arXiv subjects

Jason R. Green

Publications and source records attributed to Jason R. Green.

At least 19 recordsLinked to original sources

arXiv2026

Dynamic hysteresis in an autocatalytic reaction network

Here we show that an autocatalytic reaction network can exhibit dynamic hysteresis as a result of the competition between its intrinsic relaxation time scale and that of the periodic drive. The autocatalytic reaction steps generate bistability in the concentration of the autocatalytic species, and periodic pumping of the product species provides the external drive. Hysteresis arises from the lag between the concentration response of the autocatalytic species and the external periodic drive. The resulting hysteresis-loop area quantifies the extent of the system's hysteretic response. Using the periodically driven Schl\"ogl model as a representative bistable chemical system, we use this loop area to determine how the magnitude of the hysteretic response is controlled by the driving protocol, intrinsic fluctuations, and the size of the system. Varying the driving frequency and the strength of the fluctuations causes a turnover of the hysteresis loop area, whereas the area changes monotonically with driving amplitude and system size. These trends identify the driving protocol and fluctuation strength as primary controls on the magnitude of dynamic hysteresis. In contrast to stochastic resonance, which is typically associated with weak periodic forcing and noise-assisted amplification, dynamic hysteresis can characterize the reaction-system response over a wider range of external control conditions. We further show that the delayed concentration response is mirrored in Shannon entropy and in the total entropy production rate, connecting dynamic hysteresis to information-theoretic and stochastic-thermodynamic measures of irreversibility. Overall, we identify and interpret the role of the controlling factors in chemical dynamic hysteresis and suggest implications for efficient chemical logic gates and eventually, chemical computers.

cond-mat.stat-mech↗

arXiv2026

Harvesting Reshapes Dynamical Populations

Harvesting -- the periodic removal of individuals above or below a threshold trait value -- reshapes heterogeneous populations without altering their underlying stochastic dynamics. We study how repeated harvesting events steer the evolution of probability densities for classes of stochastic processes exhibiting both normal and anomalous dynamics, as well as a prototypical predator-prey model. Removal of the upper portion of the density drives the system to a quasi-steady state when viewed at the ``harvesting clock''. This state depends only on the harvesting threshold and frequency but not on the initial conditions. Removal of the lower portion of the density fixes its shape while generating a constant effective drift that exceeds that of the unharvested mean. Our results suggest the possibility of manipulating the dynamics of stochastic populations through external selection interventions.

cond-mat.stat-mech↗

arXiv2025

Phase space volume preserving dynamics for non-Hamiltonian systems

Infinitesimal volumes stretch and contract as they coevolve with classical phase space trajectories according to linearized dynamics. Unless these tangent-space dynamics are modified, chaotic evolution causes the volume spanned by evolving tangent vectors to collapse. However, this collapse is unphysical and due to their exponential alignment along the most expanding direction, independent of the compressibility of the phase-space volume. Here, we propose an alternative linearized dynamics and rectify the generalized Liouville equation to preserve phase space volume, even for non-Hamiltonian systems. Within a classical density matrix theory, we define the time evolution operator from the anti-symmetric part of the stability matrix so that phase space volume is time-invariant. The operator generates orthogonal transformations without distorting volume elements, providing an invariant measure for dissipative dynamics and a evolution equation for the density matrix akin to the quantum mechanical Liouville-von Neumann equation. The compressibility of volume elements is determined by a non-orthogonal operator made from the symmetric part of the stability matrix. We analyze complete sets of basis vectors for the tangent space dynamics of chaotic systems, which may be dissipative, transient or driven, without re-orthogonalization of tangent vectors. The linear harmonic oscillator, the Lorenz-Fetter model, and the H\'enon-Heiles system demonstrate the computation of the instantaneous Lyapunov exponent spectrum and the local Gibbs entropy flow rate using these bases and show that it is numerically convenient.

nlin.CD↗

arXiv2025

Phase space contraction rate for classical mixed states

Physical systems with non-reciprocal or dissipative forces evolve according to a generalization of Liouville's equation that accounts for the expansion and contraction of phase space volume. Here, we connect geometric descriptions of these non-Hamiltonian dynamics to a recently established classical density matrix theory. In this theory, the evolution of a ``maximally mixed'' classical density matrix is related to the well-known phase space contraction rate that, when ensemble averaged, is the rate of entropy exchange with the surroundings. Here, we extend the definition of mixed states to include statistical and mechanical components, describing both the deformations of local phase space regions and the evolution of ensembles within them. As a result, the equation of motion for this mixed state represents the rate of contraction for an ensemble of dissipative trajectories. Recognizing this density matrix as a covariance matrix, its contraction rate is another measure of entropy flow characterizing nonequilibrium steady states.

cond-mat.stat-mech↗

arXiv2025

Spectral bounds on the entropy flow rate and Lyapunov exponents in differentiable dynamical systems

Some microscopic dynamics are also macroscopically irreversible, dissipating energy and producing entropy. For many-particle systems interacting with deterministic thermostats, the rate of thermodynamic entropy dissipated to the environment is the average rate at which phase space contracts. Here, we use this identity and the properties of a classical density matrix to derive upper and lower bounds on the entropy flow rate with the spectral properties of the local stability matrix. These bounds are an extension of more fundamental bounds on the Lyapunov exponents and phase space contraction rate of continuous-time dynamical systems. They are maximal and minimal rates of entropy production, heat transfer, and transport coefficients set by the underlying dynamics of the system and deterministic thermostat. Because these limits on the macroscopic dissipation derive from the density matrix and the local stability matrix, they are numerically computable from the molecular dynamics. As an illustration, we show that these bounds are on the electrical conductivity for a system of charged particles subject to an electric field.

physics.class-ph↗

arXiv2024

Dissipation rates from experimental uncertainty

Active matter and driven systems exhibit statistical fluctuations in density and particle positions, providing an indirect indicator of dissipation across multiple length and time scales. Here, we quantitatively relate these measurable fluctuations to a thermodynamic speed limit that constrains the rates of heat and entropy production in nonequilibrium processes. By reparametrizing the speed limit, we show how to infer heat and entropy production rates from directly observable or controllable quantities. This approach can use available experimental data and avoid the need for analytically solvable microscopic models or full time-dependent probability distributions. The heat rate we predict agrees with experimental measurements for a Brownian particle and a microtubule active gel, which validates the approach and suggests potential for the design of experiments.

cond-mat.stat-mech↗

arXiv2024

Maximum speed of dissipation

We derive statistical-mechanical speed limits on dissipation from the classical, chaotic dynamics of many-particle systems. In one, the rate of irreversible entropy production in the environment is the maximum speed of a deterministic system out of equilibrium, $\bar S_e/k_B\geq 1/2Δt$, and its inverse is the minimum time to execute the process, $Δt\geq k_B/2\bar S_e$. Starting with deterministic fluctuation theorems, we show there is a corresponding class of speed limits for physical observables measuring dissipation rates. For example, in many-particle systems interacting with a deterministic thermostat, there is a trade-off between the time to evolve between states and the heat flux, $\bar{Q}Δt\geq k_BT/2$. These bounds constrain the relationship between dissipation and time during nonstationary process, including transient excursions from steady states.

cond-mat.stat-mech↗

arXiv2023

Classical Fisher information for differentiable dynamical systems

Fisher information is a lower bound on the uncertainty in the statistical estimation of classical and quantum mechanical parameters. While some deterministic dynamical systems are not subject to random fluctuations, they do still have a form of uncertainty: Infinitesimal perturbations to the initial conditions can grow exponentially in time, a signature of deterministic chaos. As a measure of this uncertainty, we introduce another classical information, specifically for the deterministic dynamics of isolated, closed, or open classical systems not subject to noise. This classical measure of information is defined with Lyapunov vectors in tangent space, making it less akin to the classical Fisher information and more akin to the quantum Fisher information defined with wavevectors in Hilbert space. Our analysis of the local state space structure and linear stability lead to upper and lower bounds on this information, giving it an interpretation as the net stretching action of the flow. Numerical calculations of this information for illustrative mechanical examples show that it depends directly on the phase space curvature and speed of the flow.

physics.class-ph↗

arXiv2023

Prevalence of multistability and nonstationarity in driven chemical networks

External flows of energy, entropy, and matter can cause sudden transitions in the stability of biological and industrial systems, fundamentally altering their dynamical function. How might we control and design these transitions in chemical reaction networks? Here, we analyze transitions giving rise to complex behavior in random reaction networks subject to external driving forces. In the absence of driving, we characterize the uniqueness of the steady state and identify the percolation of a giant connected component in these networks as the number of reactions increases. When subject to chemical driving (influx and outflux of chemical species), the steady state can undergo bifurcations, leading to multistability or oscillatory dynamics. By quantifying the prevalence of these bifurcations, we show how chemical driving and network sparsity tend to promote the emergence of these complex dynamics and increased rates of entropy production. We show that catalysis also plays an important role in the emergence of complexity, strongly correlating with the prevalence of bifurcations. Our results suggest that coupling a minimal number of chemical signatures with external driving can lead to features present in biochemical processes and abiogenesis.

q-bio.MN↗

arXiv2023

Thermodynamic speed limits for mechanical work

Thermodynamic speed limits are a set of classical uncertainty relations that, so far, place global bounds on the stochastic dissipation of energy as heat and the production of entropy. Here, instead of constraints on these thermodynamic costs, we derive integral speed limits that are upper and lower bounds on a thermodynamic benefit -- the minimum time for an amount of mechanical work to be done on or by a system. In the short time limit, we show how this extrinsic timescale relates to an intrinsic timescale for work, recovering the intrinsic timescales in differential speed limits from these integral speed limits and turning the first law of stochastic thermodynamics into a first law of speeds. As physical examples, we consider the work done by a flashing Brownian ratchet and the work done on a particle in a potential well subject to external driving.

cond-mat.stat-mech↗

arXiv2022

Speed limits on classical chaos

Uncertainty in the initial conditions of dynamical systems can cause exponentially fast divergence of trajectories, a signature of deterministic chaos. Here, we derive a classical uncertainty relation that sets a speed limit on the rates of local observables underlying this behavior. For systems with a time-invariant stability matrix, this general speed limit simplifies to classical analogues of the Mandelstam-Tamm versions of the time-energy uncertainty relation. This classical bound derives from our definition of Fisher information in terms of Lyapunov vectors on tangent space, analogous to the quantum Fisher information defined in terms of wavevectors on Hilbert space. This information measures fluctuations in local stability of the state space and sets a lower bound on the time of classical, dynamical systems to evolve between two distinguishable states. The bounds it sets apply to systems that are open or closed, conservative or dissipative, actively driven or passively evolving, and directly connect the geometries of phase space and information.

nlin.CD↗

arXiv2021

Stochastic paths controlling speed and dissipation

Near equilibrium, thermodynamic intuition suggests that fast, irreversible processes will dissipate more energy and entropy than slow, quasistatic processes connecting the same initial and final states. Here, we test the hypothesis that this relationship between speed and dissipation holds for stochastic processes far from equilibrium. To analyze these processes on finite timescales, we derive an exact expression for the path probabilities of continuous-time Markov chains from the path summation solution of the master equation. Applying this formula to a model for nonequilibrium self-assembly, we show that more speed can lead to less dissipation when there are strong nonequilibrium currents. In the model, the relative energies of the initial and target states control the speed, and the nonequilibrium currents of a cycle situated between these states control the path-level dissipation. This model serves as a minimal prototype for designing kinetics to sculpt the nonequilibrium path space, so that faster structure-forming paths dissipate less.

cond-mat.stat-mech↗

arXiv2021

Density matrix formulation of dynamical systems

Physical systems that dissipate, mix and develop turbulence also irreversibly transport statistical density. In statistical physics, laws for these processes have a mathematical form and tractability that depends on whether the description is classical or quantum mechanical. Here, we establish a theory for density transport in any classical dynamical system that is analogous to the density matrix formulation of quantum mechanics. Defining states in terms of a classical density matrix leads to generalizations of Liouville's theorem and Liouville's equation, establishing an alternative computationally-tractable basis for nonequilibrium statistical mechanics. The formalism is complete with classical commutators and anti-commutators that embed measures of local instability and chaos and are directly related to Poisson brackets when the dynamics are Hamiltonian. It also recovers the traditional Liouville equation and the Liouville theorem by imposing trace preservation or Hamiltonian dynamics. Applying to systems that are driven, transient, dissipative, regular, and chaotic, this formalism has the potential for broad applications.

cond-mat.stat-mech↗

arXiv2021

Unifying Quantum and Classical Speed Limits on Observables

The presence of noise or the interaction with an environment can radically change the dynamics of observables of an otherwise isolated quantum system. We derive a bound on the speed with which observables of open quantum systems evolve. This speed limit divides into Mandalestam and Tamm's original time-energy uncertainty relation and a time-information uncertainty relation recently derived for classical systems, generalizing both to open quantum systems. By isolating the coherent and incoherent contributions to the system dynamics, we derive both lower and upper bounds to the speed of evolution. We prove that the latter provide tighter limits on the speed of observables than previously known quantum speed limits, and that a preferred basis of \emph{speed operators} serves to completely characterize the observables that saturate the speed limits. We use this construction to bound the effect of incoherent dynamics on the evolution of an observable and to find the Hamiltonian that gives the maximum coherent speedup to the evolution of an observable.

quant-ph↗

arXiv2021

Thermodynamic speed limits from the regression of information

Irreversible processes accomplished in a fixed time involve nonlinearly coupled flows of matter, energy, and information. Here, using entropy production as an example, we show how thermodynamic uncertainty relations and speed limits on these nonlinear processes derive from linear regression. These uncertainty relations hold for both passive and actively-driven nonequilibrium processes and all have a mathematical form that mirrors uncertainty relations in quantum mechanics. Using optimal linear models, we show that information-theoretic variables naturally give physical predictions of the equation of motion on statistical manifolds in terms of physical observables. In these models, optimal intercepts are related to nonequilibrium analogs of Massieu functions/thermodynamic potentials, and optimal slopes are related to speed limits on collections of thermodynamic observables. Within this formalism, the second law of thermodynamics has a geometric interpretation as the nonnegativity of the slope and constrains the equation of motion. Overall, our results suggest that unknown relationships between nonequilibrium variables can be learned through statistical-mechanical inference.

cond-mat.stat-mech↗

arXiv2021

Universal dynamic scaling in chemical reactions at and away from equilibrium

Physical kinetic roughening processes are well known to exhibit universal scaling of observables that fluctuate in space and time. Are there analogous dynamic scaling laws that are unique to the chemical reaction mechanisms available synthetically and occurring naturally? Here, we formulate two complementary approaches to the dynamic scaling of stochastic fluctuations in thermodynamic observables at and away from equilibrium. Both analytical expressions and numerical simulations confirm our dynamic scaling ans{ä}tze with their associated exponents, functions, and laws. A survey of common chemical mechanisms reveals classes that organize according to the molecularity of the reactions involved, the nature of the reaction vessel and external reservoirs, (non)equilibrium conditions, and the extent of autocatalysis in the reaction network. Coupled reactions capable of chemical feedback can transition, sometimes sharply, between these classes with the variation of experimental parameters such as temperature. While path observables like the dynamical activity have scaling exponents that are time-independent, fluctuations in the entropy production and flow can have time-dependent scaling exponents and self-averaging properties as a result of temporal correlations that emerge during thermodynamically irreversible processes. Altogether, these results establish dynamic universality in the nonequilibrium fluctuations of thermodynamic observables for well-mixed chemical reactions.

cond-mat.stat-mech↗

arXiv2020

Non-normality and non-monotonic dynamics in complex reaction networks

Complex chemical reaction networks, which underlie many industrial and biological processes, often exhibit non-monotonic changes in chemical species concentrations, typically described using nonlinear models. Such non-monotonic dynamics are in principle possible even in linear models if the matrices defining the models are non-normal, as characterized by a necessarily non-orthogonal set of eigenvectors. However, the extent to which non-normality is responsible for non-monotonic behavior remains an open question. Here, using a master equation to model the reaction dynamics, we derive a general condition for observing non-monotonic dynamics of individual species, establishing that non-normality promotes non-monotonicity but is not a requirement for it. In contrast, we show that non-normality is a requirement for non-monotonic dynamics to be observed in the Rényi entropy. Using hydrogen combustion as an example application, we demonstrate that non-monotonic dynamics under experimental conditions are supported by a linear chain of connected components, in contrast with the dominance of a single giant component observed in typical random reaction networks. The exact linearity of the master equation enables development of rigorous theory and simulations for dynamical networks of unprecedented size (approaching $10^5$ dynamical variables, even for a network of only 20 reactions and involving less than 100 atoms). Our conclusions are expected to hold for other combustion processes, and the general theory we develop is applicable to all chemical reaction networks, including biological ones.

nlin.AO↗

arXiv2020

Time-information uncertainty relations in thermodynamics

Physical systems that power motion and create structure in a fixed amount of time dissipate energy and produce entropy. Whether living or synthetic, systems performing these dynamic functions must balance dissipation and speed. Here, we show that rates of energy and entropy exchange are subject to a speed limit -- a time-information uncertainty relation -- imposed by the rates of change in the information content of the system. This uncertainty relation bounds the time that elapses before the change in a thermodynamic quantity has the same magnitude as its initial standard deviation. From this general bound, we establish a family of speed limits for heat, work, entropy production, and entropy flow depending on the experimental constraints on the system. In all of these inequalities, the time scale of transient dynamical fluctuations is universally bounded by the Fisher information. Moreover, they all have a mathematical form that mirrors the Mandelstam-Tamm version of the time-energy uncertainty relation in quantum mechanics. These bounds on the speed of arbitrary observables apply to transient systems away from thermodynamic equilibrium, independent of the physical assumptions about the stochastic dynamics or their function.

cond-mat.stat-mech↗