Jun-ichi Inoue

Hokkaido University, Sapporo, Hokkaidō, Japan

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Publications (70)23.94 Total impact

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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.
    09/2014;
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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.
    08/2014;
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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.
    06/2014;
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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.
    arXiv: 1406.2874. 06/2014;
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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.
    03/2014;
  • 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.
    02/2014;
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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;
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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 $S_{i}=0$.
    09/2013;
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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.
    09/2013;
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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.
    09/2013;
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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).
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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.
  • 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;
  • 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.
    Econophysics of Systemic Risk and Network Dynamics. 01/2013;
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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 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.
    Journal of Statistical Mechanics Theory and Experiment 05/2012; 2012(07). · 1.87 Impact Factor
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    He Chen, T. Ibuki, J. Inoue
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    ABSTRACT: On the basis of statistical mechanics, we introduce a probabilistic model of labor markets for university graduates in Japan. In order to make a model of the market efficiently, we shall take into account the following assumptions. Namely, each company fixes the number of opening positions for newcomers and the number itself is independent of business year. The ability of gathering newcomers depends on the result of matching process in past business years. This fact means that the ability of the company is weaken if the company did not make their quota or the company gathered applicants too much over the quota. All labors, in particular, university graduates who are looking for their jobs can access the public information about the ranking of companies. By assuming the above essential key points, we construct the energy function of each company and describe the probability that an arbitrary company gets students at each business year by a Boltzmann-Gibbs distribution. We evaluate the relevant physical quantities such as the employment rate. We find that the system undergoes a phase transition from the `good employment phase' to `poor employment phase' with spontaneous symmetry breaking when one controls the degree of importance for the ranking. With the assistance of a chaotic map for the inflation rate given by Neugart (2004), we also attempt to draw the so-called Philips curve. The condition on which the long-time average of inflation rate becomes negative with high unemployment rate, which might be regard as an indicator for a sort of `crisis' is discussed.
    SICE Annual Conference (SICE), 2011 Proceedings of; 10/2011
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    ABSTRACT: In the past two decades, a series of international conferences on Statistical Physics, going by the name Statphys Kolkata, have been organized in Kolkata (previously Calcutta) at roughly three-year intervals, the first one being held in 1992–93. The seventh of this series, Statphys Kolkata VII (http://www.saha.ac.in/cmp/stat.vii/index.php) was held from 26–30 November 2010. This meeting was organized as part of the Silver Jubilee Celebration of the Satyendra Nath Bose National Centre for Basic Sciences, Kolkata, in collaboration with the Saha Institute of Nuclear Physics, Kolkata. In Statphys Kolkata VII, a few topics of current interest such as Collective behavior and emergent phenomena, Systems far from equilibrium, Soft matter, and Quantum critical phenomena were given special emphasis, while various other issues of Statistical Physics were also addressed. We were happy to note that the conference attracted a large number of participants, and the talk and poster sessions generated a lot of discussions, arguments and collaborations. The articles appearing in this proceedings are based on the invited talks and selected poster presentations. We would like to thank the Journal of Physics Conference Series, IOP, for publishing the proceedings of the conference, and the referees for their prompt and active support. The proceedings of the earlier Statphys Kolkata conferences have appeared in Physica A, vol 384 (2007); Physica A, vol 346 (2005); Physica A, vol 318 (2003); Physica A, vol 270 (1999); Physica A, vol 224 (1996); and Physica A, vol 186 (1992). We would like to take this opportunity to thank all the members of the organizing committee (especially Dr Anjan Kumar Chandra for extensive all-round help), and acknowledge the Centre for Applied Mathematics and Computational Science (CAMCS, Saha Institute of Nuclear Physics, Kolkata) and Satyendra Nath Bose National Centre for Basic Sciences, Kolkata, for their financial support. Jayanta Kumar Bhattacharjee, Bikas K Chakrabarti, Jun-Ichi Inoue and Parongama SenConvenors and Editors of the proceedings
    Journal of Physics Conference Series 05/2011; 297(1):011001.
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    Jun-ichi Inoue
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    ABSTRACT: As a mathematical model of associative memories, the Hopfield model was now well-established and a lot of studies to reveal the pattern-recalling process have been done from various different approaches. As well-known, a single neuron is itself an uncertain, noisy unit with a finite unnegligible error in the input-output relation. To model the situation artificially, a kind of 'heat bath' that surrounds neurons is introduced. The heat bath, which is a source of noise, is specified by the 'temperature'. Several studies concerning the pattern-recalling processes of the Hopfield model governed by the Glauber-dynamics at finite temperature were already reported. However, we might extend the 'thermal noise' to the quantum-mechanical variant. In this paper, in terms of the stochastic process of quantum-mechanical Markov chain Monte Carlo method (the quantum MCMC), we analytically derive macroscopically deterministic equations of order parameters such as 'overlap' in a quantum-mechanical variant of the Hopfield neural networks (let us call "quantum Hopfield model" or "quantum Hopfield networks"). For the case in which non-extensive number $p$ of patterns are embedded via asymmetric Hebbian connections, namely, $p/N \to 0$ for the number of neuron $N \to \infty$ ('far from saturation'), we evaluate the recalling processes for one of the built-in patterns under the influence of quantum-mechanical noise.
    Journal of Physics Conference Series 03/2011;
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    Hikaru Hino, Jun-Ichi Inoue
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    ABSTRACT: We attempt to reconstruct macroscopic properties of a stochastic labor market from the view point of its microscopic descrip-tions. Especially, we derive the so-called Philips curve which generally possesses a universal fitting form: (inflation rate) = (unemployment rate) c + b, b, c < 0. To check the validity of our probabilistic modeling, we compare our numerical results with the corresponding empirical evidence in Japanese labor markets from 1970's to 2000's.
    01/2011;
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    Jun-ichi Inoue, Yohei Saika, Masato Okada
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    ABSTRACT: We consider the problem of digital halftoning from the view point of statistical mechanics. The digital halftoning is a sort of image processing, namely, representing each grayscale in terms of black and white binary dots. The digital halftoning is achieved by making use of the threshold mask, namely, for each pixel, the halftoned binary pixel is determined as black if the original grayscale pixel is greater than or equal to the mask value and is determined as white vice versa. To determine the optimal value of the mask on each pixel for a given original grayscale image, we first assume that the human-eyes might recognize the black and white binary halftoned image as the corresponding grayscale one by linear filters. The Hamiltonian is constructed as a distance between the original and the recognized images which is written in terms of the threshold mask. We are confirmed that the system described by the Hamiltonian is regarded as a kind of antiferromagnetic Ising model with quenched disorders. By searching the ground state of the Hamiltonian, we obtain the optimal threshold mask and the resulting halftoned binary dots simultaneously. From the power-spectrum analysis, we find that the binary dots image is physiologically plausible from the view point of human-eyes modulation properties. We also propose a theoretical framework to investigate statistical performance of inverse digital halftoning, that is, the inverse process of halftoning. From the Bayesian inference view point, we rigorously show that the Bayes-optimal inverse-halftoning is achieved on a specific condition which is very similar to the so-called Nishimori line in the research field of spin glasses. Comment: 20 pages, 27 figures, using revtex4
    11/2010;

Publication Stats

114 Citations
23.94 Total Impact Points

Institutions

  • 1970–2014
    • Hokkaido University
      • • Graduate School of Information Science and Technology
      • • Graduate School of Engineering
      Sapporo, Hokkaidō, Japan
  • 2005–2010
    • Saha Institute of Nuclear Physics
      • Theoretical Condensed Matter Physics Division
      Calcutta, Bengal, India
  • 2007
    • Sony Corporation
      Edo, Tōkyō, Japan