arXiv subjects

Kun Zhao

Publications and source records attributed to Kun Zhao.

121 records · Page 7Linked to original sources

arXiv2014

Optimal Lévy-flight foraging in a finite landscape

We present a simple model to study Lévy-flight foraging in a finite landscape with countable targets. In our approach, foraging is a step-based exploratory random search process with a power-law step-size distribution $P(l) \propto l^{-μ}$. We find that, when the termination is regulated by a finite number of steps $N$, the optimum value of $μ$ that maximises the foraging efficiency can vary substantially in the interval $μ\in (1,3)$, depending on the landscape features (landscape size and number of targets). We further demonstrate that subjective returning can be another significant factor that affects the foraging efficiency in such context. Our results suggest that Lévy-flight foraging may arise through an interaction between the environmental context and the termination of exploitation, and particularly that the number of steps can play an important role in this scenario which is overlooked by most previous work. Our study not only provides a new perspective on Lévy-flight foraging, but also opens new avenues for investigating the interaction between foraging dynamics and environment as well as offers a realistic framework for analysing animal movement patterns from empirical data.

cond-mat.stat-mech↗

arXiv2014

Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

cs.CV↗

arXiv2013

Broadband Isolated Attosecond Pulses: Generation, Characterization, and Applications

The generation of the shortest isolated attosecond pulses requires both broad spectral bandwidth and control of the spectral phase. Rapid progress has been made in both aspects, leading to the generation of the world-record-shortest 67 as light pulses in 2012, and broadband attosecond continua covering a wide range of extreme ultraviolet and soft x-ray wavelengths. Such pulses have been successfully applied in photoelectron/photoion spectroscopy and the recently developed attosecond transient absorption spectroscopy to study electron dynamics in matter. In this Review, we discuss the significant recent advancement in the generation, characterization, and application of ultrabroadband isolated attosecond pulses with spectral bandwidth comparable to the central frequency, which can in principle be compressed to a single optical cycle.

physics.optics↗

arXiv2013

Fully gapped topological surface states in Bi$_2$Se$_3$ films induced by a d-wave high-temperature superconductor

Topological insulators are a new class of materials, that exhibit robust gapless surface states protected by time-reversal symmetry. The interplay between such symmetry-protected topological surface states and symmetry-broken states (e.g. superconductivity) provides a platform for exploring novel quantum phenomena and new functionalities, such as 1D chiral or helical gapless Majorana fermions, and Majorana zero modes which may find application in fault-tolerant quantum computation. Inducing superconductivity on topological surface states is a prerequisite for their experimental realization. Here by growing high quality topological insulator Bi$_2$Se$_3$ films on a d-wave superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ using molecular beam epitaxy, we are able to induce high temperature superconductivity on the surface states of Bi$_2$Se$_3$ films with a large pairing gap up to 15 meV. Interestingly, distinct from the d-wave pairing of Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$, the proximity-induced gap on the surface states is nearly isotropic and consistent with predominant s-wave pairing as revealed by angle-resolved photoemission spectroscopy. Our work could provide a critical step toward the realization of the long sought-after Majorana zero modes.

cond-mat.supr-con↗

arXiv2013

Communicating Is Crowdsourcing: Wi-Fi Indoor Localization with CSI-based Speed Estimation

Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location based service, and Wi-Fi fingerprint-based approaches are the most popular and inexpensive solutions. Among them, one of the main trends is to incorporate the built-in sensors of smartphone and to exploit crowdsourcing potentials. However the noisy built-in sensors and multi-tasking limitation of underline OS often hinder the effectiveness of these schemes. In this work, we propose a passive crowdsourcing CSI-based indoor localization scheme, C2 IL. Our scheme C2 IL only requires the locating-device (e.g., a phone) to have a 802.11n wireless connection, and it does not rely on inertial sensors only existing in some smartphones. C2 IL is built upon our innovative method to accurately estimate the moving distance purely based on 802.11n Channel State Information (CSI). Our extensive evaluations show that the moving distance estimation error of our scheme is within 3% of the actual moving distance regardless of varying speeds and environment. Relying on the accurate moving distance estimation as constraints, we are able to construct a more accurate mapping between RSS fingerprints and location. To address the challenges of collecting fingerprints, a crowdsourcing- based scheme is designed to gradually establish the mapping and populate the fingerprints. In C2 IL, we design a trajectory clustering-based localization algorithm to provide precise real-time indoor localization and tracking. We developed and deployed a practical working system of C2 IL in a large office environment. Extensive evaluation results indicate that our scheme C2 IL provides accurate localization with error 2m at 80% at very complex indoor environment with minimal overhead.

cs.NI↗

arXiv2013

Models, Entropy and Information of Temporal Social Networks

Temporal social networks are characterized by {heterogeneous} duration of contacts, which can either follow a power-law distribution, such as in face-to-face interactions, or a Weibull distribution, such as in mobile-phone communication. Here we model the dynamics of face-to-face interaction and mobile phone communication by a reinforcement dynamics, which explains the data observed in these different types of social interactions. We quantify the information encoded in the dynamics of these networks by the entropy of temporal networks. Finally, we show evidence that human dynamics is able to modulate the information present in social network dynamics when it follows circadian rhythms and when it is interfacing with a new technology such as the mobile-phone communication technology.

physics.soc-ph↗

arXiv2013

Percolation on interdependent networks with a fraction of antagonistic interactions

Recently, the percolation transition has been characterized on interacting networks both in presence of interdependent and antagonistic interactions. Here we characterize the phase diagram of the percolation transition in two Poisson interdependent networks with a percentage q of antagonistic nodes. We show that this system can present a bistability of the steady state solutions, and both first, and second order phase transitions. In particular, we observe a bistability of the solutions in some regions of the phase space also for a small fraction of antagonistic interactions 0 q_c=2/3 of antagonistic interactions is necessary to strongly reduce the region in phase-space in which both networks are percolating. This last result suggests that interdependent networks are robust to the presence of antagonistic interactions. Our approach can be extended to multiple networks, and to complex boolean rules for regulating the percolation phase transition.

cond-mat.dis-nn↗

arXiv2013

Percolation on interacting, antagonistic networks

Recently, new results on percolation of interdependent networks have shown that the percolation transition can be first order. In this paper we show that, when considering antagonistic interactions between interacting networks, the percolation process might present a bistability of the equilibrium solution. To this end, we introduce antagonistic interactions for which the functionality, or activity, of a node in a network is incompatible with the functionality, of the linked nodes in the other interacting networks. In particular, we study the percolation transition in two interacting networks with purely antagonistic interaction and different topology. For two antagonistic Poisson networks of different average degree we found a large region in the phase diagram in which there is a bistability of the steady state solutions of the percolation process, i.e. we can find that either one of the two networks might percolate. For two antagonistic scale-free networks we found that there is a region in the phase diagram in which, despite the antagonistic interactions, both networks are percolating. Finally we characterize the rich phase diagram of the percolation problems on two antagonistic networks, the first one of the two being a Poisson network and the second one being a scale-free network.

physics.soc-ph↗

arXiv2013

Connect and win: The role of social networks in political elections

Many networks do not live in isolation but are strongly interacting, with profound consequences on their dynamics. Here, we consider the case of two interacting social networks and, in the context of a simple model, we address the case of political elections. Each network represents a competing party and every agent on the election day can choose to be either active in one of the two networks (vote for the corresponding party) or to be inactive in both (not vote). The opinion dynamics during the election campaign is described through a simulated annealing algorithm. We find that for a large region of the parameter space the result of the competition between the two parties allows for the existence of pluralism in the society, where both parties have a finite share of the votes. The central result is that a densely connected social network is key for the final victory of a party. However, small committed minorities can play a crucial role, and even reverse the election outcome.

physics.soc-ph↗

arXiv2012

Analysis of a Mixture Model of Tumor Growth

We study an initial-boundary value problem (IBVP) for a coupled Cahn-Hilliard-Hele-Shaw system that models tumor growth. For large initial data with finite energy, we prove global (local resp.) existence, uniqueness, higher order spatial regularity and Gevrey spatial regularity of strong solutions to the IBVP in 2D (3D resp.). Asymptotically in time, we show that the solution converges to a constant state exponentially fast as time tends to infinity under certain assumptions.

math.AP↗

arXiv2012

Entropy of dynamical social networks

Human dynamical social networks encode information and are highly adaptive. To characterize the information encoded in the fast dynamics of social interactions, here we introduce the entropy of dynamical social networks. By analysing a large dataset of phone-call interactions we show evidence that the dynamical social network has an entropy that depends on the time of the day in a typical week-day. Moreover we show evidence for adaptability of human social behavior showing data on duration of phone-call interactions that significantly deviates from the statistics of duration of face-to-face interactions. This adaptability of behavior corresponds to a different information content of the dynamics of social human interactions. We quantify this information by the use of the entropy of dynamical networks on realistic models of social interactions.

physics.soc-ph↗

arXiv2011

Entropy rate of non-equilibrium growing networks

New entropy measures have been recently introduced for the quantification of the complexity of networks. Most of these entropy measures apply to static networks or to dynamical processes defined on static complex networks. In this paper we define the entropy rate of growing network models. This entropy rate quantifies how many labeled networks are typically generated by the growing network models. We analytically evaluate the difference between the entropy rate of growing tree network models and the entropy of tree networks that have the same asymptotic degree distribution. We find that the growing networks with linear preferential attachment generated by dynamical models are exponentially less than the static networks with the same degree distribution for a large variety of relevant growing network models. We study the entropy rate for growing network models showing structural phase transitions including models with non-linear preferential attachment. Finally, we bring numerical evidence that the entropy rate above and below the structural phase transitions follow a different scaling with the network size.

cond-mat.dis-nn↗

arXiv2011

Social network dynamics of face-to-face interactions

The recent availability of data describing social networks is changing our understanding of the "microscopic structure" of a social tie. A social tie indeed is an aggregated outcome of many social interactions such as face-to-face conversations or phone-calls. Analysis of data on face-to-face interactions shows that such events, as many other human activities, are bursty, with very heterogeneous durations. In this paper we present a model for social interactions at short time scales, aimed at describing contexts such as conference venues in which individuals interact in small groups. We present a detailed anayltical and numerical study of the model's dynamical properties, and show that it reproduces important features of empirical data. The model allows for many generalizations toward an increasingly realistic description of social interactions. In particular in this paper we investigate the case where the agents have intrinsic heterogeneities in their social behavior, or where dynamic variations of the local number of individuals are included. Finally we propose this model as a very flexible framework to investigate how dynamical processes unfold in social networks.

physics.soc-ph↗