arXiv subjects

Hiraku Nishimori

Publications and source records attributed to Hiraku Nishimori.

At least 19 recordsLinked to original sources

arXiv2026

A behavioral principle underlying attacker-defender interactions in soccer

Soccer is widely popular for its simple rules and complex yet coordinated play that unfolds on the pitch. Nevertheless, the fundamental mechanisms governing such play are not well understood: what shapes player interactions on the pitch? What short-term goals guide players' decisions about their movements over the next few seconds? We address these questions by focusing on one-on-one settings in open play, in which the attacker, in possession of the ball and typically dribbling, faces a defender aiming to stop or delay the attacker's actions over a short period. Here we develop a mathematical model of attacker-defender interactions and analyze 306 professional soccer games. Synthesizing the large-scale dataset with an analysis of the model reveals a simple behavioral principle that may underlie these interactions: the defender seeks to minimize their future relative speed to the attacker, whereas the attacker initiates their movements to preempt the defender's objective. This principle, relative-speed minimization, provides a consistent and unified account of the empirical data. Since our framework depends little on soccer-specific details, this principle may govern diverse pursuit-evasion scenarios as well as other invasion team sports.

physics.soc-ph↗

arXiv2025

Extinction and Metastability of Pheromone-Roads in Stochastic Models for Foraging Walks of Ants

Macroscopic changes of group behavior of eusocial insects are studied from the viewpoint of non-equilibrium phase transitions. Recent combined study of experiments and mathematical modeling by the group led by the third author suggests that a species of garden ant switches the individual foraging walk from pheromone-mediated to visual-cues-mediated depending on situation. If an initial pheromone-road between the nest and food sources is a detour, ants using visual cues can pioneer shorter paths. These shorter paths are reinforced by pheromone secreted by following ants, and then the detour ceases to exist. Once the old pheromone-road extincts, there will be almost no chance to reconstruct it. Hence the extinction of pheromone-road is expected to be regarded as a phase transition to an absorbing state. We propose a discrete-time model on a square lattice consisting of switching random walks interacting though time-dependent pheromone field. The numerical study shows that the critical phenomena of the present extinction transitions of pheromone-roads do not seem to belong to the directed percolation universality class associated with the usual absorbing-state transition. The new aspects are cased by the coexistence and competition with newly creating pheromone-roads. In a regime in the extinction phase, the annihilating road shows metastability and takes long time-period to be replaced by a new road.

cond-mat.stat-mech↗

arXiv2025

Interacting Particle Systems Modeling Self-Propelled Motions

In non-equilibrium statistical physics, active matters in both living and non-living systems have been extensively studied. In particular, self-propelled particle systems provide challenging research subjects in experimental and theoretical physics, since individual and collective behaviors of units performing persistent motions can not be described by usual fluctuation theory for equilibrium systems. A typical example of man-made self-propelled systems which can be easily handled in small-sized experiments is a system of camphor floats put on the surface of water. Based on the experimental and theoretical studied by Nishimori et al. (J. Phys. Soc. Jpn. 86 (2017) 101012), we propose a new type of mathematical models for complex motions of camphor disks on the surface of water. In the previous mathematical models introduced by Nishimori et al. are coupled systems of the equations of motion for camphor disks described by ordinary differential equations and the partial differential equation for the concentration field of camphor molecules in water. Here we consider coupled systems of equation of motions of camphor disks and random walks representing individual camphor molecules in water. In other words, we take into account non-equilibrium fluctuations by introducing stochastic processes into the deterministic models. Numerical simulation shows that our models can represent self-propelled motions of individual camphor disk as well as repulsive interactions among them. We focus on the one-dimensional models in which viscosity is dominant, and derive a dynamical system of a camphor disk by taking the average of random variables of our stochastic system. By studying both of stochastic models and dynamical systems, we clarify the transitions between three phases of motions for a camphor disk depending on parameters.

cond-mat.stat-mech↗

arXiv2024

Switching particle systems for foraging ants showing phase transitions in path selections

Switching interacting particle systems studied in probability theory are the stochastic processes of hopping particles on a lattice made up of slow and fast particles, where the switching between these types of particles occurs randomly at a given transition rate. This paper explores how such stochastic processes involving multiple particles can model group behaviors of ants. Recent experimental research by the last author's group has investigated how ants switch between two types of primarily relied cues to select foraging paths based on the current situation. Here, we propose a discrete-time interacting random walk model on a square lattice, incorporating two types of hopping rules. Numerical simulation results demonstrate global changes in selected homing paths, transitioning from trailing paths of the `pheromone road' to nearly optimal paths depending on the switching parameters. By introducing two types of order parameters characterizing the dependence of homing duration distributions on switching parameters, we discuss these global changes as phase transitions in ant path selections. We also study critical phenomena associated with continuous phase transitions.

cond-mat.stat-mech↗

arXiv2020

Stabilization of straight longitudinal dune under bimodal wind with large directional variation

It has been observed that the direction in which a sand dune extends its crest line depends on seasonal variation of wind direction; when the variation is small, the crest line develops more or less perpendicularly to the mean wind direction to form a transverse dune with some undulation. In the case of bimodal wind with a large relative angle, however, the dune extends its crest along the mean wind direction and evolves into an almost straight longitudinal dune. Motivated by these observations, we investigate the dynamical stability of isolated dunes using the crest line model, where the dune dynamics is represented by its crest line motion. First, we extend the previous linear stability analysis under the unidirectional wind to the case with non-zero slant angle between the wind direction and the normal direction of the crest line, and show that the stability diagram does not depend on the slant angle. Secondly, we examine how the linear stability is affected by the seasonal changes of wind direction in the case of bimodal wind with equal strength and duration. For the transverse dune, we find that the stability is virtually the same with that for the unidirectional wind as long as the dune evolution during a season is small. On the other hand, in the case of the longitudinal dune, the dispersions of the growth rates for the perturbation are drastically different from those of the unidirectional wind, and we find that the largest growth rate is always located at $k = 0$. This is because the growth of the perturbation with $k \ne 0$ is canceled by the alternating wind from opposite sides of the crest line even though it grows during each duration period of the bimodal wind.

cond-mat.soft↗

arXiv2019

Simple particle model for low-density granular flow interacting with ambient fluid

To understand the process of pattern formation in a low-density granular flow, we propose a simple particle model. This model considers spherical particles moving over an inclined flat surface based on three forces: gravity as the driving force, repulsive force due to particle collision, and drag force as the particle-- interaction through the ambient fluid. Numerical simulations of this model are conducted in two different types of two-dimensional planes, i.e., the monolayer was treated. In the horizontal plane parallel to the slope, particles aggregate at the moving front of the granular flow; and subsequently, flow instability occurs as a wavy pattern. This flow pattern is caused by the interparticle interaction arising from the drag force. Additionally, a vortex convection of particles is formed inside the aggregations. Meanwhile, in the vertical plane on the slope, particle aggregation is also found at the moving front of the granular flow. The aggregation resembles a head--tail structure, where the frontal angle against the slope approaches 60 degree from a larger angle as time progresses. Comparing the numerical result by varying the particle size, the qualitative dynamics of the granular flow are independent of size. To elucidate this reason, we perform a nondimensionalization for this model. The result indicates that our model can be simplified to dimensionless equations with one dimensionless parameter that represents the ratio of the gravity term to the excluded volume effect.

cond-mat.soft↗

arXiv2019

Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging

A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when stochasticity to the sensitivity of pheromone for ants is introduced in the model.

nlin.AO↗

arXiv2015

Splash Detail Due to Grain Incident on Granular Bed

Using the discrete element method (DEM), we study the splash processes induced by the impact of a grain on two types of granular beds, namely, randomly packed and FCC-structured beds.Good correspondence is obtained between our numerical results and the findings of previous experiments, and it is demonstrated that the packing structure of the granular bed strongly affects the splash process.The mean ejection angle for the randomly packed bed is consistent with previous experimental results. The FCC-structured bed yields a larger mean ejection angle; however, the latter result has not been confirmed experimentally. Furthermore, the ejection angle distributions and the vertical ejection speeds for individual grains vary depending on the relative timing at which the grains are ejected after the initial impact. Obvious differences are observed between the distributions of grains ejected during the earlier and later splash periods: the form of the vertical ejection speed distribution varies from a power-law form to a lognormal form with time, and more than 80\% of the kinetic energy of all ejected grains is used for earlier ejected grains.

cond-mat.soft↗

arXiv2015

Rate equation model of phototransduction into the membranous disks of mouse rod cells

A theoretical model was developed to investigate the rod phototransduction process in the mouse. In particular, we explored the biochemical reactions of several chemical components that contribute to the signaling process into/around the membranous disks in the outer segments of the rod cells. We constructed a rate equation model incorporating the molecular crowding effects of rhodopsin according to experimental results, which may hinder the diffusion of molecules on the disk mem- brane. The present model could effectively reproduce and explain the mechanisms of the following phenomena observed in experiments. First, the activations and relaxation of the wild-type mouse rod cell progressed more slowly than those of mutant cells containing half the amount of rhodopsin on the disk membrane. Second, the strong photoactivated state of the cell was sustained for a longer period when the light stimuli were strong. Finally, the lifetime of photoactivation exhibited a logarithmic increase with increasing light strength given exposure to strong light stimuli.

physics.bio-ph↗

arXiv2015

Excluded volume effect enhances the homology pairing of model chromosomes

To investigate the structural dynamics of the homology pairing of polymers, we mod- eled the scenario of homologous chromosome pairings during meiosis in Schizosaccharomyces pombe, one of the simplest model organisms of eukaryotes. We consider a simple model consist- ing of pairs of homologous polymers with the same structures that are confined in a cylindrical container, which represents the local parts of chromosomes contained in an elongated nucleus of S. pombe. Brownian dynamics simulations of this model showed that the excluded volume effects among non-homological chromosomes and the transitional dynamics of nuclear shape serve to enhance the pairing of homologous chromosomes.

physics.bio-ph↗

arXiv2015

Simple Elastic Network Models for Exhaustive Analysis of Long Double-Stranded DNA Dynamics with Sequence Geometry Dependence

Simple elastic network models of DNA were developed to reveal the structure-dynamics relationships for several nucleotide sequences. First, we propose a simple all-atom elastic network model of DNA that can explain the profiles of temperature factors for several crystal structures of DNA. Second, we propose a coarse-grained elastic network model of DNA, where each nucleotide is described only by one node. This model could effectively reproduce the detailed dynamics obtained with the all-atom elastic network model according to the sequence-dependent geometry. Through normal-mode analysis for the coarse-grained elastic network model, we exhaustively analyzed the dynamic features of a large number of long DNA sequences, approximately $\sim 150$ bp in length. These analyses revealed positive correlations between the nucleosome-forming abilities and the inter-strand fluctuation strength of double-stranded DNA for several DNA sequences.

physics.bio-ph↗

arXiv2013

Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.

q-bio.BM↗

arXiv2012

Collective Motion and Phase Transitions of Symmetric Camphor Boats

The motion of several self-propelled boats in a narrow channel displays spontaneous pattern formation and kinetic phase transitions. In contrast with previous studies on self-propelled particles, this model does not require stochastic fluctuations and it is experimentally accessible. By varying the viscosity in the system, it is possible to form either a stationary state, correlated or uncorrelated oscillations, or unidirectional flow. Here, we describe and analyze these self organized patterns and their transitions.

cond-mat.stat-mech↗

arXiv2012

Swarming of Self-Propelled Camphor Boats

When an ensemble of self-propelled camphor boats move in a one-dimensional channel, they exhibit a variety of collective behaviors. Under certain conditions, the boats tend to cluster together and move in a relatively tight formation. This type of behavior, referred to as clustering or swarming here, is one of three types recently observed in experiment. Similar clustering behavior is also reproduced in simulations based on a simple theoretical model. Here we examine this model to determine the clustering mechanism and the conditions under which clustering occurs. We also propose a method of quantifying the behavior that may be used in future experimental work.

cond-mat.soft↗

arXiv2012

Segregation pattern reorientation of granular mixture on horizontally oscillating tray

Reorientation of the segregation pattern of a binary granular mixture on a two-dimensional hor- izontally oscillating tray is numerically realized. The mixture consists of large-and-heavy particles and small-and-light particles, the segregation pattern of which shows a transition between a striped pattern perpendicular to the oscillation and that parallel to the oscillating direction according to the change of area-fractions of two types of particles. The transition mechanism is discussed on the basis of a simplified 1-dimensional dynamics.

nlin.PS↗

arXiv2012

Bifurcation analysis of the transition of dune shape under unidirectional wind

A bifurcation analysis of dune shape transition is made. By use of a reduced model of dune morphodynamics, dune skeleton model, we elucidate the transition mechanism between different shapes of dunes under unidirectional wind. It was found that the decrease in the total amount of sand in the system and/or the lateral sand flow shifts the stable state from a straight transverse dune to wavy transverse dune through a pitchfork bifurcation. A further decrease causes wavy transverse dunes to shift into barchans through a Hopf bifurcation. These bifurcation structures reveal the transition mechanism of dune shapes under unidirectional wind.

nlin.PS↗

arXiv2010

Saddle-Node Bifurcation to Jammed State for Quasi-One-Dimensional Counter Chemotactic Flow

The transition of a counter chemotactic particle flow from a free-flow state to a jammed state in a quasi-one-dimensional path is investigated. One of the characteristic features of such a flow is that the constituent particles spontaneously form a cluster that blocks the path, called a path-blocking cluster (PBC), and causes a jammed state when the particle density is greater than a threshold value. Near the threshold value, the PBC occasionally desolve itself to recover the free flow. In other words, the time evolution of the size of the PBC governs the flux of a counter chemotactic flow. In this paper, on the basis of numerical results of a stochastic cellular automata (SCA) model, we introduce a Langevin equation model for the size evolution of the PBC that reproduces the qualitative characteristics of the SCA model. The results suggest that the emergence of the jammed state in a quasi-one-dimensional counter flow is caused by a saddle-node bifurcation.

nlin.CG↗

arXiv2010

Effective Stochastic Resonance under Heterogeneous Amplitude of Noise

Effective stochastic resonance (SR) is numerically and analytically studied using a model with coupled two particles exposed to heterogeneous, i.e., particles dependent, amplitude of noise. Compared to previous SR models of single particle and to those of coupled two particles exposed to equivalent amplitude of noise, the present model exhibits a more intensive resonance of, at least, one particle exposed to the non-larger amplitude of noise with the assistance of another particle. In a certain range of conditions, this effective resonance of one particle overwhelms the poor resonance of the other particle, meaning that heterogeneous amplitude of noise leads the system, not only locally but also in the average of the whole, to the effective SR.

cond-mat.stat-mech↗