Nonequilibrium Dynamics Research Articles

Quantifying Dynamic Phenotypic Heterogeneity in Resistant Escherichia coli under Translation-Inhibiting Antibiotics.

Understanding the phenotypic heterogeneity of antibiotic-resistant bacteria following treatment and the transitions between different phenotypes is crucial for developing effective infection control strategies. The study expands upon previous work by explicating chloramphenicol-induced phenotypic heterogeneities in growth rate, gene expression, and morphology of resistant Escherichia coli using time-lapse microscopy. Correlating the bacterial growth rate and cspC expression, four interchangeable phenotypic subpopulations across varying antibiotic concentrations are identified, surpassing the previously described growth rate bistability. Notably, bacterial cells exhibiting either fast or slow growth rates can concurrently harbor subpopulations characterized by high and low gene expression levels, respectively. To elucidate the mechanisms behind this enhanced heterogeneity, a concise gene expression network model is proposed and the biological significance of the four phenotypes is further explored. Additionally, by employing Hidden Markov Model fitting and integrating the non-equilibrium landscape and flux theory, the real-time data encompassing diverse bacterial traits are analyzed. This approach reveals dynamic changes and switching kinetics in different cell fates, facilitating the quantification of observable behaviors and the non-equilibrium dynamics and thermodynamics at play. The results highlight the multi-dimensional heterogeneous behaviors of antibiotic-resistant bacteria under antibiotic stress, providing new insights into the compromised antibiotic efficacy, microbial response, and associated evolution processes.

Data-driven dynamical coarse-graining for condensed matter systems.

Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in a solution, where the molecule(s) and the solvent dynamics need to be integrated, rendering the simulations computationally costly and often unfeasible for physically/biologically relevant time scales. Standard coarse graining approaches can reproduce equilibrium distributions and structural features but do not properly include the dynamics. In this work, we develop a general data-driven coarse-graining methodology inspired by the Mori-Zwanzig formalism, which shows that macroscopic systems with a large number of degrees of freedom can be described by a few relevant variables and additional noise and memory terms. Our coarse-graining method consists of numerical integrators for the distinguished components, where the noise and interaction terms with other system components are substituted by a random variable sampled from a data-driven model. The model is parameterized using data from multiple short-time full-system simulations, and then, it is used to run long-time simulations. Applying our methodology to three systems-a distinguished particle under a harmonic and a bistable potential and a dimer with two metastable configurations-the resulting coarse-grained models are capable of reproducing not only the equilibrium distributions but also the dynamic behavior due to temporal correlations and memory effects. Remarkably, our method even reproduces the transition dynamics between metastable states, which is challenging to capture correctly. Our approach is not constrained to specific dynamics and can be extended to systems beyond Langevin dynamics, and, in principle, even to non-equilibrium dynamics.

Measuring out quasi-local integrals of motion from entanglement

Quasi-local integrals of motion are a key concept underpinning the modern understanding of many-body localisation, a phenomenon in which interactions and disorder come together. Despite the existence of several numerical ways to compute them—and in the light of the observation that much of the phenomenology of many properties can be derived from them—it is not obvious how to directly measure aspects of them in real quantum simulations; in fact, hard experimental evidence is still missing. In this work, we propose a way to extract the real-space properties of such quasi-local integrals of motion based on a spatially-resolved entanglement probe able to distinguish Anderson from many-body localisation from non-equilibrium dynamics. We complement these findings with a rigorous entanglement bound and compute the relevant quantities using tensor networks. We demonstrate that the entanglement gives rise to a well-defined length scale that can be measured in experiments.

Quantum velocity limits for multiple observables: Conservation laws, correlations, and macroscopic systems

How multiple observables mutually influence their dynamics has been a crucial issue in statistical mechanics. We here introduce a new concept, “quantum velocity limits,” to establish a quantitative and rigorous theory for nonequilibrium quantum dynamics for multiple observables. Quantum velocity limits are universal inequalities for a vector that describes velocities of multiple observables. They elucidate that the speed of an observable of our interest can be tighter bounded when we have knowledge of other observables, such as experimentally accessible ones or conserved quantities, compared with conventional speed limits for a single observable. Moreover, quantum velocity limits are conceptually distinct from the conventional speed limits because we need to introduce the velocity vector and solve an optimization problem for multiple variables to obtain them. We first derive an information-theoretical velocity limit in terms of the generalized correlation matrix of the observables and the quantum Fisher information. The velocity limit has various novel consequences: (i) conservation law in the system, a fundamental ingredient of quantum dynamics, can improve the velocity limits through the correlation between the observables and conserved quantities; (ii) speed of an observable can be bounded by a nontrivial lower bound from the information on another observable, while most of the previous speed limits provide only upper bounds; (iii) there exists a notable nonequilibrium tradeoff relation, stating that speeds of uncorrelated observables, e.g., anticommuting observables, cannot be simultaneously large; (iv) velocity limits for local observables in locally interacting many-body systems are described by the fluctuation of a local Hamiltonian, which is convergent even in the thermodynamic limit, with a nontrivial finite-size correction. Moreover, we discover another distinct velocity limit for multiple observables on the basis of the local conservation law of probability current, which becomes advantageous for macroscopic transitions of multiple quantities. Our newly found velocity limits ubiquitously apply not only to unitary quantum dynamics but to classical and quantum stochastic dynamics, offering a key step towards universal theory of far-from-equilibrium dynamics for multiple observables. Published by the American Physical Society 2024

Non-equilibrium dynamics and phase transitions in Potts model and interacting Ehrenfest urn model

We show that the recently proposed interacting Ehrenfest M-urn model at equilibrium (Cheng et al., 2020) can be exactly mapped to a mean-field M-state Potts model. By exploiting this correspondence, we show that the M-state Potts model with M≥3, with transition rates motivated by the non-equilibrium urn model, can exhibit rich non-equilibrium spin dynamics such as non-equilibrium steady states and non-equilibrium periodic states. Monte Carlo simulations of the 3-state Potts model are performed to demonstrate explicitly the first-order transitions for the equilibrium and non-equilibrium steady states, as well as the far-from-equilibrium periodic states.

Recasting tenure and labour in non-equilibrium environments: Making the case for “high-reliability” pastoral institutions

This paper explores how pastoralists collectively manage resources in contexts of high environmental variability in the drylands of southern Tunisia. The khlata, the practice of pooling herds, allows for livestock owners to manage scarce resources in environments characterized by non-equilibrium dynamics. This institution legitimizes access to a wider range of pasture land thus tracking patchy rainfall distribution, and allows for the sharing of herding labour and so allows for “absence” in pastoral production, thus enabling human mobility. The khlata, recasts conceptualizations of tenure and labour in ways that subvert neoliberal models of production, and adapt to changing political economic conditions. Such collective herding practices can be likened to “high-reliability” management ideas that accommodate the social and networked dimensions of land-use in drylands, where coordination and connectivity through institutions becomes crucial. The theoretical approach includes pastoral perspectives on tenure, where rules are not well defined and membership is fluid, contributing to a different take on conventional common-property debates and neoliberal views on property, and indeed institutions. When pastoral production is framed as a high-reliability system, the objective of maintaining security and at the same time flexibility in land tenure is emphasised: livestock owners make use of a wide range of scale-dependent resources, whether public, private, or common property. Land-use policy should therefore focus not on rules and regulations but how to support institutions that maintain a highly-reliable system within contexts of fuzzy tenure regimes. Land-use policy should therefore focus on coordinating connectivity through collective arrangements by prioritizing the “informal” and adaptive nature of institutions such as the khlata, rather than focusing on their formalization. Overall, the paper shows how the khlata redefines access to land and labour in ways that create additional options for pastoralists to adapt to changing political economic conditions in southern Tunisia.

Metastable dynamics of Rydberg atomic system under electromagnetically induced transparency

Open quantum system, coupled with an external bath is a key research field of quantum physics. Steady state is the state in which any initial state converges after a long time and is usually of the most interest. However, relatively speaking, the nonequilibrium dynamical processes of quantum many-body systems have been rarely studied. This is mainly due to the fact that quantum many-body systems generally have interactions, and the Hilbert space required for a complete description of their dynamical processes will grow exponentially with the number of particles increasing, and the computational difficulty will increase dramatically as well. Hence, it is a difficult problem to completely describe their dynamical processes completely. With the development of quantum technologies, the interest in the nonequilibrium dynamics of open quantum many-body systems is aroused. A common phenomenon is the metastable state, where the system initially relaxes into a long-lived state and then converges to the final stationary state for a longer time. In this paper, we establish a low-dimensional approximation to describe the metastability dynamics in Markovian open quantum system, based on the spectra of the Liouvillian super-operator. The separation of time scales implies a splitting in the spectrum, and this spectral division allows us to eliminate the fast decay modes by using the perturbation method, and then we establish the effective description in the low-lying eigenmodes subspace. Furthermore, we study the dynamics process of the Rydberg atomic system under electromagnetically induced transparency (EIT) conditions and find that the system can handle metastable dynamics if the atomic interactions are considered. We compare the effective dynamics in the subspace with the actual dynamics in the full space, and the results show that the effective dynamics works well on condition that the perturbation approximation holds. Our work provides a feasible idea and method for establishing an effective and simplified description of the dynamical process of open quantum many-body systems.

Short-term responses of littoral phytoplankton in a large shallow subtropical lake.

The littoral zone is an essential compartment for lake biota because of its high productivity and diversity. Moreover, phytoplankton is expected to have non-equilibrium dynamics on it. The study's aimed to explore phytoplankton in the littoral zone of a shallow lake over a short-term scale. Daily sampling was conducted for 25 consecutive summer days in 2016, at two marginal points of a continuously warm, polymictic, and oligo-mesotrophic subtropical lake (Lake Mangueira, Brazil). Cyanobacteria and Chlorophyta contributed 86% of total biomass. We observed high variability in phytoplankton structure, with species turnover over diel cycles. Redundancy analysis indicated spatial differentiation for phytoplankton structure in relation to abiotic conditions. Nutrient dynamics and humic substances were significant drivers for phytoplankton variability. Phytoplankton was positively correlated with SRP and negatively with humic substances. Our results showed a non- equilibrium state for the littoral phytoplankton of Lake Mangueira, given the high variability of abiotic conditions, even at short distances. Due to its high temporal and spatial variability, the littoralzone seems to contribute to the recruitment and maintenance of phytoplankton biodiversity in shallow lakes. Further studies should consider the functional attributes of species and the complex biological interactions of phytoplankton and macrophytes along the littoral zone.

Regression models for calculating state-to-state coefficients of the rate of vibrational energy exchanges

The paper proposes an effective algorithm for solving problems of nonequilibrium gas dynamics taking into account detailed state-to-state vibrational kinetics. One of the problems of traditional methods is their high computational complexity, which requires a lot of time and memory. The work explored the possibilities of using relaxation rate prediction to improve the performance of numerical simulations of nonequilibrium oxygen flows instead of direct calculations. For this purpose, an approach based on nonlinear regression analysis was used, which made it possible to obtain computationally efficient approximation formulas for the energy exchange rate coefficients in the model of a forced harmonic oscillator, taking into account free rotations (FHO-FR), to significantly increase the calculation speed while maintaining accuracy, and to construct an optimized model FHO-FR-reg. Using the obtained regression formulas, numerical modeling was carried out, which made it possible to validate the model for the problem of oxygen flow behind an incident and reflected shock wave. A comparison between the forced harmonic oscillator (FHO) and FHO-FR models is not possible due to the high computational complexity of the second model. With the advent of a common approximation model, it became possible to compare simulation results for these models. Numerical calculations have shown that the FHO-FR-reg model gives values of gas-dynamic parameters close to the FHO model. The developed regression models make it possible to speed up the solution of the problem of modeling oxygen relaxation several times compared to other models of similar accuracy.

Entanglement asymmetry and quantum Mpemba effect in the XY spin chain

Entanglement asymmetry is a quantity recently introduced to measure how much a symmetry is broken in a part of an extended quantum system. It has been employed to analyze the non-equilibrium dynamics of a broken symmetry after a global quantum quench with a Hamiltonian that preserves it. In this work, we carry out a comprehensive analysis of the entanglement asymmetry at equilibrium taking the ground state of the XY spin chain, which breaks the U(1) particle number symmetry, and provide a physical interpretation of it in terms of superconducting Cooper pairs. We also consider quenches from this ground state to the XX spin chain, which preserves the U(1) symmetry. In this case, the entanglement asymmetry reveals that the more the symmetry is initially broken, the faster it may be restored in a subsystem, a surprising and counter-intuitive phenomenon that is a type of a quantum Mpemba effect. We obtain a quasi-particle picture for the entanglement asymmetry in terms of Cooper pairs, from which we derive the microscopic conditions to observe the quantum Mpemba effect in this system, giving further support to the criteria recently proposed for arbitrary integrable quantum systems. In addition, we find that the power law governing symmetry restoration depends discontinuously on whether the initial state is critical or not, leading to new forms of strong and weak Mpemba effects.

Convolutional neural networks applied to differential dynamic microscopy reduces noise when quantifying heterogeneous dynamics.

Differential dynamic microscopy (DDM) typically relies on movies containing hundreds or thousands of frames to accurately quantify motion in soft matter systems. Using movies much shorter in duration produces noisier and less accurate results. This limits the applicability of DDM to situations where the dynamics are stationary over extended times. Here, we investigate a method to denoise the DDM process, particularly suited to when a limited number of imaging frames are available or when dynamics are quickly evolving in time. We use a convolutional neural network encoder-decoder (CNN-ED) model to reduce the noise in the intermediate scattering function that is computed via DDM. We demonstrate this approach of combining machine learning and DDM on samples containing diffusing micron-sized colloidal particles. We quantify how the particles' diffusivities change over time as the fluid they are suspended in gels. We also quantify how the diffusivity of particles varies with position in a sample containing a viscosity gradient. These test cases demonstrate how studies of non-equilibrium dynamics and high-throughput screens could benefit from a method to denoise the outputs of DDM.

Particle-based and continuum models for confined nematics in two dimensions.

We use the particle-based stochastic multi-particle collision dynamics (N-MPCD) algorithm to simulate confined nematic liquid crystals in regular two-dimensional polygons such as squares, pentagons and hexagons. We consider a range of values of the nematicities, U, and simulation domain sizes, R, that canvass nano-sized polygons to micron-sized polygons. We use closure arguments to define mappings between the N-MPCD parameters and the parameters in the continuum deterministic Landau-de Gennes framework. The averaged N-MPCD configurations agree with those predicted by Landau-de Gennes theory, at least for large polygons. We study relaxation dynamics or the non-equilibrium dynamics of confined nematics in polygons, in the N-MPCD framework, and the kinetic traps bear strong resemblance to the unstable saddle points in the Landau-de Gennes framework. Finally, we study nematic defect dynamics inside the polygons in the N-MPCD framework and the finite-size effects slow down the defects and attract them to polygon vertices. Our work is a comprehensive comparison between particle-based stochastic N-MPCD methods and deterministic/continuum Landau-de Gennes methods, and this comparison is essential for new-age multiscale theories.

Can we observe effects of early nonequilibrium dynamics using collective flow

The rapid expansion of the fireball created in a heavy-ion collision causes strong departures from equilibrium. Such effects are especially important in the very early phase of the collision, bringing a substantial pressure asymmetry. The longitudinal pressure is much smaller than the transverse one. We investigate effects of this early stage pressure asymmetry in a kinetic model without boost-invariance. In the kinetic evolution the asymmetry results from the compettion of the longitudinal expasnion rate and th erelaxation rate. Unlike the transverse flow, the directed flow is found to be very sensitive to the equilibration rate and the pressure anisotropy.

Interactions between temperature and nutrients determine the population dynamics of primary producers.

Global change is rapidly and fundamentally altering many of the processes regulating the flux of energy throughout ecosystems, and although researchers now understand the effect of temperature on key rates (such as aquatic primary productivity), the theoretical foundation needed to generate forecasts of biomass dynamics and extinction risk remains underdeveloped. We develop new theory that describes the interconnected effects of nutrients and temperature on phytoplankton populations and show that the thermal response of equilibrium biomass (i.e. carrying capacity) always peaks at a lower temperature than for productivity (i.e. growth rate). This mismatch is driven by differences in the thermal responses of growth, death, and per-capita impact on the nutrient pool, making our results highly general and applicable to widely used population models beyond phytoplankton. We further show that non-equilibrium dynamics depend on the pace of environmental change relative to underlying vital rates and that populations respond to variable environments differently at high versus low temperatures due to thermal asymmetries.

Molecular Simulation for Atmospheric Reactions: Non-Equilibrium Dynamics, Roaming, and Glycolaldehyde Formation following Photoinduced Decomposition of syn-Acetaldehyde Oxide.

The decomposition dynamics of vibrationally excited syn-CH3CHOO to form vinoxy + hydroxyl (CH2CHO + OH) radicals or to recombine to form glycolaldehyde (CH2OHCHO) are characterized using statistically significant numbers of molecular dynamics simulations using a full-dimensional neural-network-based potential energy surface at the CASPT2 level of theory. The computed final OH-translational and rotational state distributions agree well with experiments and probe the still unknown O-O bond strength DeOO for which best values from 22 to 25 kcal/mol are found. OH-elimination rates are consistent with experiments and do not vary appreciably with DeOO due to the non-equilibrium nature of the process. In addition to the OH-elimination pathway, OH roaming is observed following O-O scission, which leads to glycolaldehyde formation on the picosecond time scale. Together with recent work involving the methyl-ethyl-substituted Criegee intermediate, we conclude that OH roaming is a general pathway to be included in molecular-level modeling of atmospheric processes. This work demonstrates that atomistic simulations with machine-learned energy functions provide a viable route for exploring the chemistry and reaction dynamics of atmospheric reactions.

Effect of surface roughness and morphology on the adsorption and transport of CH4/CO2 mixtures in nanoporous carbons

We report here molecular simulations of the adsorption and transport behaviour of CH4/CO2 mixtures in two types of non-ideal carbon nanopores. One model decorates an otherwise slit pore with surface imperfections which disrupt the smooth walls; a second model considers a disordered media, formed of randomly arranged coronene flakes, resulting in significant tortuosity. Boundary-Driven Non-Equilibrium Molecular Dynamics (BD-NEMD) and External Force Non-Equilibrium Molecular Dynamics (EF-NEMD) are used to study adsorption and transport properties in both types of pores with varying degrees of rugosity and tortuosity. Intermolecular interactions and bulk fluid properties are described by the statistical associating fluid theory (SAFT) coarse-grained Mie potential and equation of state respectively. Strong CO2 adsorption and fast CH4 transport are observed in smooth slit pores. Small instances of surface rugosity change the dynamics significantly, reducing the transport diffusivity by over an order of magnitude. The fast plug-like flow reported in slit pores dissipates with increasing rugosity, indicating a fundamental change in the flow pattern. Furthermore, rugose pores exhibit a lower capacity for CO2 adsorption, suggesting the performance of CO2 -enhanced oil recovery may be overestimated by the smooth pore models. A pore characteristic factor is shown to be appropriate to correlate the transport diffusivities in nano-pores.

Violations of the fluctuation-dissipation theorem reveal distinct nonequilibrium dynamics of brain states.

The brain is a nonequilibrium system whose dynamics change in different brain states, such as wakefulness and deep sleep. Thermodynamics provides the tools for revealing these nonequilibrium dynamics. We used violations of the fluctuation-dissipation theorem to describe the hierarchy of nonequilibrium dynamics associated with different brain states. Together with a whole-brain model fitted to empirical human neuroimaging data, and deriving the appropriate analytical expressions, we were able to capture the deviation from equilibrium in different brain states that arises from asymmetric interactions and hierarchical organization.

(Invited) Exciton Transport in Strained 2D Semiconductors

Being atomically thin, flexible, and exhibiting considerable light emission and ultrafast non-equilibrium dynamics, semiconducting transition metal dichalcogenides (TMDs) have been considered as promising candidates for next-generation optoelectronic devices. The optical and electronic properties of TMDs are governed by a rich landscape of tightly bound excitons, including regular bright excitons, as well as optically inaccessible dark exciton states. Recently, strain engineering of monolayer TMDs has been introduced to tune their optical properties, such as the exciton transition energy, exciton-phonon coupling, or the Stokes shift [1-3].Transport of charge carriers is crucial for nanoelectronics. In conventional materials, electronic transport can be conveniently controlled by external electric fields. However, the tightly bound excitons, being neutral particles, are only weakly affected by electrical fields. We demonstrate that mechanical strain can also be used to manipulate the transport of excitons in TMDs. To this end, we apply homogeneous tensile strain to a WS2 monolayer by bending the substrate [1], which causes a redshift of the X0 exciton photoluminescence. By measuring the spatiotemporal photoluminescence after near-resonant excitation with femtosecond laser pulses, we map the spread of excitons and extract the strain-dependent diffusion coefficient [4].Furthermore, we demonstrate the propagation of excitons in an inhomogeneous strain landscape. We create inhomogeneous tensile strain in TMD monolayers by transferring them onto patterned substrates with nanopillars or by a nanoimprint technique [5]. Due to the redshift of the exciton resonances with applied strain, excitons are expected to move towards high-strain regions in an inhomogeneous strain field - the so-called "funneling" effect. We verify this behavior for the "bright" TMD material monolayer MoSe2. In the case of the "dark" monolayer WS2, we observe exactly the opposite effect. Here, the excitons are expelled from the high-strain regions ("anti-funneling") [6]. By comparing our experimental results with a microscopic theory, we explain this observation by the drift of momentum-dark KΛ excitons, which, in contrast to bright excitons, shift to higher energies with strain.Our joint experiment-theory study highlights the dominant role of momentum-dark excitons for the dynamics in monolayer TMDs and provides crucial design guidelines for TMD devices based on exciton transport.

The Observed O vi Is Just the Tip of the Iceberg: Estimating the Hidden Material in Circumgalactic and Intergalactic Clouds

This paper proposes a new method for estimating the total quantity of material in moving circumgalactic and intergalactic clouds from O vi measurements. We simulate high-velocity clouds (HVCs) with the FLASH hydrodynamic code and track the ionization and recombination of all ionization levels of oxygen as a function of time. We calculate the O vi/oxygen ratio (f O VI ) in our dynamic nonequilibrium ionization clouds, finding that it differs significantly from that in static gas. We find that O vi exists in cool, medium, and hot gas in the clouds. As such, it traces all of the hydrogen rather than merely the ionized hydrogen. The total quantity of hydrogen along a typical observed line of sight through a cloud can be estimated from the observed O vi column density, metallicity, and our f O VI . We provide the simulations’ f O VI values, a prescription for finding f O VI for observed dynamic clouds, and a methodology for calculating the total hydrogen column density from f O VI and an observed O vi column density. As examples, we use our f O VI values to estimate the total hydrogen column densities along various observed sight lines through two HVCs, Complex C and the Magellanic Stream, finding that these clouds contain more material than previous lower limits. We also extend this analysis to low-redshift intergalactic O vi clouds, finding that they contain several times more baryonic material than previously thought and therefore may account for a significant fraction of the Universe’s baryons.

Coherent Phonon Assisted Ultrafast Order-Parameter Reversal and Hidden Metallic State in Ta_{2}NiSe_{5}.

The nonequilibrium dynamics during photoinduced insulator-to-metal transition (IMT) in the excitonic insulator (EI) candidate Ta_{2}NiSe_{5} have been investigated, which reproduce the timescale and spectral features of the ultrafast switch and reveal intricate many-body interactions involving multidegrees of freedom. The key role of lattice order parameter (OP) reversal, occurring on a timescale comparable to that of purely electronic processes (<100 fs), is identified. This reversal is enabled by the anharmonic interactions between EI-OP-coupled phonons and the conventional coherent phonons, leading to a modified potential energy landscape and a high-frequency mode up-conversion. The phonon excitation depends on the dynamics of photocarriers distributed around the Fermi level, and thus intertwines with the excitonic quenching and the complete gap collapse. These findings provide a comprehensive understanding of exciton-phonon dynamics in correlated quantum materials.