arXiv subjects

Sosuke Ito

Publications and source records attributed to Sosuke Ito.

At least 19 recordsLinked to original sources

arXiv2026

Oscillatory-nonnormal decomposition of dissipation in Ornstein-Uhlenbeck processes

We provide a decomposition of the steady-state entropy production rate associated with an Ornstein-Uhlenbeck process into two contributions: one associated with oscillatory behavior and one associated with nonnormality. We also show that each contribution is associated with a different fundamental trade-off. The oscillatory contribution leads to the dissipation-coherence trade-off for noise-induced oscillations, which bounds the entropy production per oscillatory period by the number of oscillations within one correlation time. Notably, the tradeoff is twice as strict as those conjectured or derived for other systems. The nonnormal contribution leads to a trade-off between entropy production and acceleration of relaxation. We also demonstrate the decomposition using a simple bead-spring model.

cond-mat.stat-mech↗

arXiv2026

Cycle affinity and winding localize eigenvalues of Markov generators

The complex eigenvalues of Markov generators govern oscillatory properties of relaxation, autocorrelation, and linear response. We show that these eigenvalues are localized by nonequilibrium cycles of the generator, thus revealing a fundamental tradeoff between thermodynamic driving, oscillation, and decay of eigenmodes. Specifically, we prove that each complex eigenvalue is confined to a region determined by the cycle affinity and the eigenvector ``winding number'' of some nonequilibrium cycle. In discrete and continuous unicyclic systems, we also demonstrate that the winding number coincides with the ordered eigenvalue index, yielding new thermodynamic bounds on the slowest and fastest relaxation modes. In discrete multicyclic systems, our approach unifies and extends several previous inequalities and proves the Uhl--Seifert ellipse conjecture.

cond-mat.stat-mech↗

arXiv2026

Information-Geometric Signatures of Nonconservative Driving

We propose an information-geometric signature of nonconservative driving that detects violations of detailed balance using the Kullback--Leibler divergence and the Fisher information. For Markov jump processes satisfying detailed balance, we show that, near equilibrium, the acceleration of the Kullback--Leibler divergence relative to the equilibrium state is given by twice the Fisher information with respect to time. In contrast, for relaxation toward a nonequilibrium steady state, this relation is generally violated even near the steady state. We refer to the resulting discrepancy as the relaxation gap and derive a lower bound on the steady-state entropy production rate in terms of this gap. We demonstrate that this bound is particularly tight for networks with simple cyclic topologies. Finally, we show that analogous relations and bounds hold for Fokker--Planck dynamics.

cond-mat.stat-mech↗

arXiv2026

Decoding cell signaling via optimal transport and information theory

Cellular signal processing performs reliably despite molecular noise. Mutual information (MI) is widely used to quantify signaling fidelity, capturing how well outputs discriminate input states. However, it fails to capture whether the output preserves the statistical structure of the input, a property crucial in morphogen patterning and dose-dependent signaling. To address this gap, we introduce the 2-Wasserstein (2-WD) distance, which provides a geometric basis for comparing input and output distributions. We define MI as informational fidelity (INF) and the inverse of the 2-WD as geometric fidelity (GMF). Applying this dual-fidelity framework to canonical regulatory motifs under Gaussian channel approximation reveals topology-dependent trade-offs: coherent feed-forward loops can perform well in both dimensions, whereas feedback architectures reduce INF to enhance GMF. Experimental analysis of tumor necrosis factor signaling reveals dual-fidelity behavior qualitatively consistent with feedback regulation. RAS-MAPK data analysis further shows that jointly considering INF and GMF better characterizes intracellular signal relay than INF alone. Our results thus indicate that these signaling behaviors are not fully characterized by MI alone; instead, distributional correspondence provides a complementary dimension of signaling fidelity. Our study provides a practical framework for analyzing natural networks and guiding the design of task-specific synthetic circuits.

physics.bio-ph↗

arXiv2025

Geometric decomposition of information flow for overdamped Langevin systems and optimal transport in subsystems

Information flow between subsystems is a central concept in information thermodynamics, which provides the second-law-like inequalities for subsystems. This paper discusses the geometric decomposition of information flow, which was introduced for Markov jump systems [Physical Review Research, 8, 023292 (2026)], and applies it to overdamped Langevin systems. For overdamped Langevin systems, the geometric decomposition of information flow into excess and housekeeping contributions is related to the conventional definition of the 2-Wasserstein distance between marginal distributions in optimal transport theory. This formulation offers an optimal-transport interpretation of subsystem dynamics, and this optimal-transport formulation is simpler for overdamped Langevin systems than for general Markov jump systems. It is also possible to handle features that are specific to overdamped Langevin systems, such as representations based on the Koopman mode decomposition, as well as their relationship with the Fisher information matrix. As with the results for Markov jump systems, we generalize the second law of information thermodynamics using housekeeping and excess information flow, leading to the concepts of excess and housekeeping demons. We also derive a thermodynamic uncertainty relation and an information-thermodynamic speed limit incorporating excess information flow. These results are illustrated for the Gaussian case, and we discuss the conditions under which the excess and housekeeping demons emerge.

cond-mat.stat-mech↗

arXiv2025

Koopman Mode Decomposition of Thermodynamic Dissipation in Nonlinear Langevin Dynamics

Nonlinear oscillations are commonly observed in complex systems far from equilibrium, such as living organisms. These oscillations are essential for sustaining vital processes, like neuronal firing, circadian rhythms, and heartbeats. In such systems, thermodynamic dissipation is necessary to maintain oscillations against noise. However, due to their nonlinear dynamics, it has been challenging to determine how the characteristics of oscillations, such as frequency, amplitude, and coherent patterns across elements, influence dissipation. To resolve this issue, we employ Koopman mode decomposition, which recasts nonlinear dynamics as a linear evolution in a function space. This linearization allows the dynamics to be decomposed into temporal oscillatory modes coherent across elements, with the Koopman eigenvalues determining their frequencies. Using this method, we decompose thermodynamic dissipation caused by nonconservative forces into contributions from oscillatory modes in overdamped nonlinear Langevin dynamics. We show that the dissipation from each mode is proportional to its frequency squared and its intensity, providing an interpretable, mode-by-mode picture. In the noisy FitzHugh--Nagumo model, we demonstrate the effectiveness of this framework in quantifying the impact of oscillatory modes on dissipation during nonlinear phenomena like coherent resonance and bifurcation. For instance, our analysis of coherent resonance reveals that the greatest dissipation at the optimal noise intensity is supported by a broad spectrum of frequencies, whereas at non-optimal noise levels, dissipation is dominated by specific frequency modes. Our work offers a general approach to connecting oscillations to dissipation in noisy environments and improves our understanding of diverse oscillation phenomena from a nonequilibrium thermodynamic perspective.

cond-mat.stat-mech↗

arXiv2025

Geometric decomposition of information flow: New insights into information thermodynamics

We propose a decomposition of information flow into housekeeping and excess components for autonomous bipartite systems described by Markov jump processes. We introduce this decomposition using the geometric structure of probability currents and the conjugate thermodynamic forces. The housekeeping component arises from cyclic modes caused by violations of detailed balance and maintains the correlations between the two subsystems. In contrast, the excess component arises from conservative forces and alters the mutual information between the two subsystems. With this decomposition, we generalize previous results, such as the second law of information thermodynamics, the cyclic decomposition, and the information-thermodynamic extensions of thermodynamic trade-off relations.

cond-mat.stat-mech↗

arXiv2025

Duality between dissipation-coherence trade-off and thermodynamic speed limit based on thermodynamic uncertainty relation for stochastic limit cycles

We derive two fundamental trade-offs for general stochastic limit cycles in the weak-noise limit. The first is the dissipation-coherence trade-off, which was discovered and proved under additional assumptions by Santolin and Falasco [Phys. Rev. Lett. 135, 057101 (2025)]. This trade-off bounds the entropy production required for one oscillatory period using the number of oscillations that occur before steady-state correlations are disrupted. The second is the thermodynamic speed limit, which bounds the entropy production by the Euclidean length of the limit cycle. These trade-offs are obtained by substituting mutually dual observables, derived from the stability of the limit cycle, into the thermodynamic uncertainty relation. This fact allows us to regard the dissipation-coherence trade-off as the dual of the thermodynamic speed limit. We numerically demonstrate these trade-offs using the noisy R\"{o}ssler model. We also apply the trade-offs to stochastic chemical systems, where the diffusion coefficient matrix may contain zero eigenvalues. Furthermore, we show that the dissipation-coherence trade-off is always achievable by appropriately modifying the diffusion coefficient matrix based on the phase reduction.

cond-mat.stat-mech↗

arXiv2025

Precision and cost of feedback cooling

We investigate the consequences of information exchange between a system and a measurement-feedback apparatus that cools the system below the environmental temperature. A quantitative relationship between entropy pumping and information acquired about the system is derived, showing that, independent of the concrete realization of the feedback, the latter exceeds the former by a positive amount of excess information flow. This excess information flow satisfies a trade-off relation with the precision of the feedback force, which places strong constraints on both the information-theoretic cost of feedback cooling and the required magnitude of the feedback force. From these constraints, a fundamental lower bound on the energetic cost of optical feedback cooling is derived. Finally, the results are demonstrated for feedback cooling by coherent light scattering. We show that measurement precision is the major factor determining the attainable temperature. Precise measurements can also be leveraged to reduce the required feedback force, leading to significantly more energy-efficient cooling close to the fundamental bound for realistic parameter values.

cond-mat.stat-mech↗

arXiv2025

Random Coarse-Graining with Applications to Measuring Irreversibility

Thermodynamic irreversibility is a fundamental concept in statistical physics, yet its experimental measurement remains challenging, especially for complex systems. At the same time, imprecise readout is ubiquitous in experiments, but its effect on thermodynamic irreversibility has not been formulated in a general way. We introduce a novel random coarse-graining framework that incorporates a probabilistic mapping from fine-grained to coarse-grained states, and we use it both to model imprecise measurements and to identify model-free measures of irreversibility in complex many-body systems. These measures are constructed from the asymmetry of cross-correlation functions between suitably chosen observables, providing rigorous lower bounds on the entropy production. For many-particle systems, we propose a particularly practical implementation that divides real space into virtual boxes and monitors particle number densities within them, requiring only simple counting from video microscopy, without single-particle tracking, trajectory reconstruction, or prior knowledge of interactions. Owing to its generality and limited data requirements, the random coarse-graining framework offers broad applicability across diverse nonequilibrium systems.

cond-mat.stat-mech↗

arXiv2025

Thermodynamic Geometric Constraint on the Spectrum of Markov Rate Matrices

The spectrum of Markov generators encodes physical information beyond simple decay and oscillation, which reflects irreversibility and governs the structure of correlation functions. In this work, we prove an ellipse theorem that provides a universal thermodynamic geometric constraint on the spectrum of Markov rate matrices. The theorem states that all eigenvalues lie within a specific ellipse in the complex plane. In particular, the imaginary parts of the spectrum, which indicate oscillatory modes, are bounded by the maximum thermodynamic force associated with individual transitions. This spectral bound further constrains the initial short-time behavior of correlation functions between two arbitrary observables. Finally, we compare our result with a previously proposed conjecture, which remains an open problem and warrants further investigation.

cond-mat.stat-mech↗

arXiv2025

Diagrammatic expressions for steady-state distribution and static responses in population dynamics

One of the fundamental questions in population dynamics is how biological populations respond to environmental perturbations. In population dynamics, the mean fitness and the fraction of a trait in the steady state are important because they indicate how well the trait and the population adapt to the environment. In this study, we examine the parallel mutation-reproduction model, which is one of the simplest models of an evolvable population. As an extension of the Markov chain tree theorem, we derive diagrammatic expressions for the static responses of mean fitness and the steady-state distribution of the population. For the parallel mutation-reproduction model, we consider self-loops, which represent trait reproduction and are excluded from the Markov chain tree theorem for the linear master equation. To generalize the theorem, we introduce the concept of rooted $0$/$1$ loop forests, which generalize spanning trees with loops. We demonstrate that the weights of rooted $0$/$1$ loop forests yield the static responses of mean fitness and the steady-state distribution. Our results provide exact expressions for the static responses and the steady-state distribution. Additionally, we discuss approximations of these expressions in cases where reproduction or mutation is dominant. We provide numerical examples to illustrate these approximations and exact expressions.

q-bio.PE↗

arXiv2025

Inferring entropy production in many-body systems using nonequilibrium maximum entropy

We propose a method for inferring entropy production (EP) in high-dimensional stochastic systems, including many-body systems and non-Markovian systems with long memory. Standard techniques for estimating EP become intractable in such systems due to computational and statistical limitations. We infer trajectory-level EP and lower bounds on average EP by exploiting a nonequilibrium analogue of the Maximum Entropy principle, along with convex duality. Our approach uses only samples of trajectory observables, such as spatiotemporal correlations. It does not require reconstruction of high-dimensional probability distributions or rate matrices, nor impose any special assumptions such as discrete states or multipartite dynamics. In addition, it may be used to compute a hierarchical decomposition of EP, reflecting contributions from different interaction orders, and it has an intuitive physical interpretation as a "thermodynamic uncertainty relation." We demonstrate its numerical performance on a disordered nonequilibrium spin model with 1000 spins and a large neural spike-train dataset.

cond-mat.stat-mech↗

arXiv2025

Experimentally achieving minimal dissipation via thermodynamically optimal transport

Optimal transport theory, originally developed in the 18th century for civil engineering, has since become a powerful optimization framework across disciplines, from generative AI to cell biology. In physics, it has recently been shown to set fundamental bounds on thermodynamic dissipation in finite-time processes. This extends beyond the conventional second law, which guarantees zero dissipation only in the quasi-static limit and cannot characterize the inevitable dissipation in finite-time processes. Here, we experimentally realize thermodynamically optimal transport using optically trapped microparticles, achieving minimal dissipation within a finite time. As an application to information processing, we implement the optimal finite-time protocol for information erasure, confirming that the excess dissipation beyond the Landauer bound is exactly determined by the Wasserstein distance - a fundamental geometric quantity in optimal transport theory. Furthermore, our experiment achieves the bound governing the trade-off between speed, dissipation, and accuracy in information erasure. To enable precise control of microparticles, we develop scanning optical tweezers capable of generating arbitrary potential profiles. Our work establishes an experimental approach for optimizing stochastic thermodynamic processes. Since minimizing dissipation directly reduces energy consumption, these results provide guiding principles for designing high-speed, low-energy information processing.

cond-mat.stat-mech↗

arXiv2024

Infinite variety of thermodynamic speed limits with general activities

Activity, which represents the kinetic property of dynamics, plays a central role in obtaining thermodynamic speed limits (TSLs). In this paper, we discuss a unified framework that provides the existing TSLs based on different activities such as dynamical activity and dynamical state mobility. This unification is based on generalized means that include standard means such as the arithmetic, logarithmic, and geometric means, the first two of which respectively correspond to the dynamical activity and the dynamical state mobility. We also derive an infinite variety of TSLs for Markov jump processes and deterministic chemical reaction networks using different activities. The lower bound on the entropy production given by each TSL provides the minimum dissipation achievable by a conservative force. We numerically and analytically discuss the tightness of the lower bounds on the EPR in the various TSLs.

cond-mat.stat-mech↗

arXiv2024

Generalized free energy and excess/housekeeping decomposition in nonequilibrium systems: from large deviations to thermodynamic speed limits

In genuine nonequilibrium systems that undergo continuous driving, the thermodynamic forces are nonconservative, meaning they cannot be described by any free energy potential. Nonetheless, we show that the dynamics of such systems are governed by a "generalized free energy" that is derived from a large-deviations variational principle. This variational principle also yields a decomposition of fluxes, forces, and dissipation (entropy production) into a conservative "excess" part and a nonconservative "housekeeping" part. Our decomposition is universally applicable to stochastic master equations, deterministic chemical reaction networks, and open systems. We also show that the excess entropy production obeys a thermodynamic speed limit (TSL), a fundamental thermodynamic constraint on the rate of state evolution and/or external fluxes. We demonstrate our approach on several examples, including real-world metabolic networks, where we derive fundamental dissipation bounds and uncover "futile" metabolic cycles. Our generalized free energy and decomposition are empirically accessible to thermodynamic inference in both stochastic and deterministic systems. We discuss important connections to several theoretical frameworks, including information geometry and Onsager theory, as well as previous excess/housekeeping decompositions.

cond-mat.stat-mech↗

arXiv2024

Force-current structure in Markovian open quantum systems and its applications: geometric housekeeping-excess decomposition and thermodynamic trade-off relations

Thermodynamic force and irreversible current are the foundational concepts of classical nonequilibrium thermodynamics. Entropy production rate is provided by their product in classical systems, ranging from mesoscopic to macroscopic systems. However, there is no complete quantum extension of such a structure that respects quantum mechanics. In this paper, we propose anti-Hermitian operators that represent currents and forces accompanied by a gradient structure in open quantum systems described by the quantum master equation. We prove that the entropy production rate is given by the product of the force and current operators, which extends the canonical expression of the entropy production rate in the classical systems. The framework constitutes a comprehensive analogy with the nonequilibrium thermodynamics of discrete classical systems. We also show that the structure leads to the extensions of some results in stochastic thermodynamics: the geometric housekeeping-excess decomposition of entropy production and thermodynamic trade-off relations such as the thermodynamic uncertainty relation and the dissipation-time uncertainty relation. In discussing the trade-off relations, we will introduce a measure of fluctuation, which we term the quantum diffusivity.

cond-mat.stat-mech↗

arXiv2024

Microscopic theory of Mpemba effects and a no-Mpemba theorem for monotone many-body systems

Mpemba effects (MPEs), where a hotter system cools faster than a colder one, present intriguing anomalies in relaxation processes. Despite their universal observation and significant fundamental and practical implications, a comprehensive theoretical understanding based on microscopic properties remains elusive. In this Letter, we introduce two universal frameworks for classical systems to address this gap. Firstly, we reveal that MPEs, traditionally defined by macroscopic temperature comparisons, can be understood through microstate comparisons. This insight offers a straightforward and universal microscopic perspective on MPEs, relevant for experiments and numerical simulations to identify their microscopic origins. Secondly, we establish a "no-Mpemba theorem," a rigorous sufficient condition for the absence of MPEs, thereby identifying specific classes of systems devoid of these effects. Our findings are exemplified using ferromagnetic Ising models and one-dimensional multiparticle systems, demonstrating the practical applicability of our theoretical advancements.

cond-mat.stat-mech↗