arXiv subjects

Jiang Zhang

Publications and source records attributed to Jiang Zhang.

At least 91 records · Page 5Linked to original sources

arXiv2018

Complex Network Classification with Convolutional Neural Network

Classifying large scale networks into several categories and distinguishing them according to their fine structures is of great importance with several applications in real life. However, most studies of complex networks focus on properties of a single network but seldom on classification, clustering, and comparison between different networks, in which the network is treated as a whole. Due to the non-Euclidean properties of the data, conventional methods can hardly be applied on networks directly. In this paper, we propose a novel framework of complex network classifier (CNC) by integrating network embedding and convolutional neural network to tackle the problem of network classification. By training the classifiers on synthetic complex network data and real international trade network data, we show CNC can not only classify networks in a high accuracy and robustness, it can also extract the features of the networks automatically.

cs.CV↗

arXiv2018

Holonomic Surface Codes for Fault-Tolerant Quantum Computation

Surface codes can protect quantum information stored in qubits from local errors as long as the per-operation error rate is below a certain threshold. Here we propose holonomic surface codes by harnessing the quantum holonomy of the system. In our scheme, the holonomic gates are built via auxiliary qubits rather than the auxiliary levels in multilevel systems used in conventional holonomic quantum computation. The key advantage of our approach is that the auxiliary qubits are in their ground state before and after each gate operation, so they are not involved in the operation cycles of surface codes. This provides an advantageous way to implement surface codes for fault-tolerant quantum computation.

quant-ph↗

arXiv2017

Interactive Levy Flight in Interest Space

Compared to the well-studied topic of human mobility in real geographic space, very few studies focus on human mobility in virtual space, such as interests, knowledge, ideas, and so forth. However, it relates to the issues of management of public opinions, knowledge diffusion, and innovation. In this paper, we assume that the interests of a group of online users can span a Euclidean space which is called interest space, and the transfers of user interests can be modeled as the Levy Flight on the interest space. To consider the interaction between users, we assume that the random walkers are not independent but interact each other indirectly via the digital resources in the interest space. The model can successfully reproduce a set of scaling laws for describing the growth of the attention flow networks of real online communities, and the ranges of the exponents of the scaling are similar with the empirical data. Further, we can infer parameters for describing the individual behaviors of the users according to the scaling laws of the empirical attention flow network. Our model can not only provide theoretical understanding on human online behaviors, but also has wide potential applications, such as dissemination and management of public opinions, online recommendation, etc.

cs.SI↗

arXiv2017

The Hidden Flow Structure and Metric Space of Network Embedding Algorithms Based on Random Walks

Network embedding which encodes all vertices in a network as a set of numerical vectors in accordance with it's local and global structures, has drawn widespread attention. Network embedding not only learns significant features of a network, such as the clustering and linking prediction but also learns the latent vector representation of the nodes which provides theoretical support for a variety of applications, such as visualization, node classification, and recommendation. As the latest progress of the research, several algorithms based on random walks have been devised. Although their high scores for learning efficiency and accuracy have drawn much attention, there is still a lack of theoretical explanation, and the transparency of the algorithms has been doubted. Here, we propose an approach based on the open-flow network model to reveal the underlying flow structure and its hidden metric space of different random walk strategies on networks. We show that the essence of embedding based on random walks is the latent metric structure defined on the open-flow network. This not only deepens our understanding of random walk based embedding algorithms but also helps in finding new potential applications in embedding.

physics.soc-ph↗

arXiv2016

Holonomic quantum computation in the ultrastrong-coupling regime of circuit QED

We present an experimentally feasible scheme to implement holonomic quantum computation in the ultrastrong-coupling regime of light-matter interaction. The large anharmonicity and the Z2 symmetry of the quantum Rabi model allow us to build an effective three-level Λ-structured artificial atom for quantum computation. The proposed physical implementation includes two gradiometric flux qubits and two microwave resonators where single-qubit gates are realized by a two-tone driving on one physical qubit, and a two-qubit gate is achieved with a time-dependent coupling between the field quadratures of both resonators. Our work paves the way for scalable holonomic quantum computation in ultrastrongly coupled systems.

quant-ph↗

arXiv2015

The Hidden Geometry of Attention Diffusion

We propose a geometric model to quantify the dynamics of attention in online communities. Using clicks as a proxy of attention, we find that the diffusion of collective attention in Web forums and news sharing sites forms time-invariant "fields" whose density vary solely with distance from the center of the fields that represents the input of attention from the physical world. As time goes by, old information pieces are pushed farther from the center by new pieces, receive fewer and fewer clicks, and eventually become invisible in the virtual world. The discovered "attention fields" not only explain the fast decay of attention to information pieces, but also predict the accelerating growth of clicks against the active user population, which is a universal pattern relevant to the economics of scales of online interactions.

physics.soc-ph↗

arXiv2015

Exploring multi-layer flow network of international trade based on flow distances

Based on the approach of flow distances, the international trade flow system is studied from the perspective of multi-layer flow network. A model of multi-layer flow network is proposed for modelling and analyzing multiple types of flows in flow systems. Then, flow distances are introduced, and symmetric minimum flow distance is presented. Subsequently, we discuss the establishment of the multi-layer flow networks of international trade from two coupled viewpoints, i.e., the viewpoint of commodity flow and that of money flow. Thus, the multi-layer flow networks of international trade is explored. First, trading "trophic levels" are adopted to depict positions that economies occupied in the flow network. We find that the distributions of trading "trophic levels" have the similar clustering pattern for different types of commodity, and there are some regularities between money flow network and commodity flow network. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. It may indicate an abnormal economic status. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. It means that competitive countries tend to occupy the central positions in the trading of a large variety of commodities, while underdeveloped countries likely in the peripheral positions in the trading of their limited varieties of products. Fourth, we find that manufactured products have significant larger mean first-passage flow distances from the source to the sink than that of primary products.

physics.soc-ph↗

arXiv2015

Flow Distances on Open Flow Networks

Open flow network is a weighted directed graph with a source and a sink, depicting flux distributions on networks in the steady state of an open flow system. Energetic food webs, economic input-output networks, and international trade networks, are open flow network models of energy flows between species, money or value flows between industrial sectors, and goods flows between countries, respectively. Flow distances (first-passage or total) between any given two nodes $i$ and $j$ are defined as the average number of transition steps of a random walker along the network from $i$ to $j$ under some conditions. They apparently deviate from the conventional random walk distance on a closed directed graph because they consider the openness of the flow network. Flow distances are explicitly expressed by underlying Markov matrix of a flow system in this paper. With this novel theoretical conception, we can visualize open flow networks, calculating centrality of each node, and clustering nodes into groups. We apply flow distances to two kinds of empirical open flow networks, including energetic food webs and economic input-output network. In energetic food webs example, we visualize the trophic level of each species and compare flow distances with other distance metrics on graph. In input-output network, we rank sectors according to their average distances away other sectors, and cluster sectors into different groups. Some other potential applications and mathematical properties are also discussed. To summarize, flow distance is a useful and powerful tool to study open flow systems.

physics.soc-ph↗

arXiv2014

Hierarchicality of Trade Flow Networks Reveals Complexity of Products

With globalization, countries are more connected than before by trading flows, which currently amount to at least 36 trillion dollars. Interestingly, approximately 30-60 percent of global exports consist of intermediate products. Therefore, the trade flow network of a particular product with high added values can be regarded as a value chain. The problem is weather we can discriminate between these products based on their unique flow network structure. This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent $η$ can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, the flow networks of products with higher added values and complexity, such as machinery&transport equipment with larger exponents, are highlighted. These higher values indicate that their trade flow networks are more hierarchical. As a result, without extra data such as global input-output table, we can identify the product categories with higher complexity and the relative importance of a country in the global value chain solely by the trading network.

q-fin.GN↗

arXiv2013

Constrain on superconductivity of potassium intercalated phenanthrene

Raman-scattering measurements are performed in K${_x}$phenanthrene with the nominal value ${x}$ ranging from 0 to 6.0 at room temperature. Based on the Raman spectra, two phases (${x}$ = 3.0 and 4.0) are observed among the K${_x}$phenanthrene, and the immediate phase (${x}$ = 3.5) is produced. Only the ${x}$ = 3.0 phase is found to exhibit the superconducting transition at 5 K. The C-C stretching mods are observed to broaden and become disorder in K${_x}$phenanthrene (nominal value ${x}$ =2.0, 2.5, 6.0), indicating some molecular disorder in the metal intercalation process. This disorder is expected to influence the nonmetallic nature of these materials. The absence of metallic characteristics in those nonsuperconducting phases is provided from the calculated electronic structures based on the local density approximation.

cond-mat.supr-con↗

arXiv2013

The Metabolism and Growth of Web Forums

We view web forums as virtual living organisms feeding on user's attention and investigate how these organisms grow at the expense of collective attention. We find that the "body mass" ($PV$) and "energy consumption" ($UV$) of the studied forums exhibits the allometric growth property, i.e., $PV_t \sim UV_t ^ θ$. This implies that within a forum, the network transporting attention flow between threads has a structure invariant of time, despite of the continuously changing of the nodes (threads) and edges (clickstreams). The observed time-invariant topology allows us to explain the dynamics of networks by the behavior of threads. In particular, we describe the clickstream dissipation on threads using the function $D_i \sim T_i ^ γ$, in which $T_i$ is the clickstreams to node $i$ and $D_i$ is the clickstream dissipated from $i$. It turns out that $γ$, an indicator for dissipation efficiency, is negatively correlated with $θ$ and $1/γ$ sets the lower boundary for $θ$. Our findings have practical consequences. For example, $θ$ can be used as a measure of the "stickiness" of forums, because it quantifies the stable ability of forums to convert $UV$ into $PV$, i.e., to remain users "lock-in" the forum. Meanwhile, the correlation between $γ$ and $θ$ provides a convenient method to evaluate the `stickiness" of forums. Finally, we discuss an optimized "body mass" of forums at around $10^5$ that minimizes $γ$ and maximizes $θ$.

physics.soc-ph↗

arXiv2013

Capabilities' Substitutability and the "S" Curve of Export Diversity

Product diversity, which is highly important in economic systems, has been highlighted by recent studies on international trade. We found an empirical pattern, designated as the "S-shaped curve", that models the relationship between economic size (logarithmic GDP) and export diversity (the number of varieties of export products) on the detailed international trade data. As the economic size of a country begins to increase, its export diversity initially increases in an exponential manner, but overtime, this diversity growth slows and eventually reaches an upper limit. The interdependence between size and diversity takes the shape of an S-shaped curve that an be fitted by a logistic equation. To explain this phenomenon, we introduce a new parameter called "substitutability" into the list of capabilities or factors of products in the tri-partite network model (i.e., the country-capability-product model) of Hidalgo et al. As we observe, when the substitutability is zero, the model returns to Hidalgo's original model but failed to reproduce the S-shaped curve. However, in a plot of data, the data increasingly resembles an the S-shaped curve as the substitutability expands. Therefore, the diversity ceiling effect can be explained by the substitutability of different capabilities.

physics.soc-ph↗

arXiv2013

Structural and vibrational properties of phenanthrene under pressure

The structural and vibrational properties of phenanthrene are measured at high pressures up to 30.2 GPa by Raman spectroscopy and synchrotron x-ray diffraction techniques. Two phase transitions are observed in raman spectra under pressures of 2.3 GPa and 5.4 GPa with significant changes of intermolecular and intramolecular vibrational modes, and all the raman peaks disappeared in the luminesce background above 10.2 GPa. Upon further compression above 20.0 GPa, three broad bands are observed respectively around 1600, 2993 and 3181 cm$^{-1}$ in Raman spectra, strongly indicating that phenanthrene has transformed into amorphous hydrogenated carbon. Based on x-ray diffraction, the structures of corresponding phases observed in Raman spectra are identified with space group of $P_{\rm}2_{1}$ for phase I at 0-2.2 GPa, $P_{\rm}$2/\emph{m} for phase II at 2.2-5.6 GPa and $P_{\rm}$2/\emph{m}+\emph{Pmmm} for phase III at 5.6-11.4 GPa, and the structure above 11.4 GPa is identified with space group of \emph{Pmmm}. Although phenanthrene has amorphized above 20.0 GPa, the amorphous hydrogenated carbon clusters still remain the crystalline characteristic based on x-ray diffraction patterns. Our results suggest that the long-range periodicity and the local disorder state coexist in phenanthrene at high pressures.

cond-mat.supr-con↗

arXiv2013

Allometry and Dissipation of Ecological Flow Networks

An ecological flow network is a weighted directed graph in which nodes are species, edges are "who eats whom" relationships and weights are rates of energy or nutrients transfer between species. Allometric scaling is a ubiquitous feature for flow systems like river basins, vascular networks and food webs. By "ecological network analysis" method, we can reveal the hidden allometry directly on the original flow networks without cutting edges. On the other hand, dissipation law, which is another significant scaling relationship between the energy dissipation (respiration) and the throughflow of any species is also discovered on the collected flow networks. Interestingly, the exponents of allometric law ($η$) and the dissipation law ($γ$) have a strong connection for both empirical and simulated flow networks. The dissipation law exponent $γ$ rather than the topology of the network is the most important ingredient to the allometric exponent $η$. By reinterpreting $η$ as the inequality of species impacts (direct and indirect influences) to the whole network along all energy flow pathways but not the energy transportation efficiency, we found that as $γ$ increases, the relative energy loss of large nodes (with high throughflow) increases, $η$ decreases, and the inequality of the whole flow network as well as the relative importance of large species decreases. Therefore, flow structure and thermodynamic constraint are connected.

q-bio.PE↗

arXiv2012

Growing Random Geometric Graph Models of Super-linear Scaling Law

Recent researches on complex systems highlighted the so-called super-linear growth phenomenon. As the system size $P$ measured as population in cities or active users in online communities increases, the total activities $X$ measured as GDP or number of new patents, crimes in cities generated by these people also increases but in a faster rate. This accelerating growth phenomenon can be well described by a super-linear power law $X \propto P^γ$($γ>1$). However, the explanation on this phenomenon is still lack. In this paper, we propose a modeling framework called growing random geometric models to explain the super-linear relationship. A growing network is constructed on an abstract geometric space. The new coming node can only survive if it just locates on an appropriate place in the space where other nodes exist, then new edges are connected with the adjacent nodes whose number is determined by the density of existing nodes. Thus the total number of edges can grow with the number of nodes in a faster speed exactly following the super-linear power law. The models cannot only reproduce a lot of observed phenomena in complex networks, e.g., scale-free degree distribution and asymptotically size-invariant clustering coefficient, but also resemble the known patterns of cities, such as fractal growing, area-population and diversity-population scaling relations, etc. Strikingly, only one important parameter, the dimension of the geometric space, can really influence the super-linear growth exponent $γ$.

physics.soc-ph↗

arXiv2012

The Decentralized Structure of Collective Attention on the Web

Background: The collective browsing behavior of users gives rise to a flow network transporting attention between websites. By analyzing the structure of this network we uncovered a nontrivial scaling regularity concerning the impact of websites. Methodology: We constructed three clickstreams networks, whose nodes were websites and edges were formed by the users switching between sites. We developed an indicator Ci as a measure of the impact of site i and investigated its correlation with the traffic of the site Ai both on the three networks and across the language communities within the networks. Conclusions: We found that the impact of websites increased slower than their traffic. Specifically, there existed a scaling relationship between Ci and Ai with an exponent gamma smaller than 1. We suggested that this scaling relationship characterized the decentralized structure of the clickstream circulation: the World Wide Web is a system that favors small sites in reassigning the collective attention of users.

cs.IR↗

arXiv2012

Common Patterns of Energy Flow and Biomass Distribution on Weighted Food Webs

Weights of edges and nodes on food webs which are available from the empirical data hide much information about energy flows and biomass distributions in ecosystem. We define a set of variables related to weights for each species $i$, including the throughflow $T_i$, the total biomass $X_i$, and the dissipated flow $D_i$ (output to the environment) to uncover the following common patterns in 19 empirical weighted food webs: (1) DGBD distributions (Discrete version of a Generalized Beta Distribution), a kind of deformed Zipf's law, of energy flow and storage biomass; (2) The allometric scaling law $T_i\propto X_i^α$, which can be viewed as the counterpart of the Kleiber's 3/4 law at the population level; (3) The dissipation law $D_i\propto T_i^β$; and (4) The gravity law, including univariate version $f_{ij}\propto (T_iT_j)^γ$ and bivariate approvement $f_{ij}\propto T_i^{γ_1}T_j^{γ_2}$. These patterns are very common and significant in all collected webs, as a result, some remarkable regularities are hidden in weights.

q-bio.PE↗

arXiv2011

Toward a General Understanding of the Scaling Laws in Human and Animal Mobility

Recent research highlighted the scaling property of human and animal mobility. An interesting issue is that the exponents of scaling law for animals and humans in different situations are quite different. This paper proposes a general optimization model, a random walker following scaling laws (whose traveling distances in each step obey a power law distribution with exponent α) tries to diversify its visiting places under a given total traveling distance with a home-return probability. The results show that different optimal exponents in between 1 and 2 can emerge naturally. Therefore, the scaling property of human and animal mobility can be understood in our framework where the discrepancy of the scaling law exponents is due to the home-return constraint under the maximization of the visiting places diversity.

physics.bio-ph↗