Search

We present a framework for simulating the open dynamics of spin–boson systems by combining variational non-Gaussian states with a quantum trajectories approach. We apply this method to a generic spin–boson Hamiltonian that has both Tavis–Cummings and Holstein type couplings and which has broad applications to a variety of quantum simulation platforms, polaritonic physics, and quantum chemistry. Additionally, we discuss how the recently developed truncated Wigner approximation for open quantum systems can be applied to the same Hamiltonian. We benchmark the performance of both methods and identify the regimes where each method is best suited. Finally, we discuss strategies to improve each technique. [ABSTRACT FROM AUTHOR]

With the goal to study dissipative Landau–Zener (LZ) sweeps in realistic solid-state qubits, we utilize novel methods from non-Markovian open quantum system dynamics that enable reliable long-time simulations for sub-Ohmic environments. In particular, we combine a novel representation of the dynamical propagator, the uniform time evolving matrix product operator method, with a stochastic realization of finite temperature fluctuations. The latter greatly reduces the computational cost for the matrix product operator approach, enabling convergence in the experimentally relevant deeply sub-Ohmic regime. Our method allows the exact simulation of dynamical protocols with long operation times, such as the LZ sweep, in challenging parameter regimes that are realized in current experimental platforms. [ABSTRACT FROM AUTHOR]

In this work, we have studied the spin dynamics of a synthetic antiferromagnet (AFM)/heavy metal/ferromagnet double barrier magnetic tunnel junction in the presence of Ruderman–Kittel–Kasuya–Yosida (RKKY) interaction, interfacial Dzyaloshinskii–Moriya (iDM) interaction, Néel field, and Spin–Orbit Coupling (SOC) with different Spin-Transfer Torque (STT). We employ the Landau–Lifshitz–Gilbert–Slonczewski equation to investigate the AFM dynamics of the proposed system. We found that the system exhibits a transition from regular to damped oscillations with the increase in strength of STT for systems with a weaker strength of iDM interaction than RKKY interaction while displaying sustained oscillations for systems having the same order of RKKY and iDM interactions. On the other hand, the systems with sufficiently strong iDM interaction strength exhibit self-similar but aperiodic patterns in the absence of the Néel field. In the presence of the Néel field, the RKKY interaction dominating systems exhibit chaotic oscillations for low STT but display sustained oscillations under moderate STT. Our results suggest that the decay time of oscillations can be controlled via SOC. The system can work as an oscillator for low SOC but displays non-linear characteristics with the rise in SOC for systems having weaker iDM interaction than RKKY interactions. In contrast, opposite characteristics are noticed for iDM interaction dominating systems. We found periodic oscillations under low external magnetic fields in RKKY interaction dominating systems. However, moderate fields are necessary for sustained oscillation in iDM interaction dominating systems. Moreover, the system exhibits saddle-node bifurcations and chaos under moderate Néel field and SOC with suitable RKKY and iDM interactions. In addition, our results indicate that the magnon lifetime can be enhanced by increasing the strength of iDM interaction for both optical and acoustic modes. [ABSTRACT FROM AUTHOR]

In this Communication, we demonstrate that a deep artificial neural network based on a transformer architecture with self-attention layers can predict the long-time population dynamics of a quantum system coupled to a dissipative environment provided that the short-time population dynamics of the system is known. The transformer neural network model developed in this work predicts the long-time dynamics of spin-boson model efficiently and very accurately across different regimes, from weak system–bath coupling to strong coupling non-Markovian regimes. Our model is more accurate than classical forecasting models, such as recurrent neural networks, and is comparable to the state-of-the-art models for simulating the dynamics of quantum dissipative systems based on kernel ridge regression. [ABSTRACT FROM AUTHOR]

Modeling the dynamics of a quantum system coupled to a dissipative environment becomes particularly challenging when the system's dimensionality is too high to permit the computation of its eigenstates. This problem is addressed by introducing an eigenstate-free formalism, where the open quantum system is represented as a mixture of high-dimensional, time-dependent wave packets governed by coupled Schrödinger equations, while the environment is described by a multi-component quantum master equation. An efficient computational implementation of this formalism is presented, employing a variational mixed Gaussian/multiconfigurational time-dependent Hartree (G-MCTDH) ansatz for the wave packets and propagating the environment dynamics via hierarchical equations, truncated at the first or second level of the hierarchy. The effectiveness of the proposed methodology is demonstrated on a 61-dimensional model of phonon-driven vibrational relaxation of an adsorbate. G-MCTDH calculations on 4- and 10-dimensional reduced models, combined with truncated hierarchical equations for the mean fields, nearly quantitatively replicate the full-dimensional quantum dynamical results on vibrational relaxation while significantly reducing the computational time. This approach thus offers a promising quantum dynamical method for modeling complex system–bath interactions, where a large number of degrees of freedom must be explicitly considered. [ABSTRACT FROM AUTHOR]

The most general description of quantum evolution up to a time τ is a completely positive tracing preserving map known as a dynamical map Λ ̂ (τ). Here, we consider Λ ̂ (τ) arising from suddenly coupling a system to one or more thermal baths with a strength that is neither weak nor strong. Given no clear separation of characteristic system/bath time scales, Λ ̂ (τ) is generically expected to be non-Markovian; however, we do assume the ensuing dynamics has a unique steady state, implying the baths possess a finite memory time τm. By combining several techniques within a tensor network framework, we directly and accurately extract Λ ̂ (τ) for a small number of interacting fermionic modes coupled to infinite non-interacting Fermi baths. First, we use an orthogonal polynomial mapping and thermofield doubling to arrive at a purified chain representation of the baths whose length directly equates to a time over which the dynamics of the infinite baths is faithfully captured. Second, we employ the Choi–Jamiolkowski isomorphism so that Λ ̂ (τ) can be fully reconstructed from a single pure state calculation of the unitary dynamics of the system, bath and their replica auxiliary modes up to time τ. From Λ ̂ (τ) , we also compute the time local propagator L ̂ (τ). By examining the convergence with τ of the instantaneous fixed points of these objects, we establish their respective memory times τ m Λ and τ m L . Beyond these times, the propagator L ̂ (τ) and dynamical map Λ ̂ (τ) accurately describe all the subsequent long-time relaxation dynamics up to stationarity. These timescales form a hierarchy τ m L ≤ τ m Λ ≤ τ re , where τre is a characteristic relaxation time of the dynamics. Our numerical examples of interacting spinless Fermi chains and the single impurity Anderson model demonstrate regimes where τre ≫ τm, where our approach can offer a significant speedup in determining the stationary state compared to directly simulating the long-time limit. Our results also show that having access to Λ ̂ (τ) affords a number of insightful analyses of the open system thus far not commonly exploited. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of open quantum systems in strong coupling and non-Markovian regimes remains a formidable theoretical challenge. One popular and well-established method of approximation in these circumstances is provided by the polaron master equation (PME). In this work, we re-evaluate and extend the validity of the PME to capture the impact of non-Markovian polaron dressing, induced by non-equilibrium open system dynamics. By comparing with numerically exact techniques, we confirm that while the standard PME successfully predicts the dynamics of system observables that commute with the polaron transformation (e.g., populations in the Pauli z-basis), it can struggle to fully capture those that do not (e.g., coherences). This limitation stems from the mixing of system and environment degrees of freedom inherent to the polaron transformation, which affects the accuracy of calculated expectation values within the polaron frame. Employing the Nakajima–Zwanzig projection operator formalism, we introduce correction terms that provide an accurate description of observables that do not commute with the transformation. We demonstrate the significance of the correction terms in two cases, the canonical spin-boson model and a dissipative time-dependent Landau–Zener protocol, where they are shown to impact the system dynamics on both short and long timescales. [ABSTRACT FROM AUTHOR]

We present a multiscale method coupling the theory of open quantum systems with real-time ab initio treatment of electronic structure to study hot-carrier dynamics in photoexcited plasmonic systems. We combine the Markovian Stochastic Schrödinger equation with an ab initio GW coupled to the Bethe–Salpeter (BSE) equation description of the electronic degrees of freedom, interacting with a metallic nanoparticle modeled classically according to the polarizable continuum model. We apply this methodology to study the effect of relaxation (T1) and pure dephasing (T2) times on the hot-carrier dynamics in a system composed of a quantum portion described at GW/BSE level, i.e., a CHO fragment adsorbed on a vertex of a rhodium nanocube, and of the rest of the nanocube, treated classically, when irradiated with a 2.7 eV light pulse, inspired by the experimental results on plasmon-driven CO2 photoreduction. A net hole injection from rhodium to CHO is observed, with and without the classical portion of the nanocube. The nanocube effect is to enhance the generated charge population by two orders of magnitude. The nonradiative decay, via a relaxation time T1 based on the energy-gap law, produces a rapid decrease of the charge population. Results with T2 only show that a charge injection retarded with respect to the pulse, which is present in the coherent dynamics, disappears when coherence is erased. [ABSTRACT FROM AUTHOR]

The interaction between cavity photons and molecular vibrations leads to the formation of vibrational polaritons, which have demonstrated the ability to influence chemical reactivity and change material characteristics. Although ultrafast spectroscopy has been extensively applied to study vibrational polaritons, the nonlinear relationship between signal and quantum state population complicates the analysis of their kinetics. Here, we employ a second-order kinetic model and transform matrix method (TMM) to develop an effective model to capture the nonlinear relationship between the two-dimensional IR (or pump–probe) signal and excited state populations. We test this method on two types of kinetics: a sequential relaxation from the second to the first excited states of dark modes, and a Raman state relaxing into the first excited state. By globally fitting the simulated data, we demonstrate accurate extraction of relaxation rates and the ability to identify intermediate species by comparing the species spectra with theoretical ground truth, validating our method. This study demonstrates the efficacy of a second-order TMM approximation in capturing essential spectral features with up to 10% excited state population, simplifying global analysis and enabling straightforward extraction of kinetic parameters, thus empowering our methodology in understanding excited-state dynamics in polariton systems. [ABSTRACT FROM AUTHOR]

EU's Carbon Border Adjustment Mechanism (CBAM) has been promulgated. The steel industry is included in CBAM, which will undoubtedly affect the export trade of China's steel manufacturers to the EU. It is necessary to analyse the impact of CBAM on China's steel industry quantitatively. By establishing a system dynamics model that can simulate the operation mechanism of the steel supply chain in China, we have clarified the impacts of CBAM on the China's steel export and carbon reduction. Moreover, we have reasonably set up scenarios that represent the possible decarbonisation paths of China's steel industry and evaluated the implementation effect of each policy in these scenarios. The analysis shows that CBAM will lead to a decrease of 32% in export volume and a loss of 58% in export profits for China's steel exporters. The environmental benefits of CBAM are limited. Due to the low trade exposure, CBAM is unable to promote a large-scale carbon reduction in the China's steel industry. Although CBAM will bring great pressure to steel exporters, a comprehensive policy of adopting more emission reduction measures can greatly improve the carbon reduction efficiency, effectively reduce the negative impact of CBAM, and maintain the stability of steel exports. [ABSTRACT FROM AUTHOR]

Generic open quantum systems are notoriously difficult to simulate unless one looks at specific regimes. In contrast, classical dissipative systems can often be effectively described by stochastic processes, which are generally less computationally expensive. Here, we use the paradigmatic case of a dissipative quantum oscillator to give a pedagogic introduction to the modeling of open quantum systems using quasiclassical methods, i.e., classical stochastic methods that use a "quantum" noise spectrum to capture the influence of the environment on the system. Such quasiclassical methods have the potential to offer insights into the impact of the quantum nature of the environment on the dynamics of the system of interest while still being computationally tractable. [ABSTRACT FROM AUTHOR]

This article introduces an advanced Koopman mode decomposition (KMD) technique—coined Featurized Koopman Mode Decomposition (FKMD)—that uses delay embedding and a learned Mahalanobis distance to enhance analysis and prediction of high-dimensional dynamical systems. The delay embedding expands the observation space to better capture underlying manifold structures, while the Mahalanobis distance adjusts observations based on the system's dynamics. This aids in featurizing KMD in cases where good features are not a priori known. We show that FKMD improves predictions for a high-dimensional linear oscillator, a high-dimensional Lorenz attractor that is partially observed, and a cell signaling problem from cancer research. [ABSTRACT FROM AUTHOR]

Strong coupling between the molecular system and photon inside the cavity generates polaritons, which can alter reaction rates by orders of magnitude. In this work, we benchmark the surface hopping method to simulate non-adiabatic dynamics in a cavity. The comparison is made against a numerically exact method (the hierarchical equations of motion) for a model system investigating excitonic energy transfer for a broad range of parameters. Surface hopping captures the effects of the radiation mode well, both at resonance and off-resonance. We have further investigated parameters that can increase or decrease the rate of population transfer, and we find that surface hopping in general can capture both effects well. Finally, we show that the dipole self-energy term within our parameter regime does not significantly affect the system's dynamics. [ABSTRACT FROM AUTHOR]

In this work, we present a mixed quantum–classical open quantum system dynamics method for studying rate modifications of ground-state chemical reactions in an optical cavity under vibrational strong-coupling conditions. In this approach, the cavity radiation mode is treated classically with a mean-field nuclear force averaging over the remaining degrees of freedom, both within the system and the environment, which are handled quantum mechanically within the hierarchical equations of motion framework. Using this approach, we conduct a comparative analysis by juxtaposing the mixed quantum–classical results with fully quantum-mechanical simulations. After eliminating spurious peaks that can occur when not using the rigorous definition of the rate constant, we confirm the crucial role of the quantum nature of the cavity radiation mode in reproducing the resonant peak observed in the cavity frequency-dependent rate profile. In other words, it appears necessary to explicitly consider the quantized photonic states in studying reactivity modification in vibrational polariton chemistry (at least for the model systems studied in this work), as these phenomena stem from cavity-induced reaction pathways involving resonant energy exchanges between photons and molecular vibrational transitions. [ABSTRACT FROM AUTHOR]

Understanding the nonadiabatic dynamics of complex systems is a challenging task in computational photochemistry. Herein, we present an efficient and user-friendly quantum mechanics/molecular mechanics (QM/MM) interface to run on-the-fly nonadiabatic dynamics. Currently, this interface consists of an independent set of codes designed for general-purpose use. Herein, we demonstrate the ability and feasibility of the QM/MM interface by integrating it with our long-term developed JADE package. Tailored to handle nonadiabatic processes in various complex systems, especially condensed phases and protein environments, we delve into the theories, implementations, and applications of on-the-fly QM/MM nonadiabatic dynamics. The QM/MM approach is established within the framework of the additive QM/MM scheme, employing electrostatic embedding, link-atom inclusion, and charge-redistribution schemes to treat the QM/MM boundary. Trajectory surface-hopping dynamics are facilitated using the fewest switches algorithm, encompassing classical and quantum treatments for nuclear and electronic motions, respectively. Finally, we report simulations of nonadiabatic dynamics for two typical systems: azomethane in water and the retinal chromophore PSB3 in a protein environment. Our results not only illustrate the power of the QM/MM program but also reveal the important roles of environmental factors in nonadiabatic processes. [ABSTRACT FROM AUTHOR]

The use of semiconductor nanocrystals in scalable quantum technologies requires characterization of the exciton coherence dynamics in an ensemble of electronically isolated crystals in which system–bath interactions are nevertheless strong. In this communication, we identify signatures of Fano-like interference between excitons and photocarriers in the coherent two-dimensional photoluminescence excitation spectral lineshapes of mixed lead-halide perovskite nanocrystals in dilute solution. Specifically, by tuning the femtosecond-pulse spectrum, we show such interference in an intermediate coupling regime, which is evident in the coherent lineshape when simultaneously exciting the exciton and the free-carrier band at higher energy. We conclude that this interference is an intrinsic effect that will be consequential in the quantum dynamics of the system and will thus dictate decoherence dynamics, with consequences in their application in quantum technologies. [ABSTRACT FROM AUTHOR]

Disabled people can be successfully employed in most production processes, provided that one knows how to exploit their abilities and take into account their limitations in order to give them an appropriate job. However, because the level and type of production must be constantly adapted to the needs of the market, the involvement of disabled people in the production process may also change. Additionally, people with disabilities have limitations as well as additional rights that must be considered. As a result, the organisation and planning of their work, side by side with other employees, becomes more complex. Computer simulations can be a support for organising and planning the involvement of employees with disabilities in production processes. The aim of the article is to show how simulations can facilitate the organisation of work of employees with disabilities, with the changing demand for manufactured products. The paper identifies the factors that should be considered, and then presents how the employment of disabled people can affect the operation of the production line and the commercial image of the company. The study uses a combination of System Dynamics and Discrete Event Simulations. The relevant data for the simulation were derived from a production company. [ABSTRACT FROM AUTHOR]

In the previous paper [C. W. Kim and I. Franco, J. Chem. Phys. 160, 214111-1–214111-13 (2024)], we developed a theory called MQME-D, which allows us to decompose the overall energy dissipation process in open quantum system dynamics into contributions by individual components of the bath when the subsystem dynamics is governed by a Markovian quantum master equation (MQME). Here, we contrast the predictions of MQME-D against the numerically exact results obtained by combining hierarchical equations of motion (HEOM) with a recently reported protocol for monitoring the statistics of the bath. Overall, MQME-D accurately captures the contributions of specific bath components to the overall dissipation while greatly reducing the computational cost compared to exact computations using HEOM. The computations show that MQME-D exhibits errors originating from its inherent Markov approximation. We demonstrate that its accuracy can be significantly increased by incorporating non-Markovianity by exploiting time scale separations (TSS) in different components of the bath. Our work demonstrates that MQME-D combined with TSS can be reliably used to understand how energy is dissipated in realistic open quantum system dynamics. [ABSTRACT FROM AUTHOR]

We present a fully quantum dynamical treatment of a quantum heat engine and its baths based on the Hierarchy of Pure States (HOPS), an exact and general method for open quantum system dynamics. We show how the change of the bath energy and the interaction energy can be determined within HOPS for arbitrary coupling strength and smooth time dependence of the modulation protocol. The dynamics of all energetic contributions during the operation can be carefully examined both in its initial transient phase and, also later, in its periodic steady state. A quantum Otto engine with a qubit as an inherently nonlinear work medium is studied in a regime where the energy associated with the interaction Hamiltonian plays an important role for the global energy balance and, thus, must not be neglected when calculating its power and efficiency. We confirm that the work required to drive the coupling with the baths sensitively depends on the speed of the modulation protocol. Remarkably, departing from the conventional scheme of well-separated phases by allowing for temporal overlap, we discover that one can even gain energy from the modulation of bath interactions. We visualize these various work contributions using the analog of state change diagrams of thermodynamic cycles. We offer a concise, full presentation of HOPS with its extension to bath observables, as it serves as a universal tool for the numerically exact description of general quantum dynamical (thermodynamic) scenarios far from the weak-coupling limit. [ABSTRACT FROM AUTHOR]

Two-level quantum systems are fundamental physical models that continue to attract growing interest due to their crucial role as a building block of quantum technologies. The exact analytical solution of the dynamics of these systems is central to control theory and its applications, such as that to quantum computing. In this study, we reconsider the two-state charge transfer problem by extending and using a methodology developed to study (pseudo)spin systems in quantum electrodynamics contexts. This approach allows us to build a time evolution operator for the charge transfer system and to show new opportunities for the coherent control of the system dynamics, with a particular emphasis on the critical dynamic region around the transition state coordinate, where the avoided crossing of the energy levels occurs. We identify and propose possible experimental implementations of a class of rotations of the charge donor (or acceptor) that endow the electronic coupling matrix element with a time-dependent phase that can be employed to realize controllable coherent dynamics of the system across the avoided level crossing. The analogy of these rotations to reference frame rotations in generalized semiclassical Rabi models is discussed. We also show that the physical rotations in the charge-transfer systems can be performed so as to implement quantum gates relevant to quantum computing. From an exquisitely physical–mathematical viewpoint, our approach brings to light situations in which the time-dependent state of the system can be obtained without resorting to the special functions appearing in the Landau–Zener approach. [ABSTRACT FROM AUTHOR]

Many chemical reactions and molecular processes occur on time scales that are significantly longer than those accessible by direct simulations. One successful approach to estimating dynamical statistics for such processes is to use many short time series of observations of the system to construct a Markov state model, which approximates the dynamics of the system as memoryless transitions between a set of discrete states. The dynamical Galerkin approximation (DGA) is a closely related framework for estimating dynamical statistics, such as committors and mean first passage times, by approximating solutions to their equations with a projection onto a basis. Because the projected dynamics are generally not memoryless, the Markov approximation can result in significant systematic errors. Inspired by quasi-Markov state models, which employ the generalized master equation to encode memory resulting from the projection, we reformulate DGA to account for memory and analyze its performance on two systems: a two-dimensional triple well and the AIB9 peptide. We demonstrate that our method is robust to the choice of basis and can decrease the time series length required to obtain accurate kinetics by an order of magnitude. [ABSTRACT FROM AUTHOR]

The effective operations of closed-loop supply chains (CLSCs) can help companies achieve sustainability goals and boost economic performance. In practice, CLSCs must collect used products, a complex process that is often constrained by collection station capacity. However, how collection station capacity influences the bullwhip effect and the dynamic performance of CLSCs remains unclear. Here, we develop a system dynamics model for CLSCs that integrates traditional manufacturing with remanufacturing and explore the effects of the stochastic capacity constraint of the collection station on the bullwhip effect of CLSCs. We find that, generally speaking, a collection station with looser or more stable capacity constraints tends to reduce bullwhip of CLSCs. However, pertinent interactions emerge between the relevant parameters; in some situations, reducing the capacity level of a collection station may be reasonable and beneficial when the stochastic capacity constraint is very stable, or when customer demand is highly variable. We also consider the partial backlog in return collection, a phenomenon associated with the stochastic capacity constraint of a collection station, and identify a new trade-off between CLSC sustainability and economic performance. Ultimately, our findings provide evidence that will guide managers' plans for the capacity management of return collection in CLSCs. [ABSTRACT FROM AUTHOR]

The manipulation of the ultrafast quantum dynamics of a molecular system can be achieved through the application of tailored light fields. This has been done in many ways in the past. In our present investigation, we show that it is possible to exert specific control over the nonadiabatic dynamics of a generic model system describing ultrafast charge-transfer within a condensed dissipative environment by using frequency-chirped pulses. By adjusting the external photoexcitation conditions, such as the chirp parameter, we show that the final population of the excitonic and charge-transfer states can be significantly altered, thereby influencing the elementary steps controlling the transfer process. In addition, we introduce an excitation scheme based on double-pump time-resolved fluorescence spectroscopy using chirped-pulse excitations. Here, our findings reveal that chirped excitations enhance the vibrational system dynamics as evidenced by the simulated spectra, where a substantial signal intensity dependence on the chirp is observed. Our simulations show that chirped pulses are a promising tool for steering the dynamics of the charge-transfer process toward a desired target outcome. [ABSTRACT FROM AUTHOR]

In this study, we extended the optimized potentials for liquid simulation-ionic-liquid virtual site (OPLS-VSIL) force field (FF) to imidazolium-based dicationic ionic liquids (DILs) and evaluated the ability of different OPLS-based FFs (i.e., OPLS-2009IL, 0.8*OPLS-2009IL, and OPLS-VSIL) in predicting different properties of the studied DIL by comparing their results with ab initio molecular dynamics (AIMD) simulation and experimental results. To achieve this purpose, MD simulations with three different OPLS-based FFs as well as AIMD simulation were performed for [C3(mim)2][NTF2]2 DIL and its structural, dynamical, vibrational, and volumetric properties were analyzed. Structural properties of the studied DIL, i.e., radial distribution functions (RDFs), structure factor, and hydrogen-bond network, showed that compared to 0.8*OPLS-2009IL FF, there is a much better agreement between the results of both OPLS-2009IL and OPLS-VSIL FFs with the AIMD simulation. On the other hand, the results of dynamical properties, such as mean square displacements, van Hove correlation functions as well as hydrogen bond, ion pair, and ion cage dynamics, depicted that in both 0.8*OPLS-2009IL and OPLS-VSIL FFs, the dynamics of the system is almost similar, and compared to OPLS-2009IL FF, they have better agreements with experimental results where they exist. So, it can be seen that although reducing the total charge of studied DIL by 20% leads to an increase in the dynamics of the system, the type distribution of partial charges on each atom does not significantly affect the system's dynamics. The calculated infrared (IR) and power spectra showed that the vibrational features of studied DIL in three OPLS-based FFs are mostly the same and reducing total charge and different type distribution of partial charges have no significant effect on the studied system. Furthermore, in volumetric properties, OPLS-VSIL FF shows somehow better agreement with experimental results. Overall, the evaluation of different structural, dynamical, vibrational, and volumetric properties of [C3(mim)2][NTF2]2 DIL shows that the OPLS-VSIL FF may be the best choice among the different studied OPLS FFs. [ABSTRACT FROM AUTHOR]

Modeling the dynamics of glassy systems has been challenging in physics for several decades. Recent studies have shown the efficacy of Graph Neural Networks (GNNs) in capturing particle dynamics from the graph structure of glassy systems. However, current GNN methods do not take the dynamic patterns established by neighboring particles explicitly into account. In contrast to these approaches, this paper introduces a novel dynamical parameter termed "smoothness" based on the theory of graph signal processing, which explores the dynamic patterns from a graph perspective. Present graph-based approaches encode structural features without considering smoothness constraints, leading to a weakened correlation between structure and dynamics, particularly on short timescales. To address this limitation, we propose a Geometry-enhanced Graph Neural Network (Geo-GNN) to learn the smoothness of dynamics. Results demonstrate that our method outperforms state-of-the-art baselines in predicting glassy dynamics. Ablation studies validate the effectiveness of each proposed component in capturing smoothness within dynamics. These findings contribute to a deeper understanding of the interplay between glassy dynamics and static structure. [ABSTRACT FROM AUTHOR]

Increased consumption of non-renewable energy sources, such as batteries, have led to increased environmental pollution and critical energy crises. Harvesting energy from vibration sources, using piezoelectric cantilevers, may be one of the main solutions to extending the life of the battery of some autonomous devices and either reducing or eliminating the need to replace them in service. This would make sensors self-powered, for instance. To minimize the volume of the Energy Harvester, a configuration with a circular frame supporting a radial set of bimorph piezoelectric beams with a proof mass at the tip is proposed. An analytic model is first developed to investigate the behavior of the electromechanical coupling, preliminarily sizing the design parameters, and to estimate the maximum power converted. A numerical model is then developed, in the COMSOL® Multiphysics software, to analyze all of the system details. Some FEM analyses allow for verifying the accuracy of the analytic model and predicting the dynamic system behavior under different load conditions. A critical issue in properly predicting the performance of such device is the electric circuit which is coupled to extract the charge produced. Therefore, the design of this read-out circuit is herein addressed. The LTspice XVII® software is then used to model the charge readout circuit. The electronic components interconnected within the circuit are first determined, and their electrical dynamic behavior is studied when coupled with the mechanical system. The efficiency of charge production and energy storage is evaluated by integrating the whole electromechanical system, including the readout circuit with the numerical model. The performance looks compatible with the required values proposed for some practical industrial applications, being also described. [ABSTRACT FROM AUTHOR]

The open interconnection and sharing characteristics of innovation-oriented enterprises aggravate the potential detrimental effects of intellectual property risks, while the proliferation of uncertainty factors perpetually amplifies the ripples of these risks. This study employed the grounded theory method, complemented by expert interviews, case analyses of intellectual property risk incidents, examination of intellectual property-related laws and regulations, as well as other relevant materials. It gathered comprehensive risk information and conducted an in-depth exploration of the underlying factors that contribute to intellectual property risks in enterprises. These factors encompassed risks associated with intellectual property dispute feedback, intellectual property competition, open innovation, intellectual property legal aspects, and environmental considerations. An index system for risk factors is established based on the comprehensive information collected. Furthermore, a system flow diagram depicting the mechanism of risk formation is developed using the system dynamics model. The study delves into the causal relationships among all risk factors and examines their impact on the overall intellectual property risk system within the enterprise. By simulating the dynamic evolution trend of intellectual property risk over time, the research reveals insights that can assist innovation-oriented enterprises operating in open environments in optimising their intellectual property risk management strategies. [ABSTRACT FROM AUTHOR]

With the rise and rapid development of the e-commerce industry, the pressure borne by the supply chain of e-commerce enterprises is increasing, which greatly increases the complexity and uncertainty of inventory management in the e-commerce supply chain. The study integrates system dynamics and collaborative supply chain inventory management to construct a new model. The study first uses the concept of system dynamics to optimize the supply chain inventory management system; then the collaborative supply chain is used to construct a system model by combining the optimized management system. The results show that the collaborative supply chain inventory management model constructed by the study can better accelerate the product turnover rate, improve the overall operational efficiency and market competitiveness of the supply chain, and can provide new support for the development of e-commerce enterprises. [ABSTRACT FROM AUTHOR]

Coupled nonlocal nonlinear wave equations describe the dynamics of wave systems with multiple interacting components in a wide range of physical applications. Investigating the long-time behavior of the solutions is crucial for understanding the stability, dynamics, and qualitative properties of these systems. In this study, solitary wave solutions to the coupled nonlocal nonlinear wave equations are generated numerically using the Petviashvili iteration method and the long-time behavior of the obtained solutions is investigated. In order to investigate the long-time behavior of the solutions obtained for the coupled nonlocal nonlinear wave equations, a Fourier pseudospectral method for space discretization and a fourth-order Runge–Kutta scheme for time discretization are proposed. Various numerical experiments are conducted to test the performance of the Petviashvili iteration method and the Fourier pseudo-spectral method. The proposed scheme can be used to solve the coupled nonlocal nonlinear system for arbitrary kernel functions representing the details of the atomic scale effects. [ABSTRACT FROM AUTHOR]

In complex Social-Ecological Systems (SES), the interplay between ecological and social components shapes trajectories that impact human well-being and ecosystem services. While SES dynamics have been studied in static conditions, there has been less attention to how said systems respond to shocks and stressors over time and space. This special issue presents a collection of articles that use diverse methodologies—ranging from system dynamics modeling to participatory approaches—to analyze past SES changes and discuss future scenarios. Case studies from regions including Brazil, Colombia, Mexico, Honduras, Chile, Ethiopia and Mongolia illustrate key variables influencing social–ecological transitions and provide insights into potential policy strategies to support sustainable SES. The studies underscore the need for multi-scalar approaches to SES research that explicitly theorize and empirically assess trajectories across space and time. [ABSTRACT FROM AUTHOR]

Scenario and policy assessments in socioeconomic and environmental studies face significant challenges in socio-ecological systems (SES). There are a limited number of studies that have looked at the impact of different scenarios within integrated approaches, and many have used a static approach with a single driver of change. The present work analyzes the SES dynamics for a strategic basin in the Colombian Andes when implementing and analyzing scenarios and policies related to land cover and land use change using a system dynamics simulation model. The model includes natural, ecosystem services, sociocultural, and economic components. Scenarios and policy options are analyzed both individually and jointly to identify synergies or trade-off effects between the different SES components. The results showed the different trajectories of the socio-ecological system according to the cases studied, and its impact on different variables in the analyzed components. Some counterintuitive effects were also identified, such as the importance of intrinsic motivations in decision-making processes, and determinants in land management and policy design. [ABSTRACT FROM AUTHOR]

Care as usual has failed to stem the tide of mental health challenges in children and young people. Transformed models of care and prevention are required, including targeting the social determinants of mental health. Robust economic evidence is crucial to guide investment towards prioritised interventions that are effective and cost-effective to optimise health outcomes and ensure value for money. Mental healthcare and prevention exhibit the characteristics of complex dynamic systems, yet dynamic simulation modelling has to date only rarely been used to conduct economic evaluation in this area. This article proposes an integrated decision-making and planning framework for mental health that includes system dynamics modelling, cost-effectiveness analysis, and participatory model-building methods, in a circular process that is constantly reviewed and updated in a 'living model' ecosystem. We describe a case study of this approach for mental health system policy and planning that synergises the unique attributes of a system dynamics approach within the context of economic evaluation. This kind of approach can help decision makers make the most of precious, limited resources in healthcare. The application of modelling to organise and enable better responses to the youth mental health crisis offers positive benefits for individuals and their families, as well as for taxpayers. [ABSTRACT FROM AUTHOR]

In this paper, we shall deal with the long‐time dynamics of a nonlinear system of wave equation with a fractional damping and a small delay. Inspired by the works of Chueshov and Lasiecka on the property of quasi‐stability of dynamic systems, we show first the quasi‐stability property holds for the problem considered here and then prove the existence of global and exponential attractors. We shall also prove the upper semicontinuities of global attractors with respect to the fractional exponents. Finally, we shall show the continuities of global attractors with respect to a small parameter multiplying the delay term in a residual dense set and their upper semicontinuities in a complete metric space. [ABSTRACT FROM AUTHOR]

This paper is devoted to the study of a nonlocal reaction–diffusion model of Chikungunya disease with periodic time delays. We establish two threshold type results on the global dynamics for the growth of mosquitoes and the disease transmission, respectively. Further, we obtain the global attractivity of a positive steady state for a simplified nonlocal and time-delayed system with constant coefficients. We also conduct numerical simulations for the Chikungunya transmission in Ceará, Brazil to investigate the effects of spatial heterogeneity on the disease transmission. [ABSTRACT FROM AUTHOR]

This study presents a new holistic framework for modeling farmer decisionmaking by integrating both top-down and bottom-up approaches. It uses three interlinked subsystems to evaluate how changes in water policies impact farmer decisions and profits: the first model simulates water balance, the second simulates farmer behavior, and the third assesses farmer profits. Two scenarios are explored: Scenario I introduces penalties for groundwater overexploitation, and Scenario II implements awareness raising and training to encourage using modern irrigation systems. The results show that penalties lead to reductions in water requests exceeding limits by 8%, 45%, and 68% for fines of 1000, 5000, and 10,000 IRR·m-3, with corresponding net profit decreases of 1.3%, 8.0%, and 11.6%. The ranges of farmer cooperation for groundwater management vary from 20% to 50% over the 10-year simulation period. In Scenario II, increasing the radius of awareness from 0.5 to 2 km substantially increases the adoption of modern irrigation from 1457 to 2057 farmers. These findings highlight how different policy measures impact various types of farmer based on their specific characteristics and preferences. [ABSTRACT FROM AUTHOR]

This article studies the cluster consensus problem for the nonlinear multi‐agent systems subject to input saturation under the context of event triggered control. Taking ordinary consensus object as a special case, this article considers the problem of cluster consensus. The event triggered mechanism is designed and the Zeno phenomenon is ruled out. The sufficient conditions of control protocol and range estimation of domain of attraction are formulated by the linear matrix inequalities for the constraints of input saturation and nonlinear terms existed in the system dynamics. Finally, the proposed results are validated by one example in the background of spring damping system. [ABSTRACT FROM AUTHOR]

In this article, we define a generalization of the domino shuffling algorithm for tilings of the Aztec diamond to the interacting k-tilings recently introduced by S. Corteel, A. Gitlin, and the first author. We describe the algorithm both in terms of dynamics on a system of colored particles and as operations on the dominos themselves. [ABSTRACT FROM AUTHOR]

Periodically kicked Floquet systems, such as the kicked rotor, are a paradigmatic and illustrative simple model of chaos. For non-integrable quantum dynamics, there are several diagnostic measures, such as Loschmidt echo, autocorrelation function and out of time order correlator (OTOC) to study the presence of (or the transition to) chaotic behaviour. We analytically compute these measures in terms of the eigensystem of the unitary Floquet operator of the driven quantum systems. We use these expressions to determine the time variation of the measures for the quantum-kicked rotor (QKR) on the torus, for the integrable as well as the chaotic case. For a simpler integrable variant of the kicked rotor, we also give a representation theoretic derivation of its dynamics. [ABSTRACT FROM AUTHOR]

As a crucial measure to promote the coordinated development of urban and rural areas in developing countries (such as China), how to provide and manage rural infrastructure investment is a major challenge. In line with the implementation of a coordinated urban–rural development strategy, inclusive growth provides direction for rural infrastructure investment. Taking Chongqing, China, as an example, informed by the goals of inclusive growth, this study develops a system dynamics model to investigate the interaction between interdependent infrastructure systems and socioeconomic systems and to explore priorities for rural infrastructure investment. The results indicate the following: (1) more rural infrastructure investment is still needed in Chongqing by 2030; and (2) based on the importance of all types of rural infrastructures for the impact of inclusive growth goals, the ratio of budget shares invested in each dimension is, in descending order, environment infrastructure, energy infrastructure, communication infrastructure, transportation infrastructure, education infrastructure, and medical infrastructure. The approach and results of this study allow governments to assess the contribution of infrastructure provision to the goals of inclusive growth and to make better-informed infrastructure investment options. [ABSTRACT FROM AUTHOR]

The importance of sustainability in industry is dramatically rising in recent years. Controlling machine states to achieve the best trade-off between production rate and energy demand is an effective method for improving the energy efficiency of production systems. This technique is referred to as energy-efficient control (EEC) and it triggers machines in a standby state with low power requests. Reinforcement Learning (RL) algorithms can be used to successfully control production systems without the requirement of prior knowledge about system parameters. Due to the difficulty in acquiring comprehensive information about system dynamics in real-world scenarios, this is considered an important factor. The goal of this work is to create a novel RL-based model to apply EEC to multi-stage production lines with parallel machine workstations without relying on full knowledge of the system dynamics. Numerical results confirm model benefits when applied to a real line from the automotive sector. Further experiments confirm the effectiveness and generality of the approach. [ABSTRACT FROM AUTHOR]

Tuberculosis infection prevention and control (TB IPC) measures are a cornerstone of policy, but measures are diverse and variably implemented. Limited attention has been paid to the health system environment, which influences successful implementation of these measures. We used qualitative system dynamics and group-model-building methods to (1) develop a qualitative causal map of the interlinked drivers of Mycobacterium tuberculosis (Mtb) transmission in South African primary healthcare facilities, which in turn helped us to (2) identify plausible IPC interventions to reduce risk of transmission. Two 1-day participatory workshops were held in 2019 with policymakers and decision makers at national and provincial levels and patient advocates and health professionals at clinic and district levels. Causal loop diagrams were generated by participants and combined by investigators. The research team reviewed diagrams to identify the drivers of nosocomial transmission of Mtb in primary healthcare facilities. Interventions proposed by participants were mapped onto diagrams to identify anticipated mechanisms of action and effect. Three systemic drivers were identified: (1) Mtb nosocomial transmission is driven by bottlenecks in patient flow at given times; (2) IPC implementation and clinic processes are anchored within a staff 'culture of nominal compliance'; and (3) limited systems learning at the policy level inhibits effective clinic management and IPC implementation. Interventions prioritized by workshop participants included infrastructural, organizational and behavioural strategies that target three areas: (1) improve air quality, (2) improve use of personal protective equipment and (3) reduce the number of individuals in the clinic. In addition to core mechanisms, participants elaborated specific additional enablers who would help sustain implementation. Qualitative system dynamics modelling methods allowed us to capture stakeholder views and potential solutions to address the problem of sub-optimal TB IPC implementation. The participatory elements of system dynamics modelling facilitated problem-solving and inclusion of multiple factors frequently neglected when considering implementation. [ABSTRACT FROM AUTHOR]

This research explores the intricate dynamics of job displacement resulting from artificial intelligence (AI) using a sophisticated non-linear dynamical system modeled through the Lotka-Volterra equations, commonly employed in ecology to elucidate predator–prey dynamics. In this study, we interpret human jobs as the "prey" and AI technology as the "predator," identifying two equilibrium points: E1 ≡ (0, 0) signifies a state with no jobs and no AI technology, while E2 ≡ (s/β, r/α) denotes a balanced coexistence where job growth and AI development are in equilibrium. Qualitative analysis reveals four regions characterized by different trends in job expansion and AI development, with Region IV indicating a co-evolutionary phase marked by positive feedback. Stability analysis demonstrates that while E1 remains consistently unstable, E2 remains stable, providing valuable insights into system dynamics. Scenarios presented suggest a promising future where balanced growth fosters sustainable coexistence between human workers and AI, although challenges arise when AI outpaces human job growth, emphasizing the necessity of effective policy responses to mitigate adverse effects and maximize the benefits of technological advancement. Understanding these dynamics is crucial for policymakers to navigate the complexities of AI-induced job displacement and ensure equitable societal outcomes. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative approach for optical flow-based control of micro air vehicles (MAVs), addressing challenges inherent in the nonlinearity of optical flow observables. The proposed incremental nonlinear dynamic inversion (INDI) control scheme employs an efficient data-driven approach to directly estimate the inverse of the time-varying INDI control effectiveness in real-time. This method eliminates the constant effectiveness assumption typically made by traditional INDI methods and reduces the computational burden associated with inverting this variable at each time step. It effectively handles rapidly changing system dynamics, often encountered in optical flow-based control, particularly height-dependent control variables. Stability analysis of the proposed control scheme is conducted, and its robustness and efficiency are demonstrated through both numerical simulations and real-world flight tests. These tests include multiple landings of an MAV on a static, flat surface with several different tracking setpoints, as well as hovering and landings on moving and undulating surfaces. Despite the challenges posed by noisy optical flow estimates and lateral or vertical movements of the landing surfaces, the MAV successfully tracks or lands on the surface with an exponential decay of both height and vertical velocity almost simultaneously, aligning with the desired performance. [ABSTRACT FROM AUTHOR]