arXiv subjects

Liang Huang

Publications and source records attributed to Liang Huang.

126 records · Page 7Linked to original sources

arXiv2016

Relativistic Zitterbewegung in non-Hermitian photonic waveguide systems

Zitterbewegung (ZB) is a phenomenon in relativistic quantum systems where the electron wave packet exhibits a trembling or oscillating behavior during its motion, caused by its interaction or coupling with the negative energy state. To directly observe ZB in electronic systems is difficult, due to the challenges associated with the atomic scale wavelength of the electron. Photonic systems offer an alternative paradigm. We exploit the concept of pseudo parity-time (pseudo PT ) symmetry to study ZB in non-Hermitian quantum systems implemented as an experimentally feasible optical waveguide array. In particular, the non-Hermitian Hamiltonian is realized through evanescent coupling among the waveguides to form a one-dimensional lattice with periodic modulations in gain and loss along the guiding direction. As the modulation frequency is changed, we obtain a number of phenomena including periodically suppressed ZB trembling, spatial energy localization, and Hermitian-like ZB oscillations. We calculate phase diagrams indicating the emergence of different types of dynamical behaviors of the relativistic non-Hermitian quantum system in an experimentally justified parameter space. We provide numerical results and a physical analysis to explain the distinct dynamical behaviors revealed by the phase diagrams. Our findings provide a deeper understanding of both the relativistic ZB phenomenon and non-Hermitian pseudo-PT systems, with potential applications in controlling/harnessing light propagation in waveguide-based optical systems.

quant-ph↗

arXiv2016

Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles

Parsing accuracy using efficient greedy transition systems has improved dramatically in recent years thanks to neural networks. Despite striking results in dependency parsing, however, neural models have not surpassed state-of-the-art approaches in constituency parsing. To remedy this, we introduce a new shift-reduce system whose stack contains merely sentence spans, represented by a bare minimum of LSTM features. We also design the first provably optimal dynamic oracle for constituency parsing, which runs in amortized O(1) time, compared to O(n^3) oracles for standard dependency parsing. Training with this oracle, we achieve the best F1 scores on both English and French of any parser that does not use reranking or external data.

cs.CL↗

arXiv2016

GOE statistics in graphene billiards with the shape of classically integrable billiards

A crucial result in quantum chaos, which has been established for a long time, is that the spectral properties of classically integrable systems generically are described by Poisson statistics whereas those of time-reversal symmetric, classically chaotic systems coincide with those of random matrices from the Gaussian orthogonal ensemble (GOE). Does this result hold for two-dimensional Dirac material systems? To address this fundamen- tal question, we investigate the spectral properties in a representative class of graphene billiards with shapes of classically integrable circular-sector billiards. Naively one may expect to observe Poisson statistics, which is indeed true for energies close to the band edges where the quasiparticle obeys the Schrödinger equation. However, for energies near the Dirac point, where the quasiparticles behave like massless Dirac fermions, Pois- son statistics is extremely rare in the sense that it emerges only under quite strict symmetry constraints on the straight boundary parts of the sector. An arbitrarily small amount of imperfection of the boundary results in GOE statistics. This implies that, for circular sector confinements with arbitrary angle, the spectral properties will generically be GOE. These results are corroborated by extensive numerical computation. Furthermore, we provide a physical understanding for our results.

quant-ph↗

arXiv2016

Incremental Parsing with Minimal Features Using Bi-Directional LSTM

Recently, neural network approaches for parsing have largely automated the combination of individual features, but still rely on (often a larger number of) atomic features created from human linguistic intuition, and potentially omitting important global context. To further reduce feature engineering to the bare minimum, we use bi-directional LSTM sentence representations to model a parser state with only three sentence positions, which automatically identifies important aspects of the entire sentence. This model achieves state-of-the-art results among greedy dependency parsers for English. We also introduce a novel transition system for constituency parsing which does not require binarization, and together with the above architecture, achieves state-of-the-art results among greedy parsers for both English and Chinese.

cs.CL↗

arXiv2016

2.4GHZ Class AB power Amplifier For Healthcare Application

The objective of this research was to design a 2.4 GHz class AB Power Amplifier, with 0.18 um SMIC CMOS technology by using Cadence software, for health care applications. The ultimate goal for such application is to minimize the trade-offs between performance and cost, and between performance and low power consumption design. The performance of the power amplifier meets the specification requirements of the desired.

cs.OH↗

arXiv2015

Dependency-based Convolutional Neural Networks for Sentence Embedding

In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies. To exploit both deep learning and linguistic structures, we propose a tree-based convolutional neural network model which exploit various long-distance relationships between words. Our model improves the sequential baselines on all three sentiment and question classification tasks, and achieves the highest published accuracy on TREC.

cs.CL↗

arXiv2015

Opinion percolation in structured population

In a recent work [Shao $et$ $al$ 2009 Phys. Rev. Lett. \textbf{108} 018701], a nonconsensus opinion (NCO) model was proposed, where two opinions can stably coexist by forming clusters of agents holding the same opinion. The NCO model on lattices and several complex networks displays a phase transition behavior, which is characterized by a large spanning cluster of nodes holding the same opinion appears when the initial fraction of nodes holding this opinion is above a certain critical value. In the NCO model, each agent will convert to its opposite opinion if there are more than half of agents holding the opposite opinion in its neighborhood. In this paper, we generalize the NCO model by assuming that each agent will change its opinion if the fraction of agents holding the opposite opinion in its neighborhood exceeds a threshold $T$ ($T\geq 0.5$). We call this generalized model as the NCOT model. We apply the NCOT model on different network structures and study the formation of opinion clusters. We find that the NCOT model on lattices displays a continuous phase transition. For random graphs and scale-free networks, the NCOT model shows a discontinuous phase transition when the threshold is small and the average degree of the network is large, while in other cases the NCOT model displays a continuous phase transition.

physics.soc-ph↗

arXiv2015

Promoting collective motion of self-propelled agents by distance-based influence

We propose a dynamic model for a system consisting of self-propelled agents in which the influence of an agent on another agent is weighted by geographical distance. A parameter $α$ is introduced to adjust the influence: the smaller value of $α$ means that the closer neighbors have stronger influence on the moving direction. We find that there exists an optimal value of $α$, leading to the highest degree of direction consensus. The value of optimal $α$ increases as the system size increases, while it decreases as the absolute velocity, the sensing radius and the noise amplitude increase.

physics.soc-ph↗

arXiv2014

Type-Driven Incremental Semantic Parsing with Polymorphism

Semantic parsing has made significant progress, but most current semantic parsers are extremely slow (CKY-based) and rather primitive in representation. We introduce three new techniques to tackle these problems. First, we design the first linear-time incremental shift-reduce-style semantic parsing algorithm which is more efficient than conventional cubic-time bottom-up semantic parsers. Second, our parser, being type-driven instead of syntax-driven, uses type-checking to decide the direction of reduction, which eliminates the need for a syntactic grammar such as CCG. Third, to fully exploit the power of type-driven semantic parsing beyond simple types (such as entities and truth values), we borrow from programming language theory the concepts of subtype polymorphism and parametric polymorphism to enrich the type system in order to better guide the parsing. Our system learns very accurate parses in GeoQuery, Jobs and Atis domains.

cs.CL↗

arXiv2014

Magnetoelectric surface acoustic wave resonator with ultrahigh magnetic field sensitivity

A magnetoelectric surface acoustic wave (MESAW) type device based on piezoelectric/magnetostrictive heterostructure was proposed to use as weak magnetic field sensor. Unlike conventional magnetoelectric bulk laminates or film stacks collecting magnetic field induced electrical charge, the MESAW detects the shift of the center frequency, which highly depends on the magnetic field due to the giant delta E effect and the phase velocity dispersion. The magnetic field sensitivity can reach 10^(-11) Tesla in consideration of 100 Hz frequency accuracy. Additionally, the unique working mechanism of MESAW allows a broadband detection of weak magnetic field even with no bias magnetic field.

cond-mat.mtrl-sci↗

arXiv2013

Controlling collective dynamics in complex, minority-game resource-allocation systems

Resource allocation takes place in various kinds of real-world complex systems, such as the traffic systems, social services institutions or organizations, or even the ecosystems. The fundamental principle underlying complex resource-allocation dynamics is Boolean interactions associated with minority games, as resources are generally limited and agents tend to choose the least used resource based on available information. A common but harmful dynamical behavior in resource-allocation systems is herding, where there are time intervals during which a large majority of the agents compete for a few resources, leaving many other resources unused. Ac- companying the herd behavior is thus strong fluctuations with time in the number of resources being used. In this paper, we articulate and establish that an intuitive control strategy, namely pinning control, is effective at harnessing the herding dynamics. In particular, by fixing the choices of resources for a few agents while leaving majority of the agents free, herding can be eliminated completely. Our investigation is systematic in that we consider random and targeted pinning and a variety of network topologies, and we carry out a comprehensive analysis in the framework of mean-field theory to understand the working of control. The basic philosophy is then that, when a few agents waive their freedom to choose resources by receiving sufficient incentives, majority of the agents benefit in that they will make fair, efficient, and effective use of the available resources. Our work represents a basic and general framework to address the fundamental issue of fluctuations in complex dynamical systems with significant applications to social, economical and political systems.

physics.soc-ph↗

arXiv2013

Hidden symmetry and Collective behavior

We study the relationship between the partially synchronous state and the coupling structure in general dynamical systems. Our results show that, on the contrary to the widely accepted concept, topological symmetry in a coupling structure is the sufficient condition but not the necessary condition. Furthermore, we find the necessary and sufficient condition for the existence of the partial synchronization and develop a method to obtain all of the existing partially synchronous solutions for all nonspecific dynamics from a very large number of possible candidates.

nlin.PS↗

arXiv2012

Emergence of grouping in multi-resource minority game dynamics

TheMinority Game (MG) has become a paradigm to probe complex social and economical phenomena where adaptive agents compete for a limited resource, and it finds applications in statistical and nonlinear physics as well. In the traditional MG model, agents are assumed to have access to global information about the past history of the underlying system, and they react by choosing one of the two available options associated with a single resource. Complex systems arising in a modern society, however, can possess many resources so that the number of available strategies/resources can be multiple. We propose a class of models to investigate MG dynamics with multiple strategies. In particular, in such a system, at any time an agent can either choose a minority strategy (say with probability p) based on available local information or simply choose a strategy randomly (with probability 1 - p). The parameter p thus defines the minority-preference probability, which is key to the dynamics of the underlying system. A striking finding is the emergence of strategy-grouping states where a particular number of agents choose a particular subset of strategies. We develop an analytic theory based on the mean-field framework to understand the "bifurcation" to the grouping states and their evolution. The grouping phenomenon has also been revealed in a real-world example of the subsystem of 27 stocks in the Shanghai Stock Market's Steel Plate. Our work demonstrates that complex systems following the MG rules can spontaneously self-organize themselves into certain divided states, and our model represents a basic mathematical framework to address this kind of phenomena in social, economical, and even political systems.

nlin.AO↗

arXiv2007

Optimization of synchronization in gradient clustered networks

We consider complex clustered networks with a gradient structure, where sizes of the clusters are distributed unevenly. Such networks describe more closely actual networks in biophysical systems and in technological applications than previous models. Theoretical analysis predicts that the network synchronizability can be optimized by the strength of the gradient field but only when the gradient field points from large to small clusters. A remarkable finding is that, if the gradient field is sufficiently strong, synchronizability of the network is mainly determined by the properties of the subnetworks in the two largest clusters. These results are verified by numerical eigenvalue analysis and by direct simulation of synchronization dynamics on coupled-oscillator networks.

nlin.CD↗

arXiv2007

Enhancing Robustness and Immunization in geographical networks

We find that different geographical structures of networks lead to varied percolation thresholds, although these networks may have similar abstract topological structures. Thus, the strategies for enhancing robustness and immunization of a geographical network are proposed. Using the generating function formalism, we obtain the explicit form of the percolation threshold $q_{c}$ for networks containing arbitrary order cycles. For 3-cycles, the dependence of $q_c$ on the clustering coefficients is ascertained. The analysis substantiates the validity of the strategies with an analytical evidence.

physics.soc-ph↗

arXiv2007

Range-based attacks on links in random scale-free networks

$Range$ and $load$ play keys on the problem of attacking on links in random scale-free (RSF) networks. In this Brief Report we obtain the relation between $range$ and $load$ in RSF networks analytically by the generating function theory, and then give an estimation about the impact of attacks on the $efficiency$ of the network. The analytical results show that short range attacks are more destructive for RSF networks, and are confirmed numerically. Further our results are consistent with the former literature (Physical Review E \textbf{66}, 065103(R) (2002)).

cond-mat.stat-mech↗

arXiv2005

Interdependence of dynamical signals and topology: Detecting the influential nodes in networks

By studying varies dynamical processes, including coupled maps, cellular automata and coupled differential equations, on five different kinds of known networks, we found a positive relation between signal correlation and node's degree. Thus a method of identifying influential nodes in dynamical systems is proposed, its validity is studied, and potential applications on real systems are discussed.

cond-mat.stat-mech↗

arXiv2005

Geographical effects on cascading breakdowns of scale-free networks

Cascading breakdowns of real networks are severe accidents in recent years, such as the blackouts of the power transportation networks in North America. In this paper, we study the effects of geographical structure on the cascading phenomena of load-carried scale-free networks, find that more geographically constrained networks tend to have larger cascading breakdowns. Explanations by the effects of circles and large betweenness of small degree nodes are provided.

physics.soc-ph↗