# gst: triadic percolation on multilayer networks.

<< ️Triadic interactions are special types of higher-order interactions that occur when regulator nodes modulate the interactions between other two or more nodes. In presence of triadic interactions, a percolation process occurring on a single-layer network becomes a fully-fledged dynamical system, characterized by period-doubling and a route to chaos. >>

<< ️Here, (AA) generalize the model to multilayer networks and name it as the multilayer triadic percolation (MTP) model. (They) find a much richer dynamical behavior of the MTP model than its single-layer counterpart. MTP displays a Neimark-Sacker bifurcation, leading to oscillations of arbitrarily large period or pseudo-periodic oscillations. >>

<< Moreover, MTP admits period-two oscillations without negative regulatory interactions, whereas single-layer systems only display discontinuous hybrid transitions.  >> 

Hanlin Sun, Filippo Radicchi, Ginestra Bianconi. Triadic percolation on multilayer networks. arXiv: 2510.09341v1 [nlin.AO]. Oct 10, 2025.

https://arxiv.org/abs/2510.09341

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

Keywords: gst, network, chaos, 

percolation, multilayer triadic 

percolation, higher-order 

interactions, triadic interactions.

# gst: effects of inertia on the asynchronous state of a disordered Kuramoto model.

<< ️(AA) investigate the role of inertia in the asynchronous state of a disordered Kuramoto model. (They) extend an iterative simulation scheme to the case of the Kuramoto model with inertia in order to determine the self-consistent fluctuation statistics, specifically, the power spectra of network noise and single oscillators. >>

<< ️Comparison with network simulations demonstrates that this works well whenever the system is in an asynchronous state. >>

 

 << ️(AA) also find an unexpected effect when varying the degree of inertia: the correlation time of the oscillators becomes minimal at an intermediate mass of the oscillators; correspondingly, the power spectra appear flatter and thus more similar to white noise around the same value of mass. (They) also find a similar effect for the Lyapunov spectra of the oscillators when the mass is varied. >>

Yagmur Kati, Ralf Toenjes, Benjamin Lindner. Effects of inertia on the asynchronous state of a disordered Kuramoto model. Phys. Rev. E 112, 044301. Oct 6, 2025.

https://journals.aps.org/pre/abstract/10.1103/xt4m-bkp8

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

Keywords: gst, networks, noise, order, disorder, fluctuations, inertia, asynchronous states, transitions, Kuramoto model.

# gst: effective-medium theory for elastic systems with correlated disorder.

<< ️Correlated structures are intimately connected to intriguing phenomena exhibited by a variety of disordered systems such as soft colloidal gels, bio-polymer networks and colloidal suspensions near a shear jamming transition. The universal critical behavior of these systems near the onset of rigidity is often described by traditional approaches as the coherent potential approximation - a versatile version of effective-medium theory that nevertheless have hitherto lacked key ingredients to describe disorder spatial correlations. >>

<< ️Here (AA) propose a multi-purpose generalization of the coherent potential approximation to describe the mechanical behavior of elastic networks with spatially-correlated disorder. (They) apply (their) theory to a simple rigidity-percolation model for colloidal gels and study the effects of correlations in both the critical point and the overall scaling behavior. (AA) find that although the presence of spatial correlations (mimicking attractive interactions of gels) shifts the critical packing fraction to lower values, suggesting sub-isostatic behavior, the critical coordination number of the associated network remains isostatic. More importantly, (AA) discuss how their theory can be employed to describe a large variety of systems with spatially-correlated disorder. >>

Jorge M. Escobar-Agudelo, Rui Aquino, Danilo B. Liarte. Effective-medium theory for elastic systems with correlated disorder. arXiv: 2510.02090v1 [cond-mat.stat-mech]. Oct 2, 2025.

https://arxiv.org/abs/2510.02090

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

Keywords: gst, elasticity, networks, elastic networks, disorder, disorder & fluctuations.

# brain: network representations reveal structured uncertainty in music.

<< ️Music, as a structured yet perceptually rich experience, can be modeled as a network to uncover how humans encode and process auditory information. While network-based representations of music are increasingly common, the impact of feature selection on structural properties and cognitive alignment remains underexplored. >>

<< ️In this study, (AA) evaluated eight network models, each constructed from symbolic representations of piano compositions using distinct combinations of pitch, octave, duration, and interval, designed to be representative of existing approaches in the literature. By comparing these models through topological metrics, entropy analysis, and divergence with respect to inferred cognitive representations, (They) assessed both their structural and perceptual efficiency.  >>

<< ️(AA) findings reveal that simpler, feature-specific models better match human perception, whereas complex, multidimensional representations introduce cognitive inefficiencies. These results support the view that humans rely on modular, parallel cognitive networks--an architecture consistent with theories of predictive processing and free energy minimization. >>

<< ️Moreover, (AA) find that musical networks are structurally organized to guide attention toward transitions that are both uncertain and inferable. The resulting structure concentrates uncertainty in a few frequently visited nodes, creating local entropy gradients that alternate between stable and unpredictable regions, thereby enabling the expressive dynamics of tension and release that define the musical experience. >> 

<< ️These findings show that network structures make the organization of uncertainty in music observable, offering new insight into how patterned flows of expectation shape perception, and open new directions for studying how musical structures evolve across genres, cultures, and historical periods through the lens of network science. >>

Lluc Bono Rosselló, Robert Jankowski, et al. Network representations reveal structured uncertainty in music. arXiv: 2509.14053v1 [physics.soc-ph]. 17 Sep 17,  2025.

https://arxiv.org/abs/2509.14053

Also: brain, music, jazz, perception, uncertainty, network, in https://www.inkgmr.net/kwrds.html 

Keywords: brain, music, jazz, perception, auditory information, networks, structural properties, cognitive alignment, uncertainty, uncertain-- inferable transitions.

# brain: self-organized learning emerges from coherent coupling of critical neurons.

<< ️Deep artificial neural networks have surpassed human-level performance across a diverse array of complex learning tasks, establishing themselves as indispensable tools in both social applications and scientific research. >>

<< ️Despite these advances, the underlying mechanisms of training in artificial neural networks remain elusive. >>

<< ️Here, (AA) propose that artificial neural networks function as adaptive, self-organizing information processing systems in which training is mediated by the coherent coupling of strongly activated, task-specific critical neurons. >>

<< ️(AA) demonstrate that such neuronal coupling gives rise to Hebbian-like neural correlation graphs, which undergo a dynamic, second-order connectivity phase transition during the initial stages of training. Concurrently, the connection weights among critical neurons are consistently reinforced while being simultaneously redistributed in a stochastic manner. >>

<< ️As a result, a precise balance of neuronal contributions is established, inducing a local concentration within the random loss landscape which provides theoretical explanation for generalization capacity. >>

<< ️(AA) further identify a later on convergence phase transition characterized by a phase boundary in hyperparameter space, driven by the nonequilibrium probability flux through weight space. The critical computational graphs resulting from coherent coupling also decode the predictive rules learned by artificial neural networks, drawing analogies to avalanche-like dynamics observed in biological neural circuits. >>

<< ️(AA) findings suggest that the coherent coupling of critical neurons and the ensuing local concentration within the loss landscapes may represent universal learning mechanisms shared by both artificial and biological neural computation. >>

Chuanbo Liu, Jin Wang. Self-organized learning emerges from coherent coupling of critical neurons. arXiv: 2509.00107v1 [cond-mat.dis-nn]. Aug 28, 2025.

https://arxiv.org/abs/2509.00107

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

Keywords: gst, brain, neurons, networks, randomness, transitions, ai (artificial intell) (bot), learning mechanisms, self-organized learning, artificial neural networks, deep learning, neuronal coupling, criticality, stochasticity, avalanche-like dynamics.

# brain: spontaneous emergence of metacognition in neuronal computation.

<< ️Metacognition, a hallmark of human intelligence, enables individuals to assess prediction uncertainty, providing an advantage over artificial intelligence in anticipating risks and performing tasks that demand trustworthiness and reliability. >>

<< ️Here, (AA) demonstrate that metacognition can naturally emerge in recurrent neural networks trained on cognitive tasks without guidance from any probabilistic inference rules or additional network architectures. Through naturally embedded nonlinear coupling with the mean of the network output, the covariance of the network output engages in metacognition by assessing the uncertainty associated with the mean, which represents the task responses. >>

<< ️(AA) further propose testable predictions about how key features of neuronal computation in the brain—noise, neuronal correlations, and heterogeneity—contribute to metacognition. >>

Hengyuan Ma, Wenlian Lu, Jianfeng Feng. Spontaneous emergence of metacognition in neuronal computation. Phys. Rev. Research 7, 033188. Aug 22, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/f1hv-bf1f

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

Keywords: gst, brain, cognition, metacognition, learning, memory, networks, biological neural networks, biological information processing, decision making, uncertainty, stochasticity, noise, chaos.

# gst: stability of twisted states; the role of phase lag, pairwise and higher-order interactions.

<< ️Stability analysis remains a key focus in the nonlinear field. The stability of oscillator networks considering phase-lag coupling is still an unsolved puzzle. Here, (AA)  investigate the linear stability using the maximal Lyapunov exponent and evaluate the basin stability by numerical simulations. >>

<< ️The results show that the phase lag has no significant effect on the proportion of twisted states with linear stability and on their basin sizes, without considering higher-order interactions. In contrast to the stabilizing effect of higher-order interactions on twisted states, pairwise coupling suppresses their linear stability but enhances their basin stability. >>

<< ️When pairwise coupling dominates, phase lag acts to strengthen the linear stability of the twisted state. Furthermore, the phase lag reduces the degree of ordering of the system and shrinks the basin of the twisted state. >>

<< ️These results highlight the synergistic effect of phase lag with pairwise and higher-order interactions on twisted-state basins. >>

Xueqin Wang, Dong Yu, et al. Stability of twisted states: The role of phase lag, pairwise and higher-order interactions. Phys. Rev. E 112, 024202. Aug 1, 2025.

https://journals.aps.org/pre/abstract/10.1103/qmgz-h5qm

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

Keywords: gst, network, chimera, phase lags, pause, coupled oscillators, synchronization.

# gst: breakdown of stochastic resonance in complex networks

<< ️In networked systems, stochastic resonance (SR) occurs as a collective phenomenon where the entire stochastic network resonates with a weak applied periodic signal. Beyond the interplay among the network coupling, the amplitude of the external periodic signal, and the intensity of stochastic fluctuations, the maintenance of stochastic resonance also crucially depends on the resonance capacity of each oscillator composing the network. This scenario raises the question: Can local defects in the ability of oscillators to resonate break down the stochastic resonance phenomenon in the entire network?  >>

Jonah E. Friederich, Everton S. Medeiros, et al. Breakdown of stochastic resonance in complex networks. Phys. Rev. E 112, 014218. Jul 21, 2025.

https://journals.aps.org/pre/abstract/10.1103/fc2t-275m

<< ️First, (AA) found that the combinations of network coupling and noise intensity for the maintenance of SR form tongue-like structures, specifying different optimal values of these parameters depending on the number of non-resonant units. Subsequently, (They) verified that, counter-intuitively, increasing the network coupling intensity causes SR to globally fail in the presence of a few non-resonant oscillators. Additionally, the upper limit of the coupling intensity diminishes as the number of nonresonant units increases. Moreover, (They) observed that for the maintenance of SR in (Their) network, the number of non-resonant oscillators is a nonlinear function of their dissimilarity level. >>

arXiv: 2502.06626v1 [nlin.AO]. Feb 10, 2025. 

https://arxiv.org/abs/2502.06626

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

Keywords: gst, networks, coupled oscillators, stochasticity, stochastic resonance

# gst: random interaction in active matter models; critical changes in Vicsek's scenario.

<< Randomness plays a key role in the order transition of active matter but has not yet been explicitly considered in pairwise interaction connection. In this paper, (AA) introduce the perception rate 𝑃 into the Vicsek model as the probability of the interaction connections and model the connections as superposition states. (They) show that with increasing 𝑃, the polar order number undergoes an order transition and then saturation. >>

<< The order transition is a first-order phase transition with band formation, and the effect of 𝑃 is different from density. The change of the order number is linked with the interaction structure. The order transition, order saturation, and phase separation correspond to different critical changes in the local interaction number. >>

<< The global interaction structure is further analyzed as a network. The decrease of 𝑃 is comparable to random edge removal, under which the network experiences modal transitions near the critical points of the order number, and the network exhibits surprising robustness.  (AA) results suggest that random interaction can be a new important factor in active matter models, with potential applications in robotic swarms and social activities. >>

Ruizhi Jin, Kejun Dong. Role of random interaction connection in the order transition of active matter based on the Vicsek model. Phys. Rev. E 111, 064122. Jun 17, 2025.

https://journals.aps.org/pre/abstract/10.1103/9rdd-tbn7

arXiv: 2501.10669v1 [cond-mat.soft]. Jan 18, 2025. 

https://arxiv.org/abs/2501.10669

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

Keywords: gst, active matter, network, randomness, perception, criticality, transitions, swarm.

# gst: self-organization to multicriticality; when a system can self-organize to a new type of phase transition while staying on the verge of another.

<< Self-organized criticality is a well-established phenomenon, where a system dynamically tunes its structure to operate on the verge of a phase transition. Here, (AA) show that the dynamics inside the self-organized critical state are fundamentally far more versatile than previously recognized, to the extent that a system can self-organize to a new type of phase transition while staying on the verge of another. >>

<< In this first demonstration of self-organization to multicriticality, (AA) investigate a model of coupled oscillators on a random network, where the network topology evolves in response to the oscillator dynamics. (They) 

 show that the system first self-organizes to the onset of oscillations, after which it drifts to the onset of pattern formation while still remaining at the onset of oscillations, thus becoming critical in two different ways at once. >>

 

<< The observed evolution to multicriticality is robust generic behavior that (AA) expect to be widespread in self-organizing systems. Overall, these results offer a unifying framework for studying systems, such as the brain, where multiple phase transitions may be relevant for proper functioning.>>

Silja Sormunen, Thilo Gross, Jari Saramäki. Self-organization to multicriticality. arXiv: 2506.04275v1 [nlin.AO]. Jun 4, 2025. 

https://arxiv.org/abs/2506.04275

Also: network, random, self-assembly, transition, brain, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, network, random, self-assembly, transition, phase transition, multiple phase transitions, self-organizing systems, self-organized criticality, multicriticality, brain.

# gst: apropos of weakness, weak but influential; nonlinear contributions of structural connectivity to human cognitive abilities and brain functions.

<< Diverse human cognitive abilities are rooted in brain structural connectivity which has weights spanning several orders of magnitude. However, due to false-positive challenges in tractography, weak connectivity has been often treated as noise and ignored - despite its prevalence across mammalian brains. >>

Here AA show << that weak connectivity significantly predicts human cognitive abilities and supports brain functions through amplification of its small weight in a nonlinear manner. >>

AA found that << weak connectivity involves high individual variability and significantly predicts general cognitive ability and memory in individuals, and it is also critical for whole-brain dynamic simulation and structure-function coupling. Importantly, fusing two post-tractography filtering methods of streamlines potentially results in more reliable connectivity that preserves weak links and outperforms conventional thresholding in predicting cognitive abilities and functional connectivity. >>

<< At the network level, weak connectivity expands the operational capacity of brain networks to enhance both global integration and fine-grained segregation, thereby supporting a functional balance essential for cognitive abilities. >>

<< Finally, (AA) identified a specific type of weak connectivity mainly linking visual/motor to limbic areas with negative gene co-expression, which has a disproportionately large impact on cognitive predictions and network dynamics. >>

Rong Wang, Zhao Chang, et al. Weak but influential: Nonlinear contributions of structural connectivity to human cognitive abilities and brain functions. arXiv: 2505.24125v1 [q-bio.NC]. May 30, 2025.

https://arxiv.org/abs/2505.24125

Also: brain, network, weak, noise, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, brain, network, noise,  weakness, weak connectivity,  brain structural connectivity, tractography, multiple tractography algorithms, cognitive ability and memory, individual variability, global integration, fine-grained segregation, limbic areas.

# gst: disorder, chimera state, traveling chimera state, and synchronization by weak temporal couplings.

<< The mechanisms of self-sustained oscillations of brain rhythms have been studied for a long time and it is revealed that the emergence of a pacemaker loop takes a key role for these rhythms. However, it is unclear how this pacemaker loop plays a role in the resting state of the brain, where the characteristic slow-wave activities show a multi-scaled feature and can switch easily between different dynamics states. >>

<< To study this problem, herein (AA) present a neural model of pacemaker looplike network, with a weak temporal electrical coupling to mark the resting state of the brain. (They) find that different dynamics patterns can be generated by this model, including the disorder, traveling chimera state, chimera state, and synchronization. >>

<< Interestingly, (AA) observe a sensitive switching effect between the region of traveling chimera state and that of chimera state, which may provide new insights to the mechanism of quickly switching between different rhythms of the brain in the resting state. >>

<< Further, (AA) introduce an index 𝑄 to describe the fluctuations of the local order parameter of network and conjecture that there is a new regularity caused by the fluctuations. (They) find that 𝑄 is optimally dependent on the matching of parameters and thus confirms the conjecture. Moreover, (they) show that the observed traveling chimera state is robust to different forms of temporal couplings. >>

Wenbin Mao, Guoshen Liang, Zonghua Liu. Traveling chimera states by weak temporal couplings. Phys. Rev. E 111, 054220. May 27, 2025.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.054220

Also: network, brain, disorder & fluctuations, waves, chimera, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, network, brain, disorder & fluctuations, waves, chimera, brain rhythms, brain resting state, self-sustained oscillations, pacemaker loop network, traveling chimera state, temporal coupling.

# gst: hyperchaos and complex dynamical regimes in N-d neuron lattices.

AA << study the dynamics of N-dimensional lattices of nonchaotic Rulkov neurons coupled with a flow of electrical current. (They) consider both nearest-neighbor and next-nearest-neighbor couplings, homogeneous and heterogeneous neurons, and small and large lattices over a wide range of electrical coupling strengths. >>

<< As the coupling strength is varied, the neurons exhibit a number of complex dynamical regimes, including unsynchronized chaotic spiking, local quasi-bursting, synchronized chaotic bursting, and synchronized hyperchaos. >>

<< For lattices in higher spatial dimensions, (AA) discover dynamical effects arising from the ``destructive interference'' of many connected neurons and miniature ``phase transitions'' from coordinated spiking threshold crossings. In large two- and three-dimensional neuron lattices, (They) observe emergent dynamics such as local synchronization, quasi-synchronization, and lag synchronization. >>

<< These results illustrate the rich dynamics that emerge from coupled neurons in multiple spatial dimensions, highlighting how dimensionality, connectivity, and heterogeneity critically shape the collective behavior of neuronal systems. >>

Brandon B. Le, Dima Watkins. Hyperchaos and complex dynamical regimes in N-dimensional neuron lattices. arXiv: 2505.03051v1 [nlin.CD]. May 5, 2025.

https://arxiv.org/abs/2505.03051

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

Keywords: gst, brain, network, behavior, cooperation, cooperative behavior, chaos, hyperchaos, transitions, phase transitions, transition thresholds,  synchrony, dimensionality, topology of connectivity, intermittent bursting activity, interference, destructive interference.

# gst: how noise affects memory in linear recurrent networks

<< The effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous state of network, which receives a correlated or uncorrelated noise. >>

<< Two major properties are revealed: First, the memory reduced by noise is uniquely determined by the noise's power spectral density (PSD). Second, the memory will not decrease regardless of noise intensity if the PSD is in a certain class of distribution (including power law). >>

JingChuan Guan, Tomoyuki Kubota, et al. How noise affects memory in linear recurrent networks. Phys. Rev. Research 7, 023049. Apr 14, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.023049

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

Keywords: gst, noise, network, memory

# gst: synchronization and chaos in complex systems with delayed interactions.

<< Explaining the wide range of dynamics observed in ecological communities is challenging due to the large number of species involved, the complex network of interactions among them, and the influence of multiple environmental variables. >>

AA << consider a general framework to model the dynamics of species-rich communities under the effects of external environmental factors, showing that it naturally leads to delayed interactions between species, and analyze the impact of such memory effects on population dynamics. >>

<< Employing the generalized Lotka-Volterra equations with time delays and random interactions, (AA) characterize the resulting dynamical phases in terms of the statistical properties of community interactions. (Their) findings reveal that memory effects can generate persistent and synchronized oscillations in species abundances in sufficiently competitive communities. This provides an additional explanation for synchronization in large communities, complementing known mechanisms such as predator-prey cycles and environmental periodic variability. >>

<< Furthermore, (AA) show that when reciprocal interactions are negatively correlated, time delays alone can induce chaotic behavior. This suggests that ecological complexity is not a prerequisite for unpredictable population dynamics, as intrinsic memory effects are sufficient to generate long-term fluctuations in species abundances. >>

Francesco Ferraro, Christian Grilletta, et al. Synchronization and chaos in complex ecological communities with delayed interactions. arXiv: 2503.21551v1 [q-bio.PE]. Mar 27, 2025.

https://arxiv.org/abs/2503.21551

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

Keywords: gst, pause, silence, random, chaos, chaotic behavior, network, delay, time delay, delayed interactions, random interactions, memory effect 

# gst: apropos of nuanced dependencies in intricately coupled network, attractive-repulsive challenge in swarmalators with time-dependent speed.

AA << examine a network of entities whose internal and external dynamics are intricately coupled, modeled through the concept of ``swarmalators'' as introduced by O'Keeffe et al. (Nat. Commun., 8(1):1–13, 2017). (They) investigate how the entities' natural velocities impact the network's collective dynamics and path to synchronization. >>

<< Specifically, (AA) analyze two scenarios: one in which each entity has an individual natural velocity, and another where a group velocity is defined by the average of all velocities. >> 

Their << findings reveal two distinct forms of phase synchronization -- static and rotational -- each preceded by a complex state of attractive-repulsive interactions between entities. This interaction phase, which depends sensitively on initial conditions, allows for selective modulation within the network. By adjusting initial parameters, (AA) can isolate specific entities to experience attractive-repulsive interactions distinct from the group, prior to the onset of full synchronization. >>

<< This nuanced dependency on initial conditions offers valuable insights into the role of natural velocities in tuning synchronization behavior within coupled dynamic networks. >>️

Steve J. Kongni, Thierry Njougouo, et al. Attractive-repulsive challenge in swarmalators with time-dependent speed. arXiv: 2501.06048v1 [nlin.AO]. Jan 10, 2025. 

https://arxiv.org/abs/2501.06048

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

Keywords: gst, swarm, swarmalators, network

# gst: phenomenology of cracks in thin colloidal films (undergoing desiccation)

<< A number of geometric and topological properties of samples of crack-template based conductive films are examined to assess the degree to which Voronoi diagrams can successfully model structure and conductivity in such networks. >>

AA << analysis suggests that although Poisson-Voronoi diagrams are only partially successful in modeling structural features of real-world crack patterns formed in films undergoing desiccation, such diagrams can nevertheless be useful in situations where topological characteristics are more important than geometric ones. A phenomenological model is proposed that is more accurate at capturing features of the real-world crack patterns. >>️

Yuri Yu. Tarasevich, Andrei V. Eserkepov, et al. Phenomenological model of crack patterns in thin colloidal films undergoing desiccation. arXiv: 2501.07303v1 [cond-mat.dis-nn]. Jan 13, 2025.

https://arxiv.org/abs/2501.07303

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

Keywords: gst, crack, particles, network, crack pattern networks, Voronoi tessellations 

# 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 

# 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