Self-organized State Research Articles

Exploring the equilibrium and non-equilibrium properties of a cooperative trinuclear spin-crossover chain: The role of elastic frustration.

Among the large family of spin-crossover (SCO) solids, recent investigations focused on polynuclear SCO materials, whose specific molecular configurations allow the presence of multi-step transitions and elastic frustration. In this contribution, we develop the first elastic modeling of thermal and dynamical properties of trinuclear SCO solids. For that, we study a finite SCO open chain constituted of successive elastically coupled trinuclear (A=B=C) blocks, in which each site (A, B, and C) may occupy two electronic configurations, namely, low-spin (LS) and high-spin (HS) states, accompanied with structural changes. Intra- and inter-molecular springs couple the sites inside and between trimers. The model also includes the change of length inside and between the trinuclear units subsequent to the spin states changes. First, we studied the mechanical relaxation of a LS chain initially prepared with HS distances, from which we dissected the dynamics of the atomic displacements for various strengths of intra- and inter-molecular elastic constants. Second, we investigated the thermal properties of the chain at equilibrium, which revealed the existence of a rich variety of behaviors, going from: gradual LS to HS transition to multiple spin transitions with the presence of self-organized spin state structures in the plateaus. The latter were identified as emerging from antagonist short- and long-range elastic interactions between intra- and inter-block size changes. The present model opens several possible extensions, among which are the cases of coupled non-linear trimer molecules as well as that of inter-chain interactions with block-block interactions, leading to unexpected hysteretic spin transitions.

Equilibrium reconstruction method for self-organized plasmas on reversed field pinches with polarimeter-interferometer

In the reversed field pinch (RFP), plasmas exhibit various self-organized states. Among these, the three-dimensional (3D) helical state known as the “quasi-single-helical” (QSH) state enhances RFP confinement. However, accurately describing the equilibrium is challenging due to the presence of 3D structures, magnetic islands, and chaotic regions. It is difficult to obtain a balance between the available diagnostic and the real equilibrium structure. To address this issue, we introduce KTX3DFit, a new 3D equilibrium reconstruction code specifically designed for the Keda Torus eXperiment (KTX) RFP. KTX3DFit utilizes the stepped-pressure equilibrium code (SPEC) to compute 3D equilibria and uses polarimetric interferometer signals from experiments. KTX3DFit is able to reconstruct equilibria in various states, including axisymmetric, double-axis helical (DAx), and single-helical-axis (SHAx) states. Notably, this study marks the first integration of the SPEC code with internal magnetic field data for equilibrium reconstruction and could be used for other 3D configurations.

Emergent actin flows explain distinct modes of gliding motility

During host infection, Toxoplasma gondii and related unicellular parasites move using gliding, which differs fundamentally from other known mechanisms of eukaryotic cell motility. Gliding is thought to be powered by a thin layer of flowing filamentous (F)-actin sandwiched between the plasma membrane and a myosin-covered inner membrane complex. How this surface actin layer drives the various gliding modes observed in experiments—helical, circular, twirling and patch, pendulum or rolling—is unclear. Here we suggest that F-actin flows arise through self-organization and develop a continuum model of emergent F-actin flow within the confines provided by Toxoplasma geometry. In the presence of F-actin turnover, our model predicts the emergence of a steady-state mode in which actin transport is largely directed rearward. Removing F-actin turnover leads to actin patches that recirculate up and down the cell, which we observe experimentally for drug-stabilized actin bundles in live Toxoplasma gondii parasites. These distinct self-organized actin states can account for observed gliding modes, illustrating how different forms of gliding motility can emerge as an intrinsic consequence of the self-organizing properties of F-actin flow in a confined geometry.

Self-organized vortex phases and hydrodynamic interactions in Bos taurus sperm cells.

Flocking behavior is observed in biological systems from the cellular to superorganismal length scales, and the mechanisms and purposes of this behavior are objects of intense interest. In this paper, we study the collective dynamics of bovine sperm cells in a viscoelastic fluid. These cells appear not to spontaneously flock, but transition into a long-lived flocking phase after being exposed to a transient ordering pulse of fluid flow. Surprisingly, this induced flocking phase has many qualitative similarities with the spontaneous polar flocking phases predicted by Toner-Tu theory, such as anisotropic giant number fluctuations and nontrivial transverse density correlations, despite the induced nature of the phase and the clearly important role of momentum conservation between the swimmers and the surrounding fluid in these experiments. We also find a self-organized global vortex state of the sperm cells, and map out an experimental phase diagram of states of collective motion as a function of cell density and motility statistics. We compare our experiments with a parameter-matched computational model of persistently turning active particles and find that the experimental order-disorder phase boundary as a function of cell density and persistence time can be approximately predicted from measures of single-cell properties. Our results may have implications for the evaluation of sample fertility by studying the collective phase behavior of dense groups of swimming sperm.

Effects of magnetic helicity on 3D equilibria and self-organized states in KTX reversed field pinch

The reversed field pinch (RFP) is a toroidal magnetic configuration in which plasmas can spontaneously transform into different self-organized states. Among various states, the ‘quasi-single-helical’ (QSH) state has a dominant component for the magnetic field and significantly improves confinement. Many theoretical and experimental efforts have investigated the transitions among different states. This paper employs the multi-region relaxed magnetohydrodynamic model to study the properties of QSH and other states. The stepped-pressure equilibrium code (SPEC) is used to compute MHD equilibria for the Keda Torus eXperiment (KTX). The toroidal volume of KTX is partitioned into two subvolumes by an internal transport barrier. The geometry of this barrier is adjusted to achieve force balance across the interface, ensuring that the plasma in each subvolume is force-free and that magnetic helicity is conserved. By varying the parameters, we generate distinct self-organized states in KTX. Our findings highlight the crucial role of magnetic helicity in shaping these states. In states with low magnetic helicity in both subvolumes, the plasma exhibits axisymmetric behavior. With increasing core helicity, the plasma gradually transforms from an axisymmetric state to a double-axis helical state and finally to a single-helical-axis state. Elevated core magnetic helicity leads to a more pronounced dominant mode of the boundary magnetic field and a reduced core magnetic shear. This is consistent with previous experimental and numerical results in other RFP devices. We find a linear relationship between the plasma current and helicity in different self-organized states. Our findings suggest that KTX may enter the QSH state when the toroidal current reaches 0.72 MA. This study demonstrates that the stellarator equilibrium code SPEC unveils crucial RFP equilibrium properties, rendering it applicable to a broad range of RFP devices and other toroidal configurations.

Scaling law of the second-order structure function over the entire sandstorm process

This study reveals the competitive evolutionary process of the main driving factors in the early, middle and late stages of sandstorms, as shear turbulence becomes dominant and is then suppressed by enhanced thermal stability, based on quadrant analysis of the sand-laden turbulent wind field acquired from field observations over the entire sandstorm process. Moreover, the self-organized state of multiscale structures in the energy-containing region of the sand-laden turbulence is found to change significantly as the sandstorm develops. The logarithmic scaling law that governs the cumulative turbulent kinetic energy for the non-stationary flow in the early and late stages of the sandstorm is different from the existing theoretical formula. The corresponding rate of increase in the cumulative kinetic energy with increasing scale is much higher in these stages than in the middle stage of the sandstorm with steady flow. The change in self-organized state of turbulence is responsible for the flow acceleration and the thermal superimposed effect, rather than the addition of sand particles.

Self-Organized States from Solutions of Active Ring Polymers in Bulk and under Confinement.

In the present work, we study, by means of numerical simulations, the structural and dynamical behavior of a suspension of active ring polymers in bulk and under lateral confinement. At high activity, when changing the distance between the confining planes and the polymers' density, we identify the emergence of a self-organized dynamical state, characterized by the coexistence of slowly diffusing clusters of rotating disks and faster rings moving in between them. We further assess that self-organization is robust in a range of polymer sizes, and we identify a critical value of the activity, necessary to trigger cluster formation. This system has distinctive features resembling at the same time polymers, liquid crystals, and active systems, where the interplay between activity, topology, and confinement leads to a spontaneous segregation in an initially one-component solution.

Manipulation of self-organized multi-vortical states in active magnetic roller suspensions

Ensembles of active magnetic colloids demonstrate complex collective behavior and self-organization when driven out of equilibrium by external magnetic fields. The interplay between magnetic and hydrodynamic interactions often result in spontaneous self-assembly and the emergence of localized vortices in ensembles of ferromagnetic rollers. We report experimental and computational study of the self-organized multi-vortical state in ensembles of magnetic rollers under the imposed external confining potential realized by patterned substrates. We explore the behavior of the system on a substrate patterned with shallow wells ordered in a lattice with square symmetry and lattice spacing smaller than the wells’ diameter. We demonstrate, that ensembles of active magnetic rollers evolve in response to changes in the geometry of the confining lattice from a globally correlated state characterized by anti-ferromagnetic vortex ordering to a state with rapidly changing particle flows and self-organized vortical states with a lattice constant larger than one of the confining pattern. Our experimental observations are accompanied by numerical simulations based on phenomenological coarse grained particle dynamics coupled to Navier–Stokes hydrodynamics in shallow water approximation. The reported results provide insights into the collective behavior of active magnetic rollers under confinement and suggest strategies for the manipulation of collective dynamic states in active magnetic liquids.

Beyond Nature Versus Nurture: the Emergence of Emotion.

Affective science is stuck in a version of the nature-versus-nurture debate, with theorists arguing whether emotions are evolved adaptations or psychological constructions. We do not see these as mutually exclusive options. Many adaptive behaviors that humans have evolved to be good at, such as walking, emerge during development - not according to a genetically dictated program, but through interactions between the affordances of the body, brain, and environment. We suggest emotions are the same. As developing humans acquire increasingly complex goals and learn optimal strategies for pursuing those goals, they are inevitably pulled to particular brain-body-behavior states that maximize outcomes and self-reinforce via positive feedback loops. We call these recurring, self-organized states emotions. Emotions display many of the hallmark features of self-organized attractor states, such as hysteresis (prior events influence the current state), degeneracy (many configurations of the underlying variables can produce the same global state), and stability. Because most bodily, neural, and environmental affordances are shared by all humans - we all have cardiovascular systems, cerebral cortices, and caregivers who raised us - similar emotion states emerge in all of us. This perspective helps reconcile ideas that, at first glance, seem contradictory, such as emotion universality and neural degeneracy.

Electro-Elastic Modeling of Multi-Step Transitions in Two Elastically Coupled and Sterically Frustrated 1D Spin Crossover Chains

One-dimensional spin crossover (SCO) solids that convert between the low spin (LS) and the high spin (HS) states are widely studied in the literature due to their diverse thermal and optical characteristics which allow obtaining many original behaviors, such as large thermal hysteresis, incomplete spin transitions, as multi-step spin transitions with self-organized states. In the present work, we investigate the thermal behaviors of a system of two elastically coupled 1D mononuclear chains, using the electro-elastic model, by including an elastic frustration in the nearest neighbors (nn) bond length distances of each chain. The chains are made of SCO sites that are coupled elastically through springs with their nn and next-nearest neighbors. The elastic interchain coupling includes diagonal springs, while the nn inter-chain distance is fixed to that of the high spin state. The model is solved using MC simulations, performed on the spin states and the lattice distortions. When we only frustrate the first chain, we found a strong effect on the thermal dependence of the HS fraction of the second chain, which displays an incomplete spin transition with a significantly lowered transition temperature. In the second step, we frustrate both chains by imposing different frustration rates. Here, we demonstrate that for high frustration values, the thermal dependence of the total HS fraction exhibits multi-step spin transitions. The careful examination of the spin state structures in the plateau regions showed the coexistence of special dimerized ferro–antiferro patterns of type LL-HH-LL-HH along the first chain and HH-LL-HH-LL (H=HS and L=LS) along the second one, revealing that the two chains are antiferro-elastically coupled. This type of spatial modulation of the spin state and bond length distances is very attractive because it anticipates the possible existence of periodic structures in 2D lattices, made of alternate 1D SCO strings with HLHLHL structures, coupled in the ferro-like fashion along the interchain direction.

Maximum entropy states of collisionless positron–electron plasma in a dipole magnetic field

We are developing a positron–electron plasma trap based on a dipole magnetic field generated by a levitated superconducting magnet to investigate the physics of magnetized plasmas with mass symmetry as well as antimatter components. Such laboratory magnetosphere is deemed essential for the understanding of pair plasmas in astrophysical environments, such as magnetars and blackholes, and represents a novel technology with potential applications in antimatter confinement and the development of coherent gamma-ray lasers. The design of the device requires a preemptive analysis of the achievable self-organized steady states. In this study, we construct a theoretical model describing maximum entropy states of a collisionless positron–electron plasma confined by a dipole magnetic field and demonstrate efficient confinement of both species under a wide range of physical parameters by analyzing the effect of the three adiabatic invariants on the phase space distribution function. The theory is verified by numerical evaluation of spatial density, electrostatic potential, and toroidal rotation velocity for each species in correspondence with the maximum entropy state.

Raman scattering evidence on the correlation of middle range order and structural self-organization of As-S-Ge glasses in the intermediate phase region

The Raman scattering of bulk nonstoichiometric chalcogenide alloys along the pseudo-binary AsS3 – GeS4 tie-line, which completely lies in the intermediate phase (IP) region of As-S-Ge ternary system was investigated in order to reveal the structural transformations in charge of the unusual features of the middle range order, elastic and physical-chemical parameters of these glasses observed earlier. It is shown that very narrow compositional areas can form inside the IP with high level of structural self-organization, mainly due to sudden increase of the concentration of highly flexible species such as quasi-tetrahedral (QT) S=As(S1/2)3 s.u. that comprises 4-fold coordinated As atoms. In the (GeS4)x(AsS3)1-x ternary system such a compositional area appears around the Ge7.7As15.3S77 (x =0.33; < r > = 2.31) composition that is a strongly self-organized glass with an assessed concentration of QT S=As(S1/2)3 around 30 % of total atomic clusters being the building blocks of the structure. This composition consists of minimal number of atomic building species, apart from QT S=As(S1/2)3 s.u. and free sulfur only the AsS3 pyramids and edge-sharing (ES) GeS4 tetrahedra have been revealed. Actually this self-organized state seems to be compositionally “metastable” as the variation of Ge concentrations by approximately ±3.5at% transforms the most part of the QT S=As(S1/2)3 s.u. into either AsS3 pyramids or corner-sharing (CS) GeS4 tetrahedra, mixed with a number of others clusters of smaller concentration. A good correlation was found between the compositional dependence of Raman scattering normalized strengths and middle range ordering (MRO) parameters such as sizes of molecular domains (D) and correlated inter-domain distances (d), as well as the molar volume (Vm ) and longitudinal elastic modulus (CL). MRO parameters and molar volume exhibit global minima around composition (As15,3 S77 Ge7,7; x = 0.33; < r > = 2.31) corresponding to strong self - organized glass that assign it as glass with most “packed” MRO structure and meanwhile the elastic modulus reaches its maximum value.

Actin self-organization in gliding parasitic cells.

Following a playful introduction to the Toner-Tu flocking theory first inspired by the collective motion of animals, we will move down a million-fold in length scale to focus on “molecular flocks”: collectively moving actin filaments at the surface of the single-celled parasite Toxoplasma gondii. During host infection, apicomplexan parasites like Plasmodium and Toxoplasma use these myosin-powered surface actin movements to drive a form of cell locomotion called gliding, which differs fundamentally from the swim-or-crawl paradigm of eukaryotic cell motility. How does the collective motion of surface actin filaments emerge, and how does it drive the varied parasite gliding movements that we observe experimentally? I will present findings based on single-molecule imaging in live parasites and use continuum flocking theory to predict emergent filament flows in the unusual confines provided by parasite geometry. This molecular filament flocking model enables the exploration of distinct self-organized states tuned by filament lifetime, which can account for the diversity of observed Toxoplasma gliding motions. This theory-experiment interplay will illustrate how different forms of gliding motility can arise as an intrinsic consequence of emergent active filament flows on a complex surface.

Dimensional cross-over in self-organised super-radiant phases of ultra-cold atoms inside a cavity

We consider a condensate of ultra-cold bosonic atoms in a linear optical cavity illuminated by a two-pump configuration where each pump makes different angles with the direction of the cavity axis. We show that such a configuration allows a smooth transition from a one-dimensional quantum optical lattice configuration to a two-dimensional quantum optical lattice configuration induced by the cavity–atom interaction. Using a Holstein–Primakoff transformation, we find the atomic density profile of such a self-organised ground state in the super-radiant phase as a function of the angular orientations of the pumps in such a dynamical quantum optical lattice, and also provide an analysis of their structures in coordinate and momentum space. In the later part of the paper, we show how the corresponding results can also be qualitatively understood in terms of an extended Bose–Hubbard model in such a quantum optical lattice potential.

Time-Domain 3-DOF Ship Motion Modeling by a Self-Organizing State–Space Model with Measurement Data

Time-Domain 3-DOF Ship Motion Modeling by a Self-Organizing State–Space Model with Measurement Data

Local Evolution Model of the Communication Network for Reducing Outage Risk of Power Cyber-Physical System

The deep integration of power grids and communication networks is the basis for realizing the complete observability and controllability of power grids. The communication node or link is always built according to the physical nodes. This step is alternatively known as “designing with the same power tower”. However, the communication networks do not form a “one-to-one correspondence” relationship with the power physical network. The existing theory cannot be applied to guide the practical power grid planning. In this paper, a local evolution model of a communication network based on the physical power grid topology is proposed in terms of reconnection probabilities. Firstly, the construction and upgrading of information nodes and links are modeled by the reconnection probabilities. Then, the power flow entropy is employed to identify whether the power cyber-physical system (CPS) is at the self-organized state, indicating the high probability of cascading failures. In addition, on the basis of the cascading failure propagation model of the partially dependent power CPS, operation reliabilities of the power CPS are compared with different reconnection probabilities using the cumulative probability of load loss as the reliable index. In the end, a practical provincial power grid is analyzed as an example. It is shown that the ability of the power CPS to resist cascading failures can be improved by the local growth evolution model of the communication networks. The ability is greater when the probability of reconnection is p = 0.06. By updating or constructing new links, the change in power flow entropy can be effectively reduced.

Self‐organizing traffic control using carrying capacity modelling in adjacent weaving sections

The traffic carrying capacity of the road network is limited. When the limit is exceeded, traffic congestion will restrict the control and development of transportation systems. This paper aims to determine the connotation of traffic carrying capacity in some adjacent weaving sections (AWS) and put forward a novel calculation model for self-organizing carrying capacity. Firstly, the in-depth analysis found that each weaving section has a local-whole and interactive relationship with AWS. Secondly, the self-organizing critical state of AWS is analyzed by calculating the threshold from slow to congestion. Finally, the Renhe Interchange was used as an experimental object to study the carrying capacity under the self-organizing critical state of AWS. The VISSIM software and Microsoft Visual Studio 2020-C# software are employed to verify the model. The self-organizing critical occupancy rate before the optimization is 38.60%, and the carrying capacity is 7527 pcu/h. After optimization, the self-organizing critical occupancy rate is 48.70%, and the carrying capacity is 9497 pcu/h. The results show that the model can simulate the carrying capacity of self-organized criticality. It can also provide a basis for urban managers to maintain the stable development of the system and ensure the overall operation quality of the AWS.

SELF-ORGANIZING RESERVOIR NETWORK FOR ACTION RECOGNITION

Current research in human action recognition (HAR) focuses on efficient and effective modelling of the temporal features of human actions in 3-dimensional space. Echo State Networks (ESNs) are one suitable method for encoding the temporal context due to its short-term memory property. However, the random initialization of the ESN's input and reservoir weights may increase instability and variance in generalization. Inspired by the notion that input-dependent self-organization is decisive for the cortex to adjust the neurons according to the distribution of the inputs, a Self-Organizing Reservoir Network (SORN) is developed based on Adaptive Resonance Theory (ART) and Instantaneous Topological Mapping (ITM) as the clustering process to cater deterministic initialization of the ESN reservoirs in a Convolutional Echo State Network (ConvESN) and yield a Self-Organizing Convolutional Echo State Network (SO-ConvESN). SORN ensures that the activation of ESN’s internal echo state representations reflects similar topological qualities of the input signal which should yield a self-organizing reservoir. In the context of HAR task, human actions encoded as a multivariate time series signals are clustered into clustered node centroids and interconnectivity matrices by SORN for initializing the SO-ConvESN reservoirs. By using several publicly available 3D-skeleton-based action recognition datasets, the impact of vigilance threshold and reservoir perturbation of SORN in performing clustering, the SORN reservoir dynamics and the capability of SO-ConvESN on HAR task have been empirically evaluated and analyzed to produce competitive experimental results.

Helical flow states in active nematics.

We show that confining extensile nematics in three-dimensional (3D) channels leads to the emergence of two self-organized flow states with nonzero helicity. The first is a pair of braided antiparallel streams-this double helix occurs when the activity is moderate, anchoring negligible, and reduced temperature high. The second consists of axially aligned counter-rotating vortices-this grinder train arises between spontaneous axial streaming and the vortex lattice. These two unanticipated helical flow states illustrate the potential of active fluids to break symmetries and form complex but organized spatiotemporal structures in 3D fluidic devices.

A generalized Hasegawa–Mima equation in curved magnetic fields

We derive a model equation describing electrostatic plasma turbulence in general (inhomogeneous and curved) magnetic fields by analysing the effect of curved geometry on the ion fluid polarization drift velocity. The derived nonlinear equation generalizes the Hasegawa–Mima equation governing drift wave turbulence in a straight homogeneous magnetic field, and may serve as a toy model for the description of turbulent plasmas. The equation is most appropriate for configurations with a small$\boldsymbol {E}\times \boldsymbol {B}$drift velocity divergence, or a mild spatial change in$\boldsymbol {E}\times \boldsymbol {B}$drift velocity. We identify the conserved energy of the system, and obtain conditions on magnetic field topology for conservation of generalized enstrophy. Through numerical examples, we further show how the curvature of the magnetic field reshapes self-organized steady turbulent states.