Dynamical Systems Point Of View Research Articles

New cluster algebras from old: integrability beyond Zamolodchikov periodicity

Abstract We consider discrete dynamical systems obtained as deformations of mutations in cluster algebras associated with finite-dimensional simple Lie algebras. The original (undeformed) dynamical systems provide the simplest examples of Zamolodchikov periodicity: they are affine birational maps for which every orbit is periodic with the same period. Following on from preliminary work by one of us with Kouloukas, here we present integrable maps obtained from deformations of cluster mutations related to the simple root systems 
$A_3$, $B_2$, $B_3$ and $D_4$. We further show how new cluster algebras arise, by considering Laurentification, that is, a lifting to a higher-dimensional map expressed in a set of new variables (tau functions), for which the dynamics exhibits the Laurent property. For the integrable map obtained by deformation of type $A_3$, which already appeared in our previous work, we show that there is a commuting map of Quispel-Roberts-Thompson (QRT) type which is built from a composition of mutations and a permutation applied to 
the same cluster algebra of rank 6, with an additional 2 frozen variables. Furthermore, both the deformed $A_3$ map and the QRT map correspond to translation by a generator in the Mordell-Weil group of a rational elliptic surface of rank two, and the underlying cluster algebra comes from a quiver that is mutation equivalent to the $q$-Painlev\'e III quiver found by Okubo. 
The deformed integrable maps of types $B_2$, $B_3$ and $D_4$ are also related to elliptic surfaces. 

From a dynamical systems viewpoint, the message of the paper is that special families of birational maps with completely periodic dynamics under iteration admit natural deformations that are aperiodic yet completely integrable.

Chaotic roots of the modular multiplication dynamical system in Shor's algorithm

Shor's factoring algorithm, believed to provide an exponential speedup over classical computation, relies on finding the period of an exactly periodic quantum modular multiplication operator. This exact periodicity is the hallmark of an integrable system, which is paradoxical from the viewpoint of quantum chaos, given that the classical limit of the modular multiplication operator is a highly chaotic system that occupies the “maximally random” Bernoulli level of the classical ergodic hierarchy. In this work, we approach this apparent paradox from a quantum dynamical systems viewpoint, and consider whether signatures of ergodicity and chaos may indeed be encoded in such an “integrable” quantization of a chaotic system. We show that Shor's modular multiplication operator, in specific cases, can be written as a superposition of quantized A-baker's maps exhibiting more typical signatures of quantum chaos and ergodicity. This work suggests that the integrability of Shor's modular multiplication operator may stem from the interference of other “chaotic” quantizations of the same family of maps, and paves the way for deeper studies on the interplay of integrability, ergodicity, and chaos in and via quantum algorithms. Published by the American Physical Society 2024

Physics-aware recurrent convolutional neural networks for modeling multiphase compressible flows

Multiphase compressible flow systems can exhibit unsteady and fast-transient dynamics, marked by sharp gradients and discontinuities, and material boundaries that interact with the evolving flow. The transient nature of the dynamics presents challenges to employing artificial intelligence (AI) and data-driven models for predicting flow behaviors. In this study, we explore the potential of physics-aware recurrent convolutional neural networks (PARC) to model the spatiotemporal dynamics of multiphase flows in the presence of shocks and reaction fronts. PARC is a neural network model that incorporates the generic form of the diffusion–advection–reaction equation in its network architecture, which mimics the process of solving the governing equations of fluid flows. In contrast to physics-informed machine learning approaches such as physics-informed neural networks (PINNs) where models are trained to directly minimize the residual of governing equations, PARC takes a dynamical systems viewpoint and does not seek to minimize potentially nonconvex and nonlinear loss terms. To assess the ability of PARC to accurately learn and simulate the physics of multiphase flows, we train and test PARC on various flow simulation problems, including the Burgers’ equation, fluid flow behind a cylindrical cross-section, and unsteady shock interactions with a particle at varying Mach numbers. We analyze PARC’s performance and examine sources of error in its prediction, in terms of differentiation and integration schemes and different weighting strategies for the model update. Based on our observations, we discuss PARC’s capabilities and limitations in multiphase flow applications and propose future research directions.

Synchronization phenomena observed in glacial–interglacial cycles simulated in an Earth system model of intermediate complexity

Abstract. The glacial–interglacial cycles of the Quaternary exhibit 41 kyr periodicity before the Mid-Pleistocene Transition (MPT) around 1.2–0.8 Myr ago and ∼ 100 kyr periodicity after that. From the viewpoint of dynamical systems, proposed mechanisms generating these periodicities are broadly divided into two types: (i) nonlinear forced responses of a mono- or multi-stable climate system to the astronomical forcing or (ii) synchronization of internal self-sustained oscillations to the astronomical forcing. In this study, we investigate the dynamics of glacial cycles simulated by the Earth system model of intermediate complexity CLIMBER-2 with a fully interactive carbon cycle, which reproduces the MPT under gradual changes in volcanic-CO2 degassing and regolith cover. We report that, in this model, the dominant frequency of glacial cycles is set in line with the principle of synchronization. It is found that the model exhibits self-sustained oscillations in the absence of astronomical forcing. Before the MPT, glacial cycles synchronize to the 41 kyr obliquity cycles because the self-sustained oscillations have periodicity relatively close to 41 kyr. After the MPT the timescale of internal oscillations becomes too long to follow every 41 kyr obliquity cycle, and the oscillations synchronize to the 100 kyr eccentricity cycles that modulate the amplitude of climatic precession. The latter synchronization occurs with the help of the 41 kyr obliquity forcing, which enables some terminations and glaciations to occur robustly at their right timing. We term this phenomenon vibration-enhanced synchronization because of its similarity to the noise-enhanced synchronization known in nonlinear science. While we interpret the dominant periodicities of glacial cycles as the result of synchronization of internal self-sustained oscillations to the astronomical forcing, the Quaternary glacial cycles show facets of both synchronization and forced response.

Dynamical systems insights on cyclonic compound “wet” and “windy” extremes in the Eastern Mediterranean

AbstractExtreme weather, such as heavy precipitation and strong winds, can co‐occur, resulting in larger socio‐economic impacts than the linear sum of their components. These are termed “compound extremes” and are challenging to forecast even a few days before. With this aim, we investigate the “wet” and “windy” extremes associated with Eastern Mediterranean cyclones in winter. We combine insights from a synoptic classification algorithm, traditional atmospheric analysis techniques, and dynamical systems theory. In phase space, the latter quantifies atmospheric states' co‐recurrence ratio (α) and persistence (Θ−1). We base the analysis on ERA5 at various pressure levels and time lags. Our analysis is two‐fold; first, we define compound dynamical extremes (CDE) based on upper and lower deciles of α and Θ−1, linking them to the synoptic patterns. We find that CDEs are related to the depth and location of the surface cyclone and upper‐level trough. Then, we show that high co‐recurrence and persistence are associated with heavier precipitation and stronger wind speed. Second, we define compound extremes (CE), the upper 5% of precipitation intensity and wind velocity co‐occurring simultaneously. We link these back to the dynamical system metrics anomalies. Finally, we compare CEs with individual extremes and cyclone climatology. We find that CEs display significantly higher co‐recurrence and persistence than individual extremes. Indeed, days with high co‐recurrence and persistence anomalies are ∼2–18 times more likely to be allied with extreme weather, depending on the extreme type, than low co‐recurrence and persistence. Moreover, we show that the upper levels are significantly more persistent than the surface flow during a CE. The mid‐February 2012 “wet” and “windy” CE case‐study strengthened the abovementioned climatological findings. To conclude, the dynamical systems viewpoint is a valuable complement to understanding the dynamics of CEs in the Eastern Mediterranean. We foresee it to be fruitfully applied to other CEs and regions.

Wada boundaries on a hyperbolic pair of pants

In this paper, the geodesics of an open multiply connected hyperbolic manifold are presented from the dynamical system point of view. The approach is completely numerical. Similar to the closed hyperbolic case there is a zero-measure set of periodic orbits. The difference is that now, most of the geodesics escape to infinity through one of the topologically distinct channels, and initial conditions are identified to which channel the orbit escapes. The initial condition mesh reveals basins of attraction to each channel. We verified that the basin boundary points are of the Wada type by two independent methods. We have also calculated the basin entropy of the system and verified that it depends on the opening angle of the escape channels. The manifold chosen is the pair of pants together with the leaves, so there are 3 distinct exit channels.

A hyper-parameterization method for comprehensive ocean models: Advection of the image point

Idealized and comprehensive ocean models at low resolutions cannot reproduce nominally-resolved flow structures similar to those presented in the high-resolution solution. Although there are various underlying physical reasons for this, from the dynamical system point of view all these reasons manifest themselves as a low-resolution trajectory avoiding the phase space occupied by the reference solution (the high-resolution solution projected onto the coarse grid). In order to solve this problem, a set of hyper-parameterization methods has recently been proposed and successfully tested on idealized ocean models. In this work, for the first time we apply one of hyper-parameterization methods (Advection of the image point) to a comprehensive, rather than idealized, general circulation model of the North Atlantic.The results show that the hyper-parameterization method significantly outperforms the coarse-grid ocean model by reproducing both the large- and small-scale features of the Gulf Stream flow. The proposed method is much faster than even a single run of the coarse-grid ocean model, requires no modification of the model, and is easy to implement. Moreover, the method can take not only the reference solution as input data but also real measurements from different sources (drifters, weather stations, etc.), or combination of both. All this offers a great flexibility to ocean modellers working with mathematical models and/or measurements.

Stability in mechanics and dynamics; a brief historical tour from Newton to modern tools, including Riemannian structures and entropy

AbstractThis article presents some historical developments in the theory of stability in mechanics from a dynamical systems point of view, focusing on mathematical methods from the earliest developments (Newton) and explaining some classical and some recent methods used, including Riemannian structures, entropy and notions of stability in dynamics.

On the Optimal Control of HIV-TB Co-Infection and Improvement of Workplace Productivity

Human immunodeficiency virus (HIV) and tuberculosis (TB) have long been known to have a synergistic relationship. This is a result of each of the diseases impacting negatively on the immune system of the infected persons. The impact of these diseases on workforce productivity is studied in this paper from the viewpoint of dynamical systems. In this paper, we present a nonlinear ordinary differential equation model to study the dynamics of HIV-TB co-infection and its effect on workforce productivity. The main model is first decoupled into two basic submodels of HIV-only and TB-only models, whose qualitative properties are presented before the qualitative properties of the main model are studied. While the HIV-only model is shown to have a globally asymptotically stable disease-free equilibrium whenever its basic reproduction number is less than unity, the TB-only model is shown to exhibit backward bifurcation under some conditions. To investigate the impact of various intervention strategies on the control of the co-infection and improvement of workforce productivity, five time-dependent controls (involving transmission prevention for the two diseases, therapy for the two diseases, and capacity building for improved workforce productivity) are incorporated into the basic model to form an optimal control problem, which is qualitatively analyzed using Pontryagin’s maximum principle and numerically simulated. Incremental cost-effectiveness analysis is conducted with the results of the numerical simulations. It is observed that the most cost-effective strategy for fighting the spread of the co-infection with enhanced productivity is that of combining both preventative and curative measures along with skills training.

Human Sway on a Balance Platform

In the body balance process control, a variety of postural strategies for balance recovery are used. Postural strategies are automatic stable muscular patterns. Such a mechanism reduces the degrees of freedom number, simplifies, speeds up the posture adjustment, and minimizes energy expenditure. They relate to the existence of some motor coordination sets and describe three mobility strategies: ankle, hip, and step strategy. The hip strategy occurs when interference is greater or the use of the ankle strategy is impossible, for example, due to the delay of the postural information cycle. From a dynamical systems point of view, a human attempting to balance upright on an unstable balance board represents the coupling of two dynamical systems, the human balance system with neuromuscular feedback supported on the balance board (an inverted pendulum). The coupling of these two dynamical systems, with time delay and nonlinearities, creates an ideal setting for the emergence of complex postural behaviour and unanticipated interactions between the individual, task, and the external dynamical system. The article presents an analysis of the pendulums concerning the issue of maintaining balance by man.

Markov Chain Monte Carlo for Gaussian: A Linear Control Perspective

Drawing samples from a given target probability distribution is a fundamental task in many science and engineering applications. A commonly used method for sampling is the Markov chain Monte Carlo (MCMC) which simulates a Markov chain whose stationary distribution coincides with the target one. In this work, we study the convergence and complexity of MCMC algorithms from a dynamic system point of view. We focus on the special cases with Gaussian target distributions and provide a Lyapunov perspective to them using tools from linear control theory. In particular, we systematically analyze two popular MCMC algorithms: Langevin Monte Carlo (LMC) and kinetic Langevin Monte Carlo (KLMC). By applying Lyapunov theory we derive impressive complexity bounds to these algorithms: for LMC, our result is better than all existing results, and for KLMC, ours matches the best known bound. Our analysis also highlights subtle differences between sampling and optimization that could inform the more challenging task to sample from general distributions. Overall, our findings offer valuable insights for improving MCMC algorithms.

A method for preserving nominally-resolved flow patterns in low-resolution ocean simulations: Constrained dynamics

Inability of low-resolution ocean models to simulate many important aspects of the large-scale general circulation is a common problem. In the view of physics, the main reason for this failure are the missed dynamical effects of the unresolved small scales of motion on the explicitly resolved large-scale circulation. Complimentary to this mainstream physics-based perspective, we propose to address this failure from the dynamical systems point of view, namely, as the persistent tendency of phase space trajectories representing the low-resolution solution to escape the right region of the corresponding phase space, which is occupied by the reference eddy-resolving solution. Based on this concept, we propose to use methods of constrained optimization to confine the low-resolution solution to remain within the correct phase space region, without attempting to amend the eddy physics by introducing a process-based parameterization. This approach is advocated as a novel framework for data-driven hyper-parameterizations of mesoscale oceanic eddies in non-eddy-resolving models. We tested the idea in the context of classical, baroclinic beta-plane turbulence model and showed that non-eddy-resolving solution can be substantially improved towards the reference eddy-resolving benchmark.

On Planar Curves with Position-Dependent Curvature

Motivated by homothetic solutions in curvature-driven flows of planar curves, as well as their many physical applications, this article carries out a systematic study of oriented smooth curves whose curvature $$\kappa $$ is a given function of position or direction. The analysis is informed by a dynamical systems point of view. Though focussed on situations where the prescribed curvature depends only on the distance r from one distinguished point, the basic dynamical concepts are seen to be applicable in other situations as well. As an application, a complete classification of all closed solutions of $$\kappa = ar^{b}$$ , with arbitrary real constants $$a,b$$ , is established.

Live imaging approach of dynamic multicellular responses in ERK signaling during vertebrate tissue development.

The chemical and mechanical responses of cells via the exchange of information during growth and development result in the formation of biological tissues. Information processing within the cells through the signaling pathways and networks inherent to the constituent cells has been well-studied. However, the cell signaling mechanisms responsible for generating dynamic multicellular responses in developing tissues remain unclear. Here, I review the dynamic multicellular response systems during the development and growth of vertebrate tissues based on the extracellular signal-regulated kinase (ERK) pathway. First, an overview of the function of the ERK signaling network in cells is provided, followed by descriptions of biosensors essential for live imaging of the quantification of ERK activity in tissues. Then adducing four examples, I highlight the contribution of live imaging techniques for studying the involvement of spatio-temporal patterns of ERK activity change in tissue development and growth. In addition, theoretical implications of ERK signaling are also discussed from the viewpoint of dynamic systems. This review might help in understanding ERK-mediated dynamic multicellular responses and tissue morphogenesis.

Diversity of ghost notes in tubas, euphoniums and saxhorns

The ghost note is a natural note which can be played exclusively on bass brass instruments with a predominantly-expanding bore profile such as tubas, euphoniums or saxhorns. It stands between the pedal note – the lowest natural note playable, or first regime – and the instrument’s second regime. However, if the interval between the pedal note and the second regime remains close to an octave regardless of the instrument, the interval between the pedal note and the ghost note vary from a minor third to a perfect fourth. References about this note are very scarce, and it is not commonly known among tuba players. This study shows that an elementary brass model describing the player coupled to the instrument is capable of bringing both the ghost and the pedal note to light. Here, we adopt a dynamical systems point of view and perform a bifurcation analysis using a software of numerical continuation. The numerical results provided in terms of frequency intervals between pedal note and ghost note are compared with frequency intervals experimentally inferred from recordings of seven different types of tuba, each of them being played by two professional tuba players.

The Role of Energy Return on Energy Invested (EROEI) in Complex Adaptive Systems

The energy return on energy invested, EROI or EROEI, is the ratio of the energy produced by a system to the energy expended to build, maintain, and finally dismantle the system. It is an important parameter for evaluating the efficiency of energy-producing technologies. In this paper, we examine the concept of EROEI from the general viewpoint of dynamic dissipative systems, providing insights on a wider range of applications. In general, natural resources can be assimilated to energy stocks characterized by a potential that can be exploited by creating intermediate stocks. This transformation is typical of dissipative systems and for the first time, we report that the Lotka–Volterra model, usually confined to the study of the biology of populations, can represent a powerful tool to estimate the EROEI of dissipative systems and, in particular, those systems subjected to depletion. This assessment is important to evaluate the ongoing energy transition since it provides us with a model for the decline of the EROEI in the exploitation of fossil fuels.

On the Topological Dynamics of Dynamical Manifolds and Their Fundamental Group

The paper aims to deduce the relation between the category of topology and algebra from viewpoint of geometry and dynamical system. We introduce and define a dynamical manifold as a manifold associated with a time parameter. We obtain the induced chain of topological dynamics on the fundamental group from the chain of dynamical maps on a dynamical manifold. For many adjunctions in this context, we deduce the limit topological dynamics and conditional topological dynamics on the fundamental group. We use the category of commutative diagrams as chains of dynamical manifolds to deduce the chains on fundamental groups. Also, we describe how the manifold changes in a dynamical system from the view of the fundamental group.

Spatio-temporal dynamics of a model for the effect of variable ages at reproduction

Some species may have totally different ages at successful reproduction (ages at maturity) in population growth. For example, Ixodes ticks, a vector species responsible for many tick-borne diseases, may suspend development and undergo diapause during maturation process, which naturally introduce distinct ages at reproduction. Although the age at reproduction is a key demographic trait that is probably under high selective pressure, it is highly variable and the effect of this variability on spatial establishment and invasion is not well understood. In this study, a spatial mechanistic model, in the form of reaction diffusion equations with nonlocal terms incorporating two different ages at reproduction, is formulated and mathematically analyzed from a dynamical system point of view. Specifically, the persistence of the species in a bounded domain can be predicted by the net reproduction number and the spreading property in an unbounded domain in terms of spreading speed and traveling waves is characterized. Numerical simulations are conducted to further illustrate the impact of ages at reproduction on the net reproduction number and the spreading speed of the species, in particular for various scenarios of fitness tradeoffs of the premature survival and early reproduction.

Role of body temperature variations in bat immune response to viral infections.

The ability of bats to coexist with viruses without being harmed is an interesting issue that is still under investigation. Here we use a mathematical model to show that the pattern of body temperature variations observed in bats between day and night is responsible for their ability to keep viruses in check. From the dynamical systems point of view, our model displays an intriguing quasi-periodic behaviour that might be relevant in making the system robust by avoiding viral escape due to perturbations in the body temperature cycle.

Long lived transients in gene regulation

Gene expression is regulated by the set of transcription factors (TFs) that bind to the promoter. The ensuing regulating function is often represented as a combinational logic circuit, where output (gene expression) is determined by current input values (promoter bound TFs) only. However, the simultaneous arrival of TFs is a strong assumption, since transcription and translation of genes introduce intrinsic time delays and there is no global synchronisation among the arrival times of different molecular species at their targets. We present an experimentally implementable genetic circuit with two inputs and one output, which in the presence of small delays in input arrival, exhibits qualitatively distinct population-level phenotypes, over timescales that are longer than typical cell doubling times. From a dynamical systems point of view, these phenotypes represent long-lived transients: although they converge to the same value eventually, they do so after a very long time span. The key feature of this toy model genetic circuit is that, despite having only two inputs and one output, it is regulated by twenty-three distinct DNA-TF configurations, two of which are more stable than others (DNA looped states), one promoting and another blocking the expression of the output gene. Small delays in input arrival time result in a majority of cells in the population quickly reaching the stable state associated with the first input, while exiting of this stable state occurs at a slow timescale. In order to mechanistically model the behaviour of this genetic circuit, we used a rule-based modelling language, and implemented a grid-search to find parameter combinations giving rise to long-lived transients. Our analysis shows that in the absence of feedback, there exist path-dependent gene regulatory mechanisms based on the long timescale of transients. The behaviour of this toy model circuit suggests that gene regulatory networks can exploit event timing to create phenotypes, and it opens the possibility that they could use event timing to memorise events, without regulatory feedback. The model reveals the importance of (i) mechanistically modelling the transitions between the different DNA-TF states, and (ii) employing transient analysis thereof.