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Jun-ichi Inoue

Publications and source records attributed to Jun-ichi Inoue.

At least 19 recordsLinked to original sources

Magnon mediated spin entanglement in the strong coupling regime

We present that two spin defects (SDs) can be entangled through a magnon polariton mode, within the strong coupling regime. The magnonic modes are provided by an antiferromagnetic (AF) MnF$_{2}$ layer and their dispersion is characterized by the layer's thickness. The macroscopic quantum electrodynamics theory is used to describe the light-matter interactions, where the Green's functions are its core element. The individual SD relaxes by exciting the magnon polariton modes, exhibiting high enhancement values of the Purcell factor. When two SDs are considered, an oscillatory population exchange is observed between them, a sign of strong light-matter coupling, where the concurrence value is used to quantify the level of entanglement. The thinner AF layers can potentially be used to promote interactions between multiple spins through long range coupling, this is a desired feature to fabricate high demand applications in the fields of quantum measurement and computation.

quant-ph

Charge-carrier mobility in hydrogen-terminated diamond field-effect transistors

Diamond field-effect transistors (FETs) have potential applications in power electronics and high-output high-frequency amplifications. In such applications, high charge-carrier mobility is desirable for a reduced loss and high-speed operation. We have recently fabricated diamond FETs with a hexagonal-boron-nitride gate dielectric and observed a high mobility above 300 cm$^{2}$V$^{-1}$s$^{-1}$. In this study, we examine which scattering mechanism limits the mobility of our FETs through theoretical calculations. Our calculations reveal that the dominant carrier scattering is caused by surface charged impurities with the density of $\approx$1$\times10^{12}$ cm$^{-2}$, and suggest a possible increase in mobility over 1000 cm$^{2}$V$^{-1}$s$^{-1}$ by reducing the impurities.

cond-mat.mes-hall

Inequality measures in kinetic exchange models of wealth distributions

In this paper, we study the inequality indices for some models of wealth exchange. We calculated Gini index and newly introduced k-index and compare the results with reported empirical data available for different countries. We have found lower and upper bounds for the indices and discuss the efficiencies of the models. Some exact analytical calculations are given for a few cases. We also exactly compute the quantities for Gamma and double Gamma distributions.

physics.soc-ph

Online compressed sensing

In this paper, we explore the possibilities and limitations of recovering sparse signals in an online fashion. Employing a mean field approximation to the Bayes recursion formula yields an online signal recovery algorithm that can be performed with a computational cost that is linearly proportional to the signal length per update. Analysis of the resulting algorithm indicates that the online algorithm asymptotically saturates the optimal performance limit achieved by the offline method in the presence of Gaussian measurement noise, while differences in the allowable computational costs may result in fundamental gaps of the achievable performance in the absence of noise.

cs.IT

Social inequality: from data to statistical physics modeling

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.

physics.soc-ph

Large-scale empirical study on pairs trading for all possible pairs of stocks listed on the first section of the Tokyo Stock Exchange

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, namely, starting, profit-taking, and stop-loss 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 $1,784$ stocks listed on the first section of the Tokyo Stock Exchange leading up to totally $1,590,436$ 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 corresponding to `absorbing boundaries' in the literature of first-passage processes.

q-fin.TR

Infinite-range transverse field Ising models and quantum computation

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.

cond-mat.dis-nn

Maximizing a psychological uplift in love dynamics

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.

physics.soc-ph

Probabilistic flows of inhabitants in urban areas and self-organization in housing markets

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.

physics.soc-ph

Measuring social inequality with quantitative methodology: analytical estimates and empirical data analysis by Gini and $k$ indices

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.

physics.soc-ph

Statistical mechanics of human resource allocation: A mathematical modeling of job-matching in labor markets

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.

physics.soc-ph

Dynamics of probabilistic labor markets: statistical physics perspective

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.

q-fin.GN

Statistical Mechanics of Labor Markets

We introduce a probabilistic model of labor markets for university graduates, in particular, in Japan. To make a model of the market efficiently, we take into account several hypotheses. Namely, each company fixes the (business year independent) number of opening positions for newcomers. The ability of gathering newcomers depends on the result of job 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 university graduates who are looking for their jobs can access the public information about the ranking of companies. Assuming the above essential key points, we construct the local 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 sort of `phase transition' from the `good employment phase' to `poor employment phase' when one controls the degree of importance for the ranking.

q-fin.GN

Characterizing financial crisis by means of the three states random field Ising model

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 $S_{i}=0$.

q-fin.TR

Learning curve for collective behavior of zero-intelligence agents in successive job-hunting processes with a diversity of Jaynes-Shannon's MaxEnt principle

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.

q-fin.GN

Agent-based modeling of zapping behavior of viewers, television commercial allocation, and advertisement markets

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.

physics.data-an

Statistical inference of co-movements of stocks during a financial crisis

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.

q-fin.ST

On the non-stationarity of financial time series: impact on optimal portfolio selection

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.

q-fin.ST