# gst: generation of disordered networks with targeted structural properties.

<< ️Disordered spatial networks are model systems that describe structures and interactions across multiple length scales. Scattering and interference of waves in these networks can give rise to structural phase transitions, localization, diffusion, and band gaps. >>

<< ️(AA) tune the degree and type of disorder introduced into initially crystalline networks by varying the bond-bending force constant in the strain energy and the temperature profile. >>

<< ️As a case study, (AA) statistically reproduce four disordered biophotonic networks exhibiting structural color. This work presents a versatile method for generating disordered networks with tailored structural properties. It will enable new insights into structure-property relations, such as photonic band gaps in disordered networks. >>

Florin Hemmann, Vincent Glauser, Ullrich Steiner, Matthias Saba. Computer Generation of Disordered Networks with Targeted Structural Properties. arXiv: 2601.10333v1 [cond-mat.dis-nn]. Jan 15, 2026.

https://arxiv.org/abs/2601.10333

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

Keywords: gst, networks, disorder, disordered networks, waves, phase transitions.

# gst: dynamical entanglement percolation with spatially correlated disorder.

<< ️The distribution of entanglement between the nodes of a quantum network plays a fundamental role in quantum information applications. In this work, (AA) investigate the dynamics of a network of qubits where each edge corresponds to an independent two-qubit interaction. By applying tools from percolation theory, (They) study how entanglement dynamically spreads across the network. (They) show that the interplay between unitary evolution and spatially correlated disorder leads to a non-standard percolation phenomenology, significantly richer than uniform bond percolation and featuring hysteresis. >>

Lorenzo Cirigliano, Valentina Brosco, Claudio Castellano, et al. Dynamical entanglement percolation with spatially correlated disorder. arXiv: 2601.05925v1 [quant-ph]. Jan 9, 2026.

https://arxiv.org/abs/2601.05925

Also: network, disorder, in https://www.inkgmr.net/kwrds.html     qubit, in https://flashontrack.blogspot.com/search?q=qubit

Keywords: gst, networks, classical complex networks, quantum networks, qubit, disorder, percolation, entanglement, hysteresis.

# gst: ambiguous signals and efficient codes.

<< In many biological networks the responses of individual elements are ambiguous. (AA) consider a scenario in which many sensors respond to a shared signal, each with limited information capacity, and ask that the outputs together convey as much information as possible about an underlying relevant variable. In a low noise limit where can make analytic progress, (They) show that individually ambiguous responses optimize overall information transmission. >>

Marianne Bauer, William Bialek. Ambiguous signals and efficient codes. arXiv: 2512.23531v1 [physics.bio-ph]. Dec 29, 2025. 

https://arxiv.org/abs/2512.23531

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

Keywords: gst, networks, uncertainty, noise, ambiguity, ambiguous encodings, mixed selectivity, optimization, signal-to-noise ratio. 

# gst: symmetries at the origin of hierarchical emergence.

<< ️Many systems of interest exhibit nested emergent layers with their own rules and regularities, and our knowledge about them seems naturally organised around these levels. This (AA) paper proposes that this type of hierarchical emergence arises as a result of underlying symmetries. By combining principles from information theory, group theory, and statistical mechanics, one finds that dynamical processes that are equivariant with respect to a symmetry group give rise to emergent macroscopic levels organised into a hierarchy determined by the subgroups of the symmetry. >>

<< ️The same symmetries happen to also shape Bayesian beliefs, yielding hierarchies of abstract belief states that can be updated autonomously at different levels of resolution. These results are illustrated in Hopfield networks and Ehrenfest diffusion, showing that familiar macroscopic quantities emerge naturally from their symmetries. Together, these results suggest that symmetries provide a fundamental mechanism for emergence and support a structural correspondence between objective and epistemic processes, making feasible inferential problems that would otherwise be computationally intractable. >>

Fernando E. Rosas. Symmetries at the origin of hierarchical emergence. arXiv: 2512.00984v1 [q-bio.NC]. Nov 30, 2025.

https://arxiv.org/abs/2512.00984

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

Keywords: gst, networks, transitions, nested emergent layers, hierarchical emergences, subgroup symmetry, Bayesian beliefs, Hopfield networks, Ehrenfest diffusion.

# gst: apropos of itinerant behaviors, from chaotic itinerancy to intermittent synchronization in complex networks.

<< ️Although synchronization has been extensively studied, important processes underlying its emergence have remained hidden by the use of global order parameters. Here, (AA) uncover how the route unfolds through a sequential transition between two well-known but previously unconnected phenomena: chaotic itinerancy (CI) and intermittent synchronization (IS). >>

<< ️Using a new symbolic dynamics, (They) show that CI emerges as a collective yet unsynchronized exploration of different domains of the high-dimensional attractor, whose dimension is reduced as the coupling increases, ultimately collapsing back into the reference chaotic attractor of an individual unit. At this stage, the IS can emerge as irregular alternations between synchronous and asynchronous phases. The two phenomena are therefore mutually exclusive, each dominating a distinct coupling interval and governed by different mechanisms. >>

<< ️Network structural heterogeneity enhances itinerant behavior since access to different domains of the attractor depends on the nodes' topological roles. The CI--IS crossover occurs within a consistent coupling interval across models and topologies. Experiments on electronic oscillator networks confirm this two-step process, establishing a unified framework for the route to synchronization in complex systems. >>

I. Leyva, Irene Sendiña-Nadal, Christophe Letellier, et al. From chaotic itinerancy to intermittent synchronization in complex networks. arXiv: 2511.09253v1 [nlin.AO]. Nov 12, 2025.

https://arxiv.org/abs/2511.09253

Also: network, behav, intermittency, transition, attractor, chaos, collapse, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, networks, behavior, intermittency, transitions, attractor, chaos, collapse, chaotic itinerancy, intermittent synchronization, structural heterogeneity, itinerant behavior.

# gst: energy transport and chaos in a one-dimensional disordered nonlinear stub lattice

<< ️(AA) investigate energy propagation in a one-dimensional stub lattice in the presence of both disorder and nonlinearity. In the periodic case, the stub lattice hosts two dispersive bands separated by a flat band; however, (They) show that sufficiently strong disorder fills all intermediate band gaps. By mapping the two-dimensional parameter space of disorder and nonlinearity, (AA) identify three distinct dynamical regimes (weak chaos, strong chaos, and self-trapping) through numerical simulations of initially localized wave packets. >>

<< ️When disorder is strong enough to close the frequency gaps, the results closely resemble those obtained in the one-dimensional disordered discrete nonlinear Schrödinger equation and Klein-Gordon lattice model. In particular, subdiffusive spreading is observed in both the weak and strong chaos regimes, with the second moment m_2 of the norm distribution scaling as m_2 ∝ t^0.33 and m_2 ∝ t^0.5, respectively. The system’s chaotic behavior follows a similar trend, with the finite-time maximum Lyapunov exponent Λ decaying as Λ ∝ t^−0.25 and Λ ∝ t^−0.3. For moderate disorder strengths, i.e., near the point of gap closing, (They) find that the presence of small frequency gaps does not exert any noticeable influence on the spreading behavior. >>

<< ️(AA) findings extend the characterization of nonlinear disordered lattices in both weak and strong chaos regimes to other network geometries, such as the stub lattice, which serves as a representative flat-band system. >>

Su Ho Cheong, Arnold Ngapasare, et al. Energy transport and chaos in a one-dimensional disordered nonlinear stub lattice. arXiv: 2511.04159v1 [nlin.CD].  Nov 6, 2025.

https://arxiv.org/abs/2511.04159

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

Keywords: gst, networks, waves, disorder, chaos, stub lattice, subdiffusive spreading.

# gst: emergence of chimeras states in one-dimensional Ising model with long-range diffusion.

<< ️In this work, (AA) examine the conditions for the emergence of chimera-like states in Ising systems. (They) study an Ising chain with periodic boundaries in contact with a thermal bath at temperature T, that induces stochastic changes in spin variables. To capture the non-locality needed for chimera formation, (They) introduce a model setup with non-local diffusion of spin values through the whole system. More precisely, diffusion is modeled through spin-exchange interactions between units up to a distance R, using Kawasaki dynamics. This setup mimics, e.g., neural media, as the brain, in the presence of electrical (diffusive) interactions. >>

<< ️(AA) explored the influence of such non-local dynamics on the emergence of complex spatiotemporal synchronization patterns of activity. Depending on system parameters (They) report here for the first time chimera-like states in the Ising model, characterized by relatively stable moving domains of spins with different local magnetization. (They) analyzed the system at T=0, both analytically and via simulations and computed the system's phase diagram, revealing rich behavior: regions with only chimeras, coexistence of chimeras and stable domains, and metastable chimeras that decay into uniform stable domains. >>

<< ️This study offers fundamental insights into how coherent and incoherent synchronization patterns can arise in complex networked systems as it is, e.g., the brain. >>

Alejandro de Haro García, Joaquín J. Torres. Emergence of Chimeras States in One-dimensional Ising model with Long-Range Diffusion. arXiv: 2510.24903v1 [cond-mat.dis-nn]. Oct 28, 2025. 

https://arxiv.org/abs/2510.24903

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

Keywords: gst, chimera, Ising systems, stochasticity, networks, brain.

# gst: predicting the response of structurally altered and asymmetrical networks.

<< ️(AA) investigate how the response of coupled dynamical systems is modified due to a structural alteration of the interaction. >>

<< ️The majority of the literature focuses on additive perturbations and symmetrical interaction networks. Here, (They) consider the challenging problem of multiplicative structural alterations and asymmetrical interaction coupling. >>

<< ️(AA) introduce a framework to approximate the averaged response at each network node for general structural alterations, including non-normal and asymmetrical ones. (Their) findings indicate that both the asymmetry and non-normality of the structural alterations impact the global and local responses at different orders in time. (They) propose a set of matrices to identify the nodes whose response is affected the most by the structural alteration. >>

Melvyn Tyloo. Predicting the response of structurally altered and asymmetrical networks. Phys. Rev. E 112, L042301. Oct 10, 2025. 

https://journals.aps.org/pre/abstract/10.1103/3s3d-qr4l

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

Keywords: gst, networks, disorder & fluctuations, transitions.

# gst: nonreciprocity induced spatiotemporal chaos: reactive vs dissipative routes.

<< ️Nonreciprocal interactions fundamentally alter the collective dynamics of nonlinear oscillator networks. Here (AA) investigate Stuart-Landau oscillators on a ring with nonreciprocal reactive or dissipative couplings combined with Kerr-type or dissipative nonlinearities. >>

<< ️Through numerical simulations and linear analysis, (They) uncover two distinct and universal pathways by which enhanced nonreciprocity drives spatiotemporal chaos. Nonreciprocal reactive coupling with Kerr-type nonlinearity amplifies instabilities through growth-rate variations, while nonreciprocal dissipative coupling with Kerr-type nonlinearity broadens eigenfrequency distributions and destroys coherence, which, upon nonlinear saturation, evolve into fully developed chaos. In contrast, dissipative nonlinearities universally suppress chaos, enforcing bounded periodic states. >>

<< ️(AA) findings establish a minimal yet general framework that goes beyond case-specific models and demonstrate that nonreciprocity provides a universal organizing principle for the onset and control of spatiotemporal chaos in oscillator networks and related complex systems. >>

Jung-Wan Ryu. Nonreciprocity induced spatiotemporal chaos: Reactive vs dissipative routes. arXiv: 2509.20992v1 [nlin.CD]. Sep 25, 2025

https://arxiv.org/abs/2509.20992

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

Keywords: gst, networks, instability, chaos, nonreciprocity, nonreciprocal interactions, nonreciprocal reactive-- dissipative couplings.

# gst: allosteric lever: toward a principle of specific allosteric response.

<< ️Allostery, the phenomenon by which the perturbation of a molecule at one site alters its behavior at a remote functional site, enables control over biomolecular function. >>

<< ️However, a general principle of allostery, i.e., a set of quantitative and transferable “ground rules,” remains elusive. It is neither a set of structural motifs nor intrinsic motions. >>

<< ️Focusing on elastic network models, (AA) here show that an allosteric lever—a mode-coupling pattern induced by the perturbation—governs the directional, source-to-target, allosteric communication: A structural perturbation of an allosteric site couples the excitation of localized hard elastic modes with concerted long-range soft-mode relaxation. >>

<< ️Perturbations of nonallosteric sites instead couple hard and soft modes uniformly. The allosteric response is shown to be generally nonlinear and nonreciprocal, and allows for minimal structural distortions to be efficiently transmitted to specific changes at distant sites. Allosteric levers exist in proteins and “pseudoproteins”—networks designed to display an allosteric response. >>

<< ️Interestingly, protein sequences that constitute allosteric transmission channels are shown to be evolutionarily conserved. >>

Maximilian Vossel, Bert L. de Groot, Aljaž Godec. Allosteric Lever: Toward a Principle of Specific Allosteric Response. Phys. Rev. X 15, 021097. Jun 20, 2025

https://journals.aps.org/prx/abstract/10.1103/wv2k-676p

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, allosteric lever, elasticity, networks, elastic networks.

# gst: chimera states on m-directed hypergraphs.

<< Chimera states are synchronization patterns in which coherent and incoherent regions coexist in systems of identical oscillators. This elusive phenomenon has attracted a lot of interest and has been widely studied, revealing several types of chimeras. Most cases involve reciprocal pairwise couplings, where each oscillator exerts and receives the same interaction, modeled via networks. >>️

<< However, real-world systems often have non-reciprocal, non-pairwise (many-body) interactions. From previous studies, it is known that chimera states are more elusive in the presence of non-reciprocal pairwise interactions, while easier to be found when the latter are reciprocal and higher-order (many-body). >>️

<< In this work, (AA) investigate the emergence of chimera states on non-reciprocal higher-order structures, called m-directed hypergraphs, and (They) show that, not only the higher-order topology allows the emergence of chimera states despite the non-reciprocal coupling, but also that chimera states can emerge because of the directionality. >>️

<< Finally, (AA) compare the latter results with the one resulting from non-reciprocal pairwise interactions: their elusiveness confirms that the observed phenomenon is thus due to the presence of higher-order interactions. The nature of phase chimeras has been further validated through phase reduction theory. >>️

Rommel Tchinda Djeudjo, Timoteo Carletti, et al. Chimera states on m-directed hypergraphs. arXiv: 2506.12511v1 [nlin.PS]. Jun 14, 2025. 

https://arxiv.org/abs/2506.12511

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

Keywords: gst, chimera, networks, non-reciprocal pairwise interactions, non-reciprocal higher-order structures, m-directed hypergraphs.

# gst: predicting the response of structurally altered and asymmetrical networks.

AA << investigate how the response of coupled dynamical systems is modified due to a structural alteration of the interaction. The majority of the literature focuses on additive perturbations and symmetrical interaction networks. >>

<< Here, (AA) consider the challenging problem of multiplicative perturbations and asymmetrical interaction coupling. (They) introduce a framework to approximate the averaged response at each network node for general structural perturbations, including non-normal and asymmetrical ones. >>

Their << findings indicate that both the asymmetry and non-normality of the structural perturbation impact the global and local responses at different orders in time. (AA) propose a set of matrices to identify the nodes whose response is affected the most by the structural alteration. >>

Melvyn Tyloo. Predicting the response of structurally altered and asymmetrical networks. arXiv: 2506.14609v1 [cond-mat.dis-nn]. Jun 17, 2025.

https://arxiv.org/abs/2506.14609

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

Keywords: gst, networks, multiplicative perturbations, asymmetrical interaction coupling

# aibot: noise balance and stationary distribution of stochastic gradient descent.

<< The stochastic gradient descent (SGD) algorithm is the algorithm (is used) to train neural networks. However, it remains poorly understood how the SGD navigates the highly nonlinear and degenerate loss landscape of a neural network. >>

<< In this work, (AA) show that the minibatch noise of SGD regularizes the solution towards a noise-balanced solution whenever the loss function contains a rescaling parameter symmetry. Because the difference between a simple diffusion process and SGD dynamics is the most significant when symmetries are present, (AA) theory implies that the loss function symmetries constitute an essential probe of how SGD works. (They) then apply this result to derive the stationary distribution of stochastic gradient flow for a diagonal linear network with arbitrary depth and width. >>

<< The stationary distribution exhibits complicated nonlinear phenomena such as phase transitions, broken ergodicity, and fluctuation inversion. These phenomena are shown to exist uniquely in deep networks, implying a fundamental difference between deep and shallow models. >>

Liu Ziyin, Hongchao Li, Masahito Ueda. Noise balance and stationary distribution of stochastic gradient descent. Phys. Rev. E 111, 065303. Jun 6, 2025.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.065303

Also: ai (artificial intell) (bot), network, noise, disorder & fluctuations, in https://www.inkgmr.net/kwrds.html 

Keywords: ai, artificial intelligence, noise, stochasticity, networks, neural networks, deep learning,stochastic gradient descent (SGD), transitions, phase transitions, broken ergodicity, fluctuation inversion

# gst: unstable fixed points in chaotic networks

<< Understanding the high-dimensional chaotic dynamics occurring in complex biological systems such as recurrent neural networks or ecosystems remains a conceptual challenge. For low-dimensional dynamics, fixed points provide the geometric scaffold of the dynamics. However, in high-dimensional systems, even the location of fixed points is unknown. >>

Here, AA << analytically determine the number and distribution of fixed points for a canonical model of a recurrent neural network that exhibits high-dimensional chaos. This distribution reveals that fixed points and dynamics are confined to separate shells in state space. Furthermore, the distribution enables (AA) to determine the eigenvalue spectra of the Jacobian at the fixed points, showing that each fixed point has a low-dimensional unstable manifold. >>

<< Despite the radial separation of fixed points and dynamics, (They)  find that the principal components of fixed points and dynamics align and that nearby fixed points act as partially attracting landmarks for the dynamics. >>

AA results << provide a detailed characterization of the fixed point geometry and its interplay with the dynamics, thereby paving the way towards a geometric understanding of high-dimensional chaos through their skeleton of unstable fixed points. >>

Jakob Stubenrauch, Christian Keup, et al. Fixed point geometry in chaotic neural networks. Phys. Rev. Research 7, 023203. May 29, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.023203

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

Keywords: gst, chaos, networks, neural networks, ecosystems, fixed points, unstable fixed points.

# gst: accelerated first detection in discrete-time quantum walks using sharp restarts.

<< Restart is a common strategy observed in nature that accelerates first-passage processes, and has been extensively studied using classical random walks. In the quantum regime, restart in continuous-time quantum walks (CTQWs) has been shown to expedite the quantum hitting times [Phys. Rev. Lett. 130, 050802 (2023)]. >>

 Here, AA << study how restarting monitored discrete-time quantum walks (DTQWs) affects the quantum hitting times. (They) show that the restarted DTQWs outperform classical random walks in target searches, benefiting from quantum ballistic propagation, a feature shared with their continuous-time counterparts. >>

Kunal Shukla, Riddhi Chatterjee, C. M. Chandrashekar. Accelerated first detection in discrete-time quantum walks using sharp restarts. Phys. Rev. Research 7, 023069. Apr 21, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.023069

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

Keywords: gst, networks, randomness, walk, random walk, quantum walk, stochasticity, sharp restart.

# gst: biased random walks on networks with stochastic resetting.

<< This study explores biased random walk dynamics with stochastic resetting on general networks. (AA) show that the combination of biased random walks and stochastic resetting makes significant contributions by analyzing the search efficiency. (They) derive two analytical expressions for the stationary distribution and the mean first passage time, which are related to the spectral representation of the probability transition matrix of a biased random walk without resetting. These expressions can be used to determine the capacity of a random walker to reach the specific target and probe a finite network. >>

AA << apply the analytical results to two types of networks, pseudofractal scale-free webs and T-fractals, which are constructed through an iterative process. (They) also extend a strategy to explore other complex structure networks or larger networks by leveraging the spectral properties. >>

Anlin Li, Xiaohan Sun. Biased random walks on networks with stochastic resetting. Phys. Rev. E 111, 054309. May 16, 2025.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.054309

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

Keywords: gst, networks, randomness, random walk, stochasticity, stochastic resetting.

# gst: apropos of critical transitions, a new approach to extreme events.

FIG. 1. Dynamics of excitable complex networks [coupling topologies: random (RN); small-world (SW); scale-free (SF); all-to-all (complete; CP)]. 

<< Unexpected and often irreversible shifts in the state or the dynamics of a complex system often accumulate in extreme events with likely disastrous impact on the system and its environment. Detection, understanding, and possible prediction of such critical transitions are thus of paramount importance across a variety of scientific fields. >>

<< The rather modest improvement achieved so far may be due previous research mostly concentrating on either particular subsystems, considered to be of vital importance for the generating mechanism of a critical transition, or on the system as a whole. These approaches only rarely take into account the intricate, time-dependent interrelatedness of subsystems that can essentially determine emerging behaviors underlying critical transitions. >> 

AA << uncover subsystems, network vertices, and the interrelatedness of certain subsystems, network edges, as tipping elements in a networked dynamical system, forming a time-evolving tipping subnetwork. (They)  demonstrate the existence of tipping subnetworks in excitable complex networks and in human epileptic brains. These systems can repeatedly undergo critical transitions that result in extreme events. >>

AA << findings reveal that tipping subnetworks encapsulate key properties of mechanisms involved in critical transitions. >>

Timo Bröhl, Klaus Lehnertz. Emergence of a tipping subnetwork during a critical transition in networked systems: A new avenue to extreme events. Phys. Rev. Research 7, 023109. May 1, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.023109

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

Keywords: gst, networks, excitable complex networks, network edges, network vertices, subnetwork, tipping subnetworks, small-worlds, unexpected shifts, transitions, critical transition, extreme events, interrelatedness, time-dependent interrelatedness.

# gst: emergent oscillations and chaos in noncompliant microfluidic networks.

<< Incompressible fluids in microfluidic networks with nonrigid channels can exhibit flow rate oscillations analogous to electric current oscillations in RLC (resistor, inductor, capacitor) circuits. This is due to the elastic deformation of channel walls that can store and release fluid, as electric capacitors can store and release electric charges. This property is quantified through the compliance of the system, defined as the volume change relative to the pressure change. >>

<< In systems with rigid walls and incompressible fluid, compliance vanishes, and no oscillations can occur through this mechanism. >>

Here, AA << show that not only oscillations but also chaos can emerge in the flow-rate dynamics of noncompliant microfluidic networks with incompressible fluid. Notably, these dynamics emerge spontaneously, even under time-independent driving pressures. The underlying mechanism is governed by the effect of fluid inertia, which becomes relevant at moderate Reynolds numbers observed in microfluidic systems exhibiting complex flow patterns. >>

<< The results are established using a combination of direct numerical simulations and a reduced model derived from modal analysis. This approach enables (AA) to determine the onset of oscillations, the associated bifurcations, the oscillation frequencies and amplitudes, and their dependence on the driving pressures. >>

Yanxuan Shao, Jean-Regis Angilella, Adilson E. Motter. Emergent oscillations and chaos in noncompliant microfluidic networks. Phys. Rev. Fluids 10, 054401. May 1, 2025.

https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.10.054401

arXiv: 2505.00068v1 [physics.flu-dyn]. 

https://arxiv.org/abs/2505.00068

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

Keywords: gst, networks, microfluidic networks, noncompliant networks with incompressible fluid, fluid inertia, 

driving pressures, elasticity, chaos.

# gst: strange attractors in complex networks

<< Disorder and noise in physical systems often disrupt spatial and temporal regularity, yet chaotic systems reveal how order can emerge from unpredictable behavior. Complex networks, spatial analogs of chaos, exhibit disordered, non-Euclidean architectures with hidden symmetries, hinting at spontaneous order. Finding low-dimensional embeddings that reveal network patterns and link them to dimensionality that governs universal behavior remains a fundamental open challenge, as it needs to bridge the gap between microscopic disorder and macroscopic regularities. >>

<< Here, the minimal space revealing key network properties is introduced, showing that non-integer dimensions produce chaotic-like attractors. >>

Pablo Villegas. Strange attractors in complex networks. Phys. Rev. E 111, L042301. Apr 15, 2025. 

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.L042301.  

arXiv: 2504.08629v1 [cond-mat.stat-mech] . Apr 11, 2025.

https://arxiv.org/abs/2504.08629

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

Keywords: gst, disorder, disorder & fluctuations, noise, networks, attractors, self-similarity, chaos 

# behav: the benefit of ignorance for traffic through a random congestible network.

<< When traffic is routed through a network that is susceptible to congestion, the self-interested decisions made by individual users do not, in general, produce the optimal flow. This discrepancy is quantified by the so-called "price of anarchy." >>

AA << consider whether the traffic produced by self-interested users is made better or worse when users have uncertain knowledge about the cost functions of the links in the network, and define a parallel concept that (They) call the "price of ignorance."  >>

AA << introduce a simple model in which fast, congestible links and slow, incongestible links are mixed randomly in a large network and users plan their routes with finite uncertainty about which of the two cost functions describes each link. >>

<< One of (Their) key findings is that a small level of user ignorance universally improves traffic, regardless of the network composition. Further, there is an optimal level of ignorance which, in (the) model, causes the self-interested user behavior to coincide with the optimum. Many features of (AA) model can be understood analytically, including the optimal level of user ignorance and the existence of critical scaling near the percolation threshold for fast links, where the potential benefit of user ignorance is greatest. >>️

Alican Saray, Calvin Pozderac, et al. The benefit of ignorance for traffic through a random congestible network. arXiv: 2503.09684v1 [cond-mat.dis-nn]. Mar 12, 2025.

https://arxiv.org/abs/2503.09684

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

Keywords: gst, networks, behavior,  randomness, uncertainty, price of anarchy, price of ignorance