based on ARM PA

Memory safety is a key security property that stops memory corruption vulnerabilities. Existing sanitizers enforce checks and catch such bugs during development and testing. However, they either provide partial memory safety or have overwhelmingly high performance overheads. Our novel sanitizer PACSan enforces spatial and temporal memory safety with no false positives at low performance overheads. PACSan removes the majority of the overheads involved in pointer tracking by sealing metadata in pointers through ARM PA (Pointer Authentication), and performing the memory safety checks when pointers are dereferenced. We have developed a prototype of PACSan and systematically evaluated its security and performance on the Magma, Juliet, Nginx, and SPEC CPU2017 test suites, respectively. In our evaluation, PACSan shows no false positives together with negligible false negatives, while introducing stronger security guarantees and lower performance overheads than state-of-the-art sanitizers, including HWASan, ASan, SoftBound+CETS, Memcheck, LowFat, and PTAuth. Specifically, PACSan has 0.84x runtime overhead and 1.92x memory overhead on average. Compared to the widely deployed ASan, PACSan has no false positives and much fewer false negatives and reduces 7.172% runtime overheads and 89.063%memory overheads.

cs.CR↗

arXiv2022

Superconductivity with the enhanced upper critical field in the Pt-Doping CuRh2Se4 spinel

We report the effect of Pt doping on the superconductivity in CuRh2Se4 spinel using a combined experimental and theoretical study. Our XRD results reveal that the Cu(Rh1-xPtx)2Se4 crystallizes in the structure with a space group of Fd3-m (No. 227), and the lattice parameter a increases with Pt doping. The resistivity and magnetic susceptibility measurement results verify that the superconducting transition temperature (Tc) forms a dome-like shape with a maximum value of 3.84 K at x = 0.06. It is also observed that the Pt-doping slightly reduces the lower critical magnetic field from 220 Oe in CuRh2Se4 to 168 Oe in Cu(Rh0.94Pt0.06)2Se4, while it significantly enhances the upper critical magnetic field, reaching the maximum of 4.93 T in the Cu(Rh0.94Pt0.06)2Se4 sample. The heat capacity result indicates that the sample Cu(Rh0.91Pt0.09)2Se4 is a bulk superconductor. First-principles calculations suggest that the Pt-doping leads to a red-shift of a density of state peak near the Fermi level, consistent with the dome-like Tc observed experimentally.

cond-mat.supr-con↗

arXiv2022

Experimental Demonstration that No Tripartite-Nonlocal Causal Theory Explains Nature's Correlations

Quantum theory predicts the existence of genuinely tripartite-entangled states, which cannot be obtained from local operations over any bipartite entangled states and unlimited shared randomness. Some of us recently proved that this feature is a fundamental signature of quantum theory. The state $\left|{GHZ}_3\right\rangle=(\left|000\right\rangle+\left|111\right\rangle)/\sqrt{2}$ gives rise to tripartite quantum correlations which cannot be explained by any causal theory limited to bipartite nonclassical common causes of any kind (generalising entanglement) assisted with unlimited shared randomness. Hence, any conceivable physical theory which would reproduce quantum predictions will necessarily include genuinely tripartite resources. In this work, we verify that such tripartite correlations are experimentally achievable. We derive a new device-independent witness capable of falsifying causal theories wherein nonclassical resources are merely bipartite. Using a high-performance photonic $\left|{GHZ}_3\right\rangle$ states with fidelities of $ 0.9741\pm0.002$, we provide a clear experimental violation of that witness by more than $26.3$ standard deviation, under the locality and fair sampling assumption. We generalise our work to the $\left|{GHZ}_4\right\rangle$ state, obtaining correlations which cannot be explained by any causal theory limited to tripartite nonclassical common causes assisted with unlimited shared randomness.

quant-ph↗

arXiv2022

SIGMA: A Structural Inconsistency Reducing Graph Matching Algorithm

Graph matching finds the correspondence of nodes across two correlated graphs and lies at the core of many applications. When graph side information is not available, the node correspondence is estimated on the sole basis of network topologies. In this paper, we propose a novel criterion to measure the graph matching accuracy, structural inconsistency (SI), which is defined based on the network topological structure. Specifically, SI incorporates the heat diffusion wavelet to accommodate the multi-hop structure of the graphs. Based on SI, we propose a Structural Inconsistency reducing Graph Matching Algorithm (SIGMA), which improves the alignment scores of node pairs that have low SI values in each iteration. Under suitable assumptions, SIGMA can reduce SI values of true counterparts. Furthermore, we demonstrate that SIGMA can be derived by using a mirror descent method to solve the Gromov-Wasserstein distance with a novel K-hop-structure-based matching costs. Extensive experiments show that our method outperforms state-of-the-art methods.

cs.LG↗

arXiv2022

Hierarchical Visual Interface for Lecture Video Retrieval and Summarization

With the emergence of large-scale open online courses and online academic conferences, it has become increasingly feasible and convenient to access online educational resources. However, it is time consuming and challenging to effectively retrieve and present numerous lecture videos for common users. In this work, we propose a hierarchical visual interface for retrieving and summarizing lecture videos. Users can utilize the proposed interface to effectively explore the required video information through the results of the video summary generation in different layers. We retrieve the input keywords with the corresponding video layer with timestamps, a frame layer with slides, and the poster layer with summarization of the lecture videos. We verified the proposed interface with our user study by comparing it with other conventional interfaces. The results from our user study confirmed that the proposed interface can achieve high retrieval accuracy and good user experience.see video here https://www.youtube.com/watch?v=zrnejwsOVpc .

cs.HC↗

arXiv2022

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- VIII. A search for hot cores by using C$_2$H$_5$CN, CH$_3$OCHO and CH$_3$OH lines

Hot cores characterized by rich lines of complex organic molecules are considered as ideal sites for investigating the physical and chemical environments of massive star formation. We present a search for hot cores by using typical nitrogen- and oxygen-bearing complex organic molecules (C$_2$H$_5$CN, CH$_3$OCHO and CH$_3$OH), based on ALMA Three-millimeter Observations of Massive Star-forming regions (ATOMS). The angular resolutions and line sensitivities of the ALMA observations are better than 2 arcsec and 10 mJy/beam, respectively. A total of 60 hot cores are identified with 45 being newly detected, in which the complex organic molecules have high gas temperatures ($>$ 100 K) and small source sizes ($<$ 0.1 pc). So far this is the largest sample of hot cores observed with similar angular resolution and spectral coverage. The observations have also shown nitrogen and oxygen differentiation in both line emission and gas distribution in 29 hot cores. Column densities of CH$_3$OH and CH$_3$OCHO increase as rotation temperatures rise. The column density of CH$_3$OCHO correlates tightly with that of CH$_3$OH. The pathways for production of different species are discussed. Based on the spatial position difference between hot cores and UC~H{\sc ii} regions, we conclude that 24 hot cores are externally heated while the other hot cores are internally heated. The observations presented here will potentially help establish a hot core template for studying massive star formation and astrochemistry.

astro-ph.GA↗

arXiv2022

Improving the fusion of acoustic and text representations in RNN-T

The recurrent neural network transducer (RNN-T) has recently become the mainstream end-to-end approach for streaming automatic speech recognition (ASR). To estimate the output distributions over subword units, RNN-T uses a fully connected layer as the joint network to fuse the acoustic representations extracted using the acoustic encoder with the text representations obtained using the prediction network based on the previous subword units. In this paper, we propose to use gating, bilinear pooling, and a combination of them in the joint network to produce more expressive representations to feed into the output layer. A regularisation method is also proposed to enable better acoustic encoder training by reducing the gradients back-propagated into the prediction network at the beginning of RNN-T training. Experimental results on a multilingual ASR setting for voice search over nine languages show that the joint use of the proposed methods can result in 4%--5% relative word error rate reductions with only a few million extra parameters.

eess.AS↗

arXiv2022

Harnack inequality for the nonlocal equations with general growth

We consider a class of generalized nonlocal $p$-Laplacian equations. We find some proper structural conditions to establish a version of nonlocal Harnack inequalities of weak solutions to such nonlocal problems by using the expansion of positivity and energy estimates.

math.AP↗

arXiv2022

The boundedness and Hölder continuity of weak solutions to elliptic equations involving variable exponents and critical growth

In this paper we prove the boundedness and Hölder continuity of quasilinear elliptic problems involving variable exponents for a homogeneous Dirichlet and a nonhomogeneous Neumann boundary condition, respectively. The novelty of our work is the fact that we allow critical growth even on the boundary and so we close the gap in the papers of Fan-Zhao [Nonlinear Anal. 36 (1999), no. 3, 295--318.] and Winkert-Zacher [Discrete Contin. Dyn. Syst. Ser. S 5 (2012), no. 4, 865--878.] in which the critical cases are excluded. Our approach is based on a modified version of De Giorgi's iteration technique along with the localization method. As a consequence of our results, the $C^{1,α}$-regularity follows immediately.

math.AP↗

arXiv2022

Example-based Color Transfer with Gaussian Mixture Modeling

Color transfer, which plays a key role in image editing, has attracted noticeable attention recently. It has remained a challenge to date due to various issues such as time-consuming manual adjustments and prior segmentation issues. In this paper, we propose to model color transfer under a probability framework and cast it as a parameter estimation problem. In particular, we relate the transferred image with the example image under the Gaussian Mixture Model (GMM) and regard the transferred image color as the GMM centroids. We employ the Expectation-Maximization (EM) algorithm (E-step and M-step) for optimization. To better preserve gradient information, we introduce a Laplacian based regularization term to the objective function at the M-step which is solved by deriving a gradient descent algorithm. Given the input of a source image and an example image, our method is able to generate continuous color transfer results with increasing EM iterations. Various experiments show that our approach generally outperforms other competitive color transfer methods, both visually and quantitatively.

cs.CV↗

arXiv2021

A FAST Survey of HINSA in PGCCs Guided by HC3N

Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we search for HI narrow-line self-absorption (HINSA) features in twelve Planck Galactic cold clumps (PGCCs), one starless core L1521B and four star forming sources. Eight of the 12 PGCCs have emission of J=2-1 of cyanoacetylene (HC3N). With an improved HINSA extraction method more robust for weaker and blended features with high velocity resolution, the detection rates of HINSA in PGCCCs are high, at 92% overall (11/12) and 87% (7/8) among sources with HC3N J=2-1 emissions. Combining the data of molecular spectra and Planck continuum maps, we studied the morphologies, abundances and excitations of HI, CO and HC3N in PGCCs. The distribution of HINSA is similar to that of CO emission. HINSA tends to be not detected in regions associated with warm dust and background ionizing radiation, as well as regions associated with stellar objects. The abundances of HI in PGCCs are approximately 3E-4, and vary within a factor of ~3. The non-thermal velocity dispersions traced by C18O J=1-0 and HINSA are consistent with each other (0.1-0.4 km/s), larger than those of HC3N (~0.1 km/s). Carbon chain molecule abundant PGCCs provide a good sample to study HINSA.

astro-ph.GA↗

arXiv2021

From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs

Recent years have witnessed a flurry of research activity in graph matching, which aims at finding the correspondence of nodes across two graphs and lies at the heart of many artificial intelligence applications. However, matching heterogeneous graphs with partial overlap remains a challenging problem in real-world applications. This paper proposes the first practical learning-to-match method to meet this challenge. The proposed unsupervised method adopts a novel partial OT paradigm to learn a transport plan and node embeddings simultaneously. In a from-one-to-all manner, the entire learning procedure is decomposed into a series of easy-to-solve sub-procedures, each of which only handles the alignment of a single type of nodes. A mechanism for searching the transport mass is also proposed. Experimental results demonstrate that the proposed method outperforms state-of-the-art graph matching methods.

cs.LG↗

arXiv2021

Enhanced superconductivity with possible re-appearance of charge density wave states in polycrystalline Cu$_{1-x}$Ag$_x$Ir$_2$Te$_4$ alloys

In this study, we determined the effect of doping with the noble metal Ag on Ir$_2$Te$_4$ superconductors. Based on the resistivity, magnetization, and heat capacity, we explored the changes in the superconductivity and charge density wave for Cu$_{1-x}$Ag$_x$Ir$_2$Te$_4$ as a function of isoelectric substitution. We assessed a complete set of competing states from suppressed charge density wave in the low doping region to superconductor in the middle doping region and re-entrant charge density wave in the high doping region, thereby obtaining an electronic phase diagram, where the superconducting dome was near bipartite charge density wave regions with a maximum superconducting temperature Tc of about 2.93 K at an Ag doping level of 12%. The lower H$_{c1}$ and upper H$_{c2}$ critical magnetic fields were determined for some representative samples in the Cu$_{1-x}$Ag$_x$Ir$_2$Te$_4$ series based on magnetization and resistivity measurements, respectively. We showed that H$_{c1}$ decreased whereas H$_{c2}$ increased as the doping content increased. The specific heat anomalies at the superconducting transitions $ΔC_{el}/γT_c$ for representative samples comprising Cu$_{0.92}$Ag$_{0.08}$Ir$_2$Te$_4$, Cu$_{0.88}$Ag$_{0.12}$Ir$_2$Te$_4$, and Cu$_{0.85}$Ag$_{0.15}$Ir$_2$Te$_4$ were approximately 1.40, 1.44, and 1.42, respectively, which are all near the Bardeen-Cooper-Schrieffer value of 1.43 and they indicate bulk superconductivity in these compounds.

cond-mat.supr-con↗

arXiv2021

Adaptive smoothing mini-batch stochastic accelerated gradient method for nonsmooth convex stochastic composite optimization

This paper considers a class of convex constrained nonsmooth convex stochastic composite optimization problems whose objective function is given by the summation of a differentiable convex component, together with a general nonsmooth but convex component. The nonsmooth component is not required to have easily obtainable proximal operator, or have the max structure that the smoothing technique in [Nesterov, 2005] can be used. In order to solve such type problems, we propose an adaptive smoothing mini-batch stochastic accelerated gradient (AdaSMSAG) method, which combines the stochastic approximation method, the Nesterov's accelerated gradient method, and the smoothing methods that allow general smoothing approximations. Convergence of the method is established. Moreover, the order of the worst-case iteration complexity is better than that of the state-of-the-art stochastic approximation methods. Numerical results are provided to illustrate the efficiency of the proposed AdaSMSAG method for a risk management in portfolio optimization and a family of Wasserstein distributionally robust support vector machine problems with real data.

math.OC↗

arXiv2021

A refined consumer behavior model for energy systems: Application to the pricing and energy-efficiency problems

The sum-utility maximization problem is known to be important in the energy systems literature. The conventional assumption to address this problem is that the utility is concave. But for some key applications, such an assumption is not reasonable and does not reflect well the actual behavior of the consumer. To address this issue, the authors pose and address a more general optimization problem, namely by assuming the consumer's utility to be sigmoidal and in a given class of functions. The considered class of functions is very attractive for at least two reasons. First, the classical NP-hardness issue associated with sum-utility maximization is circumvented. Second, the considered class of functions encompasses well-known performance metrics used to analyze the problems of pricing and energy-efficiency. This allows one to design a new and optimal inclining block rates (IBR) pricing policy which also has the virtue of flattening the power consumption and reducing the peak power. We also show how to maximize the energy-efficiency by a low-complexity algorithm. When compared to existing policies, simulations fully support the benefit from using the proposed approach.

cs.GT↗

arXiv2021

DPVI: A Dynamic-Weight Particle-Based Variational Inference Framework

The recently developed Particle-based Variational Inference (ParVI) methods drive the empirical distribution of a set of \emph{fixed-weight} particles towards a given target distribution $π$ by iteratively updating particles' positions. However, the fixed weight restriction greatly confines the empirical distribution's approximation ability, especially when the particle number is limited. In this paper, we propose to dynamically adjust particles' weights according to a Fisher-Rao reaction flow. We develop a general Dynamic-weight Particle-based Variational Inference (DPVI) framework according to a novel continuous composite flow, which evolves the positions and weights of particles simultaneously. We show that the mean-field limit of our composite flow is actually a Wasserstein-Fisher-Rao gradient flow of certain dissimilarity functional $\mathcal{F}$, which leads to a faster decrease of $\mathcal{F}$ than the Wasserstein gradient flow underlying existing fixed-weight ParVIs. By using different finite-particle approximations in our general framework, we derive several efficient DPVI algorithms. The empirical results demonstrate the superiority of our derived DPVI algorithms over their fixed-weight counterparts.

cs.LG↗

arXiv2021

Phase transition and enhanced hardness of LaB4 under pressure

The crystalline structures of lanthanum tetraboride, LaB4, under pressure are investigated using a genetic algorithm method coupled with first-principles calculations. We find two low-enthalpy phases for LaB4 as the thermodynamic ground state up to 200 GPa: a phase previously observed in experiments (P4/mbm) and a novel orthorhombic phase (Pnma-I). The P4/mbm phase transforms to the Pnma-I phase at around 106 GPa, accompanied by breakage of the B-octahedron. The P4/mbm phase of LaB4 exhibits a high hardness (30.5 GPa) at ambient conditions, which is comparable to that of the hard material B4C. The hardness of the two low-enthalpy phases increases with pressure. The electronic band structures shows that all of the competitive phases (two stable and two metastable phases) are metallic. Phonon calculations shows the P4/mbm and Pnma-I phases are thermodynamically stable in their respective pressure ranges. This elucidation of the phase transition behavior and hardness of LaB4 provides new knowledge on the interesting high-pressure behaviors of the rare-earth metal borides.

cond-mat.mtrl-sci↗