Dissipative Dynamics Research Articles

Residue Dissipation Dynamics and Dietary Risk Assessment of Kasugamycin, Oxine-Copper, Dimethomorph, and Pyraclostrobin in Cucumber

Residue Dissipation Dynamics and Dietary Risk Assessment of Kasugamycin, Oxine-Copper, Dimethomorph, and Pyraclostrobin in Cucumber

Unified linear response theory of quantum electronic circuits

Modeling the electrical response of multi-level quantum systems at finite frequency has been typically performed in the context of two incomplete paradigms: (i) input-output theory, which is valid at any frequency but neglects dynamic losses, and (ii) semiclassical theory, which captures dynamic dissipation effects well but is only accurate at low frequencies. Here, we develop a unifying theory, valid for arbitrary frequencies, that captures both the small-signal quantum behavior and the non-unitary effects introduced by relaxation and dephasing. The theory allows a multi-level system to be described by a universal small-signal equivalent-circuit model, a resonant RLC circuit, whose topology only depends on the number of energy levels. We apply our model to a double-quantum-dot charge qubit and a Majorana qubit, showing the capability to continuously describe the systems from adiabatic to resonant and from coherent to incoherent, suggesting new and realistic experiments for improved quantum state readout. Our model will facilitate the design of hybrid quantum–classical circuits and the simulation of qubit control and quantum state readout.

A unified framework for the analysis of accuracy and stability of a class of approximate Gaussian filters for the Navier–Stokes equations

Abstract Bayesian state estimation of a dynamical system utilising a stream of noisy measurements is important in many geophysical and engineering applications. In these cases, nonlinearities, high (or infinite) dimensionality of the state space, and sparse observations pose key challenges for deriving efficient and accurate data assimilation (DA) techniques. A number of DA algorithms used commonly in practice, such as the Ensemble Kalman Filter (EnKF) or Ensemble Square Root Kalman Filter (EnSRKF), suffer from serious drawbacks such as catastrophic filter divergence and filter instability. The analysis of stability and accuracy of these DA schemes has thus far focused either on finite-dimensional dynamics, or on complete observations in case of infinite-dimensional dissipative systems. We develop a unified framework for the analysis of several well-known and empirically efficient DA techniques derived from various Gaussian approximations of the Bayesian filtering schemes for geophysical-type dissipative dynamics with quadratic nonlinearities. We establish rigorous results on (time-asymptotic) accuracy and stability of these algorithms with general covariance and observation operators. The accuracy and stability results for EnKF and EnSRKF for dissipative PDEs are, to the best of our knowledge, completely new in this general setting. It turns out that a hitherto unexploited cancellation property involving the ensemble covariance and observation operators and the concept of covariance localization in conjunction with covariance inflation play a pivotal role in the accuracy and stability for EnKF and EnSRKF. Our approach also elucidates the links, via determining functionals, between the approximate-Bayesian and control-theoretic approaches to DA. We consider the ‘model’ dynamics governed by the two-dimensional incompressible Navier–Stokes equations (NSEs) and observations given by noisy measurements of averaged volume elements or spectral/modal observations of the velocity field. In this setup, several continuous-time DA techniques, namely the so-called 3DVar, EnKF and EnSRKF reduce to a stochastically forced NSEs. For the first time, we derive conditions for accuracy and stability of EnKF and EnSRKF. The derived bounds are given for the limit supremum of the expected value of the L 2 norm and of the H 1 Sobolev norm of the difference between the approximating solution and the actual solution as the time tends to infinity. Moreover, our analysis reveals an interplay between the resolution of the observations (roughly, the ‘richness’ of the observation space) associated with the observation operator underlying the DA algorithms and covariance inflation and localization which are employed in practice for improved filter performance.

Unveiling hidden scaling relations in dissipative relaxation dynamics of strongly correlated quantum impurity systems.

Understanding the time evolution of strongly correlated open quantum systems (OQSs) in response to perturbations (quenches) is of fundamental importance to the precise control of quantum devices. It is, however, rather challenging in multi-impurity quantum systems because such evolution often involves multiple intricate dynamical processes. In this work, we apply the numerically exact hierarchical equations of motion approach to explore the influence of two different types of perturbations, i.e., sudden swapping of the energy levels of impurity systems and activating the inter-impurity spin-exchange interaction, on the dissipation dynamics of the Kondo-correlated two-impurity Anderson model over a wide range of energetic parameters. By evaluating the time-dependent impurity spectral function and other system properties, we analyze the time evolution of the Kondo state in detail and conclude a phenomenologically scaling relation for Kondo dynamics driven by these perturbations. The evolutionary scaling relationship is not only related to the Kondo characteristic energy TK but also significantly affected by the simultaneous non-Kondo dynamic characteristic energy. We expect these results will inspire subsequent theoretical studies on the dynamics of strongly correlated OQSs.

A short trajectory is all you need: A transformer-based model for long-time dissipative quantum dynamics.

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.

Robustness of interferometric power to sudden death

In this paper, we study the dissipative dynamics of interferometric power as a discord-like measure in Markovian environments such as dephasing, depolarizing, and generalized amplitude damping. Moreover, we compare the dynamics of interferometric power and entanglement by choosing the proper initial conditions. Our study shows that interferometric power decays asymptotically in all cases where the sudden death of entanglement appears. Therefore, quantum metrology based on interferometric power is more robust than entanglement.

Influences of Strain Rate and Density on the Dynamic Material Properties and Energy Dissipation Characteristics of Iron Tailing Porous Concrete

Influences of Strain Rate and Density on the Dynamic Material Properties and Energy Dissipation Characteristics of Iron Tailing Porous Concrete

Re-investigation of the interplay of fission modes and non-equilibrium fission processes in heavy actinide nuclei 249Bk and 257Md

Measurements of mass and angular distributions of fission fragments from actinide nuclei 249Bk and 257Md, produced in fusion reactions 11B and 19F + 238U, are presented. Experimentally observed mass ratio distributions indicate “multi-chance fission” through the interplay of fission modes in the fission process, and they agree well with predictions from calculations using the GEF (“GEneral description of Fission observables”) model code. Furthermore, to test the signatures of events from non-compound nuclear processes in the fission of 249Bk and 257Md nuclei, Monte Carlo statistical decay model calculations using GEMINI++ were performed for the measured mass distribution at all energies. For comparison purposes, the fission fragment mass distributions of neighboring heavy actinide nuclei, previously measured in the fission of 250Cf and 254Fm nuclei produced by 12C and 16O projectiles on a 238U target, are also presented. The measured angular anisotropy data for the 19F + 238U reaction differ from the results of the Transition State Model (TSM) at energies below the fusion barrier. As a result of the present study, we suggest considering the interplay between K relaxation time, dynamic dissipation, and their influence on shell correction to understand the evolution of fission dynamics in heavy-ion-induced actinide nuclei.

The rebound law of micro-particle on amorphous alloys under high impact velocities

Compared to their crystalline counterparts, amorphous alloys due to disordered structures are expected to have higher elasticity of deformation. However, in this work, we use the micro-ballistic impact technique to show a smaller dynamic redound of micro-particles on a Zr-based amorphous alloy than that on its corresponding polycrystalline target. We find that the two alloys follow the same rebound law of micro-particle under low impact velocities, but with increasing impact velocity the amorphous alloy exhibits a faster decrease in rebound velocity of micro-particle. This lower rebound results from the easier activations of shear banding in glassy structures, thus contributing to more significant energy dissipation during the micro-particle impact. Further analyses imply that the amorphous alloys and their crystalline counterparts are more favorable in shock wave and projectile protection, respectively. This work is useful in the understanding of the dynamic elasticity and shock energy dissipation of amorphous alloys under micro-particle impacts.

Spatiotemporal dissipation dynamics: a route to high-beam-quality and high-peak-power spatiotemporal mode-locked fiber lasers

Spatiotemporal mode-locking (STML) opens a new avenue for implementing high-energy, high-peak-power mode-locked fiber oscillators. However, the compromised beam quality poses a critical limitation to their broader applications. This study presents a method for enhancing the beam quality of STML fiber lasers by employing spatiotemporal dissipation involving the quenching and reabsorption effects of multimode erbium-doped fibers. The proposed technique introduces spatiotemporal saturable absorption, achieving high beam quality without the stringent conditions required for Kerr beam self-cleaning (BSC). Integrating spatiotemporal dissipation with Kerr BSC, we demonstrate an all-anomalous-dispersion Er-doped STML fiber laser, which produces solitons with 6.7 nJ pulse energy (the intracavity solitons with 25.8 nJ pulse energy and >52.8kW peak power), sub-500 fs pulse duration, and beam quality with M x 2/M y 2=1.23/1.20. To our knowledge, it is a record peak power for 1.5 µm band soliton lasers. Additionally, the approach enables the generation of noise-like pulses with M x 2/M y 2=1.04/1.13. This work not only advances our understanding of spatiotemporal dissipation dynamics in STML fiber lasers, but also paves the way toward high-performance STML fiber lasers, rendering them very attractive for applications.

In‐use dissipation of technology‐critical elements from vehicles and renewable energy technologies in Vienna, Austria: A public health matter?

AbstractThe rollout of electric vehicles and photovoltaic panels is essential to mitigate climate change. However, they depend on technology‐critical elements (TCEs), which can be harmful to human health and whose use is rapidly expanding, while recycling is lacking. While mining has received substantial attention, in‐use dissipation in urban areas has so far not been assessed, for example, corrosion and abrasion of vehicle components and weather‐related effects affecting thin‐film photovoltaic panels. Therefore, the question arises to which extent TCEs dissipate during use and which potential non‐occupational human health impacts could occur. We assessed the available information on urban in‐use dissipation and human health concerns and conducted exploratory modeling of in‐use technology stocks, in‐ and outflows, and in‐use dissipation of neodymium, dysprosium, lanthanum, praseodymium, cerium, gallium, germanium, and tellurium contained in 21 vehicle and renewable energy technologies, for Vienna, Austria. In prospective scenarios, TCE dynamics in a trend‐continuation vis à vis official city policy plans and a more ambitious transition scenario were then assessed. We find that electrifying the vehicle fleet without demand‐reduction is the main driver of TCE consumption, effectively doubling cumulative end‐of‐life outflows to 3,073 [2,452–3,966] t and cumulative in‐use dissipation to 9.3 [5.2–15.7] t by the year 2060. Sufficiency‐based measures could reduce demand and in‐use dissipation well below levels with continued trends, thus highlighting the need to combine decarbonization with demand‐reducing measures. These results help assess potential future in‐use dissipation dynamics and inform discussions about potential public health hazards associated with exposure to TCEs accumulating in the urban environment.

The use of pulsating jet impingement to minimize temperature oscillations caused by fluctuating heat-flux boundary conditions

Thermal cycling poses a significant challenge in modern applications employing semiconductor devices such as power electronics, owing to the dynamic heat dissipation encountered across diverse operational conditions. The oscillatory variation between peak and low temperatures can induce thermal fatigue, thereby compromising long-term reliability. To address this issue, an innovative approach involving intermittent pulsation of jets has emerged as a promising solution to mitigate peak temperatures and attenuate temperature fluctuations within acceptable limits. This paper presents a comprehensive numerical investigation into the efficacy of intermittent jet impingement in minimizing temperature fluctuations arising from transient heat-flux boundary conditions across a frequency spectrum ranging from 1 to 25 Hz. Comparative analysis against steady jets reveals that intermittent jet pulsation enables superior control over maximum temperature thresholds. An enhancement factor is introduced to quantitatively assess the effectiveness of intermittent jet pulsation, elucidating that up to 8.2 Hz, the reduction in temperature oscillation is notably enhanced compared to higher frequencies. A reduced model is developed to facilitate estimation of transient heat-transfer coefficients during the off period of the jet, shedding light on the underlying mechanisms driving enhanced heat transfer under intermittent jet conditions due to vorticity rings.

Exploiting automatic differentiation for quantum optimal control of driven dissipative two-level systems

In principle one can use Pontryagin's minimum principle to treat an optimal control problem and derive the gradient for the cost functional. However, for the driven spin-boson model studied here, the response of the system to the variation of the control is determined by the master equation and the equation of motion for the propagator of the coherent system dynamics. As a result, the application of Pontryagin's minimum principle is less straightforward. An alternative to this approach is the technique of automatic differentiation which in principle amounts to doing calculus on the fully discretized form of the optimal control problem. Automatic differentiation tools can be viewed as black boxes taking as input a program computing the cost functional and giving as output another program computing its gradient. First we derive for the polaron transformed Hamiltonian a Born-Markov master equation using the Bloch-Redfield formalism. By combining the latter with automatic differentiation we are able to implement Z-gate and coherent destruction of tunnelling with high fidelity. Optimization of a dissipative quantum gate poses a more complex numerical problem, since it should occur independent of the input state. To overcome this difficulty, we apply optimal control to the concept of resolvent of the master equation which is the generalisation of quantum unitary evolution operator in the case of dissipative dynamics.

Statistical-Physics-Informed Neural Networks (Stat-PINNs): A machine learning strategy for coarse-graining dissipative dynamics

Machine learning, with its remarkable ability for retrieving information and identifying patterns from data, has emerged as a powerful tool for discovering governing equations. It has been increasingly informed by physics, and more recently by thermodynamics, to further uncover the thermodynamic structure underlying the evolution equations, i.e., the thermodynamic potentials driving the system and the operators governing the kinetics. However, despite its great success, the inverse problem of thermodynamic model discovery from macroscopic data is in many cases non-unique, meaning that multiple pairs of potentials and operators can give rise to the same macroscopic dynamics, which significantly hinders the physical interpretability of the learned models. In this work, we consider the problem of deriving the macroscopic (continuum) equations from microscopic (particle) data, and encode knowledge from statistical mechanics to resolve this non-uniqueness for the first time. The proposed machine learning framework, named as Statistical-Physics-Informed Neural Networks (Stat-PINNs), is here developed for purely dissipative isothermal systems. Interestingly, it only uses data from short-time particle simulations to learn the thermodynamic structure, which can in turn be used to predict long-time macroscopic evolutions. We demonstrate the approach for particle systems with Arrhenius-type interactions, common to a wide range of phenomena, such as defect diffusion in solids, surface absorption, and chemical reactions. Our results from Stat-PINNs can successfully recover the known analytic solution for the case with long-range interactions and discover the hitherto unknown potential and operator governing the short-range interaction cases. We compare our results with direct particle simulations and an analogous approach that solely excludes statistical mechanics, and observe that, in addition to recovering the unique thermodynamic structure, statistical mechanics relations can increase the robustness and predictive capability of the learning strategy.

Action of liquid tune mass dampers and base isolation in high rise buildings

In areas where earthquakes are common, high-rise structure seismic resistance is a major concern. The purpose of this research is to determine whether base isolation and liquid tuned mass dampers (LTMDs) can improve tall building seismic performance. A symmetrical G+8 story RCC structure in Zone V with medium grade soil is analyzed using ETABS software, Response Spectrum Analysis, and Equivalent Static Analysis to see how the structure behaves under different load combinations. For various structural configure rations, including basic models, models with water tanks, and models with base isolation, key factors such joint displacement, storey drift, base shear, and time period are evaluated. The results show that as compared to baseline models, models with damping and isolation systems exhibit much lower joint displacements, base shear forces, and story drift. In particular, base isolation models perform better in terms of reducing structural deformations and resisting lateral forces. Furthermore, shorter time periods and higher frequencies are routinely observed in base isolated models, suggesting enhanced dynamic response and energy dissipation capabilities. The paper also covers the flexibility and benefits of using LTMDs and base isolation to reduce seismic threats. Buildings can be successfully separated from ground motion by base isolation systems, and dynamic response can be countered by LTMDs using regulated liquid sloshing. The attraction of LTMDs in improving overall stability is increased by their adaptability in minimizing torsional and lateral vibrations. The study concludes by emphasizing how crucial it is to use cutting-edge structural retrofitting methods, including base isolation and LTMDs, to improve the seismic resistance of high-rise structures. In earthquake-prone areas, engineers and legislators may proactively protect tall buildings and guarantee a safer, more robust built environment by incorporating these technologies into construction standards and design procedures.

Energy distributions of Frenkel–Kontorova-type atomic chains: Transition from conservative to dissipative dynamics

We investigate energy distributions of Frenkel–Kontorova-type atomic chains generated from large number of independent identically distributed (iid) random initial atomic positionings under two cases. In the first case, atoms at the free-end chains without dissipation (conservative case) are only coupled to one other atom, whereas each atom inside the bulk is coupled to its 2 nearest neighbors. Here, atoms located at the chain are all at the same type. Such kind of systems can be modelled by conservative standard map. We show that, when the coupling is non-linear (which leads chaotic arrangement of the atoms) for energy distribution, the Boltzmann–Gibbs statistical mechanics is constructed, namely, exponential form emerges as Boltzmann factor P(E)∝e−βE. However, when the coupling is linear (which leads linear arrangement of the atoms) the Boltzmann–Gibbs statistical mechanics fails and the exponential distribution is replaced by a q-exponential form, which generalizes the Boltzmann factor as P(E)∝eq−βqE=[1−(1−q)βqE]1/(1−q). We also show for each type of atom localization with N number of atoms, β (or βq) values can be given as a function of 1/N. In the second case, although the couplings among the atoms are exactly the same as the previous case, atoms located at the chain are now considered as being at different types. We show that, for energy distribution of such linear chains, each of the distributions corresponding to different dissipation parameters (γ) are in the q-exponential form. Moreover, we numerically verify that βq values can be given as a linear function of 1/∑n=1N(1−γ)(n−2). On the other hand, although energy distributions of the chaotic chains for different dissipation parameters are in exponential form, a linear scaling between β and γ values cannot be obtained. This scaling is possible if the energies of the chains are scaled with 1/(1−γ)−N. For both cases, clear data collapses among distributions are evident.

Experimental study on dynamic mechanical properties of multidirectional constrained water-bearing coal samples under dynamic-static coupling loading

The objective of this study is to investigate the dynamic mechanical properties of coal and rock under deep water conditions. The research employs an enhanced Split Hopkinson Pressure Bar (SHPB) testing system. Five sets of dynamic impact experiments were conducted on coal samples under varying loading conditions to analyse the changes in dynamic strength, energy dissipation, fractal dimension and other characteristics of coal samples under different water content states were analyzed. The experimental results demonstrate that: (1) Under specific strain rate conditions, the dynamic strength of saturated coal samples is lower than that of natural coal samples. As the strain rate gradually increases, the bonding force generated by free water and the Stefan effect jointly act, and the peak strength of saturated coal samples under high strain rate loading conditions is higher than that of natural coal samples. (2) Under certain strain rate conditions, the absorption energy of saturated coal samples is approximately 10% to30% lower than that of natural coal samples, and deformation hysteresis phenomenon occurs in natural coal samples, thereby improving the dynamic strength of natural coal samples relative to saturated coal samples; (3) The fractal dimension of saturated coal samples with a specific strain rate under three-dimensional dynamic static combination loading is higher than that of natural coal samples, and the percentage of small particle coal samples with debris is higher than that of natural coal samples; Finally, based on the HJC model, some coal samples were selected to simulate the coal rock failure characteristics during the triaxial loading process using ANSYS/LS-DYNA, and their stress–strain curves and failure morphology diagrams were obtained. The discrepancy between the numerical simulation and the experimental results was less than 10%, thereby further elucidating and corroborating the coal failure process and dynamic mechanical characteristics.

Dynamic response mechanisms of thin UHMWPE under high-speed impact

This study systematically explores the dynamic response mechanisms and energy dissipation mechanisms of ultra-high-molecular-weight polyethylene (UHMWPE) fiber laminated plates with thicknesses of 1.1 mm, 2.8 mm, and 5.4 mm under high-speed steel ball impacts through experimental, theoretical analysis, and dimensional analysis. By analyzing the damage mechanisms from experimental results, the main modes of energy absorption were identified, and a relatively accurate predictive model for ballistic limit speed was established. The results show that under high-speed steel ball impacts, the primary failure modes of UHMWPE fiber laminated plates are localized permanent bulging plastic deformation and perforation failure caused by compressive shear. The ballistic limit speeds for UHMWPE with thicknesses of 1.1 mm, 2.8 mm, and 5.4 mm are respectively 233.5 m/s, 415.7 m/s, and 602.9 m/s. The theoretical calculations of the energy model align well with the experimental results, indicating that as the speed increases, the proportion of tensile energy absorption gradually decreases, consistent with the observed phenomena. Near the ballistic limit, there are significant turning points in the level of energy absorption and the height of the rear bulge. The ballistic limit increases linearly with target thickness, and the unit area density energy absorption also increases continuously. Finally, this study established a dimensionless ballistic limit model considering the mechanical properties of fibers and the matrix, which through regression analysis, can accurately describe the ballistic limits of various strengths and types of fiber laminated plates, suitable for predicting the ballistic performance of various composite materials.

Classifying post-Minkowskian geometries for gravitational waves via loop-by-loop Baikov

We use the loop-by-loop Baikov representation to investigate the geometries in Feynman integrals contributing to the classical dynamics of a black-hole two-body system in the post-Minkowskian expansion of general relativity. These geometries determine the spaces of functions to which the corresponding Feynman diagrams evaluate. As a proof of principle, we provide a full classification of the geometries appearing up to three loops, i.e. fourth post-Minkowskian order, for all diagrams relevant to the conservative as well as the dissipative dynamics, finding full agreement with the literature. Moreover, we show that the non-planar top topology at four loops, which is the most complicated sector with respect to integration-by-parts identities, has an algebraic leading singularity and thus can only depend on non-trivial geometries through its subsectors.

Quantum neural network approach to Markovian dissipative dynamics of many-body open quantum systems.

Numerous variational methods have been proposed for solving quantum many-body systems, but they often face exponentially increasing computational complexity as the Hilbert space dimension grows. To address this, we introduce a novel approach using quantum neural networks to simulate the dissipative dynamics of many-body open quantum systems. This method combines neural-network quantum state representation with the time-dependent variational principle, both implemented via quantum algorithms. This results in accurate open quantum dynamics described by the Lindblad quantum master equation, exemplified by the spin-boson and transverse field Ising models. Our approach avoids the computational expense of classical algorithms and demonstrates the potential advantages of quantum computing for many-body simulations. To reduce measurement errors, we introduce a projection reset procedure, which could benefit other quantum simulations. In addition, our approach can be extended to simulate non-Markovian quantum dynamics.