Jun-ichi Inoue

Hokkaido University, Sapporo, Hokkaidō, Japan

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Publications (59)24.3 Total impact

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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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    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.
    · 1.87 Impact Factor
  • 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;
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    Takero Ibuki, Jun-ichi Inoue
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    ABSTRACT: Statistical properties of order-driven double-auction markets with Bid-Ask spread are investigated through the dynamical quantities such as response function. We first attempt to utilize the so-called {\it Madhavan-Richardson-Roomans model} (MRR for short) to simulate the stochastic process of the price-change in empirical data sets (say, EUR/JPY or USD/JPY exchange rates) in which the Bid-Ask spread fluctuates in time. We find that the MRR theory apparently fails to simulate so much as the qualitative behaviour ('non-monotonic' behaviour) of the response function $R(l)$ ($l$ denotes the difference of times at which the response function is evaluated) calculated from the data. Especially, we confirm that the stochastic nature of the Bid-Ask spread causes apparent deviations from a linear relationship between the $R(l)$ and the auto-correlation function $C(l)$, namely, $R(l) \propto -C(l)$. To make the microscopic model of double-auction markets having stochastic Bid-Ask spread, we use the minority game with a finite market history length and find numerically that appropriate extension of the game shows quite similar behaviour of the response function to the empirical evidence. We also reveal that the minority game modeling with the adaptive ('annealed') look-up table reproduces the non-linear relationship $R(l) \propto -f(C(l))$ ($f(x)$ stands for a non-linear function leading to '$\lambda$-shapes') more effectively than the fixed (`quenched') look-up table does.
    Journal of Economic Interaction and Coordination 11/2010; · 0.57 Impact Factor
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    Motohiro Makiguchi, Jun-ichi Inoue
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    ABSTRACT: An effective procedure to determine the optimal parameters appearing in artificial flockings is proposed in terms of optimization problems. We numerically examine genetic algorithms (GAs) to determine the optimal set of parameters such as the weights for three essential interactions in BOIDS by Reynolds (1987) under `zero-collision' and `no-breaking-up' constraints. As a fitness function (the energy function) to be maximized by the GA, we choose the so-called the $\gamma$-value of anisotropy which can be observed empirically in typical flocks of starling. We confirm that the GA successfully finds the solution having a large $\gamma$-value leading-up to a strong anisotropy. The numerical experience shows that the procedure might enable us to make more realistic and efficient artificial flocking of starling even in our personal computers. We also evaluate two distinct types of interactions in agents, namely, metric and topological definitions of interactions. We confirmed that the topological definition can explain the empirical evidence much better than the metric definition does.
    Computing Research Repository - CORR. 11/2010;
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    Y. Saika, T. Kakimoto, J. Inoue
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    ABSTRACT: We investigate quantum annealing (QA) via the transverse interaction with XY-type anisotropy to the ground state problems for a toy model system composed of 4 S=l/2 quantum spins interacting with anti-ferromagnetic interactions. By solving the Schrodinger equation for the toy model system, we find that the QA succeeds in deriving the ground state of the toy model system, if the target system does not have non-trivial degeneracy in the ground state. Then, we also And that the QA selectively obtains a desirable solution among the degenerate ground states by tuning the XY-type anisotropy appropriately, when the target system has non-trivial degeneracy in the ground state. Then, the spin wave theory also finds that the toy model indicates similar properties in an infinite-volume limit. Next, we find that the ground state of the target system can be obtained even if we start annealing procedure from states including excited states of the kinetic energy term, when we set the time interval to be large in solving the Schrodinger equation.
    SICE Annual Conference 2010, Proceedings of; 09/2010
  • J. Inoue, Y. Saika, M. Okada
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    ABSTRACT: Statistical mechanics of information has been applied to problems in various research topics of information science and technology [1],[2]. Among those research topics, error-correcting code is one of the most developed subjects. In the research field of error-correcting codes, Nicolas Sourlas showed that the so-called convolutional codes can be constructed by spin glass with infinite range p-body interactions and the decoded message should be corresponded to the ground state of the Hamiltonian [3]. Ruján pointed out that the bit error can be suppressed if one uses finite temperature equilibrium states as the decoding result, instead of the ground state [4], and the so-called Bayes-optimal decoding at some specific condition was proved by Nishimori [5] and Nishimori and Wong [6]. Kabashima and Saad succeeded in constructing more practical codes, namely low-density parity check (LDPC) codes by using the infinite range spin glass model with finite connectivities [7]. They used the so-called TAP (Thouless–Anderson–Palmer) equations to decode the original message for a given parity check.
    07/2010: pages 283-295;
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    Motohiro Makiguchi, Jun-ichi Inoue
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    ABSTRACT: In real flocks, it was revealed that the angular density of nearest neighbors shows a strong {\it anisotropic structure} of individuals by very recent extensive field studies by Ballerini et al [{\it Proceedings of the National Academy of Sciences USA} {\bf 105}, pp.1232-1237 (2008)]. In this paper, we show that this empirical evidence in real flocks, namely, the structure of anisotropy also emerges in an artificial flock simulation based on the {\it BOIDS} by Reynolds [{\it Computer Graphics} {\bf 21}, pp.25-34 (1987)]. We numerically find that appropriate combinations of the weights for just only three essential factors of the BOIDS, namely, `Cohesion', `Alignment' and `Separation' lead to a strong anisotropy in the flock. This result seems to be highly counter-intuitive and also provides a justification of the hypothesis that the anisotropy emerges as a result of self-organization of interacting intelligent agents (birds for instance). To quantify the anisotropy, we evaluate a useful statistics (a kind of {\it order parameters} in statistical physics), that is to say, the so-called $\gamma$-value defined as an inner product between the vector in the direction of the lowest angular density of flocks and the vector in the direction of the moving of the flock. Our results concerning the emergence of the anisotropy through the $\gamma$-value might enable us to judge whether an arbitrary flock simulation seems to be {\it realistic} or not. Comment: 7 pages, 11 figures, Proceedings of the Operational Research Society Simulation Workshop 2010 (SW10)
    04/2010;
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    Manabu Kitagata, Jun-ichi Inoue
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    ABSTRACT: A general procedure of average-case performance evaluation for population dynamics such as genetic algorithms (GAs) is proposed and its validity is numerically examined. We introduce a learning algorithm of Gibbs distributions from training sets which are gene configurations (strings) generated by GA in order to figure out the statistical properties of GA from the view point of thermodynamics. The learning algorithm is constructed by means of minimization of the Kullback-Leibler information between a parametric Gibbs distribution and the empirical distribution of gene configurations. The formulation is applied to the solvable probabilistic models having multi-valley energy landscapes, namely, the spin glass chain and the Sherrington-Kirkpatrick model. By using computer simulations, we discuss the asymptotic behaviour of the effective temperature scheduling and the residual energy induced by the GA dynamics. Comment: 14 pages, 19 figures
    04/2010;
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    Yuya Inagaki, Jun-ichi Inoue
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    ABSTRACT: We numerically investigate a mean-field Bayesian approach with the assistance of the Markov chain Monte Carlo method to estimate motion velocity fields and probabilistic models simultaneously in consecutive digital images described by spatio-temporal Markov random fields. Preliminary to construction of our procedure, we find that mean-field variables in the iteration diverge due to improper normalization factor of regularization terms appearing in the posterior. To avoid this difficulty, we rescale the regularization term by introducing a scaling factor and optimizing it by means of minimization of the mean-square error. We confirm that the optimal scaling factor stabilizes the mean-field iterative process of the motion velocity estimation. We next attempt to estimate the optimal values of hyper-parameters including the regularization term, which define our probabilistic model macroscopically, by using the Boltzmann-machine type learning algorithm based on gradient descent of marginal likelihood (type-II likelihood) with respect to the hyper-parameters. In our framework, one can estimate both the probabilistic model (hyper-parameters) and motion velocity fields simultaneously. We find that our motion estimation is much better than the result obtained by Zhang and Hanouer (1995) in which the hyper-parameters are set to some ad-hoc values without any theoretical justification. Comment: 10 pages, 21 figures, using IEEEtran.cls
    04/2010;
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    Jun-ichi Inoue
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    ABSTRACT: In terms of the stochastic process of quantum-mechanical version of Markov chain Monte Carlo method (the MCMC), we analytically derive macroscopically deterministic flow equations of order parameters such as spontaneous magnetization in infinite-range ($d(=\infty)$-dimensional) quantum spin systems. By means of the Trotter decomposition, we consider the transition probability of Glauber-type dynamics of microscopic states for the corresponding $(d+1)$-dimensional classical system. Under the static approximation, differential equations with respect to macroscopic order parameters are explicitly obtained from the master equation that describes the microscopic-law. In the steady state, we show that the equations are identical to the saddle point equations for the equilibrium state of the same system. The equation for the dynamical Ising model is recovered in the classical limit. We also check the validity of the static approximation by making use of computer simulations for finite size systems and discuss several possible extensions of our approach to disordered spin systems for statistical-mechanical informatics. Especially, we shall use our procedure to evaluate the decoding process of Bayesian image restoration. With the assistance of the concept of dynamical replica theory (the DRT), we derive the zero-temperature flow equation of image restoration measure showing some `non-monotonic' behaviour in its time evolution. Comment: 14 pages, 6 figures, using jpconf.cls, Proceedings of IW-SMI2010 in Kyoto
    Journal of Physics Conference Series 04/2010;
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    ABSTRACT: In this talk, we attempt to make a microscopic modeling the first-passage process (or the first-exit process) of the BUND future by minority game with market history. We find that the first-passage process of the minority game with appropriate history length generates the same properties as the BTP future (the middle and long term Italian Government bonds with fixed interest rates), namely, both first-passage time distributions have a crossover at some specific time scale as is the case for the Mittag-Leffler function. We also provide a macroscopic (or a phenomenological) modeling of the first-passage process of the BTP future and show analytically that the first-passage time distribution of a simplest mixture of the normal compound Poisson processes does not have such a crossover.
    03/2010;

Publication Stats

97 Citations
24.30 Total Impact Points

Institutions

  • 1970–2013
    • 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