arXiv subjects
Publications and source records attributed to Jinshan Wu.
We investigate heat transport in various quantum spin chains, using the projector operator technique. We find that anomalous heat transport is linked not to the integrability of the Hamiltonian, but to whether it can be mapped to a model of non-interacting fermions. Our results also suggest how seemingly anomalous transport may occur at low temperatures in a much wider class of models.
Quantum Mechanics (QM) is a quantum probability theory based on the density matrix. The possibility of applying classical probability theory, which is based on the probability distribution function(PDF), to describe quantum systems is investigated in this work. In a sense this is also the question about the possibility of a Hidden Variable Theory (HVT) of Quantum Mechanics. Unlike Bell's inequality, which need to be checked experimentally, here HVT is ruled out by theoretical consideration. The approach taken here is to construct explicitly the most general HVT, which agrees with all results from experiments on quantum systems (QS), and to check its validity and acceptability. Our list of experimental facts of quantum objects, which all quantum theories are required to respect, includes facts on repeat quantum measurement. We show that it plays an essential role at showing that it is very unlikely that a classical theory can successfully reproduce all QS facts, even for a single spin-1/2 object. We also examine and rule out Bell's HVT and Bohm's HVT based on the same consideration.
Modularity Q is an important function for identifying community structure in complex networks. In this paper, we prove that the modularity maximization problem is equivalent to a nonconvex quadratic programming problem. This result provide us a simple way to improve the efficiency of heuristic algorithms for maximizing modularity Q. Many numerical results demonstrate that it is very effective.
The role of weight on the weighted networks is investigated by studying the effect of weight on community structures. We use weighted modularity $Q^w$ to evaluate the partitions and Weighted Extremal Optimization algorithm to detect communities. Starting from idealized and empirical weighted networks, the distribution or matching between weights and edges are disturbed. Using dissimilarity function $D$ to distinguish the difference between community structures, it is found that the redistribution of weights does strongly affect the community structure especially in dense networks. This indicates that the community structure in networks is a suitable property to reflect the role of weight.
Based on brief review of approaches for community identification and measurement for sensitivity characterization, the accuracy and precision of several approaches for detecting communities in weighted networks are investigated. In weighted networks, the community structure should take both links and link weights into account and the partition of networks should be evaluated by weighted modularity $Q^w$. The results reveal that link weight has important effects on communities especially in dense networks. Potts model and Weighted Extremal Optimization (WEO) algorithm work well on weighted networks. Then Potts model and WEO algorithms are used to detect communities in Rhesus monkey network. The results gives nice understanding for real community structure.
Link weight is crucial in weighted complex networks. It provides additional dimension for describing and adjusting the properties of networks. The topological role of weight is studied by the effects of random redistribution of link weights based on regular network with initial homogeneous weight. The small world effect emerges due to the weight randomization. Its effects on the dynamical systems coupled by weighted networks are also investigated. Randomization of weight can increase the transition temperature in Ising model and enhance the ability of synchronization of chaotic systems dramatically.
This paper uses a database of collaboration recording between Econophysics Scientists to study the community structure of this collaboration network, which with a single type of vertex and a type of undirected, weighted edge. Hierarchical clustering and the algorithm of Girvan and Newman are presented to analyze the data. And it emphasizes the influence of the weight to results of communities by comparing the different results obtained in different weights. A function D is proposed to distinguish the difference between above results. At last the paper also gives explanation to the results and discussion about community structure.
A new representation of Game Theory is developed in this paper. State of players is represented by a density matrix, and payoff function is a set of hermitian operators, which when applied onto the density matrix give the payoff of players. By this formulism, a new way to find the equilibria of games is given by generalizing the thermodynamical evolutionary process leading to equilibrium in Statistical Mechanics. And in this formulism, when quantum objects instead of classical objects are used as the objects in the game, it's naturally leads to the so-called Quantum Game Theory, but with a slight difference in the definition of strategy state of players: the probability distribution is replaced with a density matrix. Further more, both games of correlated and independent players can be reached in this single framework, while traditionally, they are treated separately by Non-cooperative Game Theory and Coalitional Game Theory. Because of the density matrix is used as state of players, besides classical correlated strategy, quantum entangled states can also be used as strategies, which is an entanglement of strategies between players, and it is different with the entanglement of objects' states as in the so-called Quantum Game Theory. At last, in the form of density matrix, a class of quantum games, where the payoff matrixes are commutative, can be reduced into classical games. In this sense, it will put the classical game as a special case of our quantum game.
Effect of replacing the classical game object with a quantum object is analyzed. We find this replacement requires a throughout reformation of the framework of Game Theory. If we use density matrix to represent strategy state of players, they are full-structured density matrices with off-diagonal elements for the new games, while reduced diagonal density matrix will be enough for the traditional games on classical objects. In such formalism, the payoff function of every player becomes Hermitian Operator acting on the density matrix. Therefore, the new game looks really like Quantum Mechanics while the traditional game becomes Classical Mechanics.
Inspired by scientific collaboration networks, especially our empirical analysis of the network of econophysicists, an evolutionary model for weighted networks is proposed. Both degree-driven and weight-driven models are considered. Compared with the BA model and other evolving models with preferential attachment, there are two significant generalizations. First, besides the new vertex added in at every time step, old vertices can also attempt to build up new links, or to reconnect the existing links. The reconnection between both new-old and old-old nodes are recorded and the connecting times on every link is converted into the weight of the link. This provides a natural way for the evolution of edge weight. Second, besides degree and the weight of vertices, a path-related local information is also used as a reference in the preferential attachment. The path-related preferential attachment mechanism significantly increases the clustering coefficient of the network. The model shows the scale-free phenomena in degree and weight distribution. It also gives well qualitatively consistent behavior with the empirical results.
In order to take the weight of connection into consideration and to find a natural measurement of weight, we have collected papers in Econophysics and constructed a network of scientific communication to integrate idea transportation among econophysicists by collaboration, citation and personal discussion. Some basic statistics such as weight per degree are discussed in \cite{fan}. In this paper, by including the papers published recently, further statistical results for the network are reported. Clustering coefficient of weighted network is introduced and empirically studied in this network. We also compare the typical statistics on this network under different weight measurements, including random and inverse weight. The conclusion from weight-randomized network is helpful to the investigation of the geometrical role of weight.
Using the representation introduced in our another paper\cite{frame}, the well-known Quantum Prisoner's Dilemma proposed in \cite{jens}, is reexpressed and calculated. By this example and the works in \cite{frame} on classical games and Quantum Penny Flip game, which first proposed in \cite{meyer}, we show that our new representation can be a general framework for games originally in different forms.
Using the representation introduced in \cite{frame}, an artificial game in quantum strategy space is proposed and studied. Although it has well-known classical correspondence, which has classical mixture strategy Nash Equilibrium states, the equilibrium state of this quantum game is an entangled strategy (operator) state of the two players. By discovering such behavior, it partially shows the independent meaning of the new representation. The idea of entanglement of strategies, instead of quantum states, is proposed, and in some sense, such entangled strategy state can be regarded as a cooperative behavior between game players.
In this paper, we introduce a framework of new mathematical representation of Game Theory, including static classical game and static quantum game. The idea is to find a set of base vectors in every single-player strategy space and to define their inner product so as to form them as a Hilbert space, and then form a Hilbert space of system state. Basic ideas, concepts and formulas in Game Theory have been reexpressed in such a space of system state. This space provides more possible strategies than traditional classical game and traditional quantum game. So besides those two games, more games have been defined in different strategy spaces. All the games have been unified in the new representation and their relation has been discussed. General Nash Equilibrium for all the games has been proposed but without a general proof of the existence. Besides the theoretical description, ideas and technics from Statistical Physics, such as Kinetics Equation and Thermal Equilibrium can be easily incorporated into Game Theory through such a representation. This incorporation gives an endogenous method for refinement of Equilibrium State and some hits to simplify the calculation of Equilibrium State. The more privileges of this new representation depends on further application on more theoretical and real games. Here, almost all ideas and conclusions are shown by examples and argument, while, we wish, lately, we can give mathematical proof for most results.
In another paper with the same name\cite{frame}, we proposed a new representation of Game Theory, but most results are given by specific examples and argument. In this paper, we try to prove the conclusions as far as we can, including a proof of equivalence between the new representation and the traditional Game Theory, and a proof of Classical Nash Theorem in the new representation. And it also gives manipulation definition of quantum game and a proof of the equivalence between this definition and the general abstract representation. A Quantum Nash Proposition is proposed but without a general proof. Then, some comparison between Nash Equilibrium (NE) and the pseudo-dynamical equilibrium (PDE) is discussed. At last, we investigate the possibility that whether such representation leads to truly Quantum Game, and whether such a new representation is helpful to Classical Game, as an answer to the questions in \cite{enk}. Some discussion on continuous-strategy games are also included.
In this paper we study the household-structure SIS epidemic spreading on general complex networks. The household structure gives us the way to distinguish inner and the outer infection rate. Unlike household-structure models on homogenous networks, such as regular and random networks, here we consider heterogeneous networks with arbitrary degree distribution p(k). First we introduce the epidemic model. Then rate equations under mean field appropriation and computer simulations are used here to analyze our model. Some unique phenomena only existing in divergent network with household structure is found, while we also get some similar conclusions that some simple geometrical quantities of networks have important impression on infection property of infectous disease. It seems that in our model even when local cure rate is greater than inner infection rate in every household, disease still can spread on scale-free network. It implies that no disease is spreading in every single household, but for the whole network, disease is spreading. Since our society network seems like this structure, maybe this conclusion remind us that during disease spreading we should pay more attention on network structure than local cure condition.
The development of Econophysics is studied from the perspective of scientific communication networks. Papers in Econophysics published from 1992 to 2003 are collected. Then a weighted and directed network of scientific communication, including collaboration, citation and personal discussion, is constructed. Its static geometrical properties, including degree distribution, weight distribution, weight per degree, and betweenness centrality, give a nice overall description of the research works. The way we introduced here to measure the weight of connections can be used as a general one to construct weighted network.
Econophysics is a new area developed recently by the cooperation between economists, mathematicians and physicists. It's not a tool to predict future prices of stocks and exchange rates. It applies idea, method and models in Statistical Physics and Complexity to analyze data from economical phenomena. In this paper, three examples from three active main topics in Econophysics are presented first. Then using these examples, we analyze the role of Physics in Econophysics. Some comments and emphasis on Physics of Econophysics are included. New idea of network analysis for economy systems is proposed, while the actual analysis is still in progress.