Synchronous State Research Articles

Controlled synchronization of three co-rotating exciters based on a circular distribution in a vibratory system

In this article, an engineering problem of three co-rotating exciters with the circular distribution in a vibrating system is investigated. The dynamical model constructed by the motion differential equations is established. By introducing the small parameter averaged method in the dynamic equation, the synchronization and stability conditions of the electromechanical coupling dynamical model is derived. To illustrate the necessity of the controlling method, the self-synchronization of the vibrating system is firstly analyzed with the theory, numerical simulations and experiments. With the self-synchronization results, it is indicated that the ellipse trajectory which is needed in the industry can’t be realizefd by the self-synchronization motion of the vibrating system. And then, a fuzzy PID controlling method based on the master–slave controlling strategy is introduced in the vibrating system to realize the controlled synchronization. The Lyapunov stability criterion is given to certify the stability of the controlling system. Through some simulations and experiments, the effectiveness of controlled synchronization is illustrated in the discussion. Finally, the present work illuminates the feasibility and practicality for designing some new types of vibrating screens in the industry.

Collective synchronization through noise cancellation.

After decades of study, there are only two known mechanisms to induce global synchronization in a population of oscillators: Deterministic coupling and common forcing. The inclusion of independent noise in these models typically serves to drive disorder, increasing the stability of the incoherent state. Here we show that the reverse is also possible. We propose and analyze a simple general model of purely noise coupled oscillators. In the first explicit choice of noise coupling, we find the linear response around incoherence is identical to that of the paradigmatic Kuramoto model but exhibits binary phase locking instead of full coherence. We characterize the phase diagram, stationary states, and approximate low-dimensional dynamics for the model, revealing the curious behavior of this mechanism of synchronization. In the second minimal case we connect the final synchronized state to the initial conditions of the system.

Noise-induced synchrony of two-neuron motifs with asymmetric noise and uneven coupling.

Synchronous dynamics play a pivotal role in various cognitive processes. Previous studies extensively investigate noise-induced synchrony in coupled neural oscillators, with a focus on scenarios featuring uniform noise and equal coupling strengths between neurons. However, real-world or experimental settings frequently exhibit heterogeneity, including deviations from uniformity in coupling and noise patterns. This study investigates noise-induced synchrony in a pair of coupled excitable neurons operating in a heterogeneous environment, where both noise intensity and coupling strength can vary independently. Each neuron is an excitable oscillator, represented by the normal form of Hopf bifurcation (HB). In the absence of stimulus, these neurons remain quiescent but can be triggered by perturbations, such as noise. Typically, noise and coupling exert opposing influences on neural dynamics, with noise diminishing coherence and coupling promoting synchrony. Our results illustrate the ability of asymmetric noise to induce synchronization in such coupled neural oscillators, with synchronization becoming increasingly pronounced as the system approaches the excitation threshold (i.e., HB). Additionally, we find that uneven coupling strengths and noise asymmetries are factors that can promote in-phase synchrony. Notably, we identify an optimal synchronization state when the absolute difference in coupling strengths is maximized, regardless of the specific coupling strengths chosen. Furthermore, we establish a robust relationship between coupling asymmetry and the noise intensity required to maximize synchronization. Specifically, when one oscillator (receiver neuron) receives a strong input from the other oscillator (source neuron) and the source neuron receives significantly weaker or no input from the receiver neuron, synchrony is maximized when the noise applied to the receiver neuron is much weaker than that applied to the source neuron. These findings reveal the significant connection between uneven coupling and asymmetric noise in coupled neuronal oscillators, shedding light on the enhanced propensity for in-phase synchronization in two-neuron motifs with one-way connections compared to those with two-way connections. This research contributes to a deeper understanding of the functional roles of network motifs that may serve within neuronal dynamics.

Coordinated control and energy management combined with cyberattack identification in multi‐microgrid integrated with hybrid renewable‐storage

AbstractA comprehensive model is developed for coordinated control of voltage‐frequency‐inertia and identifying multiple cyberattacks simultaneously in two microgrids (MGs). The MGs are integrated with solar units, Wind turbine (WT), hybrid supercapacitor‐battery, and fuelcell. The MGs are modelled and controlled for operation under both an island and connected states. In the proposed method, a data centre is designed in which all the electrical and control signals related to the solar, wind, hybrid supercapacitor‐battery, and Fuel cell (FC) are collected, evaluated, and matched. The data centre comprises the following blocks: voltage‐frequency control, inertia control of WT, and identification of false data injection (FDI) cyberattacks on frequency, power, power/frequency, and voltage. The technique used in this article to identify FDI attacks is based on the real‐time method coupled with logical comparisons conducted in the time domain. This methodology provides prompt and precise detection, allowing for timely preventive measures and strategic responses. After FDI attacks occur, the implemented control system effectively manages and regulates the voltage and frequency at the desired levels, efficiently differentiating between ordinary functioning, faulty states, and potential cyber‐attacks. The unhealthy MG can transfer its load to the healthy MG for safety reasons. The healthy MG is then connected to the external grid and the synchronisation conditions are checked by the proposed control system. The results of the non‐linear simulation performed in MATLAB‐Simulink software confirm that the proposed model successfully operates and controls all resources (i.e. solar/wind/battery/FC), regulates the voltage/frequency under various loading conditions, and identifies FDI cyberattacks.

ICOE: A Lightweight Group-Consensus-Based Off-Chain Execution Model for Smart Contract-Based Industrial Applications

Programmable smart contracts facilitate the application of blockchain to many areas of industry, e.g., supply chains, energy, and healthcare. The off-chain execution model for blockchain smart contracts is a promising approach to achieve scalability for industrial applications, which executes each smart contract in one of the small-scale consensus groups. However, previous work based on such a model cannot efficiently handle cross-group contract transactions that involve multiple cross-group invocations between smart contracts, because of the heavyweight state synchronization and repeated executions. In this paper, we propose <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICOE</small> , a lightweight group-consensus based off-chain execution model for cross-group contract transactions without the need of state synchronization and duplicate executions, and also prove its correctness. The key novelty of our <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICOE</small> is to let the invoked smart contract only executed in its residing group and only return the execution result to the invoking smart contract, while leveraging the two-phase commit(2PC) protocol guarantees consistent commits across multiple groups within the same invoking smart contract transaction. We implement <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICOE</small> and extensive experimental results show that our <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ICOE</small> achieves a 14x improvement of throughput on average compared to the state-of-the-art model.

Cluster synchronization in a semiconductor laser

Cluster synchronization is a general phenomenon in a network of non-locally coupled oscillators. Here, we show that cluster synchronization occurs in semiconductor lasers, where the beat notes between the pairs of adjacent longitudinal modes of the laser cavity constitute a collection of coupled phase oscillators. Non-local coupling arises from the standing-wave nature of the cavity with finite mirror reflectivities, which we can actively control. Varying the coupling, we can bring the laser into a state of cluster synchronization where the two beat note families oscillate at two distinct collective frequencies. Using a coherent beat note detection technique, we show that the beat notes within the two families are synchronized in the opposite configurations—in-phase and antiphase.

Effect of higher-order interactions on chimera states in two populations of Kuramoto oscillators.

We investigate the effect of the fraction of pairwise and higher-order interactions on the emergent dynamics of the two populations of globally coupled Kuramoto oscillators with phase-lag parameters. We find that the stable chimera exists between saddle-node and Hopf bifurcations, while the breathing chimera lives between Hopf and homoclinic bifurcations in the two-parameter phase diagrams. The higher-order interaction facilitates the onset of the bifurcation transitions at a much lower disparity between the inter- and intra-population coupling strengths. Furthermore, the higher-order interaction facilitates the spread of breathing chimera in a large region of the parameter space while suppressing the spread of the stable chimera. A low degree of heterogeneity among the phase-lag parameters promotes the spread of both stable chimera and breathing chimera to a large region of the parameter space for a large fraction of the higher-order coupling. In contrast, a large degree of heterogeneity is found to decrease the spread of both chimera states for a large fraction of the higher-order coupling. A global synchronized state is observed above a critical value of heterogeneity among the phase-lag parameters. We have deduced the low-dimensional evolution equations for the macroscopic order parameters using the Ott-Antonsen Ansatz. We have also deduced the analytical saddle-node and Hopf bifurcation curves from the evolution equations for the macroscopic order parameters and found them to match with the bifurcation curves obtained using the software XPPAUT and with the simulation results.

Rapid changes in synchronizability in conductance-based neuronal networks with conductance-based coupling.

Real neurons connect to each other non-randomly. These connectivity graphs can potentially impact the ability of networks to synchronize, along with the dynamics of neurons and the dynamics of their connections. How the connectivity of networks of conductance-based neuron models like the classical Hodgkin-Huxley model or the Morris-Lecar model impacts synchronizability remains unknown. One powerful tool to resolve the synchronizability of these networks is the master stability function (MSF). Here, we apply and extend the MSF approach to networks of Morris-Lecar neurons with conductance-based coupling to determine under which parameters and for which graphs the synchronous solutions are stable. We consider connectivity graphs with a constant non-zero row sum, where the MSF approach can be readily extended to conductance-based synapses rather than the more well-studied diffusive connectivity case, which primarily applies to gap junction connectivity. In this formulation, the synchronous solution is a single, self-coupled, or "autaptic" neuron. We find that the primary determining parameter for the stability of the synchronous solution is, unsurprisingly, the reversal potential, as it largely dictates the excitatory/inhibitory potential of a synaptic connection. However, the change between "excitatory" and "inhibitory" synapses is rapid, with only a few millivolts separating stability and instability of the synchronous state for most graphs. We also find that for specific coupling strengths (as measured by the global synaptic conductance), islands of synchronizability in the MSF can emerge for inhibitory connectivity. We verified the stability of these islands by direct simulation of pairs of neurons coupled with eigenvalues in the matching spectrum.

Kaluza-Klein monopole with scalar hair

We construct a new family of rotating black holes with scalar hair and a regular horizon of spherical topology, within five dimensional (d = 5) Einstein’s gravity minimally coupled to a complex, massive scalar field doublet. These solutions represent generalizations of the Kaluza-Klein monopole found by Gross, Perry and Sorkin, with a twisted S1 bundle over a four dimensional Minkowski spacetime being approached in the far field. The black holes are described by their mass, angular momentum, tension and a conserved Noether charge measuring the hairiness of the configurations. They are supported by rotation and have no static limit, while for vanishing horizon size, they reduce to boson stars. When performing a Kaluza-Klein reduction, the d = 5 solutions yield a family of d = 4 spherically symmetric dyonic black holes with gauged scalar hair. This provides a link between two seemingly unrelated mechanisms to endow a black hole with scalar hair: the d = 5 synchronization condition between the scalar field frequency and the event horizon angular velocity results in the d = 4 resonance condition between the scalar field frequency and the electrostatic chemical potential.

Neurophysiological markers of asymmetric emotional contagion: implications for organizational contexts.

Emotions play a vital role within organizations, impacting various crucial aspects of work such as job satisfaction, performance, and employee well-being. Understanding how emotional states spread in organizational settings is therefore essential. Recent studies have highlighted that a leader's emotional state can influence their followers, with significant consequences on job performance. Leaders thus possess the ability to influence their employees' psychological state and, consequently, their well-being. However, the biological underpinnings of emotional contagion from leaders to followers remain unexplored. The field of interpersonal (neuro)physiology, which involves recording brain and peripheral activity of multiple individuals during interactions, holds great potential for investigating this phenomenon. Analyzing the time-lagged synchronization of neurophysiological activity during interactions may serve as a measure of the leader's influence on their followers in organizational contexts. In this "mini review," we examine empirical studies that have employed interpersonal (neuro)physiology to quantify the asymmetrical contagion of emotions in different contexts. Asymmetrical contagion was operationalized as the unidirectional influence exerted by one individual (i.e., the "sender") to another one (i.e., the "receiver"), whereby the receiver's state can be predicted by the sender's one. The reviewed literature reveals that delayed synchronization of physiological states is a widespread phenomenon that may underpin the transmission of emotions. These findings have significant implications for various aspects of organizational life, including leader-to-employee communication, and could drive the development of effective leadership training programs. We propose that Organizational Neuroscience may benefit from including interpersonal neurophysiology in its methodological toolkit for laboratory and field studies of leader-follower dynamics.

Function projective Mittag-Leffler synchronization of non-identical fractional-order neural networks

This article investigates the function projective Mittag-Leffler synchronization (FPMLS) between non-identical fractional-order neural networks (FONNs). The stability analysis is carried out using an existing lemma for the Lyapunov function in the FONN systems. Based on the stability theorem of FONN, a non-linear controller is designed to achieve FPMLS. Moreover, global Mittag-Leffler synchronization (GMLS) is investigated in the context of other synchronization techniques, such as projective synchronization (PS), anti-synchronization (AS) and complete synchonization (CS). Using the definition of the Caputo derivative, the Mittag-Leffler function and the Lyapunov stability theory, some stability results for the FPMLS scheme for FONN are discussed. Finally, the proposed technique is applied to a numerical example to validate its efficiency and the unwavering quality of the several applied synchronization conditions.

Dynamic theory and experimental testing in ipsilateral offset dual-motor excitation system

This paper addresses unbalanced trajectories of dual-motor vibrating screens by proposing a dynamic theory and experimental testing. First, based on the Lagrange equation, the dynamic model of ipsilateral offset dual-motor excitation system is established. Subsequently, the steady response is worked out by solving the differential equation of motion of the vibrating body. Then, the synchronization condition and synchronization stability criterion of the system are determined employing the small parameter method and the Routh–Hurwitz criterion. Numerical analysis methods are given to reveal the relationship between structural parameters and synchronization characteristics of the vibration system. Moreover, an mechanical–electric coupling model is developed to study dynamic characteristics. The results demonstrate that synchronization condition can be described with capture torque and difference of output torque between motors. The synchronization ability is enhanced by improving installation distance of the motors. Additionally, increasing angle β or decreasing angle θ of the motors is in favor of optimization of centroid trajectory; swing oscillation of the box can be controlled by adjusting the main inclination angle of motors; in such a condition, equilibrium of motion trajectory of system is enhanced. Finally, the validity method for designing vibrating screen is verified through theoretical calculations, simulation analysis, and experiments.

The absence of one's intimate partner promotes dyadic competition through enhanced interbrain synchronization between opponents.

Competition is a common occurrence in life, but the influence of intimate relationships on people's competitiveness remains unknown. Grounded in Darwin's theory of sexual selection, this study utilized EEG hyperscanning technology to investigate the influence of the presence of romantic partners and the gender of competitors on the interbrain synchronization of female individuals during competitive contexts. The research results showed that in competitive interactions, there was a significant increase in Theta and Alpha frequency band activity between females and their competitors. Interbrain synchronization was strongest when their partners were not nearby and females competed with same gender competitors. The research results indicate that intimate companionship has an impact on the early alertness and late cognitive execution mechanisms of female individuals in competition, and due to intimate relationships, females pay more attention to same-gender competitors. This study demonstrates that the presence of intimate partners can affect a female's competitive state and brain synchronization with opponents of different genders, improving the theoretical explanation of intimate relationships and competitive interactions.

Synchronization of Turing patterns in complex networks of reaction–diffusion systems set in distinct domains

We present an innovative complex network of reaction–diffusion systems set in distinct domains, with boundary couplings. The complex network models the evolution of interacting populations living in a heterogeneous and fragmented habitat, whose biological individuals migrate from one patch to another. In our model, the displacements of individuals are described by mixed boundary couplings, involving both the Neumann and Robin boundary conditions, which improve the modeling of migrations by point-wise couplings. We investigate the cases of diffusion in isotropic and anisotropic habitats and establish original sufficient conditions of synchronization in this complex network model, for complete graphs, cyclic graphs and rings of nearest neighbors. In parallel, we apply our theoretical framework to a nonlinear predator–prey model with Leslie–Gower-type functional response and explore numerically the emergence of synchronization on heterogeneous Turing patterns.

Model of Satellite Communication Channel Functioning under Conditions of Episodic Synchronization with Pulse Interference Flows

The article investigates the effect of pulse interference on information reception in conditions of episodic synchronization of frames of the physical level of a satellite communication channel with streams of radio pulses of unintended interference. An analytical model of the influence of pulse interference on the reception of information in a satellite communication channel under conditions of episodic synchronization of physical-level frames with pulse interference streams is proposed. Using the example of the DVB family of standards, the combined effect of noise and unintended impulse interference on the conditional error probabilities when receiving a synchro group, the service part of the header and the information part of the frame is shown. Estimates of the average number of frames of the physical level for the duration of the interval of episodic synchronization, the number of intervals of episodic synchronization and the proportion of elementary parcels in the frame exposed to interference, depending on the duration of the pulse interference, are given. It is shown that there are such relations between the duration of the interference pulse and the continuity of the sequence, in which the phenomenon of the episodic synchronization of physical-level frames with the flow of pulse interference has a significant impact on the functioning of the satellite communication channel. The dependences of the probability of erroneous reception of a frame of the physical level of a satellite communication channel on the signal-to-interference ratio at the fixed signal-to-noise ratio and on the duration of the interference pulse are obtained. It has been found that at high signal-to-noise ratios and the duration of the interference correlated with the duration of the service part of the frame, but significantly less than the duration of the frame, the probability of erroneous reception of the frame may be higher than at lower signal-to-noise ratios due to errors when receiving the service part of the frames.

Tradeoff analysis between time cost and energy cost for fixed-time synchronization of discontinuous neural networks

This article focuses on the tradeoff analysis between time and energy costs for fixed-time synchronization (FXTS) of discontinuous neural networks (DNNs) with time-varying delays and mismatched parameters. First, a more comprehensive lemma is systematically established to study fixed-time stability, which is less conservative than those in most current results. Besides, theoretical proof has proven that the upper bounds of the settling time (ST) in this article are more accurate compared to existing results. Second, on the grounds of the new fixed-time stability lemma, fixed-time synchronization problem for discontinuous neural networks with time-varying delays and mismatched parameters is explored, and sufficient conditions for fixed-time synchronization are obtained. Further, the upper bounds of energy cost during the synchronization process are estimated. Third, in order to achieve a balance between time cost and energy cost, the genetic algorithm is utilized to find the satisfactory control parameter. Finally, a numerical example is provided to verify the theoretical analysis’s correctness and the control mechanism’s feasibility.

Correlation of strontium anharmonicity with charge-lattice dynamics of the apical oxygens and their coupling to cuprate superconductivity

By means of Cu K edge x-ray absorption spectra of overdoped high-pressure oxygenated superconducting and , we demonstrate a remarkably strong three way correlation between the superconductivity and the local dynamics of their highly anharmonic Cu–Sr and Cu-apical O pairs. We model the latter as aspects of the Internal Quantum Tunneling Polarons (IQTPs) that give the two-site distributions in extended x-ray absorption fine structure and inelastic pair distribution function measurements. This finding obviates the common assumption that the universal Ba/Sr-apical O dielectric layer, far from only maintaining the separation of charges between the charge reservoir and the conducting domains, plays an unexpectedly active role in the unusual electronic properties of cuprate superconductors. Furthermore, we investigate the effects of the dynamic structure associated with these pairs by means of the exact diagonalization of a prototype Hamiltonian based on a six-atom cluster, with two neighboring Cu-apical O pairs bridged by an anharmonically coupled Sr atom and a planar O atom. In terms of the Kuramoto model for synchronization, these calculations show a first order phase transition, driven by anharmonicity, to a synchronized state of the IQTPs, in which a fraction of the charge originally confined to the apical O sites is transferred onto the planar O in the superconducting plane. This combination of experimental results and theory demonstrates that the Ba/Sr-apical O layer of cuprates most likely plays an important role in high temperature superconductivity via its collective charge dynamics.

Changing torque-force synchronization condition for abrasive particle improves material removal during silicon carbide abrasive machining

Silicon carbide (SiC) is extremely hard and brittle, posing challenges for traditional abrasive machining. This study used molecular dynamics simulations to investigate synchronous versus asynchronous force-torque effects on SiC abrasive machining. Multi-grit diamond abrasion of 4H-SiC was modeled by applying controlled sinusoidal forces and torques. Asynchronous force-torque increased material removal rates up to 2X versus synchronous conditions by promoting particle agglomeration and enabling trapped particles to contribute. However, asynchronous operation also produced higher surface roughness and subsurface cracking from greater penetration. The alternating forces generated larger stresses that may have driven more plastic deformation and brittle fracture. The study provided atomic-scale insights into force-torque effects, establishing guidelines to potentially enhance efficiency through asynchronous operation despite drawbacks.

Employment of Synchronized Chaotic SHA256 Random Number Generators along with their Application in the Field of Image Encryption

Background: Current work is associated with the deployment of synchronized chaotic Secure Hash Algorithm (SHA256) random number generators along with their application in image encryption. Methods: This study aimed to design a perfect communication system to encrypt and decrypt the images via image processing. We introduced a new sliding mode scheme for master-slave fourdimensional (4D) Lorenz-Stenflo systems to deal with the synchronization problem. Then, a new synchronized dynamic secure hash algorithm (SHA-256) was implemented to generate the dynamic random numbers. Results: An image encryption and decryption mechanism was implemented by using synchronized chaotic master-slave systems corresponding to the generated hash values. Here, the master systems were used for encryption, and the slave systems were responsible for the decryption mechanism. The complete design of this paper was implemented in a Python environment. Conclusion: The demonstration of simulation results includes the state responses, strange attractors, and synchronization error responses of master-slave chaotic systems with appropriate switching functions and control input. conclusion: An image encryption and decryption mechanism has been implemented by using synchronized chaotic master-slave systems corresponding to the generated hash values other: The complete design of this paper has been implemented on python environment

Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control

In this paper, we investigate the exponential synchronization problem for multi-link and multi-delayed inertial neural networks with Markov jump (MMDINNMJ) using an aperiodically intermittent adaptive control strategy. Different from most research on inertial neural networks, we take multi-link, multi-delay and Markov jump into account. The obstacle caused by the coexistence of Markov jump and multi-delay is avoided by using the delayed integral method while considering the exponential synchronization of MMDINNMJ. Additionally, under graph theory, Lyapunov stability theory and the developed control scheme, some novel sufficient conditions for synchronization at exponential rate in pth (p>0) moment of underlying networks are determined, which are strongly related to multi-link topological structure, time delay, and Markov jump. Finally, two examples are given to demonstrate the viability of the theoretical conclusions.