arXiv subjects

Bin Cheng

Publications and source records attributed to Bin Cheng.

At least 91 records · Page 5Linked to original sources

arXiv2020

Event-Triggered Consensus of Homogeneous and Heterogeneous Multi-Agent Systems with Jointly Connected Switching Topologies

This paper investigates the distributed event-based consensus problem of switching networks satisfying the jointly connected condition. Both the state consensus of homogeneous linear networks and output consensus of heterogeneous networks are studied. Two kinds of event-based protocols based on local sampled information are designed, without the need to solve any matrix equation or inequality. Theoretical analysis indicates that the proposed event-based protocols guarantee the achievement of consensus and the exclusion of Zeno behaviors for jointly connected undirected switching graphs. These protocols, relying on no global knowledge of the network topology and independent of switching rules, can be devised and utilized in a completely distributed manner. They are able to avoid continuous information exchanges for either controllers' updating or triggering functions' monitoring, which ensures the feasibility of the presented protocols.

eess.SY↗

arXiv2020

Butterfly-like anisotropic magnetoresistance and angle-dependent Berry phase in Type-II Weyl semimetal WP2

Weyl semimetal emerges as a new topologically nontrivial phase of matter, hosting low-energy excitations of massless Weyl fermions. Here, we present a comprehensive study of the type-II Weyl semimetal WP2. Transport studies show a butterfly-like magnetoresistance at low temperature, reflecting the anisotropy of the electron Fermi surfaces. The four-lobed feature gradually evolves into a two-lobed one upon increasing temperature, mainly due to the reduced relative contribution of electron Fermi surfaces compared to hole Fermi surfaces for the magnetoresistance. Moreover, angle-dependent Berry phase is further discovered from the quantum oscillations, which is ascribed to the effective manipulation of the extremal Fermi orbits by the magnetic field to feel the nearby topological singularities in the momentum space. The revealed topological characters and anisotropic Fermi surfaces of WP2 substantially enrich the physical properties of Weyl semimetals and hold great promises in topological electronic and Fermitronic device applications.

cond-mat.mtrl-sci↗

arXiv2020

$S^3$Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data

Solving depth estimation with monocular cameras enables the possibility of widespread use of cameras as low-cost depth estimation sensors in applications such as autonomous driving and robotics. However, learning such a scalable depth estimation model would require a lot of labeled data which is expensive to collect. There are two popular existing approaches which do not require annotated depth maps: (i) using labeled synthetic and unlabeled real data in an adversarial framework to predict more accurate depth, and (ii) unsupervised models which exploit geometric structure across space and time in monocular video frames. Ideally, we would like to leverage features provided by both approaches as they complement each other; however, existing methods do not adequately exploit these additive benefits. We present $S^3$Net, a self-supervised framework which combines these complementary features: we use synthetic and real-world images for training while exploiting geometric, temporal, as well as semantic constraints. Our novel consolidated architecture provides a new state-of-the-art in self-supervised depth estimation using monocular videos. We present a unique way to train this self-supervised framework, and achieve (i) more than $15\%$ improvement over previous synthetic supervised approaches that use domain adaptation and (ii) more than $10\%$ improvement over previous self-supervised approaches which exploit geometric constraints from the real data.

cs.CV↗

arXiv2020

Interior Estimates for Monge-Ampère Equation in Terms of Modulus of Continuity

We investigate the Monge-Ampère equation subject to zero boundary value and with a positive right-hand side unction assumed to be continuous or essentially bounded. Interior estimates of the solution's first and second derivatives are obtained in terms of moduli of continuity. We explicate how the estimates depend on various quantities but have them independent of the solution's modulus of convexity. Our main theorem has many useful consequences. One of them is the nonlinear dependence between the Hölder seminorms of the solution and of the right-side function, which confirms the results of Figalli, Jhaveri and Mooney (J. Func. Anal. 2016). Our technique is in part inspired by Jian and Wang (SIAM J. Math. Anal. 2007) which includes using a sequence of so-called sections.

math.AP↗

arXiv2020

A Standard-based Open Source IoT Platform: FIWARE

The ever-increasing acceleration of technology evolution in all fields is rapidly changing the architectures of data-driven systems towards the Internet-of-Things concept. Many general and specific-purpose IoT platforms are already available. This article introduces the capabilities of the FIWARE framework that is transitioning from a research to a commercial level. We base our exposition on the analysis of three real-world use cases (global IoT market, analytics in smart cities, and IoT augmented autonomous driving) and their requirements that are addressed with the usage of FIWARE. We highlight the lessons learnt during the design, implementation and deployment phases for each of the use cases and their critical issues. Finally we give two examples showing that FIWARE still maintains openness to innovation: semantics and privacy.

cs.NI↗

arXiv2020

Convergence Rate Estimates for the Low Mach and Alfvén Number Three-Scale Singular Limit of Compressible Ideal Magnetohydrodynamics

Convergence rate estimates are obtained for singular limits of the compressible ideal magnetohydrodynamics equations, in which the Mach and Alfvén numbers tend to zero at different rates. The proofs use a detailed analysis of exact and approximate fast, intermediate, and slow modes together with improved estimates for the solutions and their time derivatives, and the time-integration method. When the small parameters are related by a power law the convergence rates are positive powers of the Mach number, with the power varying depending on the component and the norm. Exceptionally, the convergence rate for two components involve the ratio of the two parameters, and that rate is proven to be sharp via corrector terms. Moreover, the convergence rates for the case of a power-law relation between the small parameters tend to the two-scale convergence rate as the power tends to one. These results demonstrate that the issue of convergence rates for three-scale singular limits, which was not addressed in the authors' previous paper, is much more complicated than for the classical two-scale singular limits.

math.AP↗

arXiv2020

Personalized Policy Learning using Longitudinal Mobile Health Data

We address the personalized policy learning problem using longitudinal mobile health application usage data. Personalized policy represents a paradigm shift from developing a single policy that may prescribe personalized decisions by tailoring. Specifically, we aim to develop the best policy, one per user, based on estimating random effects under generalized linear mixed model. With many random effects, we consider new estimation method and penalized objective to circumvent high-dimension integrals for marginal likelihood approximation. We establish consistency and optimality of our method with endogenous app usage. We apply our method to develop personalized push ("prompt") schedules in 294 app users, with a goal to maximize the prompt response rate given past app usage and other contextual factors. We found the best push schedule given the same covariates varied among the users, thus calling for personalized policies. Using the estimated personalized policies would have achieved a mean prompt response rate of 23% in these users at 16 weeks or later: this is a remarkable improvement on the observed rate (11%), while the literature suggests 3%-15% user engagement at 3 months after download. The proposed method compares favorably to existing estimation methods including using the R function "glmer" in a simulation study.

stat.ME↗

arXiv2019

Van der Waals heterostructures for high-performance device applications: challenges and opportunities

Discovery of two-dimensional materials with unique electronic, superior optoelectronic or intrinsic magnetic order have triggered worldwide interests among the fields of material science, condensed matter physics and device physics. Vertically stacking of two-dimensional materials with distinct electronic and optical as well as magnetic properties enables to create a large variety of van der Waals heterostructures. The diverse properties of the vertical heterostructures open up unprecedented opportunities for various kinds of device applications, e.g. vertical field effect transistors, ultrasensitive infrared photodetectors, spin-filtering devices and so on, which are inaccessible in the conventional material heterostructures. Here, we review the current status of vertical heterostructures device applications in vertical transistors, infrared photodetectors and spintronic memory/transistors. The relevant challenges for achieving high-performance devices are presented. We also provide outlook on future development of vertical heterostructure devices with integrated electronic and optoelectronic as well as spintronic functinalities.

physics.app-ph↗

arXiv2019

An Interior A Priori Estimate for Solutions to Monge-Ampère Equations with Right-Hand Side Close to One

We consider Monge-Ampére equations with the right hand side function close to a constant and from a function class that is larger than any Hölder class and smaller than the Dini-continuous class. We establish an upper bound for the modulus of continuity of the solution's second derivatives. This bound depends exponentially on a quantity similar to but larger than the Dini semi-norm. We establish explicit control on the shape of the sequence of shrinking sections, hence revealing the nature of such exponential dependence.

math.AP↗

arXiv2019

A simulation study of methods for handling disease progression in dose-finding clinical trials

In traditional dose-finding studies, dose-limiting toxicity (DLT) is determined within a fixed time observation window where DLT is often defined as a binary outcome. In the setting of oncology dose-finding trials, often patients in advanced stage of diseases are enrolled. Therefore, disease progression may occur within the DLT observation window leading to treatment discontinuation and rendering the patient unevaluable for DLT assessment. As a result, additional patients have to be enrolled, increasing the sample size. We propose and compare several practical methods for handling disease progression which occurs within the DLT observation window, in the context of the time-to-event continual reassessment method (TITE-CRM) which allows using partial observations. The methods differ on the way they define an evaluable patient and in the way incomplete observations are included. The methods are illustrated and contrasted in the context of a single simulated trial, and compared via simulations under various scenarios of dose-progression relationship, in the setting of advanced soft-tissue sarcoma.

stat.AP↗

arXiv2019

Speedup in Classical Simulation of Gaussian Boson Sampling

Gaussian boson sampling is a promising model for demonstrating quantum computational supremacy, which eases the experimental challenge of the standard boson-sampling proposal. Here by analyzing the computational costs of classical simulation of Gaussian boson sampling,we establish a lower bound for achieving quantum computational supremacy for a class of Gaussian boson-sampling problems, where squeezed states are injected into every input mode. Specifically, we propose a method for simplifying the brute-force calculations for the transition probabilities in Gaussian boson sampling, leading to a significant reduction of the simulation costs. Particularly, our numerical results indicate that we can simulate 18 photons Gaussian boson sampling at the output subspace on a normal laptop, 20 photons on a commercial workstation with 256 cores, and suggest about 30 photons for supercomputers. These numbers are significantly smaller than those in standard boson sampling, suggesting Gaussian boson sampling may be more feasible for demonstrating quantum computational supremacy.

quant-ph↗

arXiv2019

Shallow water equations on a fast rotating surface

We prove that for rotating shallow water equations on a surface of revolution with variable Coriolis parameter and vanishing Rossby and Froude numbers, the classical solution satisfies uniform estimates on a fixed time interval with no dependence on the small parameters. Upon a transformation using the solution operator associated with the large operator, the solution converges strongly to a limit for which the governing equation is given. We also characterize the kernel of the large operator and define a projection onto that kernel. With these tools, we are able to show that the time-averages of the solution are close to longitude-independent zonal flows and height field.

math.AP↗

arXiv2019

Fog Function: Serverless Fog Computing for Data Intensive IoT Services

Fog computing can support IoT services with fast response time and low bandwidth usage by moving computation from the cloud to edge devices. However, existing fog computing frameworks have limited flexibility to support dynamic service composition with a data-oriented approach. Function-as-a-Service (FaaS) is a promising programming model for fog computing to enhance flexibility, but the current event- or topic-based design of function triggering and the separation of data management and function execution result in inefficiency for data-intensive IoT services. To achieve both flexibility and efficiency, we propose a data-centric programming model called Fog Function and also introduce its underlying orchestration mechanism that leverages three types of contexts: data context, system context, and usage context. Moreover, we showcase a concrete use case for smart parking where Fog Function allows service developers to easily model their service logic with reduced learning efforts compared to a static service topology. Our performance evaluation results show that the Fog Function can be scaled to hundreds of fog nodes. Fog Function can improve system efficiency by saving 95% of the internal data traffic over cloud function and it can reduce service latency by 30% over edge function.

cs.DC↗

arXiv2019

Ubiquitous Complexity of Entanglement Spectra

In recent years, the entanglement spectra of quantum states have been identified to be highly valuable for improving our understanding on many problems in quantum physics, such as classification of topological phases, symmetry-breaking phases, and eigenstate thermalization, etc. However, it remains a major challenge to fully characterize the entanglement spectrum of a given quantum state. An outstanding problem is whether the difficulty is intrinsically technical or fundamental? Here using the tools in computational complexity, we perform a rigorous analysis to pin down the counting complexity of entanglement spectra of (i) states generated by polynomial-time quantum circuits, (ii) ground states of gapped 5-local Hamiltonians, and (iii) projected entangled-pair states (PEPS). We prove that despite the state complexity, the problems of counting the number of sizable elements in the entanglement spectra all belong to the class $\mathsf{\# P}$-complete, which is as hard as calculating the partition functions of Ising models. Our result suggests that the absence of an efficient method for solving the problem is fundamental in nature, from the point of view of computational complexity theory.

quant-ph↗

arXiv2019

Experimental Cryptographic Verification for Near-Term Quantum Cloud Computing

Recently, there are more and more organizations offering quantum-cloud services, where any client can access a quantum computer remotely through the internet. In the near future, these cloud servers may claim to offer quantum computing power out of reach of classical devices. An important task is to make sure that there is a real quantum computer running, instead of a simulation by a classical device. Here we explore the applicability of a cryptographic verification scheme that avoids the need of implementing a full quantum algorithm or requiring the clients to communicate with quantum resources. In this scheme, the client encodes a secret string in a scrambled IQP (instantaneous quantum polynomial) circuit sent to the quantum cloud in the form of classical message, and verify the computation by checking the probability bias of a class of output strings generated by the server. We provided a theoretical extension and implemented the scheme on a 5-qubit NMR quantum processor in the laboratory and a 5-qubit and 16-qubit processors of the IBM quantum cloud. We found that the experimental results of the NMR processor can be verified by the scheme with about $2.5\%$ error, after noise compensation by standard techniques. However, the fidelity of the IBM quantum cloud is currently too low to pass the test (about $42\%$ error). This verification scheme shall become practical when servers claim to offer quantum-computing resources that can achieve quantum supremacy.

quant-ph↗

arXiv2019

Direct evidence for charge compensation induced large magnetoresistance in thin WTe2

Since the discovery of extremely large non-saturating magnetoresistance (MR) in WTe2, much effort has been devoted to understanding the underlying mechanism, which is still under debate. Here, we explicitly identify the dominant physical origin of the large non-saturating MR through in-situ tuning of the magneto-transport properties in thin WTe2 film. With an electrostatic doping approach, we observed a non-monotonic gate dependence of the MR. The MR reaches a maximum (10600%) in thin WTe2 film at certain gate voltage where electron and hole concentrations are balanced, indicating that the charge compensation is the dominant mechanism of the observed large MR. Besides, we show that the temperature dependent magnetoresistance exhibits similar tendency with the carrier mobility when the charge compensation is retained, revealing that distinct scattering mechanisms may be at play for the temperature dependence of magneto-transport properties. Our work would be helpful for understanding mechanism of the large MR in other nonmagnetic materials and offers an avenue for achieving large MR in the non-magnetic materials with electron-hole pockets.

cond-mat.mes-hall↗

arXiv2019

Modulation of magnetism via electric field in MgO nanoribbons

We report on a theoretical study of electromagnetic properties of zigzag magnesium oxides nanoribbons (Z-MgONRs). We propose that the polar charges and the spin polarization are the two key factors for edge magnetism. Based on first-principle calculations, we demonstrate that both O- and Mg-edges are magnetic and their magnetic moments all can be efficiently modulated via external electric field.And the edge magnetism is further studied in the framework of effective tight-binding model, which provides a starting point for the calculation of one particle Green's function and the determination of exchange interactions. Utilizing the linear response model, we find that Z-MgONRs exhibit two kinds of exchange interaction with extremely different natures. The magnetism in O-edge is strongly localized with ferromagnetic order while the magnetism in Mg-edge is itinerant with Ruderman-Kittel-Kasuya-Yosida (RKKY) like interactions. And these two couplings can also be modulated by electric field, giving rise to the electrical modulations of spin-density-wave (SDW) and the modulation of Curie temperature in O-edge. All these suggest that Z-MgONRs are ideal platforms for ME coupling and appealing candidates for manifold applications.

cond-mat.mes-hall↗

arXiv2019

Three-Scale Singular Limits of Evolutionary PDEs

Singular limits of a class of evolutionary systems of partial differential equations having two small parameters and hence three time scales are considered. Under appropriate conditions solutions are shown to exist and remain uniformly bounded for a fixed time as the two parameters tend to zero at different rates. A simple example shows the necessity of those conditions in order for uniform bounds to hold. Under further conditions the solutions of the original system tend to solutions of a limit equation as the parameters tend to zero.

math.AP↗