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Cheol-Min Ghim

Publications and source records attributed to Cheol-Min Ghim.

7 recordsLinked to original sources
arXiv2025

Memory-aware feedback enhances power in active information engines

We study an information engine operating in an active bath, where a Brownian particle confined in a harmonic trap undergoes feedback-driven displacement cycles. Unlike thermal environments, active baths exhibit temporally correlated fluctuations, introducing memory effects that challenge conventional feedback strategies. Extending the framework of stochastic thermodynamics to account for such memory, we analyze a feedback protocol that periodically shifts the potential minimum based on noisy measurements of the particle's position. We show that conventional feedback schemes, optimized for memoryless thermal baths, can degrade performance in active media due to the disruption of bath-particle memory by abrupt resetting. To overcome this degradation, we introduce a class of memory-preserving feedback protocols that partially retain the covariance between the particle's displacement and active noise, thereby exploiting the temporal persistence of active fluctuations. Through asymptotic analysis, we show how the feedback gain -- which quantifies the strength of positional shifts -- nontrivially shapes the engine's work and power profiles. In particular, we demonstrate that in active media, intermediate gains outperform full-shift resetting. Our results reveal the critical interplay between bath memory, measurement noise, and feedback gain, offering guiding principles for designing high-performance information engines in nonequilibrium environments.

cond-mat.stat-mech↗
arXiv2025

Intelligent Soft Matter: Towards Embodied Intelligence

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static or predefined functions, intelligent soft matter dynamically interacts with its environment. It integrates multiple sensory inputs, retains experiences, and makes decisions to optimize its responses. Inspired by biological systems, these materials intend to leverage the inherent properties of soft matter: flexibility, self-evolving, and responsiveness to perform functions that mimic cognitive processes. By synthesizing current research trends and projecting their evolution, we present a forward-looking perspective on how intelligent soft matter could be constructed, with the aim of inspiring innovations in fields such as biomedical devices, adaptive robotics, and beyond. We highlight new pathways for integrating design of sensing, memory and action with internal low-power operations and discuss challenges for practical implementation of materials with "intelligent behavior". These approaches outline a path towards to more robust, versatile and scalable materials that can potentially act, compute, and "think" by their inherent intrinsic material behaviour beyond traditional smart technologies relying on external control.

cond-mat.soft↗
arXiv2024

Enlightening the blind spot of the Michaelis-Menten rate law: The role of relaxation dynamics in molecular complex formation

The century-long Michaelis-Menten rate law and its modifications in the modeling of biochemical rate processes stand on the assumption that the concentration of the complex of interacting molecules, at each moment, rapidly approaches an equilibrium (quasi-steady state) compared to the pace of molecular concentration changes. Yet, in the case of actively time-varying molecular concentrations with transient or oscillatory dynamics, the deviation of the complex profile from the quasi-steady state becomes relevant. A recent theoretical approach, known as the effective time-delay scheme (ETS), suggests that the delay by the relaxation time of molecular complex formation contributes to the substantial breakdown of the quasi-steady state assumption. Here, we systematically expand this ETS and inquire into the comprehensive roles of relaxation dynamics in complex formation. Through the modeling of rhythmic protein-protein and protein-DNA interactions and the mammalian circadian clock, our analysis reveals the effect of the relaxation dynamics beyond the time delay, which extends to the dampening of changes in the complex concentration with a reduction in the oscillation amplitude compared to the quasi-steady state. Interestingly, the combined effect of the time delay and amplitude reduction shapes both qualitative and quantitative oscillatory patterns such as the emergence and variability of the mammalian circadian rhythms. These findings highlight the downside of the routine assumption of quasi-steady states and enhance the mechanistic understanding of rich time-varying biomolecular processes.

q-bio.MN↗
arXiv2022

Birth and Death of One-dimensional Domains in Cylindrically Confined Liquid Crystals

Nematic liquid crystal (LC) is a partially ordered matter that has been a popular model system for studying a variety of topological behaviors in condensed matter. In this work, utilizing a spontaneously twisting achiral LC, we introduce a one-dimensional (1D) model system to investigate how domains and topological defects arise and annihilate, reminiscing the Kibble-Zurek mechanism. Because of the unusual elastic properties, lyotropic chromonic LCs form a double-twist structure in a cylindrical capillary with degenerate planar anchoring, exhibiting chiral symmetry breaking despite the absence of intrinsic chirality. Consequently, the domains of different handedness coexist with equal probabilities, forming the topological defects between them. We experimentally measure the domain-length distribution and its time evolution, best fitted by a three-parameter log-normal distribution. We propose that the coalescence within a train of 1D domains having the normal length distribution and randomly assigned handedness, may lead to the domains of the log-normal-like length distribution. Our cylindrically confined LC provides a practical model system to study the formation and annihilation of domains and defects in 1D.

cond-mat.soft↗
arXiv2021

The Boltzmann fair division for distributive justice

Fair division is a significant, long-standing problem and is closely related to social and economic justice. The conventional division methods such as cut-and-choose are hardly applicable to realworld problems because of their complexity and unrealistic assumptions about human behaviors. Here we propose a fair division method from a completely different perspective, using the Boltzmann distribution. The Boltzmann distribution adopted from the physical sciences gives the most probable and unbiased distribution derived from a goods-centric, rather than a player-centric, division process. The mathematical model of the Boltzmann fair division was developed for both homogeneous and heterogeneous division problems, and the players' key factors (contributions, needs, and preferences) could be successfully integrated. We show that the Boltzmann fair division is a well-balanced division method maximizing the players' total utility, and it could be easily finetuned and applicable to complex real-world problems such as income/wealth redistribution or international negotiations on fighting climate change.

econ.GN↗
arXiv2008

The fixation probability of rare mutators in finite asexual populations

A mutator is an allele that increases the mutation rate throughout the genome by disrupting some aspect of DNA replication or repair. Mutators that increase the mutation rate by the order of 100 fold have been observed to spontaneously emerge and achieve high frequencies in natural populations and in long-term laboratory evolution experiments with \textit{E. coli}. In principle, the fixation of mutator alleles is limited by (i) competition with mutations in wild-type backgrounds, (ii) additional deleterious mutational load, and (iii) random genetic drift. Using a multiple locus model and employing both simulation and analytic methods, we investigate the effects of these three factors on the fixation probability $P_{fix}$ of an initially rare mutator as a function of population size $N$, beneficial and deleterious mutation rates, and the strength of mutations $s$. Our diffusion based approximation for $P_{fix}$ successfully captures effects (ii) and (iii) when selection is fast compared to mutation ($μ/s \ll 1$). This enables us to predict the conditions under which mutators will be evolutionarily favored. Surprisingly, our simulations show that effect (i) is typically small for strong-effect mutators. Our results agree semi-quantitatively with existing laboratory evolution experiments and suggest future experimental directions.

q-bio.PE↗