General Oscillator Research Articles

Kardar-Parisi-Zhang universality class in the synchronization of oscillator lattices with time-dependent noise.

Systems of oscillators subject to time-dependent noise typically achieve synchronization for long times when their mutual coupling is sufficiently strong. The dynamical process whereby synchronization is reached can be thought of as a growth process in which an interface formed by the local phase field gradually roughens and eventually saturates. Such a process is here shown to display the generic scale invariance of the one-dimensional Kardar-Parisi-Zhang universality class, including a Tracy-Widom probability distribution for phase fluctuations around their mean. This is revealed by numerical explorations of a variety of oscillator systems: rings of generic phase oscillators and rings of paradigmatic limit-cycle oscillators, like Stuart-Landau and van der Pol. It also agrees with analytical expectations derived under conditions of strong mutual coupling. The nonequilibrium critical behavior that we find is robust and transcends the details of the oscillators considered. Hence, it may well be accessible to experimental ensembles of oscillators in the presence of, e.g., thermal noise.

Energy-based theory of autoresonance in chains of coupled damped-driven generic oscillators.

An energy-based theory of autoresonance in driven dissipative chains of coupled generic oscillators is discussed on the basis of a variational principle concerning the energy functional. The theory is applied to chains of delayed Duffing-Ueda oscillators and the equationsthat together govern the autoresonance forces and solutions are derived and solved analytically for generic values of parameters and initial conditions, including the case of quenched time-delay disorder. Remarkably, the presence of retarded potentials with time-delayed feedback drastically modify the autoresonance scenario preventing the growth of the energy oscillation over specific regions of the parameter space. Additionally, effective harmonic forces with a slowly varying frequency are derived from the exact autoresonant excitations and the effectiveness of the theory is demonstrated at suppressing the chaos induced by homogeneous periodic excitations in such oscillator chains. Numerical experiments confirmed all the theoretical predictions.

Temperature compensation through kinetic regulation in biochemical oscillators

Nearly all circadian clocks maintain a period that is insensitive to temperature changes, a phenomenon known as temperature compensation (TC). Yet, it is unclear whether there is any common feature among different systems that exhibit TC. From a general timescale invariance, we show that TC relies on the existence of certain period-lengthening reactions wherein the period of the system increases strongly with the rates in these reactions. By studying several generic oscillator models, we show that this counterintuitive dependence is nonetheless a common feature of oscillators in the nonlinear (far-from-onset) regime where the oscillation can be separated into fast and slow phases. The increase of the period with the period-lengthening reaction rates occurs when the amplitude of the slow phase in the oscillation increases with these rates while the progression speed in the slow phase is controlled by other rates of the system. The positive dependence of the period on the period-lengthening rates balances its inverse dependence on other kinetic rates in the system, which gives rise to robust TC in a wide range of parameters. We demonstrate the existence of such period-lengthening reactions and their relevance for TC in all four model systems we considered. Theoretical results for a model of the Kai system are supported by experimental data. A study of the energy dissipation also shows that better TC performance requires higher energy consumption. Our study unveils a general mechanism by which a biochemical oscillator achieves TC by operating in parameter regimes far from the onset where period-lengthening reactions exist.

High-order phase reduction for coupled 2D oscillators.

Phase reduction is a general approach to describe coupled oscillatory units in terms of their phases, assuming that the amplitudes are enslaved. The coupling should be small for such reduction, but one also expects the reduction to be valid for finite coupling. This paper presents a general framework, allowing us to obtain coupling terms in higher orders of the coupling parameter for generic two-dimensional oscillators and arbitrary coupling terms. The theory is illustrated with an accurate prediction of Arnold's tongue for the van der Pol oscillator exploiting higher-order phase reduction.

Limits of entrainment of circadian neuronal networks.

Circadian rhythmicity lies at the center of various important physiological and behavioral processes in mammals, such as sleep, metabolism, homeostasis, mood changes, and more. Misalignment of intrinsic neuronal oscillations with the external day-night cycle can disrupt such processes and lead to numerous disorders. In this work, we computationally determine the limits of circadian synchronization to external light signals of different frequency, duty cycle, and simulated amplitude. Instead of modeling circadian dynamics with generic oscillator models (e.g., Kuramoto-type), we use a detailed computational neuroscience model, which integrates biomolecular dynamics, neuronal electrophysiology, and network effects. This allows us to investigate the effect of small drug molecules, such as Longdaysin, and connect our results with experimental findings. To combat the high dimensionality of such a detailed model, we employ a matrix-free approach, while our entire algorithmic pipeline enables numerical continuation and construction of bifurcation diagrams using only direct simulation. We, thus, computationally explore the effect of heterogeneity in the circadian neuronal network, as well as the effect of the corrective therapeutic intervention of Longdaysin. Last, we employ unsupervised learning to construct a data-driven embedding space for representing neuronal heterogeneity.

Synchronization and stability in automotive transportation networks

AbstractThe aim of this study was to analyze and evaluate synchronization and stability issues for the planning, operation, and control of processes in automotive transportation networks. We modeled transportation networks by using a coupled oscillator network based on a modified Kuramoto model. Each transport process was mapped as a phase oscillator indicating the transport time, period, and delay. The method could be applied to complex networks where it has not been possible to find analytical solutions. The novel generic oscillator approach was then applied to two transport topologies, namely, milk‐run and just‐in‐sequence transport, based on real‐world problems from a German car manufacturer. We conducted a detailed study of the parameter regions where different synchronization regimes occurred and investigated how the topology influenced the stability and dynamic behavior of transport networks. In particular, we focused on how transport period offsets and transport delays affected synchronous states. We showed that by the introduction of a transport synchronization matrix, the synchronization states in a transport network could be represented in a compact and comprehensive manner. Moreover, thresholds for round‐trip stability could be calculated by analyzing the phase decoupling of a milk‐run. These results were used for the vehicle route planning of milk‐runs with synchronization constraints. Furthermore, the influence of the time delay of a track and trace system on the transport synchronization was analyzed. Finally, for the subsequent investigation of a just‐in‐sequence transport network, we showed how an adaptive control mechanism could re‐synchronize an out‐of‐tune delivery process.

Local Oscillator Phase Noise Impact on M-ary Modulation Schemes

This paper presents the impact of a local oscillator phase noise on digital modulation schemes based on bit error rate and error vector magnitude. The adopted methodology enables base band metrics estimation which is dependent of a specific communication standard. A generic local oscillator phase noise model is presented to evaluate the impact of different phase noise values on error vector magnitude and bit error rate. For a phase noise of -65dBc @ 1kHz the error vector magnitude changes from 7% to 12.8%. Increasing the modulation order leads to bit error rate increment for the same phase noise value.

Explosive Transition in Coupled Oscillators Through Mixed Attractive-Repulsive Interactions

The emergence of many fascinating dynamic behaviors is affected by more than one interaction among the elements or cells in a network. In fact, the concurrence and competition of different types of effects among subsystems show a strong connection to the dynamic transition process between oscillation patterns. Here, a network of generic oscillators with mixed attractive-repulsive couplings is introduced to demonstrate the transition from oscillatory states to stationary equilibria, specifically for van der Pol oscillators and Lorenz oscillators. Through the observation of the normalized amplitude changing with the coupling strength, the sudden and irreversible transition appears in both systems, which has a close relation to the mutual repulsion on coupled oscillators. Whereas, for coupled van der Pol oscillators, three typical transition scenarios are found by varying the weight ratio of these two couplings, while the Lorenz system shows only one transition mode no matter how the weight ratio changes. Besides, in the cases of explosive transitions, the coexistence areas of oscillatory and death states also reveal a distinct manifestation for periodic and chaotic systems. The details of theoretical critical transition points on the first-order phase transition are also obtained. Our results pave a new way to control the explosive phenomenon, which is crucial to explain the sudden oscillation quenching and the coexistence of oscillatory and stationary states in biological as well as chemical systems.

Non-quantum chirality in a driven Brusselator

We report the discovery of non-quantum chirality in the a periodically driven Brusselator. In contrast to standard chirality from quantum contexts, this novel type of chirality is governed by rate equations, namely by purely classical equations of motion. The Brusselator chirality was found by computing high-resolution phase diagrams depicting the number of spikes, local maxima, observed in stable periodic oscillations of the Brusselator as a function of the frequency and amplitude of the external drive. We also discuss how to experimentally observe non-quantum chirality in generic oscillators governed by nonlinear sets of rate equations.

Considerations on prediction horizon and dissipative losses for wave energy converters

The non-causal optimal control law for wave energy converters leads to a requirement of predicting waves and wave forces over a future horizon. Using examples of generic body shapes and oscillation modes, the authors show through computations of the velocity reference trajectory how the length of prediction horizon required to reach the maximum power output depends on the level of dissipative losses in the conversion chain . The sensitivity to noise is discussed, and so is the use of filtering to improve performance when the available prediction horizon is short or predictions are inaccurate . Considerations are also made for amplitude constraints and other effects encountered in a real system. With realistic assumptions for the level of dissipative losses, results indicate that the prediction horizon needed to approach the maximum achievable power output for real systems ranges from only a few seconds up to about half a wave period, which is shorter than that has generally been assumed earlier.

Modelling oscillations in the supply chain: the case of a just-in-sequence supply process from the automotive industry

Pervasive and ubiquitous oscillations, mapping the repetitive variation in time of a specific state, are well known as abundant phenomena in research and practice. Motivated by the success of oscillators in the modelling, analysis and control of dynamical systems, we developed a related approach for the dynamic description of supply chains. This paper aims to introduce a generic oscillator model for supply chains by the original application of oscillator equations. Therefore an established oscillator model for deductive modelling of supply chain echelons is used. With the help of coupled van der Pol oscillators, the dynamical interaction of an inventory system is described and applied to a real-life supply process in automotive industry. According to its reductionist approach only two differential equations are used to analyse a Just-in-Sequence supply process in car industry. Based on the fact that any oscillatory state can be reduced to the phase of the oscillation (phase reduction), a phase space map is generated. This compact visual reference of the supply process can act as the quantitative basis for an adaptive control mechanism during its operation. By delaying or accelerating the inventory oscillations of the supplier stock a detuned coupled supply process can be re-synchronised without changing the amplitude. An additional analysis of Hilbert transform is applied to determine the boundaries of phase-locking between the inventory oscillation phases, where the instantaneous phases are bounded. Furthermore parameters of the synchronisation threshold and the transient phases between synchronous and non-synchronous regimes have been investigated, supported by an Arnold tongue representation. The investigations show that with the help of a generic oscillatory model it is possible to measure and quantify phenomena of inventory dynamics in supply chains. Especially the analysis of synchronisation phenomena with the help of phase space and Arnold tongue representations foster developments of performance measurement in supply chain management.

Perturbations both trigger and delay seizures due to generic properties of slow-fast relaxation oscillators.

The mechanisms underlying the emergence of seizures are one of the most important unresolved issues in epilepsy research. In this paper, we study how perturbations, exogenous or endogenous, may promote or delay seizure emergence. To this aim, due to the increasingly adopted view of epileptic dynamics in terms of slow-fast systems, we perform a theoretical analysis of the phase response of a generic relaxation oscillator. As relaxation oscillators are effectively bistable systems at the fast time scale, it is intuitive that perturbations of the non-seizing state with a suitable direction and amplitude may cause an immediate transition to seizure. By contrast, and perhaps less intuitively, smaller amplitude perturbations have been found to delay the spontaneous seizure initiation. By studying the isochrons of relaxation oscillators, we show that this is a generic phenomenon, with the size of such delay depending on the slow flow component. Therefore, depending on perturbation amplitudes, frequency and timing, a train of perturbations causes an occurrence increase, decrease or complete suppression of seizures. This dependence lends itself to analysis and mechanistic understanding through methods outlined in this paper. We illustrate this methodology by computing the isochrons, phase response curves and the response to perturbations in several epileptic models possessing different slow vector fields. While our theoretical results are applicable to any planar relaxation oscillator, in the motivating context of epilepsy they elucidate mechanisms of triggering and abating seizures, thus suggesting stimulation strategies with effects ranging from mere delaying to full suppression of seizures.

Emergent rhythms in coupled nonlinear oscillators due to dynamic interactions.

The role of a new form of dynamic interaction is explored in a network of generic identical oscillators. The proposed design of dynamic coupling facilitates the onset of a plethora of asymptotic states including synchronous states, amplitude death states, oscillation death states, a mixed state (complete synchronized cluster and small amplitude desynchronized domain), and bistable states (coexistence of two attractors). The dynamical transitions from the oscillatory to the death state are characterized using an average temporal interaction approximation, which agrees with the numerical results in temporal interaction. A first-order phase transition behavior may change into a second-order transition in spatial dynamic interaction solely depending on the choice of initial conditions in the bistable regime. However, this possible abrupt first-order like transition is completely non-existent in the case of temporal dynamic interaction. Besides the study on periodic Stuart-Landau systems, we present results for the paradigmatic chaotic model of Rössler oscillators and the MacArthur ecological model.

Generative Embeddings of Brain Collective Dynamics Using Variational Autoencoders.

We consider the problem of encoding pairwise correlations between coupled dynamical systems in a low-dimensional latent space based on few distinct observations. We use variational autoencoders (VAEs) to embed temporal correlations between coupled nonlinear oscillators that model brain states in the wake-sleep cycle into a two-dimensional manifold. Training a VAE with samples generated using two different parameter combinations results in an embedding that encodes the repertoire of collective dynamics, as well as the topology of the underlying connectivity network. We first follow this approach to infer the trajectory of brain states measured from wakefulness to deep sleep from the two end points of this trajectory; then, we show that the same architecture was capable of representing the pairwise correlations of generic Landau-Stuart oscillators coupled by complex network topology.

Complex interplay between spectral harmonicity and different types of cross-frequency couplings in nonlinear oscillators and biologically plausible neural network models.

Cross-frequency coupling (CFC) refers to the nonlinear interaction between oscillations in different frequency bands, and it is a rather ubiquitous phenomenon that has been observed in a variety of physical and biophysical systems. In particular, the coupling between the phase of slow oscillations and the amplitude of fast oscillations, referred as phase-amplitude coupling (PAC), has been intensively explored in the brain activity recorded from animals and humans. However, the interpretation of these CFC patterns remains challenging since harmonic spectral correlations characterizing nonsinusoidal oscillatory dynamics can act as a confounding factor. Specialized signal processing techniques are proposed to address the complex interplay between spectral harmonicity and different types of CFC, not restricted only to PAC. For this, we provide an in-depth characterization of the time locked index (TLI) as a tool aimed to efficiently quantify the harmonic content of noisy time series. It is shown that the proposed TLI measure is more robust and outperforms traditional phase coherence metrics (e.g., phase locking value, pairwise phase consistency) in several aspects. We found that a nonlinear oscillator under the effect of additive noise can produce spurious CFC with low spectral harmonic content. On the other hand, two coupled oscillatory dynamics with independent fundamental frequencies can produce true CFC with high spectral harmonic content via a rectification mechanism or other post-interaction nonlinear processing mechanisms. These results reveal a complex interplay between CFC and harmonicity emerging in the dynamics of biologically plausible neural network models and more generic nonlinear and parametric oscillators. We show that, contrary to what is usually assumed in the literature, the high harmonic content observed in nonsinusoidal oscillatory dynamics is neither a sufficient nor necessary condition to interpret the associated CFC patterns as epiphenomenal. There is mounting evidence suggesting that the combination of multimodal recordings, specialized signal processing techniques, and theoretical modeling is becoming a required step to completely understand CFC patterns observed in oscillatory rich dynamics of physical and biophysical systems.

Thermodynamic cost of synchronizing a population of beating cilia

Synchronization among arrays of beating cilia is one of the emergent phenomena in biological processes at mesoscopic scales. Strong inter-ciliary couplings modify the natural beating frequencies, ω, of individual cilia to produce a collective motion that moves around a group frequency ω m. Here we study the thermodynamic cost of synchronizing cilia arrays by mapping their dynamics onto a generic phase oscillator model. The model suggests that upon synchronization the mean heat dissipation rate is decomposed into two contributions, dissipation from each cilium’s own natural driving force and dissipation arising from the interaction with other cilia, the latter of which can be interpreted as the one produced by a potential with a time-dependent protocol in the framework of our model. The spontaneous phase-synchronization of beating dynamics of cilia induced by strong inter-ciliary coupling is always accompanied with a significant reduction of dissipation for the cilia population, suggesting that organisms as a whole expend less energy by attaining a temporal order. At the level of individual cilia, however, a population of cilia with |ω| < ω m expend a greater amount of energy upon synchronization.

Primordial power spectra for curved inflating universes

Exact numerical primordial primordial power spectra are computed and plotted for the for the best-fit Planck 2018 curved universe parameters. It is found that the spectra have generic cut-offs and oscillations within the observable window for the level of curvature allowed by current CMB measurements and provide a better fit to current data. Derivations for the Mukhanov-Sasaki equation for curved universes are presented and analysed, and theoretical implications for the quantum and classical initial conditions for inflation are discussed within the curved regime.

Multi-level quantum Rabi model for anharmonic vibrational polaritons.

We propose a cavity QED approach to describe light-matter interaction of an infrared cavity field with an anharmonic vibration of a single nonpolar molecule. Starting from a generic Morse oscillator potential with quantized nuclear motion, we derive a multilevel quantum Rabi model to study vibrational polaritons beyond the rotating-wave approximation. We analyze the spectrum of vibrational polaritons in detail and compare it with available experiments. For high excitation energies, the system exhibits a dense manifold of polariton level crossings and avoided crossings as the light-matter coupling strength and cavity frequency are tuned. We also analyze polariton eigenstates in nuclear coordinate space. We show that the bond length of a vibrational polariton at a given energy is never greater than the bond length of a Morse oscillator with the same energy. This type of polariton bond strengthening occurs at the expense of the creation of virtual infrared cavity photons and may have implications in chemical reactivity of polariton states.

Position representation of effective electron-electron interactions in solids

An essential ingredient in many model Hamiltonians, such as the Hubbard model, is the effective electron-electron interaction $U$, which enters as matrix elements in some localized basis. These matrix elements provide the necessary information in the model, but the localized basis is incomplete for describing $U$. We present a systematic scheme for computing the manifestly basis-independent dynamical interaction in position representation, $U({\bf r},{\bf r}';\omega)$, and its Fourier transform to time domain, $U({\bf r},{\bf r}';\tau)$. These functions can serve as an unbiased tool for the construction of model Hamiltonians. For illustration we apply the scheme within the constrained random-phase approximation to the cuprate parent compounds La$_2$CuO$_4$ and HgBa$_2$CuO$_4$ within the commonly used 1- and 3-band models, and to non-superconducting SrVO$_{3}$ within the $t_{2g}$ model. Our method is used to investigate the shape and strength of screening channels in the compounds. We show that the O 2$p_{x,y}-$Cu 3$d_{x^2-y^2}$ screening gives rise to regions with strong attractive static interaction in the minimal (1-band) model in both cuprates. On the other hand, in the minimal ($t_{2g}$) model of SrVO$_3$ only regions with a minute attractive interaction are found. The temporal interaction exhibits generic damped oscillations in all compounds, and its time-integral is shown to be the potential caused by inserting a frozen point charge at $\tau=0$. When studying the latter within the three-band model for the cuprates, short time intervals are found to produce a negative potential.

Optimal Noise-Canceling Networks.

Natural and artificial networks, from the cerebral cortex to large-scale power grids, face the challenge of converting noisy inputs into robust signals. The input fluctuations often exhibit complex yet statistically reproducible correlations that reflect underlying internal or environmental processes such as synaptic noise or atmospheric turbulence. This raises the practically and biophysically relevant question of whether and how noise filtering can be hard wired directly into a network's architecture. By considering generic phase oscillator arrays under cost constraints, we explore here analytically and numerically the design, efficiency, and topology of noise-canceling networks. Specifically, we find that when the input fluctuations become more correlated in space or time, optimal network architectures become sparser and more hierarchically organized, resembling the vasculature in plants or animals. More broadly, our results provide concrete guiding principles for designing more robust and efficient power grids and sensor networks.