arXiv subjects

Qian Zhang

Publications and source records attributed to Qian Zhang.

At least 451 records · Page 25Linked to original sources

arXiv2016

$μ$SR evidence for the U(1) quantum spin liquid ground state in the triangular antiferromagnet YbMgGaO$_4$

Muon spin relaxation and rotation ($μ$SR) experiments on single crystals of the structurally perfect triangular antiferromagnet YbMgGaO$_4$ indicate the absence of both static long-range magnetic order and spin freezing down to 0.048 K in zero field. Below 0.4 K, the $μ^{+}$ spin relaxation rates, which are proportional to the dynamic correlation function of the Yb$^{3+}$ spins,exhibit temperature-independent plateaus. Same behavior is revealed by temperature-independent local susceptibilities extracted from the Knight shifts of the $μ^{+}$ spin rotation frequencies under a transverse field of 20 Oe. All these $μ$SR results unequivocally support the formation of a gapless U(1) quantum spin liquid ground state in the triangular antiferromagnet YbMgGaO$_4$.

cond-mat.str-el↗

arXiv2016

Modelling and Analysis of Network Security - an Algebraic Approach

Game theory has been applied to investigate network security. But different security scenarios were often modeled via different types of games and analyzed in an ad-hoc manner. In this paper, we propose an algebraic approach for modeling and analyzing uniformly several types of network security games. This approach is based on a probabilistic extension of the value-passing Calculus of Communicating Systems (CCS) which is regarded as a Generative model for Probabilistic Value-passing CCS (PVCCSG for short). Our approach gives a uniform framework, called PVCCSG based security model, for the security scenarios modeled via perfect and complete or incomplete information games. We present then a uniform algorithm for computing the Nash equilibria strategies of a network security game on its PVCCSG based security model. The algorithm first generates a transition system for each of the PVCCSG based security models, then simplifies this transition system through graph-theoretic abstraction and bisimulation minimization. Then, a backward induction method, which is only applicable to finite tree models, can be used to compute all the Nash equilibria strategies of the (possibly infinite) security games. This algorithm is implemented and can also be tuned smoothly for computing its social optimal strategies. The effectiveness and efficiency of this approach are further demonstrated with four detailed case studies from the field of network security.

cs.CR↗

arXiv2016

3D Keypoint Detection Based on Deep Neural Network with Sparse Autoencoder

Researchers have proposed various methods to extract 3D keypoints from the surface of 3D mesh models over the last decades, but most of them are based on geometric methods, which lack enough flexibility to meet the requirements for various applications. In this paper, we propose a new method on the basis of deep learning by formulating the 3D keypoint detection as a regression problem using deep neural network (DNN) with sparse autoencoder (SAE) as our regression model. Both local information and global information of a 3D mesh model in multi-scale space are fully utilized to detect whether a vertex is a keypoint or not. SAE can effectively extract the internal structure of these two kinds of information and formulate high-level features for them, which is beneficial to the regression model. Three SAEs are used to formulate the hidden layers of the DNN and then a logistic regression layer is trained to process the high-level features produced in the third SAE. Numerical experiments show that the proposed DNN based 3D keypoint detection algorithm outperforms current five state-of-the-art methods for various 3D mesh models.

cs.CV↗

arXiv2015

Topical differences between Chinese language Twitter and Sina Weibo

Sina Weibo, China's most popular microblogging platform, is currently used by over $500M$ users and is considered to be a proxy of Chinese social life. In this study, we contrast the discussions occurring on Sina Weibo and on Chinese language Twitter in order to observe two different strands of Chinese culture: people within China who use Sina Weibo with its government imposed restrictions and those outside that are free to speak completely anonymously. We first propose a simple ad-hoc algorithm to identify topics of Tweets and Weibo. Different from previous works on micro-message topic detection, our algorithm considers topics of the same contents but with different \#tags. Our algorithm can also detect topics for Tweets and Weibos without any \#tags. Using a large corpus of Weibo and Chinese language tweets, covering the period from January $1$ to December $31$, $2012$, we obtain a list of topics using clustered \#tags that we can then use to compare the two platforms. Surprisingly, we find that there are no common entries among the Top $100$ most popular topics. Furthermore, only $9.2\%$ of tweets correspond to the Top $1000$ topics on Sina Weibo platform, and conversely only $4.4\%$ of weibos were found to discuss the most popular Twitter topics. Our results reveal significant differences in social attention on the two platforms, with most popular topics on Sina Weibo relating to entertainment while most tweets corresponded to cultural or political contents that is practically non existent in Sina Weibo.

cs.SI↗

arXiv2015

Prediction of the Yield of Enzymatic Synthesis of Betulinic Acid Ester Using Artificial Neural Networks and Support Vector Machine

3\b{eta}-O-phthalic ester of betulinic acid is of great importance in anticancer studies. However, the optimization of its reaction conditions requires a large number of experimental works. To simplify the number of times of optimization in experimental works, here, we use artificial neural network (ANN) and support vector machine (SVM) models for the prediction of yields of 3\b{eta}-O-phthalic ester of betulinic acid synthesized by betulinic acid and phthalic anhydride using lipase as biocatalyst. General regression neural network (GRNN), multilayer feed-forward neural network (MLFN) and the SVM models were trained based on experimental data. Four indicators were set as independent variables, including time (h), temperature (C), amount of enzyme (mg) and molar ratio, while the yield of the 3\b{eta}-O-phthalic ester of betulinic acid was set as the dependent variable. Results show that the GRNN and SVM models have the best prediction results during the testing process, with comparatively low RMS errors (4.01 and 4.23respectively) and short training times (both 1s). The prediction accuracy of the GRNN and SVM are both 100% in testing process, under the tolerance of 30%.

cs.LG↗

arXiv2015

Fast evaluation of the Caputo fractional derivative and its applications to fractional diffusion equations

We present an efficient algorithm for the evaluation of the Caputo fractional derivative $_0^C\!D_t^αf(t)$ of order $α\in (0,1)$, which can be expressed as a convolution of $f'(t)$ with the kernel $t^{-α}$. The algorithm is based on an efficient sum-of-exponentials approximation for the kernel $t^{-1-α}$ on the interval $[Δt, T]$ with a uniform absolute error $\varepsilon$, where the number of exponentials $N_{\text{exp}}$ needed is of the order $O\left(\log\frac{1}{\varepsilon}\left( \log\log\frac{1}{\varepsilon}+\log\frac{T}{Δt}\right) +\log\frac{1}{Δt}\left( \log\log\frac{1}{\varepsilon}+\log\frac{1}{Δt}\right) \right)$. As compared with the direct method, the resulting algorithm reduces the storage requirement from $O(N_T)$ to $O(N_{\text{exp}})$ and the overall computational cost from $O(N_T^2)$ to $O(N_TN_{\text{exp}})$ with $N_T$ the total number of time steps. Furthermore, when the fast evaluation scheme of the Caputo derivative is applied to solve the fractional diffusion equations, the resulting algorithm requires only $O(N_SN_{\text{exp}})$ storage and $O(N_SN_TN_{\text{exp}})$ work with $N_S$ the total number of points in space; whereas the direct methods require $O(N_SN_T$) storage and $O(N_SN_T^2)$ work. The complexity of both algorithms is nearly optimal since $N_{\text{exp}}$ is of the order $O(\log N_T)$ for $T\gg 1$ or $O(\log^2N_T)$ for $T\approx 1$ for fixed accuracy $\varepsilon$. We also present a detailed stability and error analysis of the new scheme for solving linear fractional diffusion equations. The performance of the new algorithm is illustrated via several numerical examples. Finally, the algorithm can be parallelized in a straightforward manner.

math.NA↗

arXiv2015

Committed activists and the reshaping of status-quo social consensus

The role of committed minorities in shaping public opinion has been recently addressed with the help of multi-agent models. However, previous studies focused on homogeneous populations where zealots stand out only for their stubbornness. Here, we consider the more general case in which individuals are characterized by different propensities to communicate. In particular, we correlate commitment with a higher tendency to push an opinion, acknowledging the fact that individuals with unwavering dedication to a cause are also more active in their attempts to promote their message. We show that these \textit{activists} are not only more efficient in spreading their message but that their efforts require an order of magnitude fewer individuals than a randomly selected committed minority to bring the population over to a new consensus. Finally, we address the role of communities, showing that partisan divisions in the society can make it harder for committed individuals to flip the status-quo social consensus.

physics.soc-ph↗

arXiv2015

Generation of pseudo-high-order group velocity locked vector solitons in fiber lasers

We propose and experimentally demonstrate the generation of pseudo-high-order group velocity locked vector solitons (GVLVS) in a fiber laser using a SESAM as the mode locker. With the help of an external all-fiber polarization resolved system, a GVLVS with a two-humped pulse along one polarization while a single-humped pulse along the orthogonal polarization could be obtained. The phase difference between the two humps is 180 degree.

physics.optics↗

arXiv2015

Modelling and Analysis Network Security -- a PVCCS approach

In this work, we propose a probabilistic value-passing CCS (Calculus of Communicating System) approach to model and analyze a typical network security scenario with one attacker and one defender. By minimizing this model with respect to probabilistic bisimulation and abstracting it through graph-theoretic methods, two algorithms based on backward induction are designed to compute Nash Equilibrium strategy and Social Optimal strategy respectively. For each algorithm, the correctness is proved and an implementation is realized. Finally, this approach is illustrated by a detailed case study.

cs.CR↗

arXiv2015

Breaking the challenge of signal integrity using time-domain spoof surface plasmon polaritons

In modern integrated circuits and wireless communication systems/devices, three key features need to be solved simultaneously to reach higher performance and more compact size: signal integrity, interference suppression, and miniaturization. However, the above-mentioned requests are almost contradictory using the traditional techniques. To overcome this challenge, here we propose time-domain spoof surface plasmon polaritons (SPPs) as the carrier of signals. By designing a special plasmonic waveguide constructed by printing two narrow corrugated metallic strips on the top and bottom surfaces of a dielectric substrate with mirror symmetry, we show that spoof SPPs are supported from very low frequency to the cutoff frequency with strong subwavelength effects, which can be converted to the time-domain SPPs. When two such plasmonic waveguides are tightly packed with deep-subwavelength separation, which commonly happens in the integrated circuits and wireless communications due to limited space, we demonstrate theoretically and experimentally that SPP signals on such two plasmonic waveguides have better propagation performance and much less mutual coupling than the conventional signals on two traditional microstrip lines with the same size and separation. Hence the proposed method can achieve significant interference suppression in very compact space, providing a potential solution to break the challenge of signal integrity.

physics.optics↗

arXiv2015

Spin Polarization Inversion at Benzene-Absorbed Fe4N Surface

We report a first-principle study on electronic structure and simulation of the spin-polarized scanning tunneling microscopy graphic of a benzene/Fe4N interface. Fe4N is a compound ferromagnet suitable for many spintronic applications. We found that, depending on the particular termination schemes and interface configurations, the spin polarization on the benzene surface shows a rich variety of properties ranging from cosine-type oscillation to polarization inversion. Spin-polarization inversion above benzene is resulting from the hybridizations between C pz and the out-of-plane d orbitals of Fe atom.

cond-mat.mtrl-sci↗

arXiv2015

An Approach to Making SPAI and PSAI Preconditioning Effective for Large Irregular Sparse Linear Systems

We investigate the SPAI and PSAI preconditioning procedures and shed light on two important features of them: (i) For the large linear system $Ax=b$ with $A$ irregular sparse, i.e., with $A$ having $s$ relatively dense columns, SPAI may be very costly to implement, and the resulting sparse approximate inverses may be ineffective for preconditioning. PSAI can be effective for preconditioning but may require excessive storage and be unacceptably time consuming; (ii) the situation is improved drastically when $A$ is regular sparse, that is, all of its columns are sparse. In this case, both SPAI and PSAI are efficient. Moreover, SPAI and, especially, PSAI are more likely to construct effective preconditioners. Motivated by these features, we propose an approach to making SPAI and PSAI more practical for $Ax=b$ with $A$ irregular sparse. We first split $A$ into a regular sparse $\tilde A$ and a matrix of low rank $s$. Then exploiting the Sherman--Morrison--Woodbury formula, we transform $Ax=b$ into $s+1$ new linear systems with the same coefficient matrix $\tilde A$, use SPAI and PSAI to compute sparse approximate inverses of $\tilde A$ efficiently and apply Krylov iterative methods to solve the preconditioned linear systems. Theoretically, we consider the non-singularity and conditioning of $\tilde A$ obtained from some important classes of matrices. We show how to recover an approximate solution of $Ax=b$ from those of the $s+1$ new systems and how to design reliable stopping criteria for the $s+1$ systems to guarantee that the approximate solution of $Ax=b$ satisfies a desired accuracy. Given the fact that irregular sparse linear systems are common in applications, this approach widely extends the practicability of SPAI and PSAI. Numerical results demonstrate the considerable superiority of our approach to the direct application of SPAI and PSAI to $Ax=b$.

math.NA↗

arXiv2015

Robust Dropping Criteria for F-norm Minimization Based Sparse Approximate Inverse Preconditioning

Dropping tolerance criteria play a central role in Sparse Approximate Inverse preconditioning. Such criteria have received, however, little attention and have been treated heuristically in the following manner: If the size of an entry is below some empirically small positive quantity, then it is set to zero. The meaning of "small" is vague and has not been considered rigorously. It has not been clear how dropping tolerances affect the quality and effectiveness of a preconditioner $M$. In this paper, we focus on the adaptive Power Sparse Approximate Inverse algorithm and establish a mathematical theory on robust selection criteria for dropping tolerances. Using the theory, we derive an adaptive dropping criterion that is used to drop entries of small magnitude dynamically during the setup process of $M$. The proposed criterion enables us to make $M$ both as sparse as possible as well as to be of comparable quality to the potentially denser matrix which is obtained without dropping. As a byproduct, the theory applies to static F-norm minimization based preconditioning procedures, and a similar dropping criterion is given that can be used to sparsify a matrix after it has been computed by a static sparse approximate inverse procedure. In contrast to the adaptive procedure, dropping in the static procedure does not reduce the setup time of the matrix but makes the application of the sparser $M$ for Krylov iterations cheaper. Numerical experiments reported confirm the theory and illustrate the robustness and effectiveness of the dropping criteria.

math.NA↗

arXiv2015

Structural Patterns of the Occupy Movement on Facebook

In this work we study a peculiar example of social organization on Facebook: the Occupy Movement -- i.e., an international protest movement against social and economic inequality organized online at a city level. We consider 179 US Facebook public pages during the time period between September 2011 and February 2013. The dataset includes 618K active users and 753K posts that received about 5.2M likes and 1.1M comments. By labeling user according to their interaction patterns on pages -- e.g., a user is considered to be polarized if she has at least the 95% of her likes on a specific page -- we find that activities are not locally coordinated by geographically close pages, but are driven by pages linked to major US cities that act as hubs within the various groups. Such a pattern is verified even by extracting the backbone structure -- i.e., filtering statistically relevant weight heterogeneities -- for both the pages-reshares and the pages-common users networks.

cs.SI↗

arXiv2015

Modeling Multi-wavelength Pulse Profiles of Millisecond Pulsar PSR B1821-24

PSR B1821$-$24 is a solitary millisecond pulsar (MSP) which radiates multi-wavelength pulsed photons. It has complex radio, X-ray and $γ$-ray pulse profiles with distinct peak phase-separations that challenge the traditional caustic emission models. Using the single-pole annular gap model with suitable magnetic inclination angle ($α=40^\circ$) and viewing angle ($ζ=75^\circ$), we managed to reproduce its pulse profiles of three wavebands. It is found that the middle radio peak is originated from the core gap region at high altitudes, and the other two radio peaks are originated from the annular gap region at relatively low altitudes. Two peaks of both X-ray and $γ$-ray wavebands are fundamentally originated from annular gap region, while the $γ$-ray emission generated from the core gap region contributes somewhat to the first $γ$-ray peak. Precisely reproducing the multi-wavelength pulse profiles of PSR B1821$-$24 enables us to understand emission regions of distinct wavebands and justify pulsar emission models.

astro-ph.SR↗

arXiv2014

FlexAuc: Serving Dynamic Demands in a Spectrum Trading Market with Flexible Auction

In secondary spectrum trading markets, auctions are widely used by spectrum holders (SHs) to redistribute their unused channels to secondary wireless service providers (WSPs). As sellers, the SHs design proper auction schemes to stimulate more participants and maximize the revenue from the auction. As buyers, the WSPs determine the bidding strategies in the auction to better serve their end users. In this paper, we consider a three-layered spectrum trading market consisting of the SH, the WSPs and the end users. We jointly study the strategies of the three parties. The SH determines the auction scheme and spectrum supplies to optimize its revenue. The WSPs have flexible bidding strategies in terms of both demands and valuations considering the strategies of the end users. We design FlexAuc, a novel auction mechanism for this market to enable dynamic supplies and demands in the auction. We prove theoretically that FlexAuc not only maximizes the social welfare but also preserves other nice properties such as truthfulness and computational tractability.

cs.NI↗

arXiv2014

Collective attention in the age of (mis)information

In this work we study, on a sample of 2.3 million individuals, how Facebook users consumed different information at the edge of political discussion and news during the last Italian electoral competition. Pages are categorized, according to their topics and the communities of interests they pertain to, in a) alternative information sources (diffusing topics that are neglected by science and main stream media); b) online political activism; and c) main stream media. We show that attention patterns are similar despite the different qualitative nature of the information, meaning that unsubstantiated claims (mainly conspiracy theories) reverberate for as long as other information. Finally, we categorize users according to their interaction patterns among the different topics and measure how a sample of this social ecosystem (1279 users) responded to the injection of 2788 false information posts. Our analysis reveals that users which are prominently interacting with alternative information sources (i.e. more exposed to unsubstantiated claims) are more prone to interact with false claims.

cs.SI↗

arXiv2014

Multi-scale Modeling for Piezoelectric Composite Materials

In this paper, we focus on multi-scale modeling and simulation of piezoelectric composite materials. A multi-scale model for piezoelectric composite materials under the framework of Heterogeneous Multi-scale Method(HMM) is proposed. For materials with periodic microstructure, macroscopic model is derived from microscopic model of piezoelectric composite material by asymptotic expansion. Convergence analysis under the framework of homogenization theory is carried out. Moreover, error estimate between HMM solutions and homogenization solutions is derived. A 3-D numerical example of 1-3 type piezoelectric composite materials is employed to verify the error estimate.

math-ph↗