Classical Evolution Research Articles

Analysis of electron spectra dynamics in a moving periodical ponderomotive potential

Abstract The interaction between freely propagating electrons and light waves is typically described using an approximation in which we assume that the electron’s velocity nearly does not change during the interaction. In this article we analytically describe the dynamics of electrons in an interaction potential generated by an optical beat wave beyond this regime and find a structure of sharp electron distribution peaks that periodically alternate in the energy/momentum spectrum. In classical description we analytically solve the nonlinear equation of motion, which is an analogy to mathematical pendulum. While addressing the problem using quantum mechanics we first use parabolic approximation of the interaction potential and then we also study the evolution of electron wavepacket in an infinite periodical potential. Using numerical simulations we show the classical and quantum evolution of the electron spectra during the interaction for different conditions and experimental settings.

On the exact Maxwell evolution equation of resonator dynamics

In a recent publication [Opt. Express 32, 20904 (2024)], the accuracy of the main evolution equation that governs resonator dynamics in the coupled-mode theory (CMT) was questioned. The study concluded that the driving force is proportional to the temporal derivative of the excitation field rather than the excitation field itself. This conclusion was reached with a derivation of an “exact” Maxwell evolution (EME) equation obtained directly from Maxwell’s equations, which was further supported by extensive numerical tests. Hereafter, we argue that the original derivation lacks mathematical rigor. We present a direct and rigorous derivation that establishes a solid mathematical foundation for the EME equation. This new approach clarifies the origin of the temporal derivative in the excitation term of CMT and elucidates the approximations present in the classical CMT evolution equation through a straightforward argument.

Classical correspondence beyond the Ehrenfest time for open quantum systems with general Lindbladians

Quantum and classical systems evolving under the same formal Hamiltonian H may exhibit dramatically different behavior after the Ehrenfest timescale tE∼log(ħ-1), even as ħ→0. Coupling the system to a Markovian environment results in a Lindblad equation for the quantum evolution. Its classical counterpart is given by the Fokker–Planck equation on phase space, which describes Hamiltonian flow with friction and diffusive noise. The quantum and classical evolutions may be compared via the Wigner-Weyl representation. Due to decoherence, they are conjectured to match closely for times far beyond the Ehrenfest timescale as ħ→0. We prove a version of this correspondence, bounding the error between the quantum and classical evolutions for any sufficiently regular Hamiltonian H(x, p) and Lindblad functions Lk(x,p). The error is small when the strength of the diffusion D associated to the Lindblad functions satisfies D≫ħ4/3, in particular allowing vanishing noise in the classical limit. Our method uses a time-dependent semiclassical mixture of variably squeezed Gaussian states. The states evolve according to a local harmonic approximation to the Lindblad dynamics constructed from a second-order Taylor expansion of the Lindbladian. Both the exact quantum trajectory and its classical counterpart can be expressed as perturbations of this semiclassical mixture, with the errors bounded using Duhamel’s principle. We present heuristic arguments suggesting the 4/3 exponent is optimal and defines a boundary in the sense that asymptotically weaker diffusion permits a breakdown of quantum-classical correspondence at the Ehrenfest timescale. Our presentation aims to be comprehensive and accessible to both mathematicians and physicists. In a shorter companion paper, we treat the special case of Hamiltonians that decompose into kinetic and potential energy with linear Lindblad operators, with explicit bounds that can be applied directly to physical systems.

Parameter estimation in vapor-liquid equilibrium modeling of compounds related to biodiesel production using opposite point-based differential evolution algorithm.

Biodiesel stands out as the most favorable alternatives to fossil-derived diesel, offering a multitude of environmental benefits. At various stages of biodiesel production, the separation processes necessitate thermodynamic models with the capability to correlate and predict phase equilibria of mixtures. In this study, application of the classical differential evolution (DE) and its new enhanced version, the OPDE algorithm, for modeling vapor-liquid equilibrium (VLE) associated with components related to biodiesel production is presented. The algorithms were analysed and contrasted in terms of their performance, in estimating parameters for Wilson, NRTL and UNIFAC models. Additionally, classical least-squares (LS) and error-in-variable (EIV) approaches were examined and compared. Also, VLE datasets for a specific system have been merged, and parameters have been estimated. The findings suggest that parameters obtained through LS approach align with those reported in literature, indicating faster convergence in all problems. In contrast, the EIV approach achieved a higher objective function value compared to the LS approach, exhibiting low deviation. OPDE outperformed DE in terms of performance. The enhancement in RMSTD value has been found within range 91%-99% for EIV approach. Further, novel findings derived from some of the studied VLE datasets are presented.

The effects of herding and dispersal behaviour on the evolution of cooperation on complete networks

Evolutionary graph theory has considerably advanced the process of modelling the evolution of structured populations, which models the interactions between individuals as pairwise contests. In recent years, these classical evolution models have been extended to incorporate more realistic features, e.g. multiplayer games. A recent series of papers have developed a new evolutionary framework including structure, multiplayer interactions, evolutionary dynamics, and movement. However, so far, the developed models have mainly considered independent movement without coordinated behaviour. Although the theory underlying the framework has been developed and explored in various directions, several movement mechanisms have been produced which characterise coordinated movement, for example, herding. By embedding these newly constructed movement distributions, within the evolutionary setting of the framework, we demonstrate that certain levels of aggregation and dispersal benefit specific types of individuals. Moreover, by extending existing parameters within the framework, we are not only able to develop a general process of embedding any of the considered movement distributions into the evolutionary setting on complete graphs but also analytically produce the probability of fixation of a mutant on a complete N-sized network, for the multiplayer Public Goods and Hawk–Dove games. Also, by applying weak selection methods, we extended existing previous analyses on the pairwise Hawk–Dove Game to encompass the multiplayer version considered in this paper. By producing neutrality and equilibrium conditions, we show that hawks generally do worse in our models due to the multiplayer nature of the interactions.

Defects trigger redox reactivities between metal and lattice oxygen in high-entropy layered double hydroxide for boosting oxygen evolution in alkaline

The oxygen evolution reaction (OER) at the anode undergoes a sluggish multi-step process, thereby impeding overall water splitting. As the classical adsorbate evolution mechanism (AEM) involves multiple oxygen-containing intermediates, such as *OH, *O and *OOH, breaking the linear relationship of the adsorption energies between *OH and *OOH is the key to efficient oxygen evolution. Herein, we report a high-entropy FeCoNiAlZn layered double hydroxide decorated with defects (E-FeCoNiAlZn LDH) for boosting oxygen evolution in alkaline. The product exhibits high OER activity with a low overpotential of 220 at 10 mA cm−2 and outstanding stability with negligible decline after 100 h operation. The defects in E-FeCoNiAlZn LDH not only enhance the adsorption of *OH by metal sites but also foster the release of oxygen from lattice, which triggers the coupled oxygen evolution mechanism (COM). This mechanism has only *OH and *OO intermediates, perfectly avoiding the obstacles of linear relationship between *OH and *OOH. Theoretical calculations demonstrate that the introduction of defects enhances the adsorption of *OH due to the presence of unsaturated bonds. Additionally, it is evidence that the O 2p band is elevated, leading to a weakening of the metal-O bond and a reduction of the energy barrier for OO coupling.

Effects of freeze-thaw cycles on fatigue performance of asphalt mixture and a fatigue-freeze-thaw damage evolution model

To study the effect of freeze-thaw (FT) cycles on the fatigue performance of composite crumb rubber modified asphalt mixtures (CCRMA), a semicircular bending fatigue test based on the digital image correlation technique (DIC) was used to measure the fatigue life (Nf) of CCRMA and SBS modified asphalt mixtures (SBSMA) and the horizontal strain (Exx) of the DIC deformation field under repeated loading. The variation laws of Nf, Exx and the damage factor (D) defined based on Exx were analyzed under FT cycle conditions. In addition, considering the important influence of FT cycles on the Nf and damage evolution characteristics of asphalt mixtures, based on the classical Chaboche damage evolution model, the influence of FT cycle was considered, a fatigue-freeze-thaw damage evolution model that reflects the effects of FT cycling variables and stress levels on asphalt mixtures was constructed. The results indicate that the Exx peak of asphalt mixture shifts forward with increasing FT cycle number. After 20 FT cycles, the Nf of CCRMA decreased by 73.4 %, 62.1 %, and 75.1 %, while that of SBSMA decreased by 76.5 %, 58.6 %, and 74.6 % at stress ratios of 0.2, 0.3, and 0.4, respectively. The fatigue-freeze-thaw damage evolution model predictions were in agreement with experimental results, with the goodness of fit (R2) of all Nf prediction models being greater than 0.9. With the exception of a few outliers, the relative error between the measured and predicted Nf for the two asphalt mixtures was within 15 %. This indicates that the model can effectively predict the Nf and damage evolution laws of asphalt mixtures at different stress levels after an arbitrary number of FT cycles. The related research results provide a theoretical basis for predicting the Nf of new roads in cold regions under FT cycles.

A new perspective on tumor progression: Evolution via selection for function.

Tumorigenesis is commonly attributed to Darwinian processes involving natural selection among cells and groups of cells. However, progressing tumors are those that also achieve an appropriate group phenotypic composition (GPC). Yet, the selective processes acting on tumor GPCs are distinct from that associated with classical Darwinian evolution (i.e. natural selection based on differential reproductive success) as tumors are not genuine evolutionary individuals and do not exhibit heritable variation in fitness. This complex evolutionary scenario is analogous to the recently proposed concept of 'selection for function' invoked for the evolution of both living and non-living systems. Therefore, we argue that it is inaccurate to assert that Darwinian processes alone account for all the aspects characterizing tumorigenesis and cancer progression; rather, by producing the genetic and phenotypic diversity required for creating novel GPCs, these processes fuel the evolutionary success of tumors that is dependent on selection for function at the tumor level.

A fixed point evolution algorithm based on expanded Aitken rapid iteration method for global numeric optimization

Evolution algorithms based on mathematical models whose reproduction operators are derived from mathematical models are a promising branch of metaheuristic algorithms. Aitken rapid iteration method, as a fixed point iteration technique for solving nonlinear equations, performs a procedure of progressive display of a root and generates an iterative sequence that exhibits a convergent trend. Inspired by the idea that an iterative sequence gradually converges to the optimal point during the progressive display procedure of a fixed point of an equation, a fixed point evolution algorithm based on the expanded Aitken rapid iteration method (FPEea) is proposed. To develop FPEea, an expanded Aitken rapid model is first constructed. Then, three polynomials which are derived from the expanded Aitken rapid model are used as the reproduction operator of FPEea to produce offspring. The performance of FPEea is investigated on CEC2019 and CEC2020 benchmark function sets, as well as four engineering design problems. Experimental results show that FPEea is an effective and competitive algorithm compared with several classical evolution algorithms and state-of-the-art algorithms.

Multi-phase-field modeling of the dissolution behavior of stoichiometric particles on experimentally relevant length scales

The dissolution of stoichiometric particles within a melt plays a crucial role in various material processes. This study presents a comprehensive phase-field model to analyze the dissolution behavior of these stoichiometric particles under experimental conditions. Our approach addresses the classical phase-field challenges related to modeling stoichiometric compounds and scaling to experimentally relevant lengths in a multi-phase, multi-component context. To overcome the difficulties posed by stoichiometric compounds, we rederive the classical phase-field evolution equations for a multi-phase system, adopting a composition-independent free energy expression for the stoichiometric compound. Additionally, we extend Feyen’s high driving force model [Feyen and Moelans, Acta Materialia, 256 (2023)] to multi-component systems, allowing us to perform quantitative simulations for technologically relevant material systems at experimental length scales within a reasonable computing time. The model’s precision in capturing diffusion-controlled transformations, including dissolution, growth, and the Gibbs–Thomson effect, is validated against analytical solutions for a hypothetical system. The quantitative nature of the model is validated by applying it to the dissolution of Al2O3 particles in CaO–Al2O3–SiO2 slags. We break new ground by conducting three-dimensional simulations for a system size of 875μm×875μm×875μm, directly comparable to confocal scanning laser microscopy experiments, where previous models were limited to two-dimensional simulations and a system size of 2μm×2μm. This validation underscores the model’s proficiency to quantitatively describe the diffusion-controlled dissolution of Al2O3 at the experimentally relevant length scales.

Differences between quantum and classical adiabatic evolution

Differences between quantum and classical adiabatic evolution

A modified constitutive model for whole-life thermal-mechanical fatigue incorporating dynamic strain aging in 316LN stainless steel

A comprehensive analysis of experimental data is presented for 316LN stainless steel subjected to isothermal and thermal-mechanical fatigue loading conditions within the temperature range of 350–600 °C. The study aims to provide a thorough understanding of the cyclic behavior through meticulous data integration, supplementation, and the use of stress decomposition methods combined with a classical damage evolution definition. The modeling approach employed in this study is based on the classical AF-OW-Kang model, with the incorporation of the Arrhenius term in the plastic flow rate equation. Furthermore, to consider the effect of dynamic strain aging at varying temperatures, temperature-dependent terms are introduced into the equations that govern the evolution of isotropic stress and backstress, resulting in enhanced accuracy in describing cyclic hardening behavior. Additionally, a modified damage evolution equation is utilized, along with equations for isotropic stress and backstress evolution, to address cyclic softening. Simulation results confirm the effectiveness of the modified model in capturing the cyclic hardening/softening behavior of 316LN stainless steel throughout the whole-life time, under both isothermal and thermal-mechanical fatigue loading conditions.

Box2Mask: Box-Supervised Instance Segmentation via Level-Set Evolution.

In contrast to fully supervised methods using pixel-wise mask labels, box-supervised instance segmentation takes advantage of simple box annotations, which has recently attracted increasing research attention. This paper presents a novel single-shot instance segmentation approach, namely Box2Mask, which integrates the classical level-set evolution model into deep neural network learning to achieve accurate mask prediction with only bounding box supervision. Specifically, both the input image and its deep features are employed to evolve the level-set curves implicitly, and a local consistency module based on a pixel affinity kernel is used to mine the local context and spatial relations. Two types of single-stage frameworks, i.e., CNN-based and transformer-based frameworks, are developed to empower the level-set evolution for box-supervised instance segmentation, and each framework consists of three essential components: instance-aware decoder, box-level matching assignment and level-set evolution. By minimizing the level-set energy function, the mask map of each instance can be iteratively optimized within its bounding box annotation. The experimental results on five challenging testbeds, covering general scenes, remote sensing, medical and scene text images, demonstrate the outstanding performance of our proposed Box2Mask approach for box-supervised instance segmentation. In particular, with the Swin-Transformer large backbone, our Box2Mask obtains 42.4% mask AP on COCO, which is on par with the recently developed fully mask-supervised methods.

Absolute dimensions of solar-type eclipsing binaries

Context. The binary star NY Hya is a bright, detached, double-lined eclipsing system with an orbital period of just under five days with two components each nearly identical to the Sun and located in the solar neighbourhood. Aims. The objective of this study is to test and confront various stellar evolution models for solar-type stars based on accurate measurements of stellar mass and radius. Methods. We present new ground-based spectroscopic and photometric as well as high-precision space-based photometric and astrometric data from which we derive orbital as well as physical properties of the components via the method of least-squares minimisation based on a standard binary model valid for two detached components. Classic statistical techniques were invoked to test the significance of model parameters. Additional empirical evidence was compiled from the public domain; the derived system properties were compared with archival broad-band photometry data enabling a measurement of the system’s spectral energy distribution that allowed an independent estimate of stellar properties. We also utilised semi-empirical calibration methods to derive atmospheric properties from Strömgren photometry and related colour indices. Results. We measured (percentages are fractional uncertainties) masses, radii, and effective temperatures of the two stars in NY Hya and found them to be MA = 1.1605 ± 0.0090 M⊙ (0.78%), RA = 1.407 ± 0.015 R⊙ (1.1%), Teff, A = 5595 ± 61 K (1.09%), MB = 1.1678 ± 0.0096 M⊙ (0.82%), RB = 1.406 ± 0.017 R⊙ (1.2%), and Teff, B = 5607 ± 61 K (1.09%). The atmospheric properties from Strömgren photometry agree well with spectroscopic results. No evidence was found for nearby companions from high-resolution imaging. A detailed analysis of space-based data revealed a small but significant eccentricity (e cos ω) of the orbit. The spectroscopic and frequency analysis on photometric time series data reveal evidence of clear photospheric activity on both components likely in the form of star spots caused by magnetic activity. Conclusions. We confronted the observed physical properties with classic and magnetic stellar evolution models. Classic models yielded both young pre-main-sequence and old main-sequence turn-off solutions with the two components at super-solar metallicities, in disagreement with observations. Based on chromospheric activity and X-ray observations, we invoke magnetic models. While magnetic fields are likely to play an important role, we still encounter problems in explaining adequately the observed properties. To reconcile the observed tensions we also considered the effects of star spots known to mimic magnetic inhibition of convection. Encouraging results were obtained, although unrealistically large spots were required on each component. Overall we conclude that NY Hya proves to be complex in nature, and requires additional follow-up work aiming at a more accurate determination of stellar effective temperature and metallicity.

Variability of Blue Supergiants in the LMC with TESS

The blue supergiant (BSG) problem, namely, the overabundance of BSGs inconsistent with classical stellar evolution theory, remains an open question in stellar astrophysics. Several theoretical explanations have been proposed, which may be tested by their predictions for the characteristic time variability. In this work, we analyze the light curves of a sample of 20 BSGs obtained from the Transiting Exoplanet Survey Satellite (TESS) mission. We report a characteristic signal in the low-frequency (f ≲ 2 day−1) range for all our targets. The amplitude spectrum has a peak frequency of ∼0.2 day−1, and we are able to fit it by a modified Lorentzian profile. The signal itself shows strong stochasticity across different TESS sectors, suggesting its driving mechanism happens on short (≲months) timescales. Our signals resemble those obtained for a limited sample of hotter OB stars and yellow supergiants, suggesting their possible common origins. We discuss three possible physical explanations: stellar winds launched by rotation, convection motions that reach the stellar surface, and waves from the deep stellar interior. The peak frequency of the signal favors processes related to the convective zone caused by the iron opacity peak, and the shape of the spectra might be explained by the propagation of high-order, damped gravity waves excited from that zone. We discuss the uncertainties and limitations of all these scenarios.

Rapid oxygen isotopic exchange between bicarbonate and water during photosynthesis

Whether rapid oxygen isotopic exchange between bicarbonate and water occurs in photosynthesis is the key to determine the source of oxygen by classic 18O-labeled photosynthetic oxygen evolution experiments. Here we show that both Microcystis aeruginosa and Chlamydomonas reinhardtii utilize a significant proportion (>16%) of added bicarbonate as a carbon source for photosynthesis. However, oxygen isotopic signal in added bicarbonate cannot be traced in the oxygen in organic matter synthesized by these photosynthetic organisms. This contradicts the current photosynthesis theory, which states that photosynthetic oxygen evolution comes only from water, and oxygen in photosynthetic organic matter comes only from carbon dioxide. We conclude that the photosynthetic organisms undergo rapid exchange of oxygen isotope between bicarbonate and water during photosynthesis. At the same time, this study also provides isotopic evidence for a new mechanism that half of the oxygen in photosynthetic oxygen evolution comes from bicarbonate photolysis and half comes from water photolysis, which provides a new explanation for the bicarbonate effect, and suggests that the Kok-Joliot cycle of photosynthetic oxygen evolution, must be modified to include a molecule of bicarbonate in addition to one molecule of water which in turn must be incorporated into the cycle instead of two water molecules. Furthermore, this study provides a theoretical basis for constructing a newer artificial photosynthetic reactor coupling light reactions with the dark reactions.

Non-Commutative Classical and Quantum Fractionary Cosmology: FRW Case

In this work, we will explore the effects of non-commutativity in fractional classical and quantum schemes using the flat Friedmann–Robertson–Walker (FRW) cosmological model coupled to a scalar field in the K-essence formalism. In previous work, we have obtained the commutative solutions in both regimes in the fractional framework. Here, we introduce non-commutative variables, considering that all minisuperspace variables qnci do not commute, so the symplectic structure was modified. In the quantum regime, the probability density presents a new structure in the scalar field corresponding to the value of the non-commutative parameter, in the sense that this probability density undergoes a shift back to the direction of the scale factor, causing classical evolution to arise earlier than in the commutative world.

Cosmology in Lorentzian Regge calculus: causality violations, massless scalar field and discrete dynamics

We develop a model of spatially flat, homogeneous and isotropic cosmology in Lorentzian Regge calculus, employing four-dimensional Lorentzian frusta as building blocks. By examining the causal structure of the discrete spacetimes obtained by gluing such four-frusta in spatial and temporal direction, we find causality violations if the sub-cells connecting spatial slices are spacelike. A Wick rotation to the Euclidean theory can be defined globally by a complexification of the variables and an analytic continuation of the action. Introducing a discrete free massless scalar field, we study its equations of motion and show that it evolves monotonically. Furthermore, in a continuum limit, we obtain the equations of a homogeneous scalar field on a spatially flat Friedmann background. Vacuum solutions to the causally regular Regge equations are static and flat and show a restoration of time reparametrisation invariance. In the presence of a scalar field, the height of a frustum is a dynamical variable that has a solution if causality violations are absent and if an inequality relating geometric and matter boundary data is satisfied. Edge lengths of cubes evolve monotonically, yielding a contracting or an expanding branch of the Universe. In a small deficit angle expansion, the system can be deparametrised via the scalar field and a continuum limit of the discrete theory can be defined which we show to yield the relational Friedmann equation. These properties are obstructed if higher orders of the deficit angle are taken into account. Our results suggest that the inclusion of timelike sub-cells is necessary for a causally regular classical evolution in this symmetry restricted setting. Ultimately, this works serves as a basis for forthcoming investigations on the cosmological path integral within the framework of effective spin foams.

Quantum simulation approach to implementing nuclear density functional theory via imaginary time evolution

The quantum imaginary time evolution (QITE) algorithm is a direct implementation of the classical imaginary time evolution algorithm on quantum computer. We implement the QITE algorithm for the case of nuclear Hartree-Fock equations in a formalism equivalent to nuclear density functional theory. We demonstrate the algorithm in the case of the helium-4 nucleus with a simplified effective interaction of the Skyrme kind and demonstrate that the QITE, as implemented on simulated quantum computer, gives identical results to the classical algorithm. Published by the American Physical Society 2024

Handling the balance of operators in evolutionary algorithms through a weighted Hill Climbing approach

Evolutionary Algorithms (EAs) are a well-known domain within Artificial Intelligence. EAs have demonstrated their ability to tackle intricate optimization problems using evolutionary theory principles. However, balancing the dual exploration and exploitation processes remains a crucial concern. This paper introduces the Balanced Hill Climbing Weight Algorithm with Diversity (BHWEAD), an innovative approach that combines elements from classic Genetic Algorithm and Differential Evolution. BHWEAD uniquely employs the Hill Climbing local search to guide the influence of its operators, ensuring an optimal interplay between exploration and exploitation. Additionally, it incorporates a diversity control mechanism, resetting specific solutions to prevent premature convergence to suboptimal solutions. The main contribution of the BHWEAD is the mechanism that permits the balance of the exploration and exploitation stages; also, the incorporation of Hill Climbing permits a proper balance of the influence of the operators. Notice that the proposal can escape from suboptimal solutions using a diversity-based strategy. Tested against the CEC2017 benchmark functions in both 50 and 100 dimensions, BHWEAD outperformed 12 notable EAs, underscoring its potential for high-dimensional optimization problems. Besides, the proposed BHWEAD has also been tested over seven engineering problems, and the comparisons include some memetic algorithms., The paper provides additional insights into the algorithm’s design, conducts a comparative analysis, and identifies potential areas for improvement.