arXiv subjects

Artemy Kolchinsky

Publications and source records attributed to Artemy Kolchinsky.

At least 19 recordsLinked to original sources

arXiv2026

Quo vadis, stochastic thermodynamics?

Stochastic thermodynamics is a framework for describing non-equilibrium processes at the level of fluctuating trajectories, where the state of a system evolves as a stochastic time series, allowing thermodynamic quantities such as work, heat, and entropy production to be defined along individual realizations rather than at the ensemble level only. Over the past three decades, the field has yielded fundamental results, including fluctuation theorems and several universal bounds, such as thermodynamic uncertainty relations, speed limit theorems, and many others. Many of them have been tested on a range of experimental platforms. This Perspective reviews recent developments in stochastic thermodynamics that extend its scope beyond its traditional domains, including systems with memory and hidden degrees of freedom, microscopic approaches to interacting and active matter, and geometric formulations based on optimal transport. Next, the Perspective surveys the challenges that arise when applying these ideas to macroscopic and complex systems, where the link between statistical irreversibility and thermodynamic dissipation becomes less direct. Finally, emerging applications in non-physical contexts are highlighted, including computation, biological systems, and social dynamics. Transcending the traditional boundaries of physics, these developments catalyze an unorthodox framework to tackle the thermodynamics of complex systems.

cond-mat.stat-mech↗

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

Elementary derivation of the dissipation-coherence bound for stochastic oscillators

The dissipation-coherence bound is a conjectured tradeoff between entropy production and the quality of stochastic oscillations. We show that this bound can be derived by combining the higher-order ``thermodynamic uncertainty relation'' with a simple condition on phase-current fluctuations. In one-dimensional cyclic systems, our proposed condition is shown to be equivalent to the dissipation-coherence bound itself. Our approach yields an elementary proof in the weak-noise Gaussian regime and extends naturally to some non-Gaussian systems, as we illustrate with a run-and-tumble particle. Finally, we contrast current-based and spectral formulations of the dissipation-coherence bound.

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

Wasserstein-2 gradient flows and the geometry of entropy production in classical and quantum stochastic thermodynamics

The second law does more than set the direction of thermodynamic evolution: it endows nonequilibrium transformations with an underlying geometry. In this work, we provide a unified geometric description of entropy production in classical and quantum thermodynamics based on Wasserstein-2 structures arising from gradient flows of free energy. We review how relaxation to equilibrium, in overdamped diffusions, discrete detailed-balanced Markov chains, and dissipative Lindblad dynamics, can be formulated as a gradient flow on the space of states. The associated Wasserstein-2 distance bounds entropy production, yielding a finite-time refinement of the second law. We extend this framework beyond purely dissipative dynamics by introducing generalized Wasserstein-2 metrics that incorporate conservative (Hamiltonian) dynamics in both classical inertial systems and open quantum systems, yielding intrinsic distances that exactly characterize minimal entropy production under fixed dissipative mobilities. We establish equivalence bounds between purely dissipative and Hamiltonian-dissipative geometries, explicitly quantifying how inertial or coherent dynamics can reduce dissipation. Finally, when restricted to equilibrium distributions, we recover the thermodynamic length of linear response-including the quantum thermodynamic length-thereby linking optimal transport, thermodynamic length, and counterdiabatic protocols within a single geometric framework. All in all, our results extend the Riemannian program of thermodynamics further from equilibrium and provide a geometric foundation for optimal protocols beyond the overdamped setting.

cond-mat.stat-mech↗

arXiv2026

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↗

arXiv2026

Information bounds production in replicator systems

Environmental fluctuations can shape replicator dynamics, with important consequences for both prebiotic and modern ecosystems. However, it remains unclear how simple replicators can acquire and use information about fluctuating environments, given that such information processing is often assumed to require sophisticated mechanisms for sensing and control. Here, we show that even simple replicator networks can increase productivity by exploiting environmental information in a functional way. Using a model of autocatalytic replicators in a flow reactor, we derive an information-theoretic decomposition of productivity, with separate contributions from environmental uncertainty, side information, and distribution mismatch. We derive optimal strategies and universal bounds on the benefit of information and compare our findings with existing work, including ``Kelly gambling'' in information theory. By applying our framework to a model of real-world molecular replicators, we demonstrate the benefits of internal memory and propose an experimental setup for detecting functional information in a minimal chemical system.

physics.bio-ph↗

arXiv2026

Towards Worst-Case Guarantees with Scale-Aware Interpretability

Neural networks organize information according to the hierarchical, multi-scale structure of natural data. Methods to interpret model internals should be similarly scale-aware, explicitly tracking how features compose across resolutions and guaranteeing bounds on the influence of fine-grained structure that is discarded as irrelevant noise. We posit that the renormalisation framework from physics can meet this need by offering technical tools that can overcome limitations of current methods. Moreover, relevant work from adjacent fields has now matured to a point where scattered research threads can be synthesized into practical, theory-informed tools. To combine these threads in an AI safety context, we propose a unifying research agenda -- \emph{scale-aware interpretability} -- to develop formal machinery and interpretability tools that have robustness and faithfulness properties supported by statistical physics.

hep-th↗

arXiv2025

Neutral theory of cooperative dynamics

Mutualistic interactions are widespread in nature, from plant communities and microbiomes to human organizations. Along with competition for resources, cooperative interactions shape biodiversity and contribute to the robustness of complex ecosystems. We present a stochastic neutral theory of cooperator species. Our model shares with the classic neutral theory of biodiversity the assumption that all species are equivalent, but crucially differs in requiring cooperation between species for replication. With low migration, our model displays a bimodal species-abundance distribution, with a high-abundance mode associated with a core of cooperating species. This core is responsible for maintaining a diverse pool of long-lived species, which are present even at very small migration rates. We derive analytical expressions of the steady-state species abundance distribution, as well as scaling laws for diversity, number of species, and residence times. With high migration, our model recovers the results of classic neutral theory. We briefly discuss implications of our analysis for research on the microbiome, synthetic biology, and the origin of life.

q-bio.PE↗

arXiv2025

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↗

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

Thermodynamics of Darwinian selection in molecular replicators

We consider the relationship between thermodynamics, fitness, and Darwinian selection in autocatalytic molecular replicators. We uncover a thermodynamic bound that relates fitness, replication rate, and thermodynamic affinity of replication. This bound applies to a broad range of systems, including elementary and non-elementary autocatalytic reactions, polymer-based replicators, and certain kinds of autocatalytic sets. In addition, we show that the critical selection coefficient (the minimal fitness difference visible to selection) is bounded by a simple function of the affinity. Our results imply fundamental thermodynamic bounds on selection strength in molecular evolution, complementary to other bounds that arise from finite population sizes and error thresholds. These bounds may be relevant for understanding thermodynamic constraints faced by early replicators at the origin of life. We illustrate our approach on several examples, including a classic model of replicators in a chemostat.

q-bio.PE↗

arXiv2025

Spatiotemporal organization of chemical oscillators via phase separation

We study chemical oscillators in the presence of phase separation. By imposing timescale separation between slow reactions and fast diffusion, we define a dynamics at phase equilibrium for the relevant degrees of freedom. We demonstrate that phase separation affects reaction kinetics by localizing reactants within phases, allowing for control of oscillator frequency and amplitude. The analysis is validated with a spatial model. Finally, relaxing the timescale separation between reactions and diffusion leads to waves of phase equilibria at mesoscopic scales.

cond-mat.soft↗

arXiv2025

Maximizing free energy gain

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesisto energy storage systems such as fuels and batteries. Here we consider the maximization of free energy -- and by extension, the maximum extractable work -- that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system, while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

cond-mat.stat-mech↗

arXiv2025

The Physics of Life: Exploring Information as a Distinctive Feature of Living Systems

This paper explores the idea that information is an essential and distinctive feature of living systems. Unlike non-living systems, living systems actively acquire, process, and use information about their environments to respond to changing conditions, sustain themselves, and achieve other intrinsic goals. We discuss relevant theoretical frameworks such as ``semantic information'' and ``fitness value of information''. We also highlight the broader implications of our perspective for fields such as origins-of-life research and astrobiology. In particular, we touch on the transition to information-driven systems as a key step in abiogenesis, informational constraints as determinants of planetary habitability, and informational biosignatures for detecting life beyond Earth. We briefly discuss experimental platforms which offer opportunities to investigate these theoretical concepts in controlled environments. By integrating theoretical and experimental approaches, this perspective advances our understanding of life's informational dynamics and its universal principles across diverse scientific domains.

cond-mat.soft↗

arXiv2025

Generalized Zurek's bound on the cost of an individual classical or quantum computation

We consider the minimal thermodynamic cost of an individual computation, where a single input $x$ is mapped to a single output $y$. In prior work, Zurek proposed that this cost was given by $K(x\vert y)$, the conditional Kolmogorov complexity of $x$ given $y$ (up to an additive constant which does not depend on $x$ or $y$). However, this result was derived from an informal argument, applied only to deterministic computations, and had an arbitrary dependence on the choice of protocol (via the additive constant). Here we use stochastic thermodynamics to derive a generalized version of Zurek's bound from a rigorous Hamiltonian formulation. Our bound applies to all quantum and classical processes, whether noisy or deterministic, and it explicitly captures the dependence on the protocol. We show that $K(x\vert y)$ is a minimal cost of mapping $x$ to $y$ that must be paid using some combination of heat, noise, and protocol complexity, implying a tradeoff between these three resources. Our result is a kind of "algorithmic fluctuation theorem" with implications for the relationship between the Second Law and the Physical Church-Turing thesis.

cond-mat.stat-mech↗

arXiv2024

Geometric thermodynamics of reaction-diffusion systems: Thermodynamic trade-off relations and optimal transport for pattern formation

We establish universal relations between pattern formation and dissipation with a geometric approach to nonequilibrium thermodynamics of deterministic reaction-diffusion systems. We first provide a way to systematically decompose the entropy production rate (EPR) based on the orthogonality of thermodynamic forces, in this way identifying the amount of dissipation caused by each factor. This enables us to extract the excess EPR that genuinely contributes to the time evolution of patterns. We also show that a similar geometric method further decomposes the EPR into detailed contributions, e.g., the dissipation from each point in real or wavenumber space. Second, we relate the excess EPR to the details of the change in patterns through two types of thermodynamic trade-off relations for reaction-diffusion systems: thermodynamic speed limits and thermodynamic uncertainty relations. The former relates dissipation and the speed of pattern formation, and the latter bounds the excess EPR with partial information on patterns, such as specific Fourier components of concentration distributions. In connection with the derivation of the thermodynamic speed limits, we also extend optimal transport theory to reaction-diffusion systems, which enables us to measure the speed of the time evolution. This extension of optimal transport also solves the minimization problem of the dissipation associated with the transition between two patterns, and it constructs energetically efficient protocols for pattern formation. We numerically demonstrate our results using chemical traveling waves in the Fisher-Kolmogorov-Petrovsky-Piskunov equation and changes in symmetry in the Brusselator model. Our results apply to general reaction-diffusion systems and contribute to understanding the relations between pattern formation and unavoidable dissipation.

cond-mat.stat-mech↗

arXiv2024

Thermodynamic dissipation does not bound replicator growth and decay rates

In a well-known paper, Jeremy England derived a bound on the free energy dissipated by a self-replicating system [England, "Statistical physics of self-replication", The Journal of Chemical Physics, 2013]. This bound is usually interpreted as a universal relationship that connects thermodynamic dissipation to replicator per-capita decay and growth rates. We argue from basic thermodynamic principles against this interpretation. In fact, we suggest that such a relationship cannot exist in principle, because it is impossible for a thermodynamically-consistent replicator to undergo both per-capita growth and per-capita decay back into reactants. Instead, replicator may decay into separate waste products, but in that case, replication and decay are two independent physical processes, and there is no universal relationship that connects their thermodynamic and dynamical properties.

cond-mat.stat-mech↗