Dynamic Transition Research Articles

From high-dimensional committors to reactive insights.

Transition path theory (TPT) offers a powerful formalism for extracting the rate and mechanism of rare dynamical transitions between metastable states. Most applications of TPT either focus on systems with modestly sized state spaces or use collective variables to try to tame the curse of dimensionality. Increasingly, expressive function approximators such as neural networks and tensor networks have shown promise in computing the central object of TPT, the committor function, even in very high-dimensional systems. That progress prompts our consideration of how one could use such a high-dimensional function to extract mechanistic insights. Here, we present and illustrate a straightforward but powerful way to track how individual dynamical coordinates evolve during a reactive event. The strategy, which involves marginalizing the reactive ensemble, naturally captures the evolution of the dynamical coordinate's distribution, not just its mean reactive behavior.

Ultrafast optical induction of magnetic order at a quantum critical point

Time-resolved ultrafast spectroscopy has emerged as a promising tool to dynamically induce and manipulate non-trivial electronic states of matter out-of-equilibrium. Here we theoretically investigate light pulse driven dynamics in a Kondo lattice system close to quantum criticality. Based on a time-dependent auxiliary fermion mean-field calculation we show that light can dehybridize the local Kondo screening and induce oscillating magnetic order out of a previously paramagnetic state. Depending on the laser pulse field amplitude and frequency the Kondo singlet can be completely deconfined, inducing a dynamic Lifshitz transition that changes the Fermi surface topology. These phenomena can be identified in harmonic generation and time-resolved angle-resolved photoemission spectroscopy spectra. Our results shed new light on non-equilibrium states in heavy fermion systems.

Correction: Demographic transition and population dynamics in Xinjiang, China

Correction: Demographic transition and population dynamics in Xinjiang, China

Chiral Steric Effect for Improved Phase Transition and Exciton Dynamics in Efficient and Stable All‐Polymer Solar Cells

AbstractChiral materials exhibit distinctive properties that improve the performance of organic solar cells (OSCs). In this study, chiral PM6 is integrated into PM6:PY‐IT blends to fabricate chiral quasi‐binary OSCs (cOSCs). The produced devices displayed an increased short‐circuit current and fill factor, achieving a peak efficiency of 16.60% compared to 15.96% for the standard PM6:PY‐IT cell. Additionally, the incorporation of chiral PM6 significantly enhanced the thermal stability, with the cOSCs retaining over 80% of their initial efficiency after 1000 h of operation. The steric effect of chiral PM6 altered the molecular packing, thereby improving the overall crystallinity. The optimized nanoscale domain morphology resulted in a more effective blend film, leading to superior device performance. Moreover, the chirality‐induced orbital angular momentum increased the ratio of triplet states, which is a key factor for increasing the photocurrent in OSCs. The delocalization of electron wavefunctions is driven by chiral steric effects, and it diminished the Coulomb attraction between the interfacial electron–hole pairs, which enhanced the efficient charge generation. This study provides valuable insights into the role of chirality in optimizing both the performance and stability of OSCs.

Quantum optimal control of molecular coherent states

Abstract In this paper, we address the optimal control problem in molecular systems, focusing on transitions within coherent states characterised by complex coefficients. Employing Hölder’s inequality, we establish a mathematical relationship between the energy requirement and the distance separating the initial and the target coherent states. A key part of our study is the application of this framework to the H2O molecule, specifically examining the local OH bond. Here, we demonstrate how energy requirements for the state transitions are influenced by the distance between these states. Furthermore, we investigate the effects of a heat bath coupled to the system, by analysing its impact on transferring the molecular system to different final coherent states. These coherent states are defined as almost eigenvectors of the Generalised Heisenberg Algebra (GHA) annihilation operator. By using the Perolomov approach, another type of coherent states for the Morse potential associated with the GHA can be constructed. By leveraging the GHA structure, we revisit and analyse Morse coherent states previously established for certain diatomic molecules, offering a deeper insight into the dynamics of state transitions under various conditions.

Complex dynamic behavioral transitions in auditory neurons induced by chaotic activity

Chaotic sequences are widely used in secure communication due to their high randomness. Chaotic resonance (CR) refers to the resonant response of a system to weak signals induced by chaotic activity, but its practical application remains limited. This study designs a simplified FitzHugh-Nagumo (FHN) auditory neuron model by simulating the physiological activities of auditory neurons and considering the combined stimulation of chaotic activity and sound signals. It is found that the neuron dynamics depend on both external sound stimuli and chaotic current intensity. Chaotic currents induce spikes in the neuron output sequence through CR, and the spikes become more frequent with increasing current intensity, eventually leading to a chaotic state regardless of the initial state. However, the sensitivity of the initial value of this chaotic sequence shifts to the chaotic current excitation system. The injection of chaotic currents can reduce the system's average Hamiltonian energy under certain conditions. By measuring the complexity of the generated sequences, we find that the addition of chaotic currents can enhance the complexity of the original sequences, and the enhancement ability increases with the intensity. This provides a new approach to enhance the complexity of original chaotic sequences. Moreover, different chaotic currents can induce different chaotic sequences with varying abilities to enhance the complexity of the original sequences. We hope our work can contribute to secure communication.

Anesthesia alters complexity of spontaneous and stimulus-related neuronal firing patterns in rat visual cortex

Complexity of neuronal firing patterns may serve as an indicator of sensory information processing across different states of consciousness. Recent studies have shown that spontaneous changes in brain states can occur during general anesthesia, which may influence neuronal complexity and the state of consciousness. In this study, we investigated how the firing patterns of cortical neurons, both at rest and during visual stimulation, are affected by spontaneously changing brain states under varying levels of anesthesia. Extracellular unit activity was measured in the primary visual cortex of unrestrained rats as the inhaled concentration of desflurane was incrementally reduced to 6%, 4%, 2%, and 0%. Using dimensionality reduction and density-based clustering on individual unit activities, we identified five distinct population states, which underwent dynamic transitions independent of the anesthetic level during both resting and stimulus conditions. One population state that occurred mainly in deep anesthesia exhibited a paradoxically increased number of active neurons and asynchronous spiking, suggesting a spontaneous reversal towards an awake-like condition. However, this was contradicted by the observation of low neuronal complexity in both spontaneous and stimulus-related spike activity, which more closely aligns with unconsciousness. Our findings reveal that transient neuronal states with distinct spiking patterns can emerge in visual cortex at constant anesthetic concentrations. The reduced complexity in states associated with deep anesthesia likely indicates a disruption of conscious sensory information processing.

Market-oriented reforms and wealth inequality in China

Over the last few decades, China’s growing wealth inequality has mirrored the contemporary global trend. We investigate the effects of China’s market-oriented reforms on wealth inequality using a dynamic general equilibrium model with an incomplete market and idiosyncratic risks. Focusing on the relaxation of private entry and the easing of financial constraints as two pivotal reforms, we show that our model-generated results closely match the actual wealth distribution from 1995 to 2018, with the reform of private enterprise entry accounting for most of the widening wealth disparity. We elucidate the underlying mechanisms of these two reforms using counterfactual simulations and discover that through the savings rate mechanism, the two reforms will collectively form an inverted U-shaped Kuznets curve in wealth inequality as reforms deepen in the future. By calculating the transition dynamics from 1995 to 2035, we confirm that the Kuznets turning point in China lies between 2020 and 2025.

Dynamical analysis of the Rulkov model with quasiperiodic forcing

This paper investigates the dynamical behavior of the Rulkov neuron model under quasiperiodic forcing, focusing on the emergence and mechanisms of strange nonchaotic attractors (SNAs). SNAs are characterized by fractal geometry without sensitive dependence on initial conditions, and their formation mechanisms, such as torus-doubling, fractal, bubble, Heagy–Hammel, and multi-intermittency routes, are explored in detail. The study employs Lyapunov exponents, singular continuous spectrum, and phase sensitivity to detect and characterize the strange and nonchaotic properties of attractors. Numerical simulations reveal the transition dynamics between strange nonchaotic, quasiperiodic, and chaotic states, emphasizing the role of transient dynamics in understanding the complex behavior of neural systems under multifrequency stimuli. The findings provide deeper insights into the intricate dynamical processes in neuron models, potentially aiding the development of advanced models for neural response prediction in varying environments.

Flow regime mechanisms in sequencing batch reactor (SBR) configurations on aerobic granular sludge formation using particle image velocimetry (PIV)

Indah Water Konsortium (IWK) consistently encounters challenges in managing over 7000 sewage treatment plants (STPs) due to inadequate infrastructure for centralized treatment. In addressing the challenge of land acquisition during STP upgrades, aerobic granular sludge (AGS) technology is worth exploring. The AGS systems are designed in sequencing batch reactors (SBRs) as a superior alternative to reduce land requirements. Research trends on AGS formation by flow regime mechanism are not yet fully comprehended for different SBR configurations (column and rectangular-type) as sufficient adjusted aeration rates in producing high-quality effluent. In this study, mature AGS of about 2736 μm was achieved at 57 days of formation in rectangular-type SBR by laminar flow with an aeration rate of 4 L/min. Due to transitional flow dynamics, there was a delay of about 54 % of mature AGS (2505 μm) on day 88 in column-type SBR at an aeration rate of 6 L/min. Microbial growth indicated that effective mixing was essential in wastewater treatment to ensure uniform distribution of oxygen, nutrients, and microorganisms, while excessive agitation must be avoided to maintain granular integrity. Thus, this research offers insights into the novelty of AGS for full-scale application.

The hot deformation behavior of a L12 precipitation strengthened face centered cubic high entropy alloy

In this work, the hot compressive deformation behavior of a homogenized Ni45Co15Cr15Fe15Al8Ti2 high entropy alloy was investigated at deformation temperatures of 900–1200°C and strain rates of 10−3-1 s−1. Initially, combined the true stress-strain curves and hyperbolic sine function model, the constitutive equation for the flow stress of the alloy during the hot deformation process was established. Additionally, the hot processing map of the alloy at a true strain of ε = 0.5 was plotted based on the DMM model. Coupled with microstructural observations, the optimal hot processing parameters for the alloy were determined to be T = 1070–1200 °C and ε̇= 0.001–0.05 s−1. Finally, the deformed microstructure of the alloy under different temperatures and strain rates was characterized using EBSD, and the dynamic recrystallization mechanisms was revealed. The flow stress decreases with the increasing deformation temperature and decreasing strain rate. As the deformation temperature increases from 900°C to 1200°C, the dynamic recrystallization mechanism transitions from continuous dynamic recrystallization (CDRX) to discontinuous dynamic recrystallization (DDRX). The findings of this study will provide valuable guidance for the development of hot forging parameters of the L12 strengthened FCC high-entropy alloys.

Characterization and visualization of gas–liquid two-phase flow based on wire-mesh sensor

Gas–liquid two-phase flow is prevalent in both industrial production and the natural environment, making the exploration of its flow behavior critically important. In this study, we design a wire-mesh sensor and measurement system to conduct dynamic experiments on vertical upward gas–liquid two-phase flow, obtaining multi-channel data under various conditions. We develop an integrated limited penetrable visibility graph network (ILPVGNet) to quantitatively assess the dynamic transition from slug flow to bubble flow using network metrics. The results demonstrate that this approach effectively integrates multi-channel measurements, revealing the evolution dynamics and internal coupling mechanisms of gas–liquid two-phase flow. To better observe fine flow structures and details, we perform visualization and super-resolution analysis on the multi-channel data, significantly enhancing image clarity and restoring detailed features, thereby improving our ability to intuitively analyze complex gas–liquid flow behaviors.

Enhanced decoupling of conductivity relaxation from structural relaxation in non-stoichiometric protic ionic liquids involving triflic acid and 2-aminoethyl hydrogen sulfate.

The glass transition dynamics and conductivity relaxation are studied for a series of non-stoichiometric protic ionic liquids (PILs) based on 2-aminoethyl hydrogen sulfate and triflic acid with varying molar ratios (denoted as AT-55, AT-46, AT-37, AT-28, and AT-19) by broadband dielectric spectroscopy in a wide frequency (10-1-107Hz) and temperature range (173-353K). The results indicate that the addition of acid lowers the glass transition temperature, as confirmed by the activation energy fine structure analysis and a crossover in the conductivity relaxation time. Notably, samples with higher acid content deliver markedly increased conductivity. In addition, detailed analysis of the permittivity and modulus spectra reveals enhanced decoupling between the structural (α-process) and conductivity relaxation in samples with a higher acid content. Remarkably, nano-phase separation in AT-28 and AT-19 samples is observed, resulting in a second glass transition temperature indicating a more mobile phase. Based on the above-mentioned findings, we infer that increased acid content disrupts strong ionic interactions within the IL fraction, resulting in a decrease in the glass transition temperature and leading to nano-phase separation into distinct acid-rich and IL-rich phases with varying Tg values. This phase separation alters the long-range ionic pathways, shifting from being solely governed by IL cluster dynamics to a scenario where charge transport becomes largely decoupled from the dynamics of IL-rich clusters. Hence, modulating the stoichiometry of PILs appears a promising approach to enhance the conductivity together with widening the usable temperature range for applications.

Quantum phase transition and composite excitations of antiferromagnetic spin trimer chains in a magnetic field

Motivated by recent advancements in theoretical and experimental studies of the high-energy excitations on an antiferromagnetic trimer chain, we numerically investigate the quantum phase transition and composite dynamics in this system by applying a magnetic field. The numerical methods we used include the exact diagonalization, density matrix renormalization group, time-dependent variational principle, and cluster perturbation theory. From calculating the entanglement entropy, we have revealed the phase diagram which includes the XY-I, 1/3 magnetization plateau, XY-II, and ferromagnetic phases. Both the critical XY-I and XY-II phases are characterized by the conformal field theory with a central charge c ≃ 1. By analyzing the dynamic spin structure factor, we elucidate the distinct features of spin dynamics across different phases. In the regime with weak intertrimer interaction, we identify the intermediate-energy and high-energy modes in the XY-I and 1/3 magnetization plateau phases as internal trimer excitations, corresponding to the propagating of doublons and quartons, respectively. Notably, applying a magnetic field splits the high-energy spectrum into two branches, labeled as the upper quarton and lower quarton. Furthermore, we explore the spin dynamics of a frustrated trimerized model closely related to the quantum magnet Na2Cu3Ge4O12. In the end, we extend our discuss on the possibility of the quarton Bose-Einstein condensation in the trimer systems. Our results are expected to be further verified through the inelastic neutron scattering and resonant inelastic X-ray scattering, and also provide valuable insights for exploring high-energy exotic excitations.

Fertility Transition in India : An inter state analysis (for the period 2011 to 2021)

This study examines the dynamics of fertility transition across five diverse Indian states - Bihar, Maharashtra, Rajasthan, Kerala and Tamil Nadu- from 2011 to 2021. Fertility transition is a critical demographic process with profound implications for social, economic, and public policy planning. These states were selected due to their varied socio-economic profiles, cultural practices, and regional disparities, offering a comprehensive view of fertility trends in India. Through the analysis of data obtained from the decennial population censuses, the study identifies patterns, trends, and drivers of fertility change, taking into consideration factors such as education, urbanization, access to healthcare, and economic development. The aim is to unravel the specific pathways through which these states have embarked on their unique fertility transitions, moving towards lower fertility rates and a demographic dividend.

Uniqueness of glasses prepared via x-ray induced yielding

The yield point marks the beginning of plastic deformation for a solid subjected to sufficient stress, but it can alternatively be reached by x-ray irradiation. We characterize this latter route in terms of thermodynamics, structure and dynamics for a series of GeSe3chalcogenide glasses with different amount of disorder. We show that a sufficiently long irradiation at room temperature results in a stationary and unique yielding state, independent of the initial state of the glass. The glass at yield is more disordered and has higher enthalpy than the annealed glass, but its properties are not extreme: they rather match those of a glass instantaneously quenched from a temperature 20% higher than the glass-transition temperature. This is a well-known, key temperature for glass-forming liquids which marks the location of a dynamical transition, and it is remarkable that different glasses upon irradiation head all there.

Exploring the dynamics of socio-technical transitions: Advancing grid-connected wind and solar energy adoption in Nigeria

Globally, countries are transitioning their national electricity grid system to meet the obligations of the Paris Agreement. National grid-connected renewable electricity provides an opportunity to reduce greenhouse gas emissions. Specifically, in a developing country like Nigeria, renewable energies such as solar and wind power can play a critical role not only in transitioning away from fossil-fuel based electricity systems but also to address prevalent energy security challenges, electricity supply deficit and gaps in energy access. Policies, plans, and strategies to ensure grid-connected renewable energy have been put in place, but these measures have proved ineffective. Likewise, there are limited studies that investigate these transition problems, including drivers and enablers from a developing country perspective. This research fills that gap in knowledge by investigating these transition dynamics through a qualitative approach applying the multi-level perspective framework. Thirty-one (31) key energy and non-energy actors were interviewed, and the transcripts thematically analysed. Findings indicate that there is prospect for Nigeria to transform its electricity system. However, there are major deterrents including institutional, infrastructural, incumbent electricity system instability and economic barriers. The paper highlights that there is a level of regime stability/instability that will enable renewable energy development. In addition, practical and policy insights are offered to overcome identified challenges towards accelerating electricity system transformation. Future studies should also explore the degree of instability, stability and change in developing country settings necessary for energy transition to occur. Finally, this paper advances debates in energy transition and socio-technical system studies.

Changing the game: Situating energy citizenship in the Dutch socio-technical landscape

The multilevel perspective (MLP) has made paramount theoretical contributions to transitions studies. However, it has been criticized for weakly considering individual agency. Using the energy transition as a case study, this paper asks how the energy citizenship literature can enhance current understandings of the ways individuals shape socio-technical transitions within the MLP framework. We use extensive interview data to simultaneously examine the cognitive and behavioral dimensions that drive energy citizens’ engagement in energy transitions. Our findings indicate that individuals leverage the landscapes and regimes in different ways, which hold implications for socio-technical transitions. As such, individuality is a key and understudied issue within the MLP framework. The contributions of this paper are twofold. First, it contributes to the MLP framework by shedding light on an additional dimension – i.e., individuals – thereby enriching current knowledge of the dynamics of socio-technical transitions. Second, it uses primary data collected in the Netherlands that is sufficiently granular to take the individuality question to the next level.

Genome assembly, gene content, and plastic gene expression responses to salinity changes in the Brackishwater Clam (Corbicula japonica) from a dynamic estuarine environment

Estuaries are dynamic transition zones between marine and freshwater environments, where salinity varies greatly on spatial and temporal scales. The temporal salinity fluctuations of these habitats require organisms to rapidly regulate ionic concentrations and osmotic pressure to survive in these dynamic conditions. Understanding the extent of plasticity of euryhaline animals is vital for predicting their responses and resilience to salinity change. We generated the first high-resolution genome and transcriptome sequences of C. japonica. In comparison with 11 other molluscan genomes, the C. japonica genome displayed striking expansions of putative neuron-related genes and gene families. The involvement of these genes in the glutamate/GABA-glutamine and glycine cycle suggests a possible contribution to the excitation of neuronal networks, particularly under high salinity conditions. This study contributes to our understanding of mechanisms underlying the rapid responses of estuarine species to changing conditions and raises many intriguing hypotheses and questions for future investigation.

Analysis of complex excitation patterns using Feynman-like diagrams

Many extended chemical and biological systems self-organise into complex patterns that drive the medium behaviour in a non-linear fashion. An important class of such systems are excitable media, including neural and cardiac tissues. In extended excitable media, wave breaks can form rotating patterns and turbulence. However, the onset, sustaining and elimination of such complex patterns is currently incompletely understood. The classical theory of phase singularities in excitable media was recently challenged, as extended lines of conduction block were identified as phase discontinuities. Here, we provide a theoretical framework that captures the rich dynamics in excitable systems in terms of three quasiparticles: heads, tails, and pivots. We propose to call these quasiparticles ‘cardions’. In simulations and experiments, we show that these basic building blocks combine into at least four different bound states. By representing their interactions similarly to Feynman diagrams in physics, the creation and annihilation of vortex pairs are shown to be sequences of dynamical creation, annihilation, and recombination of the identified quasiparticles. We draw such diagrams for numerical simulations, as well as optical voltage mapping experiments performed on cultured human atrial myocytes (hiAMs). Our results provide a new, unified language for a more detailed theory, analysis, and mechanistic insights of dynamical transitions in excitation patterns.