arXiv subjects

Tao Zhou

Publications and source records attributed to Tao Zhou.

At least 343 records · Page 19Linked to original sources

arXiv2019

Regional economic status inference from information flow and talent mobility

Novel data has been leveraged to estimate socioeconomic status in a timely manner, however, direct comparison on the use of social relations and talent movements remains rare. In this letter, we estimate the regional economic status based on the structural features of the two networks. One is the online information flow network built on the following relations on social media, and the other is the offline talent mobility network built on the anonymized resume data of job seekers with higher education. We find that while the structural features of both networks are relevant to economic status, the talent mobility network in a relatively smaller size exhibits a stronger predictive power for the gross domestic product (GDP). In particular, a composite index of structural features can explain up to about 84% of the variance in GDP. The result suggests future socioeconomic studies to pay more attention to the cost-effective talent mobility data.

physics.soc-ph↗

arXiv2018

Possible pairing symmetry in the FeSe-based superconductors determined by quasiparticle interference

We study the momentum-integrated quasiparticle interference (QPI) in the FeSe-based superconductors. This method was recently proposed theoretically and has been applied to determine the pairing symmetry in these materials experimentally. Our findings suggest that, if the incipient bands and the superconducting (SC) pairing on them are taken into consideration, then the experimentally measured bound states and momentum-integrated QPI can be well fitted, even if the SC order parameter does not change sign on the Fermi surfaces. Therefore, we offer an alternative explanation to the experimental data, calling for more careful identification of the pairing symmetry that is important for the pairing mechanism.

cond-mat.supr-con↗

arXiv2018

Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems

The polynomial chaos (PC) expansion has been widely used as a surrogate model in the Bayesian inference to speed up the Markov chain Monte Carlo (MCMC) calculations. However, the use of a PC surrogate introduces the modeling error, that may severely distort the estimate of the posterior distribution. This error can be corrected by increasing the order of the PC expansion, but the cost for building the surrogate may increase dramatically. In this work, we seek to address this challenge by proposing an adaptive procedure to construct a multi-fidelity PC surrogate. This new strategy combines (a large number of) low-fidelity surrogate model evaluations and (a small number of) high-fidelity model evaluations, yielding an adaptive multi-fidelity approach. Here the low-fidelity surrogate is chosen as the prior-based PC surrogate, while the high-fidelity model refers to the true forward model. The key idea is to construct and refine the multi-fidelity approach over a sequence of samples adaptively determined form data, so that the approximation can eventually concentrate to the posterior distribution. We illustrate the performance of the proposed strategy through two nonlinear inverse problems. It is shown that the proposed adaptive multi-fidelity approach can improve significantly the accuracy, yet without a dramatic increase in the computational complexity. The numerical results also indicate that our new algorithm can enhance the efficiency by several orders of magnitude compared to a standard MCMC approach using only the true forward model.

math.NA↗

arXiv2018

Close and ordinary social contacts: how important are they in promoting large-scale contagion?

An outstanding problem of interdisciplinary interest is to understand quantitatively the role of social contacts in contagion dynamics. In general, there are two types of contacts: close ones among friends, colleagues and family members, etc., and ordinary contacts from encounters with strangers. Typically, social reinforcement occurs for close contacts. Taking into account both types of contacts, we develop a contact-based model for social contagion. We find that, associated with the spreading dynamics, for random networks there is coexistence of continuous and discontinuous phase transitions, but for heterogeneous networks the transition is continuous. We also find that ordinary contacts play a crucial role in promoting large scale spreading, and the number of close contacts determines not only the nature of the phase transitions but also the value of the outbreak threshold in random networks. For heterogeneous networks from the real world, the abundance of close contacts affects the epidemic threshold, while its role in facilitating the spreading depends on the adoption threshold assigned to it. We uncover two striking phenomena. First, a strong interplay between ordinary and close contacts is necessary for generating prevalent spreading. In fact, only when there are propagation paths of reasonable length which involve both close and ordinary contacts are large scale outbreaks of social contagions possible. Second, abundant close contacts in heterogeneous networks promote both outbreak and spreading of the contagion through the transmission channels among the hubs, when both values of the threshold and transmission rate among ordinary contacts are small. We develop a theoretical framework to obtain an analytic understanding of the main findings on random networks, with support from extensive numerical computations.

physics.soc-ph↗

arXiv2018

Learning to Sketch with Deep Q Networks and Demonstrated Strokes

Doodling is a useful and common intelligent skill that people can learn and master. In this work, we propose a two-stage learning framework to teach a machine to doodle in a simulated painting environment via Stroke Demonstration and deep Q-learning (SDQ). The developed system, Doodle-SDQ, generates a sequence of pen actions to reproduce a reference drawing and mimics the behavior of human painters. In the first stage, it learns to draw simple strokes by imitating in supervised fashion from a set of strokeaction pairs collected from artist paintings. In the second stage, it is challenged to draw real and more complex doodles without ground truth actions; thus, it is trained with Qlearning. Our experiments confirm that (1) doodling can be learned without direct stepby- step action supervision and (2) pretraining with stroke demonstration via supervised learning is important to improve performance. We further show that Doodle-SDQ is effective at producing plausible drawings in different media types, including sketch and watercolor.

cs.CV↗

arXiv2018

Detecting competing orders through the edge states in the heterostructures with high-Tc superconductors

Considering a $d$-wave superconductor being in proximity to a two-dimensional Weyl model, a topological superconductor with gapless edge states may be realized. We here demonstrate that the system can become topologically trivial when an additional d-density-wave order is also included. The edge states become gapped and may be detected in experiments. For this, the d-density-wave order can be detected experimentally, so that different scenarios for the pseudogap in high-T$_c$ superconductors may be distinguished. Moreover, this method may be used to detect various hidden orders through putting high-T$_c$ superconductors being in proximity to various topological nontrivial materials.

cond-mat.supr-con↗

arXiv2018

Transition semi-wave solutions of reaction diffusion equations with free boundaries

In this paper, we define the transition semi-wave solution of the following reaction diffusion equation with free boundaries \begin{equation}\label{0.1} \left\{ \begin{aligned} u_{t}=u_{xx}+f(t,x,u),\ \ &t\in\Real, x 1, $$ we prove that the semi-wave connecting $1$ and $0$ is unique provided it exists. Furthermore, we prove that any bounded transition semi-wave connecting $1$ and 0 is exactly the semi-wave. In the cases where $f$ is KPP-Fisher type and almost periodic in time (space), i.e., $f(t,x,u)=u(c(t)-u)$ (resp. $u(a(x)-u)$) with $c(t)$ (resp. $a(x)$) being almost periodic, applying totally different method, we also prove any bounded transition semi-wave connecting the unique almost periodic positive solution of $u_{t}=u(c(t)-u)$ (resp. $u_{xx}+u(a(x)-u)=0$) and $0$ is exactly the unique almost periodic semi-wave. Finally, we provide an example of the heterogeneous equation to show the existence of the transition semi-wave without any global mean speeds.

math.AP↗

arXiv2018

Spreading speeds of KPP-type lattice systems in heterogeneous media

In this paper, we investigate spreading properties of the solutions of the Kolmogorov-Petrovsky-Piskunov-type, (to be simple,KPP-type) lattice system \begin{equation}\label{firstequation}\overset{.}u_{i}(t) =d^{\prime}_{i}(u_{i+1}(t)-u_{i}(t))+d_{i}(u_{i-1}(t)-u_{i}(t))+f(i,u_{i}).\end{equation} we develop some new discrete Harnack-type estimates and homogenization techniques for this lattice system to construct two speeds $\overlineω\leq \underline ω$ such that $\displaystyle{\lim_{t\rightarrow+\infty}}\sup \limits_{i\geqωt}|u_i(t)|=0$ for any $ω>\overlineω$, and $\displaystyle{\lim_{t\rightarrow+\infty}}\sup \limits_{0\leq i\leqωt}|u_i(t)-1|=0$ for any $ω<\underlineω$. These speeds are characterized by two generalized principal eigenvalues of the linearized systems. In particular, we derive the exact spreading speed when the coefficients are random stationary ergodic or almost periodic (where $\underlineω= \overlineω$). Finally, in the case where $f_{s}^{\prime}(i,0)$ is almost periodic in $i$ and the diffusion rate $d_i'=d_i$ is independent of $i$, we show that the spreading speeds in the positive and negative directions are identical even if $ f(i,u_{i})$ is not invariant with respect to the reflection.

math.AP↗

arXiv2018

An adaptive multi-fidelity PC-based ensemble Kalman inversion for inverse problems

The ensemble Kalman inversion (EKI), as a derivative-free methodology, has been widely used in the parameter estimation of inverse problems. Unfortunately, its cost may become moderately large for systems described by high dimensional nonlinear PDEs, as EKI requires a relatively large ensemble size to guarantee its performance. In this paper, we propose an adaptive multi-fidelity polynomial chaos (PC) based EKI technique to address this challenge. Our new strategy combines a large number of low-order PC surrogate model evaluations and a small number of high-fidelity forward model evaluations, yielding a multi-fidelity approach. Especially, we present a new approach that adaptively constructs and refines a multi-fidelity PC surrogate during the EKI simulation. Since the forward model evaluations are only required for updating the low-order multi-fidelity PC model, whose number can be much smaller than the total ensemble size of the classic EKI, the entire computational costs are thus significantly reduced. The new algorithm was tested through the two-dimensional time fractional inverse diffusion problems and demonstrated great effectiveness in comparison with PC based EKI and classic EKI.

math.NA↗

arXiv2018

X-ray coherent diffraction imaging with an objective lens: towards 3D mapping of thick polycrystals

We report on a new x-ray imaging method, which combines the high spatial resolution of coherent diffraction imaging with the ability of dark field microscopy to map grains within thick polycrystalline specimens. An x-ray objective serves to isolate a grain and avoid overlap of diffraction spots. Iterative oversampling routines are used to reconstruct the shape and strain field within the grain from the far field intensity pattern. The limitation on resolution caused by the finite numerical aperture of the objective is overcome by the Fourier synthesis of several diffraction patterns. We demonstrate the method by an experimental study of a ~500 nm Pt grain for the two cases of a real and a virtual image plane. In the latter case the spatial resolution is 13 nm rms. Our results confirm that no information on the pupil function of the lens is required and that lens aberrations are not critical.

physics.ins-det↗

arXiv2018

Kuramoto dilemma alleviated by optimizing connectivity and rationality

Recently, Antonioni and Cardillo proposed a coevolutionary model based on the intertwining of oscillator synchronization and evolutionary game theory [Phys. Rev. Lett. \textbf{118}, 238301 (2017)], in which each Kuramoto oscillator can decide whether to interact-or not-with its neighbors, and all oscillators can receive some benefits from the local synchronization but those who choose to interact must pay a cost. Oscillators are allowed to update their strategies according to payoff difference, wherein the strategy of an oscillator who has obtained higher payoff is more likely to be followed. Utilizing this coevolutionary model, we find that the global synchronization level reaches the highest level when the average degree of the underlying interaction network is moderate. We also study how synchronization is affected by the individual rationality in choosing strategy.

physics.soc-ph↗

arXiv2018

Customer Sharing in Economic Networks with Costs

In an economic market, sellers, infomediaries and customers constitute an economic network. Each seller has her own customer group and the seller's private customers are unobservable to other sellers. Therefore, a seller can only sell commodities among her own customers unless other sellers or infomediaries share her sale information to their customer groups. However, a seller is not incentivized to share others' sale information by default, which leads to inefficient resource allocation and limited revenue for the sale. To tackle this problem, we develop a novel mechanism called customer sharing mechanism (CSM) which incentivizes all sellers to share each other's sale information to their private customer groups. Furthermore, CSM also incentivizes all customers to truthfully participate in the sale. In the end, CSM not only allocates the commodities efficiently but also optimizes the seller's revenue.

cs.GT↗

arXiv2018

Spreading speeds of nonlocal KPP equations in heterogeneous media

In this paper, we prove the existence of the spreading speed of nonlocal KPP equations in two cases: 1. The media is almost periodic and the kernel of diffusion is continuous; 2. The media is periodic and the diffusion is not continuous but weak irreducible. To do this, we develop the theory of generalized principal eigenvalues, the method homogenization and special Harnack's inequalities of nonlocal diffusion equations.

math.AP↗

arXiv2018

Payoff Control in the Iterated Prisoner's Dilemma

Repeated game has long been the touchstone model for agents' long-run relationships. Previous results suggest that it is particularly difficult for a repeated game player to exert an autocratic control on the payoffs since they are jointly determined by all participants. This work discovers that the scale of a player's capability to unilaterally influence the payoffs may have been much underestimated. Under the conventional iterated prisoner's dilemma, we develop a general framework for controlling the feasible region where the players' payoff pairs lie. A control strategy player is able to confine the payoff pairs in her objective region, as long as this region has feasible linear boundaries. With this framework, many well-known existing strategies can be categorized and various new strategies with nice properties can be further identified. We show that the control strategies perform well either in a tournament or against a human-like opponent.

cs.GT↗

arXiv2018

Certifying quantumness with the classical fidelity threshold

For a given ensemble of input and target states, the classical fidelity threshold (CFT) is the maximum valve of the averaged fidelity, and it can be achieved with a measure-and-prepare operation. This quantity can be employed to verify whether the channel is in the quantum domain or not. In a recent work by Chiribella and Xie [Phys. Rev. Lett. {\bf 110}, 213601 (2013)], it was showed that all the information about the input and target states can be equivalently described by an entangled state and an effective entanglement-braking (EB) channel, and the CFTs can be defined with the Choi matrix of the effective EB channel. Following this idea, the protocol proposed by Fuchs and Sasaki [Quantum. Inf. Comput, {\bf 3}, 377 (2003)] are reformulated in terms of the effective EB channel, and ss applications, the deterministic and probabilistic CFTs for qubit states and the coherent states are derived in this paper.

quant-ph↗

arXiv2018

On Predictability of Time Series

The method to estimate the predictability of human mobility was proposed in [C. Song \emph{et al.}, Science {\bf 327}, 1018 (2010)], which is extensively followed in exploring the predictability of disparate time series. However, the ambiguous description in the original paper leads to some misunderstandings, including the inconsistent logarithm bases in the entropy estimator and the entropy-predictability-conversion equation, as well as the details in the calculation of the Lempel-Ziv estimator, which further results in remarkably overestimated predictability. This paper demonstrates the degree of overestimation by four different types of theoretically generated time series and an empirical data set, and shows the intrinsic deviation of the Lempel-Ziv estimator for highly random time series. This work provides a clear picture on this issue and thus helps researchers in correctly estimating the predictability of time series.

physics.soc-ph↗

arXiv2018

Data-driven polynomial chaos expansions: a weighted least-square approximation

In this work, we combine the idea of data-driven polynomial chaos expansions with the weighted least-square approach to solve uncertainty quantification (UQ) problems. The idea of data-driven polynomial chaos is to use statistical moments of the input random variables to develop an arbitrary polynomial chaos expansion, and then use such data-driven bases to perform UQ computations. Here we adopt the bases construction procedure by following \cite{Ahlfeld_2016SAMBA}, where the bases are computed by using matrix operations on the Hankel matrix of moments. Different from previous works, in the postprocessing part, we propose a weighted least-squares approach to solve UQ problems. This approach includes a sampling strategy and a least-squares solver. The main features of our approach are two folds: On one hand, our sampling strategy is independent of the random input. More precisely, we propose to sampling with the equilibrium measure, and this measure is also independent of the data-driven bases. Thus, this procedure can be done in prior (or in a off-line manner). On the other hand, we propose to solve a Christoffel function weighted least-square problem, and this strategy is quasi-linearly stable -- the required number of PDE solvers depends linearly (up to a logarithmic factor) on the number of (data-driven) bases. This new approach is thus promising in dealing with a class of problems with epistemic uncertainties. Several numerical tests are presented to show the effectiveness of our approach.

math.NA↗

arXiv2018

Resolving different pairing states in Weyl superconductors through the single-particle spectrum

We study theoretically single-particle spectra of Weyl superconductors. Three different superconducting pairing states are addressed, which are the BCS-type states with the $s$-wave pairing symmetry and the $p+ip$-wave pairing symmetry, and the FFLO pairing state. We elaborate that these three states can be resolved well based on the bulk and surface spectral functions as well as the local density of states. The single impurity effect is also explored, which may help us to differentiate the BCS-type pairing states and the FFLO state further.

cond-mat.supr-con↗