Jun-ichi Inoue

Hokkaido University, Sapporo, Hokkaidō, Japan

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Publications (81)41.04 Total impact

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    ABSTRACT: Social inequality is a topic of interest since ages, and has attracted researchers across disciplines to ponder over it origin, manifestation, characteristics, consequences, and finally, the question of how to cope with it. It is manifested across different strata of human existence, and is quantified in several ways. In this review we discuss the origins of social inequality, the historical and commonly used non-entropic measures such as Lorenz curve, Gini index and the recently introduced $k$ index. We also discuss some analytical tools that aid in understanding and characterizing them. Finally, we argue how statistical physics modeling helps in reproducing the results and interpreting them.
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    ABSTRACT: Social inequality manifested across different strata of human existence can be quantified in several ways. Here we compute non-entropic measures of inequality such as Lorenz curve, Gini index and the recently introduced k index analytically from known distribution functions. We characterize the distribution functions of different quantities such as votes, journal citations, city size, etc. with suitable fits, compute their inequality measures and compare with the analytical results. A single analytic function is often not sufficient to fit the entire range of the probability distribution of the empirical data, and fit better to two distinct functions with a single crossover point. Here we provide general formulas to calculate these inequality measures for the above cases. We attempt to specify the crossover point by minimizing the gap between empirical and analytical evaluations of measures. Regarding the k index as an `extra dimension', both the lower and upper bounds of the Gini index are obtained as a function of the k index. This type of inequality relations among inequality indices might help us to check the validity of empirical and analytical evaluations of those indices.
    Physica A: Statistical Mechanics and its Applications 07/2015; 429:184-204. DOI:10.1016/j.physa.2015.01.082 · 1.72 Impact Factor
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    Mitsuaki Murota · Jun-ichi Inoue
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    ABSTRACT: We carry out a large-scale empirical data analysis to examine the efficiency of the so-called pairs trading. On the basis of relevant three thresholds $(\theta,\varepsilon,\Omega)$, namely, starting ($\theta$), profit-taking ($\varepsilon$) and stop-loss ($\Omega$), for the `first-passage process' of the spread (gap) between two highly-correlated stocks, we construct an effective strategy to make a trade via `active' stock-pairs automatically. The algorithm is applied to about $1,784$ stocks listed on the first section of the Tokyo Stock Exchange leading up to totally ${}_{1,784}C_{2}=1,590,436$ pairs. We are numerically confirmed that the asset management by means of the pairs trading works effectively at least for the past three years (2010-2012) data sets in the sense that the profit rate becomes positive (totally positive arbitrage) in most cases of the possible combinations of thresholds $(\theta,\varepsilon,\Omega)$ (`absorbing boundaries' in the literature of first-passage processes).
    12/2014; DOI:10.1007/s40844-015-0002-5
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    Jun-ichi Inoue
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    ABSTRACT: We present a brief review on information processing, computing and inference via quantum fluctuation, and clarify the relationship between the probabilistic information processing and theory of quantum spin glasses through the analysis of the infinite-range model. We also argue several issues to be solved for the future direction in the research field.
    The European Physical Journal Special Topics 09/2014; 224(1). DOI:10.1140/epjst/e2015-02348-x · 1.76 Impact Factor
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    Malay Banerjee · Anirban Chakraborti · Jun-ichi Inoue
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    ABSTRACT: In this paper, we investigate the dynamical properties of a psychological uplift in lovers. We first evaluate extensively the dynamical equations which were recently given by Rinaldi et. al., Physica A 392, pp.3231-3239 (2013). Then, the dependences of the equations on several parameters are numerically examined. From the view point of lasting partnership for lovers, especially, for married couples, one should optimize the parameters appearing in the dynamical equations to maintain the love for their respective partners. To achieve this optimization, we propose a new idea where the parameters are stochastic variables and the parameters in the next time step are given as expectations over a Boltzmann-Gibbs distribution at a finite temperature. This idea is very general and might be applicable to other models dealing with human relationships.
    Nonlinear Maps and their Applications, Edited by Ricardo López-Ruiz, Danièle Fournier-Prunaret, Yoshifumi Nishio, Clara Grácio, 08/2014; Springer., ISBN: 978-3-319-12327-1
  • Yosuke Otsubo · Jun-Ichi Inoue · Kenji Nagata · Masato Okada
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    ABSTRACT: We examine the average-case performance of a code-division multiple-access (CDMA) multiuser demodulator in which quantum fluctuations are utilized to demodulate the original message within the context of Bayesian inference. The quantum fluctuations are built into the system as a transverse field in the infinite-range Ising spin glass model. We evaluate the performance measurements by using statistical mechanics. We confirm that the CDMA multiuser modulator using quantum fluctuations achieve roughly the same performance as the conventional CDMA multiuser modulator through thermal fluctuations on average. We also find that the relationship between the quality of the original information retrieval and the amplitude of the transverse field is somehow a "universal feature" in typical probabilistic information processing, viz., in image restoration, error-correcting codes, and CDMA multiuser demodulation.
    Physical Review E 07/2014; 90(1-1):012126. DOI:10.1103/PhysRevE.90.012126 · 2.33 Impact Factor
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    Takao Hishikawa · Jun-ichi Inoue
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    ABSTRACT: We propose a simple probabilistic model to explain the spatial structure of the rent distribution of housing market in city of Sapporo. Here we modify the mathematical model proposed by Gauvin et. al. Especially, we consider the competition between two distances, namely, the distance between house and center, and the distance between house and office. Computer simulations are carried out to reveal the self-organized spatial structure appearing in the rent distribution. We also compare the resulting distribution with empirical rent distribution in Sapporo as an example of cities designated by ordinance. We find that the lowest ranking agents (from the viewpoint of the lowest `willing to pay') are swept away from relatively attractive regions and make several their own `communities' at low offering price locations in the city.
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    Jun-ichi Inoue
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    ABSTRACT: We provide a mathematical model to investigate the resource allocation problem for agents, say, university graduates who are looking for their positions in labor markets. The basic model is described by the so-called Potts spin glass which is well-known in the research field of statistical physics. In the model, each Potts spin (a tiny magnet in atomic scale length) represents the action of each student, and it takes a discrete variable corresponding to the company he/she applies for. We construct the energy to include three distinct effects on the students' behavior, namely, collective effect, market history and international ranking of companies. In this model system, the correlations (the adjacent matrix) between students are taken into account through the pairwise spin-spin interactions. We carry out computer simulations to examine the efficiency of the model. We also show that some chiral representation of the Potts spin enables us to obtain some analytical insights into our labor markets.
  • Jun-ichi Inoue · He Chen
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    ABSTRACT: We provide a mathematical model to investigate the human resource allocation problem for agents, say, university graduates who are looking for their positions in labor markets. The basic model is described by the so-called Potts spin glass which is well-known in the research field of statistical physics. In the model, each Potts spin (a tiny magnet in atomic scale length) represents the action of each student, and it takes a discrete variable corresponding to the company he/she applies for. We construct the energy to include three distinct effects on the students' behavior, namely, collective effect, market history and international ranking of companies. In this model system, the correlations (the adjacent matrix) between students are taken into account through the pairwise spin-spin interactions. We carry out computer simulations to examine the efficiency of the model. We also show that some chiral representation of the Potts spin enables us to obtain some analytical insights into our labor markets.
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    Mitsuaki Murota · Jun-ichi Inoue
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    ABSTRACT: We propose a formula of time-series prediction by means of three states random field Ising model (RFIM). At the economic crisis due to disasters or international disputes, the stock price suddenly drops. The macroscopic phenomena should be explained from the corresponding microscopic view point because there are existing a huge number of active traders behind the crushes. Hence, here we attempt to model the artificial financial market in which each trader $i$ can choose his/her decision among `buying', `selling' or `staying (taking a wait-and-see attitude)', each of which corresponds to a realization of the three state Ising spin, namely, $S_{i}=+1$, -1 and $S_{i}=0$, respectively. The decision making of traders is given by the Gibbs-Boltzmann distribution with the energy function. The energy function contains three distinct terms, namely, the ferromagnetic two-body interaction term (endogenous information), random field term as external information (exogenous news), and chemical potential term which controls the number of traders who are watching the market calmly at the instance. We specify the details of the model system from the past financial market data to determine the conjugate hyper-parameters and draw each parameter flow as a function of time-step. Especially we will examine to what extent one can characterize the crisis by means of a brand-new order parameter --- `turnover' --- which is defined as the number of active traders who post their decisions $S_{i}=1,-1$, instead of $S_{i}=0$.
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    He Chen · Jun-ichi Inoue
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    ABSTRACT: Inspired by the unsupervised learning or self-organization in the machine learning context, here we attempt to draw `learning curve' for the collective behavior of job-seeking `zero-intelligence' labors in successive job-hunting processes. Our labor market is supposed to be opened especially for university graduates in Japan, where the students have several successive chances n=0,1,2,... to obtain their positions within an academic (business) year. In this sense, the `cumulative unemployment rate' in our model system is regarded as an error-measurement in the collective intelligence of students, and the job-hunting stage n-dependence of the error constructs a learning curve. In our simple toy-model of probabilistic labor market, the diversity of students' behavior is built-in by means of the Jaynes-Shannon's MaxEnt (Maximum Entropy) principle. Then, we discuss the speed of convergence for the error-measurement, where we consider a scenario in which the students do not use any information about the result of job-hunting processes in the previous stage. Our approach enables us to examine the existence of the condition on which macroscopic quantity, say, `stage-wise unemployment rate' becomes `scale-invariant' in the sense that it does not depend on the job-hunting stage n. From the macroscopic view point, the problem could be regarded as a human resource allocation.
    09/2013; 10(1). DOI:10.14441/eier.A2013004
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    He Chen · Jun-ichi Inoue
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    ABSTRACT: We introduce a toy probabilistic model to analyze job-matching processes in recent Japanese labor markets for university graduates by means of statistical physics. We show that the aggregation probability of each company is rewritten by means of non-linear map under several conditions. Mathematical treatment of the map enables us to discuss the condition on which the rankings of arbitrary two companies are reversed during the dynamics. The so-called `mismatch' between students and companies is discussed from both empirical and theoretical viewpoints.
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    Hiroyuki Kyan · Jun-ichi Inoue
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    ABSTRACT: We propose a simple probabilistic model of zapping behavior of television viewers. Our model might be regarded as a `theoretical platform' to investigate the human collective behavior in the macroscopic scale through the zapping action of each viewer at the microscopic level. The stochastic process of audience measurements as macroscopic quantities such as television program rating point or the so-called gross rating point (GRP for short) are reconstructed using the microscopic modeling of each viewer's decision making. Assuming that each viewer decides the television station to watch by means of three factors, namely, physical constraints on television controllers, exogenous information such as advertisement of program by television station, and endogenous information given by `word-of-mouth communication' through the past market history, we shall construct an aggregation probability of Gibbs-Boltzmann-type with the energy function. We discuss the possibility for the ingredients of the model system to exhibit the collective behavior due to not exogenous but endogenous information.
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    ABSTRACT: In order to figure out and to forecast the emergence phenomena of social systems, we propose several probabilistic models for the analysis of financial markets, especially around a crisis. We first attempt to visualize the collective behaviour of markets during a financial crisis through cross-correlations between typical Japanese daily stocks by making use of multi- dimensional scaling. We find that all the two-dimensional points (stocks) shrink into a single small region when a economic crisis takes place. By using the properties of cross-correlations in financial markets especially during a crisis, we next propose a theoretical framework to predict several time-series simultaneously. Our model system is basically described by a variant of the multi-layered Ising model with random fields as non-stationary time series. Hyper-parameters appearing in the probabilistic model are estimated by means of minimizing the 'cumulative error' in the past market history. The justification and validity of our approaches are numerically examined for several empirical data sets.
    Journal of Physics Conference Series 09/2013; 473(1). DOI:10.1088/1742-6596/473/1/012008
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    Giacomo Livan · Jun-ichi Inoue · Enrico Scalas
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    ABSTRACT: We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, more accurate, correlation estimates. Then, we investigate the possible consequences of instabilities in empirical correlation coefficient measurements on optimal portfolio selection. We rely on previously published works which provide a framework allowing us to take into account possible risk underestimations due to the non-optimality of the portfolio weights being used in order to distinguish such non-optimality effects from risk underestimations genuinely due to non-stationarities. We interpret such results in terms of instabilities in some spectral properties of portfolio correlation matrices.
  • Takero Ibuki · Sei Suzuki · Jun-ichi Inoue
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    ABSTRACT: We investigate cross-correlations between typical Japanese stocks collected through Yahoo!Japan website ( http://finance.yahoo.co.jp/ ). By making use of multi-dimensional scaling (MDS) for the cross-correlation matrices, we draw two-dimensional scattered plots in which each point corresponds to each stock. To make a clustering for these data plots, we utilize the mixture of Gaussians to fit the data set to several Gaussian densities. By minimizing the so-called Akaike Information Criterion (AIC) with respect to parameters in the mixture, we attempt to specify the best possible mixture of Gaussians. It might be naturally assumed that all the two-dimensional data points of stocks shrink into a single small region when some economic crisis takes place. The justification of this assumption is numerically checked for the empirical Japanese stock data, for instance, those around 11 March 2011.
  • Sei Suzuki · Jun-ichi Inoue · Bikas K. Chakrabarti
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    ABSTRACT: The transverse Ising model was introduced in 1960s to study an order-disorder transition in hydrogen-bonded ferroelectric systems. Later, a significant amount of efforts have been devoted to the study of transverse Ising models. As a result, a lot of basic properties of a zero-temperature quantum phase transition of quantum many-body systems, ground-state properties of a frustrated or disordered system in the presence of quantum fluctuations, and the nature of non-equilibrium dynamics of a quantum system driven by controlling quantum fluctuations have been so far clarified. Also the study of quantum computation and information processing using quantum fluctuations has progressed recently. After a brief historical introduction of the transverse Ising models, Chap. 1 presents a qualitative property of the models obtained by the simple mean field theory, and gives a summary of following chapters as well as a list of experimental systems well represented by the transverse Ising models.
    Lecture Notes in Physics 01/2013; DOI:10.1007/978-3-642-33039-1
  • Sei Suzuki · Jun-ichi Inoue · Bikas K. Chakrabarti
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    ABSTRACT: Competing interactions between spins or frustration give rise to intriguing many-body states with spatially modulated spin structures. The simplest model with the regular frustration is the classical axial next nearest neighbour Ising (ANNNI) model. The classical ANNNI model is described by a system of Ising spins with nearest neighbour interactions along all the lattice directions (x, y and z) as well as a competing next nearest neighbour interaction in one axial direction (z for instance). Chapter 4 discusses detailed results on quantum ANNNI models in a transverse field with a brief introduction to the classical model. Analytic studies on the basis of an interacting fermion representation of the model, real-space and field theoretic renormalisation group techniques, the numerical exact diagonalisation method, and Monte Carlo simulations have revealed a variety of ground-state phases of the quantum ANNNI chain. These are mentioned in Chap. 4. Studies of higher dimensional quantum ANNNI models are also presented there. Appendices of this chapter include details of approximate methods used in the study of the quantum ANNNI chain.
    01/2013: pages 73-103;
  • Sei Suzuki · Jun-ichi Inoue · Bikas K. Chakrabarti
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    ABSTRACT: Chapter 10 mentions the XY model in a transverse field and the Kitaev model as related models to the transverse Ising model. The XY model in a transverse field is another simplest model, except the transverse Ising model, that exhibits a zero-temperature quantum phase transition. It also gives the pseudo-spin representation of the BCS Hamiltonian of the superconductivity. The spin-1/2 transverse XY chain can be diagonalised by using the Jordan-Wigner transformation, as the transverse Ising chain is. The Kitaev model, on the other hand, can be transformed into a free fermion model coupled with a field, which commutes with the Hamiltonian, by the Jordan-Wigner transformation, though it is defined in two dimension. Several properties of the ground state and the dynamical behaviour following a slow quench of a parameter are mentioned.
    01/2013: pages 355-375;
  • Sei Suzuki · Jun-ichi Inoue · Bikas K. Chakrabarti
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    ABSTRACT: Chapter 11 provides a brief summary and an outlook of the book.
    01/2013: pages 377-379;