# gst: apropos of transitions, towards a theory for the formation of chimera patterns in complex networks

This AA work << formalizes a systematic method by evoking pattern formation theory to explain the emergence of chimera states in complex networks. >>

They << show that the randomness of network topology, as reflected in the localization of the graph Laplacian eigenvectors, determines the emergence of chimera patterns, underscoring the critical role of network structure. In particular, this approach explains how amplitude and phase chimeras arise separately and explores whether phase chimeras can be chaotic or not. (AA) findings suggest that chimeras result from the interplay between local and global dynamics at different time scales. >>

Malbor Asllani, Alex Arenas. Towards a Theory for the Formation of Chimera Patterns in Complex Networks. arXiv: 2412.05504v1 [nlin.AO]. Dec 7, 2024.

https://arxiv.org/abs/2412.05504

Also: chimera, network, transition, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, chimera, network, transition

# gst: self-organized chimera states in pulse-coupled oscillator systems.

<< Coupled oscillator systems can lead to states in which synchrony and chaos coexist. These states are called “chimera states.” >>

️

AA << study a variation of a pulse-coupled oscillator (PCO) model that has been shown to produce chimera states, demonstrate that it reproduces several of the expected chimera properties, like the formation of multiple heads and the ability to control the natural drift that Kuramoto's chimera states experience in a ring, and explain how chimera states emerge. >>️

<< Three notable aspects of chimeras in our PCO networks (with time-discrete coupling) are the absence of firing events from the tail (which still almost synchronize their phases), the reliable onset of the phenomenon from virtually any initial configuration, and the lack of a superimposed structure (e.g., artificially splitting the population into subgroups) and thus the self-organized nature of the phenomenon. >>️

Arke Vogell, Udo Schilcher, et al. Chimera states in pulse-coupled oscillator systems. Phys. Rev. E 110, 054214. Nov 26, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.054214 

Also: chimera, self-assembly, chaos, network,  in https://www.inkgmr.net/kwrds.html 

Keywords: gst, chimera, self-assembly, chaos, network 

# game: balance exploration and exploitation, making decisions cooperatively without sharing information.

<< Multiagent reinforcement learning (MARL) studies crucial principles that are applicable to a variety of fields, including wireless networking and autonomous driving. (AA) propose a photonic-based decision-making algorithm to address one of the most fundamental problems in MARL, called the competitive multiarmed bandit (CMAB) problem. >>

AA << demonstrate that chaotic oscillations and cluster synchronization of optically coupled lasers, along with (their) proposed decentralized coupling adjustment, efficiently balance exploration and exploitation while facilitating cooperative decision making without explicitly sharing information among agents. >>

AA << study demonstrates how decentralized reinforcement learning can be achieved by exploiting complex physical processes controlled by simple algorithms. >>

Shun Kotoku, Takatomo Mihana, et al. Decentralized multiagent reinforcement learning algorithm using a cluster-synchronized laser network. Phys. Rev. E 110, 064212. Dec 11, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.064212

Img: https://x.com/PhysRevE/status/1866889144657465632

Also: game, chaos, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: game, cooperation, chaos, exploration, exploitation, ai, artificial intelligence, MARL, CMAB.

# gst: apropos of diffusive anomalies, anomalous diffusion of active Brownian particles in responsive elastic gels.

Here, AA << examine via extensive computer simulations the dynamics of SPPs (self-propelled particles) in deformable gellike structures responsive to thermal fluctuations. (AA) treat tracer particles comparable to and larger than the mesh size of the gel. (They) observe distinct trapping events of active tracers at relatively short times, leading to subdiffusion; it is followed by an escape from meshwork-induced traps due to the flexibility of the network, resulting in superdiffusion. >>

AA << thus find crossovers between different transport regimes. (They) also find pronounced nonergodicity in the dynamics of SPPs and non-Gaussianity at intermediate times. The distributions of trapping times of the tracers escaping from “cages” in (..)  quasiperiodic gel often reveal the existence of two distinct timescales in the dynamics. At high activity of the tracers these timescales become comparable. >>

<< Furthermore, (AA) find that the mean waiting time exhibits a power-law dependence on the activity of SPPs (in terms of their Péclet number). (Their) results additionally showcase both exponential and nonexponential trapping events at high activities. Extensions of this setup are possible, with the factors such as anisotropy of the particles, different topologies of the gel network, and various interactions between the particles (also of a nonlocal nature) to be considered. >>

Koushik Goswami, Andrey G. Cherstvy, et al. Anomalous diffusion of active Brownian particles in responsive elastic gels: Nonergodicity, non-Gaussianity, and distributions of trapping times. Phys. Rev. E 110, 044609. Oct 29, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.044609

Also: particle, random, escape, network, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, particle, random, random walks, escape, network

# gst: protected chaos in a topological lattice.

<< The erratic nature of chaotic behavior is thought to erode the stability of periodic behavior, including topological oscillations. However, (AA) discover that in the presence of chaos, non-trivial topology not only endures but also provides robust protection to chaotic dynamics within a topological lattice hosting non-linear oscillators. >>

<< Despite the difficulty in defining topological invariants in non-linear settings, non-trivial topological robustness still persists in the parametric state of chaotic boundary oscillations. (AA) demonstrate this interplay between chaos and topology by incorporating chaotic Chua's circuits into a topological Su-Schrieffer-Heeger (SSH) circuit. >>

<< By extrapolating from the linear limit to deep into the non-linear regime, (AA) find that distinctive correlations in the bulk and edge scroll dynamics effectively capture the topological origin of the protected chaos. (Their)  findings suggest that topologically protected chaos can be robustly achieved across a broad spectrum of periodically-driven systems, thereby offering new avenues for the design of resilient and adaptable non-linear networks. >>️

Haydar Sahin, Hakan Akgün, et al. Protected chaos in a topological lattice. arXiv: 2411.07522v1 [cond-mat.mes-hall]. Nov 12, 2024.

https://arxiv.org/abs/2411.07522

Also: chaos, random, instability, transition, network, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: gst, chaos, random,  instability, transition, network, AI, Artificial Intelligence

# gst: apropos of transverse instabilities, from chimeras to extensive chaos

<< Populations of coupled oscillators can exhibit a wide range of complex dynamical behavior, from complete synchronization to chimera and chaotic states. We can thus expect complex dynamics to arise in networks of such populations. >>️

Here AA << analyze the dynamics of networks of populations of heterogeneous mean-field coupled Kuramoto-Sakaguchi oscillators, and show that the instability that leads to chimera states in a simple two-population model also leads to extensive chaos in large networks of coupled populations. >>️

Pol Floriach, Jordi Garcia-Ojalvo, Pau Clusella. From chimeras to extensive chaos in networks of heterogeneous Kuramoto oscillator populations. arXiv: 2407.20408v2 [nlin.CD]. Oct 11, 2024.

https://arxiv.org/abs/2407.20408

Also: chimera, instability, chaos, network, in 

https://www.inkgmr.net/kwrds.html 

Keywords: gst, chimera, instability, chaos, network

# life: don't worry folks! Mr Donald will not run again in 2028. Anzicheforse?

<< In September, Donald Trump said he would run for president again in 2028 if he didn't win this week's general election. >>️

<< But on Tuesday, Donald Trump won the vote to become the 47th president of the United States. So, can he still run for office in 2028? >>️

<< And just a few months before that, at the NRA's annual meeting in May, Trump mentioned running for a third term. >>️

<< Here's what to know about term limits and if Trump can run for president a third time, now that he's won twice. >>

<< The 22nd Amendment to the Constitution ... >>️️

Lianna Norman, Joyce Orlando. Can Trump run for president again in 2028? Here’s what to know about term limits. USA TODAY NETWORK, Florida. Nov 7, 2024. 

https://eu.floridatoday.com/story/news/2024/11/07/trump-run-again-term-limits-22nd-amendment-constitution/76087581007/

Also: Mr. Donald, in https://www.inkgmr.net/kwrds.html 

Keywords: life, Donald, potus, potus race

# gst: apropos of noise-assisted phenomena, self-organized transport in noisy dynamic networks.

AA << present a numerical study of multicommodity transport in a noisy, nonlinear network. The nonlinearity determines the dynamics of the edge capacities, which can be amplified or suppressed depending on the local current flowing across an edge. (AA) consider network self-organization for three different nonlinear functions: For all three (They) identify parameter regimes where noise leads to self-organization into more robust topologies, that are not found by the sole noiseless dynamics. Moreover, the interplay between noise and specific functional behavior of the nonlinearity gives rise to different features, such as (i) continuous or discontinuous responses to the demand strength and (ii) either single or multistable solutions. (AA) study shows the crucial role of the activation function on noise-assisted phenomena. >>️

Frederic Folz, Kurt Mehlhorn, Giovanna Morigi. Self-organized transport in noisy dynamic networks. Phys. Rev. E 110, 044310. Oct 21, 2024. 

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.044310

Also: network, noise, behavior, self-assembly, instability, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, network, noise, behavior, self-assembly, stability 

# life: fast-and-flexible decision-making with modulatory interactions

<< Multi-agent systems in biology, society, and engineering are capable of making decisions through the dynamic interaction of their elements. Nonlinearity of the interactions is key for the speed, robustness, and flexibility of multi-agent decision-making. >>

AA << introduce modulatory, that is, multiplicative, in contrast to additive, interactions in a nonlinear opinion dynamics model of fast-and-flexible decision-making. (..) Modulatory interactions introduce an extra source of nonlinearity that greatly enriches the model decision-making behavior in a mathematically tractable way. >>

AA << model provides new tools to understand the role of these interactions in networked decision-making and to engineer them in artificial systems. >>

Rodrigo Moreno-Morton, Anastasia Bizyaeva, et al. Fast-and-flexible decision-making with modulatory interactions. arXiv: 2410.00798v1 [math.DS]. Oct 1, 2024.

https://arxiv.org/abs/2410.00798

Also: behav, network, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: life, decision-making, modulatory interactions, behavior, behaviour, network, ai, artificial intelligence

# game: aperiodic Parrondo (behavior based on the binary Fibonacci, Thue–Morse and Rudin–Shapiro sequences); persistence and heterogeneity effects.

AA << study the effectiveness of employing archetypal aperiodic sequencing -- namely Fibonacci, Thue-Morse, and Rudin-Saphiro -- on the Parrondian effect. From a capital gain perspective, (their) results show that these series do yield a Parrondo's Paradox with the Thue-Morse based strategy outperforming not only the other two aperiodic strategies but benchmark Parrondian games with random and periodical (AABBAABB…) switching as well. The least performing of the three aperiodic strategies is the Rudin-Shapiro. >>

AA << analyze the cross-correlation between the capital generated by the switching protocols and that of the isolated losing games. This analysis reveals that a pronounced anti-correlation (below -0.95) with both isolated games is typically required to achieve a robust manifestation of Parrondo's effect. >>

About << the influence of the sequencing on the capital using the lacunarity and persistence measures (AA) observe that the switching protocols tend to become less performing in terms of the capital as one increases the persistence and thus approaches the features of an isolated losing game. >>

Respect to << lacunarity, a property related to heterogeneity, (AA) notice that for small persistence the performance increases with the lacunarity with a maximum (..). In respect of this, (AA) work shows that  the optimisation of a switching protocol is strongly dependent on a fine tune between persistence and heterogeneity. >>

Marcelo A. Pires, Erveton P. Pinto, et al. Parrondo's effects with aperiodic protocols. arXiv: 2410.02987v1 [physics.soc-ph]. Oct 3, 2024.

https://arxiv.org/abs/2410.02987

Also: Parrondo, tit-for-tat, game, behav, network, in https://www.inkgmr.net/kwrds.html 

Keywords: Parrondo, tit-for-tat, game, behavior, behaviour, network

# game: apropos of Parrondo's paradox, winning with losses driven by reputation and reciprocity

AA << investigate two such social behaviors, reputation and reciprocity, and their role in explaining Darwin’s survival of the fittest, examining how these fundamental principles govern individual interactions and shape broader social dynamics. >>

<< Current theories hint at two main facets of social interaction, reputation and reciprocity, as potential drivers behind this cooperative evolution. Reputation revolves around building and sustaining trust, social worth, and overall community standing. Conversely, reciprocity governs the mutual exchange of actions or benefits, influencing our choices. >>

<< One intriguing concept explored in this domain is Parrondo’s paradox: combining or switching between two losing strategies might surprisingly achieve a winning outcome. The role of Parrondo’s paradox in complex systems has sparked key research into chaotic many-body, quantum, and algorithmic network applications, where combining elements yields opposing beneficial results. Similarly, social physicists aim to uncover hidden mechanisms that govern societal phenomena by integrating the paradox’s counterintuitive principles. >>️

<< The game-theoretic Parrondo’s paradox emerges through multiple iterations of these interactions (..) A naive observation might conclude that in either scheme the chance of individuals losing to the environment is higher than gaining from the environment. For the reputation scheme, one is rewarded with a singular capital from the environment but is punished with two. Similarly, the reciprocity scheme only allows for the redistribution of capital or loss of capital. In reality, diverse schemes can be adopted by different individuals. Thus, (AA) suggest two forms of switching: (1) stochastic switching, where the individual randomly selects one of two schemes to employ with equal probability, and (2) rule-based switching, where the individual only selects the reputation scheme if it passes the reputation threshold ρ; otherwise, it employs the reciprocity scheme. >>

AA << also performed simulations on other network topologies (..) Parrondo’s paradox is strongly observed in small-world networks, weakly in the Erdős-Rényi network, and absent in scale-free networks. >>

To conclude, some of these observations << underscore the profound capability of rule-based switching mechanisms inherent in Parrondo’s paradox to emulate and forecast key aspects of real-world social phenomena. Such insights are invaluable for developing sophisticated models and strategies in various fields, ranging from social sciences to policy making, where accurate predictions of social behavior and dynamics are crucial. >>

Joel Weijia Lai, Kang Hao Cheong. Winning with Losses: The Surprising Success of Negative Strategies in Social Interaction Behavior. Phys. Rev. Lett. 133, 167401. Oct 16, 2024. 

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.133.167401

Also: Parrondo, tit-for-tat, game, behav, network, in https://www.inkgmr.net/kwrds.html 

Keywords: Parrondo, tit-for-tat, game, behavior, behaviour, network

# brain: time delay in 'reservoir brain' as a reservoir network, a hypothesis

<< Both the predictive power and the memory storage capability of an artificial neural network called a reservoir computer increase when time delays are added into how the network processes signals, according to a new model. >>️

<< They also suggest that incorporating time delays could offer advantages to living neural networks (such as those found in human and animal brains). Such a finding would be tantalizing, as time delays are known to decrease performance in living systems. For example, for a baseball player facing an oncoming ball, a longer time delay between perception and action (which is learned from experience) will decrease the likelihood they hit a home run. Are there instead cases in which time delays increase an organism’s ability to perform some task? Has evolution shaped our brains, which could perhaps be thought of as a collection of reservoir computers, so that the time delay between one neuron sending a signal and a second receiving it is exactly the right length for understanding the visual and audio that constantly impinge upon our eyes and ears? Does adding time delays impact the number of neurons the brain needs to operate correctly? Further work is needed to answer these questions, but such work could lead to a new understanding of how biological organism’s function.  >>️

Sarah Marzen. Time Delays Improve Performance of Certain Neural Networks. Physics 17, 111. July 22, 2024. 

https://physics.aps.org/articles/v17/111 

Also: pause, silence, jazz, network, brain, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: gst, brain, network, neural network, reservoir network, reservoir computer, time delay, ai, artificial intelligence

# gst: apropos of 'filamentous' and 'fibrous' scenarios, criticality enhances the reinforcement of disordered networks by rigid inclusions.

<< The mechanical properties of biological materials are spatially heterogeneous. Typical tissues are made up of a spanning fibrous extracellular matrix in which various inclusions, such as living cells, are embedded. >>️

<< Recent work has shown that, in isolation, such networks exhibit unusual viscoelastic behavior indicative of an underlying mechanical phase transition controlled by network connectivity and strain. How this behavior is modified when inclusions are present is unclear. >>

AA << present a theoretical and computational study of the influence of rigid inclusions on the mechanics of disordered elastic networks near the connectivity-controlled central force rigidity transition. >>️

<< Combining scaling theory and coarse-grained simulations, (AA) predict and confirm an anomalously strong dependence of the composite stiffness on inclusion volume fraction, beyond that seen in ordinary composites. (..) this enhancement is a consequence of the interplay between inter-particle spacing and an emergent correlation length, leading to an effective finite-size scaling imposed by the presence of inclusions. >>

AA << show that this enhancement is a consequence of the interplay between inter-particle spacing and an emergent correlation length, leading to an effective finite-size scaling imposed by the presence of inclusions. >>️

AA << discuss potential experimental tests and implications for (their)  predictions in real systems. >>

️

Jordan L. Shivers, Jingchen Feng, Fred C. MacKintosh. Criticality enhances the reinforcement of disordered networks by rigid inclusions. arXiv:  2407.19563v1 [cond-mat.soft]. Jul 28, 2024. 

https://arxiv.org/abs/2407.19563

Also: network, transition, disorder, elastic, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, network, transition, disorder, elasticity, rigidity, criticality, bifurcations

# gst: networks of pendula with diffusive interactions, chaotic regime seems to emerge at low energies.

AA << study a system of coupled pendula with diffusive interactions, which could depend both on positions and on momenta. The coupling structure is defined by an undirected network, while the dynamic equations are derived from a Hamiltonian; as such, the energy is conserved. >>️

<< The behaviour observed showcases a mechanism for the appearance of chaotic oscillations in conservative systems. For Hamiltonians with two degrees of freedom, it has been shown how chaos can emerge near a saddle-centre equilibrium possessing a homoclinic orbit. (AA) have seen that higher-dimensional systems having mixed equilibria, i.e., generalisations of a saddle-center where the eigenvalues are only imaginary and reals, also show chaotic behaviour close to those points.  >>️

AA << complement the analysis with some numerical simulations showing the interplay between bifurcations of the origin and transitions to chaos of nearby orbits. A key feature is that the observed chaotic regime emerges at low energies. >>

️

Riccardo Bonetto, Hildeberto Jardón-Kojakhmetov, Christian Kuehn. Networks of Pendula with Diffusive Interactions. arXiv: 2408.02352v1 [math.DS]. Aug 5, 2024.

https://arxiv.org/abs/2408.02352

Also: pendulum, network, transition, chaos, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, pendulum, network, transition, chaos, bifurcation

# gst: Resonancelike emergence of chaos in complex networks of damped-driven nonlinear systems.

AA << solve a critical outstanding problem in this multidisciplinary research field: the emergence and persistence of spatiotemporal chaos in complex networks of damped-driven nonlinear oscillators in the significant weak-coupling regime, while they exhibit regular behavior when uncoupled. >>

They << uncover and characterize the basic physical mechanisms concerning both heterogeneity-induced and impulse-induced emergence, enhancement, and suppression of chaos in starlike and scale-free networks of periodically driven, dissipative nonlinear oscillators. >>️

Ricardo Chacon, Pedro J. Martínez. Resonancelike emergence of chaos in complex networks of damped-driven nonlinear systems. Phys. Rev. E 110, 014209. Jul 19, 2024. 

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.014209

Also: network, chaos, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, network, resonance, chaos

# gst: discontinuous transition to chaos in a canonical random neural network

AA << study a paradigmatic random recurrent neural network introduced by Sompolinsky, Crisanti, and Sommers (SCS). In the infinite size limit, this system exhibits a direct transition from a homogeneous rest state to chaotic behavior, with the Lyapunov exponent gradually increasing from zero. (AA)  generalize the SCS model considering odd saturating nonlinear transfer functions, beyond the usual choice 𝜙⁡(𝑥)=tanh⁡𝑥. A discontinuous transition to chaos occurs whenever the slope of 𝜙 at 0 is a local minimum [i.e., for 𝜙′′′⁢(0)>0]. Chaos appears out of the blue, by an attractor-repeller fold. Accordingly, the Lyapunov exponent stays away from zero at the birth of chaos. >>

In the figure 7 << the pink square is located at the doubly degenerate point (𝑔,𝜀)=(1,1/3). >>️️

Diego Pazó. Discontinuous transition to chaos in a canonical random neural network. Phys. Rev. E 110, 014201. July 1, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.014201

Also: chaos, random, network, transition, neuro, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, chaos, random, network, transition, neuro

# gst: when generalized diffusion could result from stochastic processes.

<< Despite the success of fractional Brownian motion (fBm) in modeling systems that exhibit anomalous diffusion due to temporal correlations, recent experimental and theoretical studies highlight the necessity for a more comprehensive approach of a generalization that incorporates heterogeneities in either the tracers or the environment. >>

AA present << a modification of Lévy's representation of fBm for the case in which the generalized diffusion coefficient is a stochastic process. (They) derive analytical expressions for the autocovariance function and both ensemble- and time-averaged mean squared displacements. Further, (AA)  validate the efficacy of the developed framework in two-state systems, comparing analytical asymptotic expressions with numerical simulations. >>️

Adrian Pacheco-Pozo, Diego Krapf. Fractional Brownian motion with fluctuating diffusivities. Phys. Rev. E 110, 014105. Jul 1, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.014105

Also: disorder, fluctuations, network, transition, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, fractional Brownian motion, fBm, Lévy, disorder, fluctuations, anomalous, network, transition

# gst: the strangeness of networks, the hypothesis of a connection between the kinetics of networks and anomalous transport theory.

<< Many real-world networks change over time. Think, for example, of social interactions, gene activation in a cell, or strategy making in financial markets, where connections and disconnections occur all the time. >>

AA team << has gained groundbreaking insights into this problem by recasting the discrete dynamics of a network as a continuous time series (..). In doing so, the researchers have discovered that if the breaking and forming of links are represented as a particle moving in a suitable geometric space, then its motion is subdiffusive—that is, slower than it would be if it diffused normally. What’s more, the particles’ motions are well described by fractional Brownian motion, a generalization of Einstein’s classic model. This feat establishes a profound connection between the kinetics of time-varying or “temporal” networks and anomalous transport theory, opening fresh prospects for developing predictive equations of motion for networks. >>️

Ivan Bonamassa. Strange Kinetics Shape Network Growth. Physics 17, 96. Jun 17, 2024.

https://physics.aps.org/articles/v17/96

Evangelos S. Papaefthymiou, Costas Iordanou, Fragkiskos Papadopoulos. Fundamental Dynamics of Popularity-Similarity Trajectories in Real Networks. Phys. Rev. Lett. 132, 257401. Jun 17, 2024. 

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.132.257401

Also: network, transition, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, network, transition

# gst: evolving disorder and chaos induces acceleration of elastic waves.

<< Static or frozen disorder, characterised by spatial heterogeneities, influences diverse complex systems, encompassing many-body systems, equilibrium and nonequilibrium states of matter, intricate network topologies, biological systems, and wave-matter interactions. >>

AA << investigate elastic wave propagation in a one-dimensional heterogeneous medium with diagonal disorder. (They) examine two types of complex elastic materials: one with static disorder, where mass density randomly varies in space, and the other with evolving disorder, featuring random variations in both space and time. (AA) results indicate that evolving disorder enhances the propagation speed of Gaussian pulses compared to static disorder. Additionally, (They) demonstrate that the acceleration effect also occurs when the medium evolves chaotically rather than randomly over time. The latter establishes that evolving randomness is not a unique prerequisite for observing wavefront acceleration, introducing the concept of chaotic acceleration in complex media. >>️

M. Ahumada, L. Trujillo, J. F. Marín. Evolving disorder and chaos induces acceleration of elastic waves. arXiv: 2403.02113v1 [cond-mat.dis-nn]. Mar 4, 2024. 

https://arxiv.org/abs/2403.02113

Also: waves, elastic, chaos, transition, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, waves, elastic, chaos, transition

# evol: emergence of single vs. multi-state allostery

      FIG. 1. The elastic network model

<< Allostery, the change of activity of a  macromolecule in response to a perturbation at a distance from its active site, is thought to be a ubiquitous feature of proteins. Initially described in the context of multimeric proteins, it is now understood to underlie the regulation of proteins with diverse structural architectures, from receptors to signaling proteins and metabolic enzymes. >>️

<< Here, (AA) analyze a simplified model of protein allostery under a range of physical and evolutionary constraints. (They) find that a continuum of mechanisms between two archetypes emerges through evolution. In one limit, a single-state mechanism exists where ligand binding induces a displacement along a single normal mode, and in the other limit, a multi-state mechanism exists where ligand binding induces a switch across an energy barrier to a different stable state. Importantly, whenever the two mechanisms are possible, the multi-state mechanism confers a stronger allosteric effect and thus a selective advantage. >>

️

Eric Rouviere, Rama Ranganathan, Olivier Rivoire. Emergence of Single- versus Multi-State Allostery. PRX Life 1, 023004. Nov 9, 2023.

https://journals.aps.org/prxlife/abstract/10.1103/PRXLife.1.023004

Also: allostery in FonT https://flashontrack.blogspot.com/search?q=allostery

Also: allosterico in Notes 

(quasi-stochastic poetry)

https://inkpi.blogspot.com/search?q=allosterico

Keywords: gst, allostery, elastic, evolution