arXiv subjects

Kyosuke Adachi

Publications and source records attributed to Kyosuke Adachi.

At least 19 recordsLinked to original sources

arXiv2026

Beyond local detailed balance: Microscopic rates reshape nonequilibrium phase behavior

Local detailed balance (LDB) is a central guiding principle for modeling nonequilibrium stochastic dynamics, yet it only constrains the ratio of forward and backward transition rates and does not fix the steady state. Although the functional form of rates under the same LDB has been shown to affect steady-state correlations and transition temperatures, whether it can qualitatively reshape phase behavior in strongly interacting systems, such as the morphology and stability of phase-separated patterns, remains unclear. Here, for a two-dimensional driven lattice gas with attractive nearest-neighbor interactions, we consider hopping rates with a parameter that preserves the same LDB but tunes asymmetry along the driving force. We find that this parameter controls qualitative phase behavior: in the homogeneous phase, it reverses the sign of the structure-factor discontinuity and hence the anisotropy in long-range density correlations; in the phase-separated regime, it switches the orientation of anisotropic patterns and their long-time stability. Both effects are coherently captured by an approximate fluctuating hydrodynamic equation. The results demonstrate that, in contrast to equilibrium systems, qualitative features of nonequilibrium phases are controlled by the specific choice of dynamical rules even under the same LDB.

cond-mat.stat-mech↗

arXiv2026

Loop expansion in polymer field theory: application to phase separation

Liquid-liquid phase separation underlies phenomena ranging from protein condensate formation to the phase coexistence of synthetic polymers. Although the random phase approximation (RPA) is widely used to predict such phase behavior, its quantitative accuracy for binodals of polymer solutions, particularly outside the high-density regime, remains incompletely characterized. Here, we develop a field theoretic loop expansion in homopolymer systems by identifying the inverse polymer density $\rho^{-1}$ as the Planck constant $\hbar$ in quantum field theory. We calculate the leading-order and next-to-leading-order corrections to the RPA free energy, denoted as RPA+ and RPA++, respectively. Testing the binodal predicted by the RPA+ against molecular dynamics simulations of bead-spring chains with Gaussian pair interactions, we find that the RPA+ qualitatively improves the dilute-phase coexistence density over the RPA, while the critical point error remains comparable to that of the RPA. Our results establish the loop expansion as a systematic route for refining the RPA-based binodal predictions for polymer phase separation.

cond-mat.soft↗

arXiv2026

Mean-Field Convective Phase Separation under Thermal Gradients

Nonequilibrium conditions fundamentally change how systems undergo phase separation. In systems with temperature gradients, attractive particles have been shown to form periodic patterns and steady convective currents, but a clear theoretical explanation for this behavior is still missing. Here, we present a dynamical mean-field model that describes the mechanism behind this convective phase separation. Using linear stability analysis, we show that the transition from a uniform state to a periodic pattern is driven by the emergence of a dominant unstable mode. Numerical simulations confirm the predicted phase diagram and demonstrate that these convective currents are a robust feature of the steady state, appearing regardless of the initial conditions. These results provide a direct approach for understanding how temperature gradients drive the formation of steady-state convective patterns.

cond-mat.stat-mech↗

arXiv2025

Convection Patterns in Nonequilibrium Kawasaki Dynamics at Low Temperature

We study a conservative stochastic lattice gas (Kawasaki dynamics) coupled in the bulk to a heat bath, which leads to standard phase separation at low uniform temperatures. Instead, a macroscopic temperature gradient drives the system into a nonequilibrium steady state. In this state, the usual long-range order is replaced by robust convection patterns, featuring regularly spaced stripe structures. We show that these nonequilibrium states differ markedly from equilibrium configurations with the same local temperature profiles. Finally, we develop a macroscopic description that captures these behaviors and provides a unified framework for understanding the observed patterns.

cond-mat.stat-mech↗

arXiv2025

Bubble formation in active binary mixture model

Phase separation, the spontaneous segregation of density, is a ubiquitous phenomenon observed across diverse physical and biological systems. Within a crowd of motile elements, active phase separation emerges from the interplay of activity (i.e., self-propulsion) and density interactions. A striking feature of active phase separation is the persistent formation of dilute-phase bubbles within the dense phase, which has been explored in theoretical models. However, the fundamental parameters that systematically control bubble formation remain unclear in conventional self-propelled particle models. Here, we introduce an active binary mixture model in which solutes and solvents dynamically exchange positions on a lattice; both solutes and solvents are self-propelled particles, but solvents play a role analogous to empty space in typical dry active matter. Within this model, we find that spontaneous bubble formation of solvents can be tuned by activity asymmetry, which is the difference between the solute and solvent activities. Numerical simulations reveal that moderate solvent activity enhances bubble formation, while larger solvent activity, comparable to solute activity, suppresses it. By employing mean-field theory, which captures essential phase behaviors, we consider the mechanism for the enhancement of bubble formation induced by solvent activity. Beyond these findings, when solute and solvent activities are equal, we apply the finite-size scaling analysis to estimate the critical exponents for active phase separation under the suppression of bubbles. Our findings establish activity asymmetry as a key control parameter for active matter phase transitions, offering new insights into universality in nonequilibrium systems.

cond-mat.soft↗

arXiv2024

Does the random nature of cell-virus interactions during in vitro infections affect TCID$_{50}$ measurements and parameter estimation by mathematical models?

Endpoint dilution (TCID50) assays cannot count the number of infectious virions (IVs), and instead are limited to counting the number of Specific INfections caused by the sample (SIN). The latter depends not only on whether virions are infectious, but also on the cells and the experimental conditions under which they interact. These interactions are random and controlled by parameters such as the rates at which IVs lose infectivity, enter cells, or fail to replicate following cell entry. Here, stochastic TCID50 assays are simulated to determine how the random number of infected wells relates to the parameters and the number of IVs in a sample. We introduce a new parameter estimation method based on the likelihood of observing a given TCID50 assay outcome given the model-predicted number of IVs in the sample. We then successively evaluate how parameter estimates are affected by the use of: 1) the new likelihood function vs the typical assumption of Gaussian-distributed measurement errors; 2) IV vs SIN units to express virus in the model; and 3) a stochastic vs an ODE model to simulate the course of a virus infection. Unlike previous methods, the new likelihood correctly handles measurements beyond the detection limits, and results in non-Gaussian distributions. Expressing virus using IV units makes it possible to impose physical constraints (e.g. one IV cannot infect more than one cell), and yields more biologically useful parameters (e.g. mutation emergence likelihood depends on the number of IVs, not SIN, produced). Using a stochastic rather than an ODE model we show that the variability observed between replicate in vitro virus infections is consistent with the level of stochasticity introduced by the TCID50 assay, which can be reduced through better assay design. The framework introduced herein offers several important improvements over current methods and should be widely adopted.

physics.bio-ph↗

arXiv2024

Dynamical phase transitions in single particle Brownian motion without drift

Dynamical phase transitions (DPTs) arise from qualitative changes in the long-time behavior of stochastic trajectories, often observed in systems with kinetic constraints or driven out of equilibrium. Here we demonstrate that first-order DPTs can occur even in the large deviations of a single Brownian particle without drift, but only when the system's dimensionality exceeds four. These DPTs are accompanied by temporal phase separations in the trajectories and exhibit dimension-dependent order due to the threshold behavior for bound state formation in Schr\"{o}dinger operators. We also discover second-order DPTs in one-dimensional Brownian motion, characterized by universal exponents in the rate function of dynamical observables. Our results establish a novel framework linking classical DPTs to quantum phase transitions.

cond-mat.stat-mech↗

arXiv2024

Universality in the dynamical phase transitions of Brownian motion

We study the dynamical phase transitions (DPTs) appearing for a single Brownian particle without drift. We first explore how first-order DPTs in large deviations can be found even for a single Brownian particle without any force upon raising the dimension to higher than four. The DPTs accompany temporal phase separations in their dynamical paths, which we numerically confirm by fitting to scaling functions. We next investigate how second-order DPTs can appear in one-dimensional free Brownian motion by choosing the observable, which essentially captures the localization transition of the trajectories. We discuss and confirm that the DPTs predicted for high dimensions can also be found when considering many Brownian particles at lower dimensions.

cond-mat.stat-mech↗

arXiv2024

Power-law correlation in the homogeneous disordered state of anisotropically self-propelled systems

Self-propelled particles display unique collective phenomena, due to the intrinsic coupling of density and polarity. For instance, the giant number fluctuation appears in the orientationally ordered state, and the motility-induced phase separation appears in systems with repulsion. Effects of strong noise typically lead to a homogeneous disordered state, in which the coupling of density and polarity can still play a significant role. Here, we study universal properties of the homogeneous disordered state in two-dimensional systems with uniaxially anisotropic self-propulsion. Using hydrodynamic arguments, we propose that the density correlation and polarity correlation generically exhibit power-law decay with distinct exponents (-2 and -4, respectively) through the coupling of density and polarity. Simulations of self-propelled lattice gas models indeed show the predicted power-law correlations, regardless of whether the interaction type is repulsion or alignment. Further, by mapping the model to a two-component boson system and employing non-Hermitian perturbation theory, we obtain the analytical expression for the structure factors, the Fourier transform of the correlation functions. This reveals that even the first order of the interaction strength induces the power-law correlations.

cond-mat.stat-mech↗

arXiv2024

Predicting heteropolymer interactions: demixing and hypermixing of disordered protein sequences

Cells contain multiple condensates which spontaneously form due to the heterotypic interactions between their components. Although the proteins and disordered region sequences that are responsible for condensate formation have been extensively studied, the rule of interactions between the components that allow demixing, i.e., the coexistence of multiple condensates, is yet to be elucidated. Here we construct an effective theory of the interaction between heteropolymers by fitting it to the molecular dynamics simulation results obtained for more than 200 sequences sampled from the disordered regions of human proteins. We find that the sum of amino acid pair interactions across two heteropolymers predicts the Boyle temperature qualitatively well, which can be quantitatively improved by the dimer pair approximation, where we incorporate the effect of neighboring amino acids in the sequences. The improved theory, combined with the finding of a metric that captures the effective interaction strength between distinct sequences, allowed the selection of up to three disordered region sequences that demix with each other in multicomponent simulations, as well as the generation of artificial sequences that demix with a given sequence.The theory points to a generic sequence design strategy to demix or hypermix thanks to the low dimensional nature of the space of the interactions that we identify. As a consequence of the geometric arguments in the space of interactions, we find that the number of distinct sequences that can demix with each other is strongly constrained, irrespective of the choice of the coarse-grained model. Altogether, we construct a theoretical basis for methods to estimate the effective interaction between heteropolymers, which can be utilized in predicting phase separation properties as well as rules of assignment in the localization and functions of disordered proteins.

cond-mat.soft↗

arXiv2023

Activity-induced ferromagnetism in one-dimensional quantum many-body systems

We study a non-Hermitian quantum many-body model in one dimension analogous to the Vicsek model or active spin models, and investigate its quantum phase transitions. The model consists of two-component hard-core bosons with ferromagnetic interactions and activity, i.e., spin-dependent asymmetric hopping. Numerical results show the emergence of a ferromagnetic order induced by the activity, a quantum counterpart of flocking, that even survives in the absence of ferromagnetic interaction. We confirm this phenomenon by proving that activity generally increases the ground state energies of the paramagnetic states, whereas the ground state energy of the ferromagnetic state does not change. By solving the two-particle case, we find that the effective alignment is caused by avoiding the bound state formation due to the non-Hermitian skin effect in the paramagnetic state. We employ a two-site mean-field theory based on the two-particle result and qualitatively reproduce the phase diagram. We further numerically study a variant of our model with the hard-core condition relaxed, and confirm the robustness of ferromagnetic order emerging due to activity.

cond-mat.quant-gas↗

arXiv2023

Universal properties of repulsive self-propelled particles and attractive driven particles

Motility-induced phase separation (MIPS) is a nonequilibrium phase separation that has a different origin from equilibrium phase separation induced by attractive interactions. Similarities and differences in collective behaviors between these two types of phase separation have been intensely discussed. Here, to study another kind of similarity between MIPS and attraction-induced phase separation under a nonequilibrium condition, we perform simulations of active Brownian particles with uniaxially anisotropic self-propulsion (uniaxial ABPs) in two dimensions. We find that (i) long-range density correlation appears in the homogeneous state, (ii) anisotropic particle configuration appears in MIPS, where the anisotropy removes the possibility of microphase separation suggested for isotropic ABPs [X.-Q. Shi et al., Phys. Rev. Lett. 125, 168001 (2020)], and (iii) critical phenomena for the anisotropic MIPS presumably belong to the universality class for two-dimensional uniaxial ferromagnets with dipolar long-range interactions. Properties (i)-(iii) are common to the well-studied randomly driven lattice gas (RDLG), which is a particle model that undergoes phase separation by attractive interactions under external driving forces, suggesting that the origin of phase separation is not essential for macroscopic behaviors of uniaxial ABPs and RDLG. Based on the observations in uniaxial ABPs, we construct a coarse-grained Langevin model, which shows properties (i)-(iii) and corroborates the generality of the findings.

cond-mat.stat-mech↗

arXiv2022

Vortex dynamics in the two-dimensional BCS-BEC crossover

The Bardeen-Cooper-Schrieffer (BCS) condensation and Bose-Einstein condensation (BEC) are the two limiting ground states of paired Fermion systems, and the crossover between these two limits has been a source of excitement for both fields of high temperature superconductivity and cold atom superfluidity. For superconductors, ultra-low doping systems like graphene and LixZrNCl successfully approached the crossover starting from the BCS-side. These superconductors offer new opportunities to clarify the nature of charged-particles transport towards the BEC regime. Here we report the study of vortex dynamics within the crossover using their Hall effect as a probe in LixZrNCl. We observed a systematic enhancement of the Hall angle towards the BCS-BEC crossover, which was qualitatively reproduced by the phenomenological time-dependent Ginzburg-Landau (TDGL) theory. LixZrNCl exhibits a band structure free from various electronic instabilities, allowing us to achieve a comprehensive understanding of the vortex Hall effect and thereby propose a global picture of vortex dynamics within the crossover. These results demonstrate that gate-controlled superconductors are ideal platforms towards investigations of unexplored properties in BEC superconductors.

cond-mat.supr-con↗

arXiv2022

Universal constraint on nonlinear population dynamics

Ecological and evolutionary processes show various population dynamics depending on internal interactions and environmental changes. While crucial in predicting biological processes, discovering general relations for such nonlinear dynamics has remained a challenge. Here, we derive a universal information-theoretical constraint on a broad class of nonlinear dynamical systems represented as population dynamics. The constraint is interpreted as a generalization of Fisher's fundamental theorem of natural selection. Furthermore, the constraint indicates nontrivial bounds for the speed of critical relaxation around bifurcation points, which we argue are universally determined only by the type of bifurcation. Our theory is verified for an evolutionary model and an epidemiological model, which exhibit the transcritical bifurcation, as well as for an ecological model, which undergoes limit-cycle oscillation. This work paves a way to predict biological dynamics in light of information theory, by providing fundamental relations in nonequilibrium statistical mechanics of nonlinear systems.

physics.bio-ph↗

arXiv2021

Activity-induced phase transition in a quantum many-body system

A crowd of nonequilibrium entities can show phase transition behaviors that are prohibited in conventional equilibrium setups. An interesting question is whether similar activity-driven phase transitions also occur in pure quantum systems. Here we introduce a minimally simple quantum many-body model that undergoes quantum phase transitions induced by non-Hermiticity. The model is based on a classical anisotropic lattice gas model that undergoes motility-induced phase separation (MIPS), and the quantum phase diagram includes other active phases such as the flocking phase. The quantum phase transitions, which in principle can be tested in ultracold atom experiments, is also identified as the transitions of dynamical paths in the classical kinetics upon the application of biasing fields. This approach sheds light on the useful connection between classical nonequilibrium kinetics and non-Hermitian quantum physics.

cond-mat.stat-mech↗

arXiv2021

Surface wetting by kinetic control of liquid-liquid phase separation

Motivated by the observations of intracellular phase separations and the wetting of cell membranes by protein droplets, we study the nonequilibrium surface wetting by Monte Carlo simulations of a lattice gas model involving particle creation. We find that, even when complete wetting should occur in equilibrium, the fast creation of particles can hinder the surface wetting for a long time due to the bulk droplet formation. Performing molecular dynamics simulations, we show that this situation also holds in colloidal particle systems when the disorder density is sufficiently high. The results suggest an intracellular control mechanism of surface wetting by changing the speed of component synthesis.

physics.bio-ph↗

arXiv2020

Universality of active and passive phase separation in a lattice model

The motility-induced phase separation (MIPS) is the spontaneous aggregation of active particles, while equilibrium phase separation (EPS) is thermodynamically driven by attractive interactions between passive particles. Despite such difference in the microscopic mechanism, similarities between MIPS and EPS like free energy structure and critical phenomena have been discussed. Here we introduce and analyze a 2D lattice gas model that undergoes both MIPS and EPS by tuning activity and interaction parameters. Based on simulations and mean-field theory, we find that the MIPS and EPS critical points are connected through a line of nonequilibrium critical points. According to the size scaling of physical quantities and time evolution of the domain size, both the static and dynamical critical exponents seem consistent with the 2D spin-exchange Ising universality over the whole critical line. The results suggest that activity effectively enhances attractive interactions between particles and leaves intact the critical properties of phase separation.

cond-mat.stat-mech↗

arXiv2019

Chromatin state switching in a polymer model with mark-conformation coupling

We investigate the phase transition properties of the polymer-Potts model, a chain composed of monomers with magnetic degrees of freedom, with the motivation to study the conformation and mark switching dynamics of chromatin. By the mean-field approximation, we find that the phase transition between the swollen-disordered state and the compact-ordered state is discrete; it is first-order as in the long-range Potts model, but with a significantly larger jump in magnetization (i.e., mark coherence) upon the ordering transition. The results imply how small changes in epigenetic writer concentrations can lead to a macroscopic switching of the chromatin state, suggesting a simple mechanism of discrete switching observed, for instance, in cell differentiation.

physics.bio-ph↗