arXiv subjects

Massimiliano Esposito

Publications and source records attributed to Massimiliano Esposito.

At least 37 records · Page 2Linked to original sources

arXiv2025

Nonequilibrium fluctuation-response relations for state-current correlations

Recently, novel exact identities known as Fluctuation-Response Relations (FRRs) have been derived for nonequilibrium steady states of Markov jump processes. These identities link the fluctuations of state or current observables to a combination of responses of these observables to perturbations of transition rates. Here, we complement these results by deriving analogous FRRs applicable to mixed covariances of one state and one current observable. We further derive novel Inverse FRRs expressing individual state or current response in terms of a combination of covariances rather than vice versa. Using these relations, we demonstrate that the breaking of the Onsager symmetry requires the presence of state-current correlations. On the practical side, we demonstrate the applicability of FRRs for explaining the behavior of fluctuations in quantum dot devices or enzymatic reaction networks.

cond-mat.stat-mech↗

arXiv2025

Dissipation and fluctuations of CMOS ring oscillators close to criticality

We analyze a thermodynamically consistent model of CMOS-based ring oscillators near the onset of coherent voltage oscillations. For driving voltages close to the critical value, we derive the normal form of the Hopf bifurcation that underlies the oscillation transition in the thermodynamic limit. Using this normal form, we determine the phase and amplitude dynamics, and demonstrate that entropy dissipation decreases in the oscillating state for ring oscillators with more than three inverters. These findings culminate in a stability-dissipation relation, which links the observed decrease in dissipation to an increase in the local stability of the oscillating state. Next, we characterize finite-size fluctuations of the amplitude and phase near the critical voltage, using a stochastic version of the normal form. We demonstrate that close to the transition, finite-size fluctuations remain important at arbitrary system size, introducing oscillations even below the critical voltage. We further show that these noise-induced oscillations have an anomalously short decoherence time that scales sub-linearly with the system-size, in contrast to the behavior far from criticality.

cond-mat.stat-mech↗

arXiv2025

Macroscopic theory of multipartite correlations in permutation-invariant open quantum systems

Information-theoretic quantities have received significant attention as system-independent measures of correlations in many-body quantum systems, e.g., as universal order parameters of synchronization. In this work, we present a method to determine the macroscopic behavior of the steady-state multipartite mutual information between $N$ interacting units undergoing Markovian evolution that is invariant under unit permutations. Using this approach, we extend a conclusion previously drawn for classical systems that the extensive scaling of mutual information is either not possible for systems relaxing to fixed points of the mean-field dynamics or such scaling is not robust to perturbations of system dynamics. In contrast, robust extensive scaling occurs for system relaxing to time-dependent attractors, e.g., limit cycles. We illustrate the applicability of our method on the driven-dissipative Lipkin-Meshkov-Glick model.

quant-ph↗

arXiv2025

Faradaic and capacitive charging of an electrolyte-filled pore in response to a small applied potential

Electrochemical devices often charge both through Faradaic reactions and electric double layer formation. Here, we study these coupled processes in a model system of a long electrolyte-filled pore subject to a small suddenly-applied potential, close to the equilibrium potential $Ψ^\text{eq}$ at which there is no net Faradaic charge transfer. Specifically, we solve the coupled Poisson-Nernst-Planck and Frumkin-Butler-Volmer equations by asymptotic approximations, using the pore's small inverse aspect ratio as the small parameter. In the early-time limit, the reaction-diffusion equations yield an extended Faradaic transmission line model that includes a voltage source, $Ψ_\text{eq}$, biasing the Faradaic reactions, captured by the resistance $R_F$. In the long-time limit, the model exhibits a nontrivial potential of zero charge, $Ψ_\text{pzc} = Ψ_\text{eq}[1 - \hat{Z}(0)/R_F]$, where $\hat{Z}(0)$ is the experimentally accessible zero-frequency impedance of the system. This expression provides a new means to experimentally measure the Faradaic contribution to $Ψ_\text{pzc}$.

cond-mat.stat-mech↗

arXiv2025

Macroscopic fluctuation-response theory and its use for gene regulatory networks

Gaussian macroscopic fluctuation theory underpins the understanding of noise in a broad class of nonequilibrium systems. We derive exact fluctuation-response relations linking the power spectral density of stationary fluctuations to the linear response of stable nonequilibrium steady states. Both of these can be determined experimentally and used to reconstruct the kernel of the linearized dynamics and the diffusion matrix, and thus any features of the Gaussian theory. We apply our theory to gene regulatory networks with negative feedback, and derive an explicit internal-external noise decomposition of the power spectral density for any networks, including cross-correlations.

cond-mat.stat-mech↗

arXiv2025

Coarse Graining Photo-Isomerization Reactions: Thermodynamic Consistency and Implications for Molecular Ratchets

We formulate thermodynamically consistent coarse-graining procedures for molecular systems undergoing thermally and photo-induced transitions: starting from elementary vibronic transitions, we derive effective photo-isomerization reactions interconverting ground-state species. Crucially, the local detailed balance condition, that constrains reaction kinetics to thermodynamics, remains satisfied throughout the coarse-graining procedures. It applies to the effective photo-isomerization reactions just as it does to the elementary vibronic transitions. We then demonstrate that autonomous photo-driven molecular ratchets operate via the same fundamental mechanism as chemically driven ones. Because the local detailed balance remains satisfied, autonomous photo-driven molecular ratchets, like chemically driven ones, operate exclusively through an information ratchet mechanism. This reveals that their design and optimization should prioritize molecular properties governing the information ratchet mechanism, rather than those influencing energetic bias.

cond-mat.stat-mech↗

arXiv2025

Gears in Chemical Reaction Networks: Optimizing Energy Transduction Efficiency

Similarly to gear systems in vehicles, most chemical reaction networks (CRNs) involved in energy transduction have at their disposal multiple transduction pathways, each characterized by distinct efficiencies. We conceptualize these pathways as `chemical gears' and demonstrate their role in refining the second law of thermodynamics. This allows us to determine the optimal efficiency of a CRN, and the gear enabling it, solely based on its topology and operating conditions, defined by the chemical potentials of its input and output species. By suitably tuning reaction kinetics, a CRN can be engineered to self-regulate its gear settings, maintaining optimal efficiency under varying external conditions. We demonstrate this principle in a biological context with a CRN where enzymes function as gear shifters, autonomously adapting the system to achieve near-optimal efficiency across changing environments. Additionally, we examine artificial molecular motors and reveal that their gearing mechanisms are far from optimally regulated.

q-bio.MN↗

arXiv2025

Energy Transduction in Complex Networks with Multiple Resources: The Chemistry Paradigm

We extend the traditional framework of steady state energy transduction -- typically characterized by a single input and output -- to multi-resource transduction in open chemical reaction networks (CRNs). Transduction occurs when stoichiometrically balanced processes are driven against their spontaneous directions by coupling them with thermodynamically favorable ones. However, when multiple processes (resources) interact through a shared CRN, identifying the relevant set of processes for analyzing transduction becomes a critical and complex challenge. To address this, we introduce a systematic procedure based on elementary processes, which cannot be further decomposed into subprocesses. Our theory generalizes the methodology used to define transduction efficiency in thermal engines operating between multiple heat baths. By selecting a reference equilibrium environment, it explicitly reveals the inherently relative nature of transduction efficiency and ties its definition to exergy. This framework also allows one to exclude unusable outputs from efficiency calculations. We further extend the concept of chemical gears to multi-process transduction, demonstrating their versatility as an analytical tool in complex settings. Finally, we apply our framework to central metabolic pathways, uncovering deep insights into their operation and highlighting the crucial difference between thermodynamic efficiencies and stoichiometric yields.

q-bio.MN↗

arXiv2025

Hypergraph-Based Models of Random Chemical Reaction Networks: Conservation Laws, Connectivity, and Percolation

Random graph models have been instrumental in characterizing complex networks, but chemical reaction networks (CRNs) are better represented as hypergraphs. Traditional models of random CRNs often reduce CRNs to bipartite graphs, representing species and reactions as distinct nodes, or simpler derived graphs, which can obscure the relationship between the statistical properties of these representations and the physical characteristics of the CRN. We introduce a straightforward model for generating random CRNs that preserves their hypergraph structure as well as atomic composition, enabling the direct study of chemically relevant features. Notably, our approach distinguishes two notions of connectivity that are equivalent in graphs but differ fundamentally in hypergraphs. These notions exhibit percolation-like phase transitions, which we analyze in detail. The first type of connectivity has relevance to steady-state synthesis and transduction, determining the effective reactions an open CRN can perform at steady state. The second type is suitable to identify which species can be produced from a given initial set of species in a closed CRN. Our findings highlight the importance of hypergraph-based modeling for uncovering the complex behaviors of CRNs.

cond-mat.stat-mech↗

arXiv2025

Quantifying dissipation in flocking dynamics: When tracking internal states matters

Aligning self-propelled particles undergo a nonequilibrium flocking transition from apolar to polar phases as their interactions become stronger. We propose a thermodynamically consistent lattice model, in which the internal state of the particles biases their diffusion, to capture such a transition. Changes of internal states and jumps between lattice sites obey local detailed balance with respect to the same interaction energy. We unveil a crossover between two regimes: for weak interactions, the dissipation is maximal, and partial inference (namely, based on discarding the dynamics of internal states) leads to a severe underestimation; for strong interactions, the dissipation is reduced, and partial inference captures most of the dissipation. Finally, we reveal that the macroscopic dissipation, evaluated at the hydrodynamic level, coincides with the microscopic dissipation upon coarse-graining. We argue that this correspondence stems from a generic mapping of active lattice models with local detailed balance into a specific class of non-ideal reaction-diffusion systems.

cond-mat.stat-mech↗

arXiv2025

Dissipation enables robust extensive scaling of multipartite correlations

We investigate the multipartite mutual information between $N$ discrete-state stochastic units interacting in a network that is invariant under unit permutations. We show that when the system relaxes to fixed point attractors, multipartite correlations in the stationary state either do not scale extensively with $N$, or the extensive scaling is not robust to arbitrarily small perturbations of the system dynamics. In particular, robust extensive scaling cannot occur in thermodynamic equilibrium. In contrast, mutual information scales extensively when the system relaxes to time-dependent attractors (e.g., limit cycles), which can occur only far from equilibrium. This demonstrates the essential role of dissipation in the generation and maintenance of multipartite correlations. We illustrate our theory with the nonequilibrium Potts model.

cond-mat.stat-mech↗

arXiv2025

Macroscopic Stochastic Thermodynamics

Starting at the mesoscopic level with a general formulation of stochastic thermodynamics in terms of Markov jump processes, we identify the scaling conditions that ensure the emergence of a (typically nonlinear) deterministic dynamics and an extensive thermodynamics at the macroscopic level. We then use large deviations theory to build a macroscopic fluctuation theory around this deterministic behavior, which we show preserves the fluctuation theorem. For many systems (e.g. chemical reaction networks, electronic circuits, Potts models), this theory does not coincide with Langevin-equation approaches (obtained by adding Gaussian white noise to the deterministic dynamics) which, if used, are thermodynamically inconsistent. Einstein-Onsager theory of Gaussian fluctuations and irreversible thermodynamics are recovered at equilibrium and close to it, respectively. Far from equilibirum, the free energy is replaced by the dynamically generated quasi-potential (or self-information) which is a Lyapunov function for the macroscopic dynamics. Remarkably, thermodynamics connects the dissipation along deterministic and escape trajectories to the Freidlin-Wentzell quasi-potential, thus constraining the transition rates between attractors induced by rare fluctuations. A coherent perspective on minimum and maximum entropy production principles is also provided. For systems that admit a continuous-space limit, we derive a nonequilibrium fluctuating field theory with its associated thermodynamics. Finally, we coarse grain the macroscopic stochastic dynamics into a Markov jump process describing transitions among deterministic attractors and formulate the stochastic thermodynamics emerging from it.

cond-mat.stat-mech↗

arXiv2025

What is a chemostat? Insights from hybrid dynamics and stochastic thermodynamics

At the microscopic scale, open chemical reaction networks are described by stochastic reactions that follow mass-action kinetics and are coupled to chemostats. We show that closed chemical reaction networks -- with specific stoichiometries imposed by mass-action kinetics -- behave like open ones in the limit where the abundances of a subset of species become macroscopic, thus playing the role of chemostats. We prove that this limit is thermodynamically consistent by recovering the local detailed balance condition of open chemical reaction networks and deriving the proper expression of the entropy production rate. In particular, the entropy production rate features two contributions: one accounting for the dissipation of the stochastic reactions, the other for the dissipation of continuous reactions controlling the chemostats. Finally, we illustrate our results for two prototypical examples.

q-bio.MN↗

arXiv2025

Nonequilibrium Fluctuation-Response Relations: From Identities to Bounds

In nonequilibrium steady states of Markov jump processes, we derive exact Fluctuation-Response Relations (FRRs) that express the covariance between any pair of currents in terms of static responses in a notably simple form, thus generalizing the fluctuation-dissipation theorem far from equilibrium. We begin by considering perturbations in the symmetric part of the rates. We demonstrate that FRRs imply a hierarchy of thermodynamic bounds. These hierarchies prove the recently conjectured Response Thermodynamic Uncertainty Relation (R-TUR), which bounds the ratio between any current's response and its variance by the entropy production rate (EPR). We furthermore strengthen this bound in two distinct ways, using partial EPR in one case and pseudo-EPR in the other. For perturbations in the antisymmetric part of the rates, we show that the ratio between any current's response and its variance is bounded by traffic, a metric representing the total number of transitions per unit time in the system. As an application, we use FRRs to explain the origin of positive correlations between currents in Coulomb-blockaded systems previously observed in experiments.

cond-mat.stat-mech↗

arXiv2025

Nonanalytic Landau functionals shaping the finite-size scaling of fluctuations and response functions in and out of equilibrium

Landau theory relates phase transitions to the minimization of the Landau functional (e.g., free energy functional), which is expressed as a power series of the order parameter. It has been shown that the critical behavior of certain physical systems can be described using Landau functionals that include nonanalytic terms, corresponding to odd or even noninteger powers of the absolute value of the order parameter. In particular, these nonanalytic terms can determine the order of the phase transition and the values of the critical exponents. Here, we show that such terms can also shape the finite-size scaling behavior of fluctuations of observables (e.g., of energy or magnetization) or the response functions (e.g., heat capacity or magnetic susceptibility) at the continuous phase transition point. We demonstrate this on two examples, the equilibrium molecular zipper and the nonequilibrium version of the Curie--Weiss model.

cond-mat.stat-mech↗

arXiv2025

Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks

Molecular dynamics (MD) simulations play a crucial role in scientific research. Yet their computational cost often limits the timescales and system sizes that can be explored. Most data-driven efforts have been focused on reducing the computational cost of accurate interatomic forces required for solving the equations of motion. Despite their success, however, these machine learning interatomic potentials (MLIPs) are still bound to small time-steps. In this work, we introduce TrajCast, a transferable and data-efficient framework based on autoregressive equivariant message passing networks that directly updates atomic positions and velocities lifting the constraints imposed by traditional numerical integration. We benchmark our framework across various systems, including a small molecule, crystalline material, and bulk liquid, demonstrating excellent agreement with reference MD simulations for structural, dynamical, and energetic properties. Depending on the system, TrajCast allows for forecast intervals up to $30\times$ larger than traditional MD time-steps, generating over 15 ns of trajectory data per day for a solid with more than 4,000 atoms. By enabling efficient large-scale simulations over extended timescales, TrajCast can accelerate materials discovery and explore physical phenomena beyond the reach of traditional simulations and experiments. An open-source implementation of TrajCast is accessible under https://github.com/IBM/trajcast.

physics.comp-ph↗

arXiv2025

Critical Fluctuations at Finite-Time Dynamical Phase Transition

We explore the critical properties of the recently discovered finite-time dynamical phase transition in the non-equilibrium relaxation of Ising magnets after a temperature quench. The transition is characterized by a sudden switch in the relaxation dynamics and it occurs at a sharp critical time. While previous works have focused either on mean-field interactions or on investigating the critical time, we analyze the critical fluctuations at the phase transition in the nearest-neighbor Ising model on a square lattice using Monte Carlo simulations. By means of a finite-size scaling analysis, we extract the critical exponents for the transition. In two spatial dimensions, we find that the exponents are consistent with those of the two-dimensional Ising universality class when the system is initially in the vicinity of the critical point. For initial temperatures below the critical one, however, the critical exponents differ from the Ising-exponents, indicating a distinct dynamical critical phenomenon.

cond-mat.stat-mech↗

arXiv2025

Critical heat current fluctuations in Curie-Weiss model in and out of equilibrium

In some models of nonequilibrium phase transitions, fluctuations of the analyzed currents have been observed to diverge with system size. To assess whether this behavior is universal across phase transitions, we examined heat current fluctuations in the Curie-Weiss model, a paradigmatic model of the paramagnetic-ferromagnetic phase transition, coupled to two thermal baths. This model exhibits phase transitions driven by both the temperature and the magnetic field. We find that at the temperature-driven phase transition, the heat current noise consists of two contributions: the equilibrium part, which vanishes with system size, and the nonequilibrium part, which diverges with system size. For small temperature differences, this leads to nonmonotonic scaling of fluctuations with system size. In contrast, at the magnetic-field-driven phase transition, heat current fluctuations do not diverge when observed precisely at the phase transition point. Instead, out of equilibrium, the noise is enhanced at the magnetic field values away but close to the phase transition point, due to stochastic switching between two current values. The maximum value of noise increases exponentially with system size, while the position of this maximum shifts towards the phase transition point. Finally, on the methodological side, the paper demonstrates that current fluctuations in large systems can be effectively characterized by combining a path integral approach for macroscopic fluctuations together with an effective two-state model describing subextensive transitions between the two macroscopic states involved in the phase transition.

cond-mat.stat-mech↗