arXiv subjects

Jinshan Wu

Publications and source records attributed to Jinshan Wu.

At least 19 recordsLinked to original sources

arXiv2026

Language Hierarchization Provides the Optimal Solution to Human Working Memory Limits

Language is a uniquely human trait, conveying information efficiently by organizing word sequences in sentences into hierarchical structures. A central question persists: Why is human language hierarchical? In this study, we show that hierarchization optimally solves the challenge of our limited working memory capacity. We established a likelihood function that quantifies how well the average number of units according to the language processing mechanisms aligns with human working memory capacity (WMC) in a direct fashion. The maximum likelihood estimate (MLE) of this function, tehta_MLE, turns out to be the mean of units. Through computational simulations of symbol sequences and validation analyses of natural language sentences, we uncover that compared to linear processing, hierarchical processing far surpasses it in constraining the tehta_MLE values under the human WMC limit, along with the increase of sequence/sentence length successfully. It also shows a converging pattern related to children's WMC development. These results suggest that constructing hierarchical structures optimizes the processing efficiency of sequential language input while staying within memory constraints, genuinely explaining the universal hierarchical nature of human language.

cs.CL↗

arXiv2023

Two indicators rule them all: Mean and standard deviation used to calculate other journal indicators based on log-normal distribution of citation counts

Two journal-level indicators, respectively the mean ($m^i$) and the standard deviation ($v^i$) are proposed to be the core indicators of each journal and we show that quite several other indicators can be calculated from those two core indicators, assuming that yearly citation counts of papers in each journal follows more or less a log-normal distribution. Those other journal-level indicators include journal h index, journal one-by-one-sample comparison citation success index $S_j^i$, journal multiple-sample $K^i-K^j$ comparison success rate $S_{j,K^j}^{i,K^i }$, and minimum representative sizes $κ_j^i$ and $κ_i^j$, the average ranking of all papers in a journal in a set of journals($R^t$). We find that those indicators are consistent with those calculated directly using the raw citation data ($C^i=\{c_1^i,c_2^i,\dots,c_{N^i}^i \},\forall i$) of journals. In addition to its theoretical significance, the ability to estimate other indicators from core indicators has practical implications. This feature enables individuals who lack access to raw citation count data to utilize other indicators by simply using core indicators, which are typically easily accessible.

cs.DL↗

arXiv2021

Free utility model for explaining the social gravity law

Social gravity law widely exists in human travel, population migration, commodity trade, information communication, scientific collaboration and so on. Why is there such a simple law in many complex social systems is an interesting question. Although scientists from fields of statistical physics, complex systems, economics and transportation science have explained the social gravity law, a theoretical explanation including two dominant mechanisms, namely individual interaction and bounded rationality, is still lacking. Here we present a free utility model, whose objective function is mathematically consistent with the Helmholtz free energy in physics, from the perspective of individual choice behavior to explain the social gravity law. The basic assumption is that bounded rational individuals interacting with each other will trade off the expected utility and information-processing cost to maximize their own utility. The previous explanations of the social gravity law including the maximum entropy model, the free cost model, the Logit model and the destination choice game model are all special cases under our model. Further, we extend the free utility model to the network. This model not only helps us to better understand the underlying mechanisms of spatial interaction patterns in complex social systems, but also provides a new perspective for understanding the potential function in game theory and the user equilibrium model in transportation science.

physics.soc-ph↗

arXiv2020

Quantum Inspired Word Representation and Computation

Word meaning has different aspects, while the existing word representation "compresses" these aspects into a single vector, and it needs further analysis to recover the information in different dimensions. Inspired by quantum probability, we represent words as density matrices, which are inherently capable of representing mixed states. The experiment shows that the density matrix representation can effectively capture different aspects of word meaning while maintaining comparable reliability with the vector representation. Furthermore, we propose a novel method to combine the coherent summation and incoherent summation in the computation of both vectors and density matrices. It achieves consistent improvement on word analogy task.

cs.CL↗

arXiv2017

Do Mathematicians, Economists and Biomedical Scientists Trace Large Topics More Strongly Than Physicists?

In this work, we extend our previous work on largeness tracing among physicists to other fields, namely mathematics, economics and biomedical science. Overall, the results confirm our previous discovery, indicating that scientists in all these fields trace large topics. Surprisingly, however, it seems that researchers in mathematics tend to be more likely to trace large topics than those in the other fields. We also find that on average, papers in top journals are less largeness-driven. We compare researchers from the USA, Germany, Japan and China and find that Chinese researchers exhibit consistently larger exponents, indicating that in all these fields, Chinese researchers trace large topics more strongly than others. Further correlation analyses between the degree of largeness tracing and the numbers of authors, affiliations and references per paper reveal positive correlations -- papers with more authors, affiliations or references are likely to be more largeness-driven, with several interesting and noteworthy exceptions: in economics, papers with more references are not necessary more largeness-driven, and the same is true for papers with more authors in biomedical science. We believe that these empirical discoveries may be valuable to science policy-makers.

physics.soc-ph↗

arXiv2017

Allometric Scaling in Scientific Fields

Allometric scaling can reflect underlying mechanisms, dynamics and structures in complex systems; examples include typical scaling laws in biology, ecology and urban development. In this work, we study allometric scaling in scientific fields. By performing an analysis of the outputs/inputs of various scientific fields, including the numbers of publications, citations, and references, with respect to the number of authors, we find that in all fields that we have studied thus far, including physics, mathematics and economics, there are allometric scaling laws relating the outputs/inputs and the sizes of scientific fields. Furthermore, the exponents of the scaling relations have remained quite stable over the years. We also find that the deviations of individual subfields from the overall scaling laws are good indicators for ranking subfields independently of their sizes.

physics.soc-ph↗

arXiv2015

Interrelations among scientific fields and their relative influence revealed by input-output analysis

In this paper, we try to answer two questions about any given scientific discipline: First, how important is each subfield and second, how does a specific subfield influence other subfields? We modify the well-known open-system Leontief Input-Output Analysis in economics into a closed-system analysis focusing on eigenvalues and eigenvectors and the effects of removing one subfield. We apply this method to the subfields of physics. This analysis has yielded some promising results for identifying important subfields (for example the field of statistical physics has large influence while it is not among the largest subfields) and describing their influences on each other (for example the subfield of mechanical control of atoms is not among the largest subfields cited by quantum mechanics, but our analysis suggests that these fields are strongly connected). This method is potentially applicable to more general systems that have input-output relations among their elements.

physics.soc-ph↗

arXiv2014

Rényi Information flow in the Ising model with single-spin dynamics

The $n$-index Rényi mutual information and transfer entropy for the two-dimensional kinetic Ising model with arbitrary single-spin dynamics in the thermodynamic limit are derived as functions of thermodynamic quantities. By means of Monte Carlo simulations with the Wolff algorithm, we calculate the information flows in the Ising model with the Metropolis dynamics and the Glauber dynamics. We find that, not only the global Rényi transfer entropy, but also the pairwise Rényi transfer entropy peaks in the disorder phase. Therefore, the Rényi information flows may be used as better tools than the Shannon counterparts in the study of phase transitions in complex dynamical systems.

cond-mat.stat-mech↗

arXiv2014

Games on graphs: A minor modification of payoff scheme makes a big difference

Various social dilemma games that follow different strategy updating rules have been studied on many networks.The reported results span the entire spectrum, from significantly boosting,to marginally affecting,to seriously decreasing the level of cooperation.Experimental results that are qualitatively different from theoretical prediction have also been reported.It is widely believed that the results are largely determined by three elements,including payoff matrices of the underlying 2*2 games,the way that the strategic states of the players are updated and the structure of the networks.Here we discuss the impact of a seemly non-essential mechanism -- what we refer to as a "payoff scheme". Specifically, in each round after the states of all of the players are determined,the payoff scheme is how each player's payoff is calculated.In addition to the two conventions in which either the accumulated or the averaged payoff is calculated from playing with all of the neighboring players,we here study the effects of calculating the payoff from pairing up with one random player from among the neighboring players. Based on probability theory, in a situation of uncorrelated events, the average payoff that involves all of the neighbors should,in principal,be equivalent to the payoff from pairing up with one neighbor.However,our simulation of games on graphs shows that, in many cases,the two payoff schemes lead to qualitatively different levels of cooperation.This finding appears to provide a possible explanation for a wide spectrum of observed behaviors in the literature.We have also observed that results from the randomly-pairing-one mechanism are more robust than the involving-all-neighbours mechanism because,in the former case, neither the other three main elements nor the initial states of the players have a large impact on the final level of cooperation compared with in the latter case.

physics.soc-ph↗

arXiv2014

Logical gaps in the approximate solutions of the social learning game and an exact solution

After the social learning models were proposed, finding the solutions of the games becomes a well-defined mathematical question. However, almost all papers on the games and their applications are based on solutions built upon either an add-hoc argument or a twisted Bayesian analysis of the games. Here, we present logical gaps in those solutions and an exact solution of our own. We also introduced a minor extension to the original game such that not only logical difference but also difference in action outcomes among those solutions become visible.

physics.soc-ph↗

arXiv2014

From sparse to dense and from assortative to disassortative in online social networks

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.

physics.soc-ph↗

arXiv2013

Stability of Mixed-Strategy-Based Iterative Logit Quantal Response Dynamics in Game Theory

Using the Logit quantal response form as the response function in each step, the original definition of static quantal response equilibrium (QRE) is extended into an iterative evolution process. QREs remain as the fixed points of the dynamic process. However, depending on whether such fixed points are the long-term solutions of the dynamic process, they can be classified into stable (SQREs) and unstable (USQREs) equilibriums. This extension resembles the extension from static Nash equilibriums (NEs) to evolutionary stable solutions in the framework of evolutionary game theory. The relation between SQREs and other solution concepts of games, including NEs and QREs, is discussed. Using experimental data from other published papers, we perform a preliminary comparison between SQREs, NEs, QREs and the observed behavioral outcomes of those experiments. For certain games, we determine that SQREs have better predictive power than QREs and NEs.

physics.soc-ph↗

arXiv2013

Phase transitions in Ising model induced by weight redistribution on weighted regular networks

In order to investigate the role of the weight in weighted networks, the collective behavior of the Ising system on weighted regular networks is studied by numerical simulation. In our model, the coupling strength between spins is inversely proportional to the corresponding weighted shortest distance. Disordering link weights can effectively affect the process of phase transition even though the underlying binary topological structure remains unchanged. Specifically, based on regular networks with homogeneous weights initially, randomly disordering link weights will change the critical temperature of phase transition. The results suggest that the redistribution of link weights may provide an additional approach to optimize the dynamical behaviors of the system.

cond-mat.stat-mech↗

arXiv2013

Do scientists trace hot topics?

Do scientists follow hot topics in their scientific investigations? In this paper, by performing analysis to papers published in the American Physical Society (APS) Physical Review journals, it is found that papers are more likely to be attracted by hot fields, where the hotness of a field is measured by the number of papers belonging to the field. This indicates that scientists generally do follow hot topics. However, there are qualitative differences among scientists from various countries, among research works regarding different number of authors, different number of affiliations and different number of references. These observations could be valuable for policy makers when deciding research funding and also for individual researchers when searching for scientific projects.

physics.soc-ph↗

arXiv2013

Efficient learning strategy of Chinese characters based on network approach

Based on network analysis of hierarchical structural relations among Chinese characters, we develop an efficient learning strategy of Chinese characters. We regard a more efficient learning method if one learns the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW) strategy, which is based on a new measure of nodes' importance that takes into account both the weight of the nodes and the hierarchical structure of the network. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.

physics.soc-ph↗

arXiv2010

Emergence of Global Preferential Attachment From Local Interaction

Global degree/strength based preferential attachment is widely used as an evolution mechanism of networks. But it is hard to believe that any individual can get global information and shape the network architecture based on it. In this paper, it is found that the global preferential attachment emerges from the local interaction models, including distance-dependent preferential attachment (DDPA) evolving model of weighted networks(M. Li et al, New Journal of Physics 8 (2006) 72), acquaintance network model(J. Davidsen et al, Phys. Rev. Lett. 88 (2002) 128701) and connecting nearest-neighbor(CNN) model(A. Vazquez, Phys. Rev. E 67 (2003) 056104). For DDPA model and CNN model, the attachment rate depends linearly on the degree or strength, while for acquaintance network model, the dependence follows a sublinear power law. It implies that for the evolution of social networks, local contact could be more fundamental than the presumed global preferential attachment. This is onsistent with the result observed in the evolution of empirical email networks.

cond-mat.stat-mech↗

arXiv2010

Non-equilibrium BBGKY Hierarchy from the Redfield Equation

A BBGKY-like hierarchy is derived from the non-equilibrium Redfield equation. Two further approximations are introduced and each can be used to truncate and solve the hierarchy. In the first approximation such a truncation is performed by replacing two-particle Green's functions (GFs) in the hierarchy by their values at equilibrium. The second method is developed based on the cluster expansion, which constructs two-particle GFs from one-particle GFs and neglects the correlation part. A non-equilibrium Wick's Theorem is proved to provide a basis for this non-equilibrium cluster expansion. Using those two approximations, our method of solving the Redfield equation, for instance, of an N-site chain of interacting spinless fermions, involves an eigenvalue problem with dimension $2^{N}$ and a linear system with dimension $N^2$ in the first case, and a nonlinear equation with dimension $N^2$ in the second case, which can be solved iteratively via a sequence of $N^2$ linear systems. Other currently available direct methods correspond to a linear system or an eigenvalue system with dimension $4^N$ plus an eigenvalue system with dimension $2^N$. As a test of the methods, for small systems with size N=4, results are found to be consistent with results made available by other direct methods. Although not discussed here, extending both methods to their next levels is straightforward. This indicates a promising potential for this BBGKY-like approach of non-equilibrium kinetic equations.

cond-mat.stat-mech↗

arXiv2010

Kubo formula for finite size systems

We demonstrate that the proper calculation of the linear response for finite-size systems can only be performed if the coupling to the leads/baths is explicitly taken into consideration. We exemplify this by obtaining a Kubo-type formula for heat transport in a finite-size system coupled to two thermal baths, kept at different temperatures. We show that the proper calculation results in a well-behaved response, without the singular contributions from degenerate states encountered when Kubo formulae for infinite-size systems are inappropriately used for finite-size systems.

cond-mat.stat-mech↗