Abrupt Phase Transition Research Articles

Hysteresis in a generalized Kuramoto model with a first-order approximate coupling function and inhomogeneous coupling strengths

We investigate hysteresis in a generalized Kuramoto model with identical oscillators, focusing on coupling strength inhomogeneity, which results in oscillators being coupled to others with varying strength, and a first-order approximation of general coupling functions. With the coupling function and the coupling strength inhomogeneity, each oscillator acquires an effective intrinsic frequency proportional to its individual coupling strength. This is analogous to the positive coupling strength-frequency correlation introduced explicitly or implicitly in some previous models with nonidentical oscillators that show explosive synchronization and hysteresis. Through numerical simulations and analysis using truncated Gaussian, uniform, and truncated power-law coupling strength distributions, we observe that the system can exhibit abrupt phase transitions and hysteresis. The distribution of coupling strengths significantly affects the hysteresis regions within the parameter space of the coupling function. Additionally, numerical simulations of models with weighted networks including a brain network confirm the existence of hysteresis due to the first-order approximate coupling function and coupling strength inhomogeneity, suggesting the broad applicability of our findings to complex real-world systems.

Formation of vanadium dioxide nanocrystal arrays via post-growth annealing for stable and energy-efficient switches

The abrupt and reversible semiconductor-metal phase transition in vanadium dioxide nanocrystals has attracted considerable attention for potential applications in oxide electronics, including neuromorphic systems. This study presents a systematic investigation of post-growth annealing conditions for the formation of single VO2 M-phase nanocrystals arrays from VOx films synthesized by atomic layer deposition. The composition of the initial VOx films and the annealing parameters were found to significantly affect the morphology, phase composition and electrical properties of the obtained single nanocrystal arrays. Our results demonstrate that the formation of VO2 M-phase nanocrystal arrays occurs at annealing temperatures of 650 °C and above, irrespective of the initial film composition. More homogeneous in size nanocrystals are formed from initial VOx films with higher V+4 content. The structures with the initial V+4 content of 60 % annealed at 650 °C for 2 h demonstrates the resistive switching with an energy less than 150 fJ, and a total number of stable switching cycles more than 101⁰. Our results pave the way for the novel energy-efficient nanoelectronic and nanophotonic devices based on VO₂ nanoparticles.

Consensus decision making on a complete graph: complex behaviour from simple assumptions

In this paper we investigate a model of consensus decision making [Hartnett A. T., et al., Phys. Rev. Lett., 2016, 116, 038701] following a statistical physics approach presented in [Sarkanych P., et al., Phys. Biol., 2023, 20, 045005]. Within this approach, the temperature serves as a measure of fluctuations, not considered before in the original model. Here, we discuss the model on a complete graph. The main goal of this paper is to show that an analytical description may lead to a very rich phase behaviour, which is usually not expected for a complete graph. However, the variety of individual agent (spin) features - their inhomogeneity and bias strength - taken into account by the model leads to rather non-trivial collective effects. We show that the latter may emerge in a form of continuous or abrupt phase transitions sometimes accompanied by re-entrant and order-parameter flipping behaviour. In turn, this may lead to appealing interpretations in terms of social decision making. We support analytical predictions by numerical simulation. Moreover, while analytical calculations are performed within an equilibrium statistical physics formalism, the numerical simulations add yet another dynamical feature - local non-linearity or conformity of the individual to the opinion of its surroundings. This feature appears to have a strong impact both on the way in which an equilibrium state is approached as well as on its characteristics.

Assembling Smallest Prussian Blue Analogs Using Chiral Hydrogen Bond-Donating Unit toward Complete Phase Transition.

Exploring methods for assembling functional materials at the molecular level may yield functional expressions derived from the assembly method. This study developed novel switchable molecular assemblies characterized by abrupt, complete phase transitions promoted via hydrogen bonding with a chiral carboxylic acid. These assemblies were prepared by aggregating discrete molecules that are unresponsive to external stimuli. Furthermore, enantiopure hydrogen-bond donor (HBD) molecules provide switchable compounds with cooperative and abrupt phase transitions, whereas the racemic mixture of the HBD provides a hydrogen-bonded one-dimensional compound with a broad and incomplete phase transition when structural disordering is observed. This study presents a novel strategy for observing metal-to-metal electron-transfer-coupled spin transitions via hydrogen-bond formation.

Climate network analysis of extreme events: Tropical cyclones.

Climate networks based on surface air temperature data are analyzed to identify distinct signatures of tropical cyclones, which appear in the Indian Ocean. These networks, which are percolating networks, show an abrupt phase transition in the order parameter and the susceptibility during cyclonic events. The behavior seen is compared for the months October-November 2016, when three successive cyclones, viz., cyclone Kyant, cyclone Nada, and cyclone Vardah, were seen, and compared with a year where a single cyclone, cyclone Ockhi, was seen in December 2017. All these cyclones were seen in the Bay of Bengal. The microtransitions, i.e., the locations of jumps in the order parameter, for these two cases show distinct patterns. The signatures of the cyclones can be seen in other quantities like the node degrees and their geographic distributions and other network characterizers. We also compare these with a cyclone, cyclone Ashoba (2015), seen in the Arabian Sea where cyclones are rarer. The networks also show the signatures of precursor behavior, which has implications for further analysis.

Piezo strain-controlled phase transition in single-crystalline Mott switches for threshold-manipulated leaky integrate-and-fire neurons.

Electrical manipulation of the metal-insulator transition (MIT) in quantum materials has attracted considerable attention toward the development of ultracompact neuromorphic devices because of their stimuli-triggered transformations. VO2 is expected to undergo abrupt electronic phase transition by piezo strain near room temperature; however, the unrestricted integration of defect-free VO2 films on piezoelectric substrates is required to fully exploit this emerging phenomenon in oxide heterostructures. Here, we demonstrate the integration of single-crystalline VO2 films on highly lattice-mismatched PMN-PT piezoelectric substrates using a single-crystal TiO2-nanomembrane (NM) template. Using our strategy on heterogeneous integration, single-crystal-like steep transition was observed in the defect-free VO2 films on TiO2-NM-PMN-PT. Unprecedented TMI modulation (5.2 kelvin) and isothermal resistance of VO2 [ΔR/R (Eg) ≈ 18,000% at 315 kelvin] were achieved by the efficient strain transfer-induced MIT, which cannot be achieved using directly grown VO2/PMN-PT substrates. Our results provide a fundamental strategy to realize a single-crystalline artificial heterojunction for promoting the application of artificial neurons using emergent materials.

Explosive epidemic transitions induced by quarantine fatigue

Quarantine measures are one of the first lines of defense against the spread of infectious diseases. However, maintaining these measures over extended periods can be challenging due to a phenomenon known as quarantine fatigue. In this paper, we investigate the impact of quarantine fatigue on the spread of infectious diseases by using an epidemic model on random networks with cliques. In our model, susceptible individuals can be quarantined up to n times, after which they stop complying with quarantine orders due to fatigue. Our results show that quarantine fatigue may induce a regime in which increasing the probability of detecting and isolating infected individuals (along with their close contacts) could subsequently increase the expected number of cases at the end of an outbreak. Moreover, we observe that quarantine fatigue can trigger an abrupt phase transition at the critical reproduction number R0=1. Finally, we explore a scenario where a non-negligible number of individuals are infected at the beginning of an epidemic, and our results show that, depending on the value of n, an abrupt transition between a controlled epidemic and a large epidemic event can occur for R0<1.

Graded Inconel-stainless steel multi-material structure by inter- and intralayer variation of metal alloys

Additively manufactured multi-metal hybrid structures can be designed as functionally graded materials providing an optimized response at specific positions for particular applications. In this study, liquid dispersed metal powder bed fusion is used to synthesize a multi-metal structure based on Inconel 625 (IN625) and stainless steel 316L (S316L) stainless steel regions, built on a S316L base plate. Both alloys alternate several times along the build direction as well as within the individual sublayers. The multi-metal sample was investigated by optical microscopy, scanning electron microscopy, microhardness measurements, nanoindentation and energy-dispersive X-ray spectroscopy. Cross-sectional synchrotron X-ray micro-diffraction 2D mapping was carried out at the high-energy material science beamline of the storage ring PETRAIII in Hamburg. Sharp morphological S316L-to-IN625 interfaces along the sample's build direction are observed on the micro- and nanoscale. A gradual phase transition encompassing about 1 mm is revealed in the transverse direction. Mechanical properties change gradually following abrupt or smooth phase transitions between the alloys where a higher strength is determined for the superalloy. The two-dimensional distribution of phases can be assessed indirectly as S316L and IN625 in this multi-metal sample possess a <110> and a <100> fiber crystallographic texture, respectively. Tensile residual stresses of ∼900 and ∼800 MPa in build direction and perpendicular to it, respectively, are evaluated from measured residual X-ray elastic strains. Generally, the study indicates possibilities and limitations of liquid dispersed metal powder bed fusion for additive manufacturing of functionally graded materials with unique synergetic properties and contributes to the understanding of optimization of structurally and functionally advanced composites.

Modified Heider balance on Erdös-Rényi networks.

The lack of signed random networks in standard balance studies has prompted us to extend the Hamiltonian of the standard balance model. Random networks with tunable parameters are suitable for better understanding the behavior of standard balance as an underlying dynamics. Moreover, the standard balance model in its original form does not allow preserving tensed triads in the network. Therefore, the thermal behavior of the balance model has been investigated on a fully connected signed network recently. It has been shown that the model undergoes an abrupt phase transition with temperature. Considering these two issues, we examine the thermal behavior of the structural balance model defined on Erdös-Rényi random networks within the range of their connected regime. We provide a mean-field solution for the model. We observe a first-order phase transition with temperature for a wide range of connection probabilities. We detect two transition temperatures, T_{cold} and T_{hot}, characterizing a hysteresis loop. We find that with decreasing the connection probability, both T_{cold} and T_{hot} decrease. However, the slope of decreasing T_{hot} with decreasing connection probability is larger than the slope of decreasing T_{cold}. Hence, the hysteresis region gets narrower until it disappears in a certain connection probability. We provide a phase diagram in the temperature-tie density plane to accurately observe the metastable or coexistence region behavior. Then we justify our mean-field results with a series of Monte Carlo simulations.

Generic criterion for explosive synchronization in heterogeneous phase oscillator populations

Ordered and disordered behavior in large ensembles of coupled oscillators map to different functional states in a wide range of applications, e.g., active and resting states in the brain and stable and unstable power grid configurations. For this reason, explosive synchronization transitions, which facilitate fast, abrupt changes between these functional states, has recently seen significant interest from researchers. While previous work has identified properties of complex systems that support explosive synchronization, these investigations have been conducted largely on an ad-hoc basis. Here we provide an exact criterion for explosive synchronization in coupled phase oscillator ensembles by investigating the necessary relationship between dynamical and structural disorder. This result provides a critical step towards untangling the intertwined properties of complex systems responsible for abrupt phase transitions and bistability in biological and engineered systems.

Tamm plasmon polaritons induced active terahertz ultra-narrowband absorbing with MoS2

Tamm cavity resonant properties and singular phase behaviors of the one-dimensional photonic crystal stacked system with doped MoS2 have been comprehensively studied. Active multichannel terahertz ultra-narrowband wave absorption originated from the coupling effect of Tamm plasmon polaritons and Fabry-Perot modes. To reveal the critical absorption criterion, absorption amplitude changes in the same coupling mode order are discussed. We specifically discovered that this system has a pair of phase singularities (i.e., points of maximum absorptivity) corresponding to opposite abrupt phase transitions. It means an additional monitoring indicator used for high-sensitive label-free detection of media that outperforms metasurface absorption systems with one singularity is valuable, and no etching is required. More importantly, the phase transition phenomenon can be switched by electric-driven MoS2 via changing conductivity. These results demonstrated the proposed structure is suitable for potential terahertz applications including multifunctional phase-sensitive detectors and high-performance sensors.

Two-way enhancement of sensitivity by tailoring higher-order exceptional points

Higher-order exceptional points in non-Hermitian systems have recently been used as a tool to engineer high-sensitivity devices, attracting tremendous attention from multidisciplinary fields. Here, we present a simple yet effective scheme to enhance the device sensitivity by slightly deviating the gain-neutral-loss linear configuration to a triangular one, resulting in an abrupt phase transition from third-order to second-order exceptional points. Our analysis demonstrates that the exceptional points can be tailored by a judicious tuning of the coupling parameters of the system, resulting in enhanced sensitivity to a small perturbation. The tunable coupling also leads to a sharp change in the sensitivity slope, enabling the perturbation to be measured precisely as a function of coupling. This two-way detection of the perturbation opens up a rich landscape toward ultrasensitive measurements, which could be applicable to a wide range of non-Hermitian ternary platforms.

Synchronization of frustrated phase oscillators in the small-world networks

We numerically study the synchronization of an identical population of Kuramoto–Sakaguchi phase oscillators in Watts–Strogatz networks. We find that, unlike random networks, phase shift could enhance the synchronization in small-world networks. We also observe abrupt phase transition with hysteresis at some values of phase shifts in small-world networks, signs of an explosive phase transition. Moreover, we report the emergence of Chimera states at some values of phase shift close to the transition points, which consist of spatially coexisting synchronized and desynchronized domains.

Calculations of the Evolution of the Ca L23 Fine Structure in Amorphous Calcium Carbonate.

Amorphous calcium carbonate (ACC) has been found in many different organisms. Biogenic ACC is frequently a precursor in the formation of calcite and aragonite. The process of structural transformation is therefore of great interest in the study of crystallization pathways in biomineralization. Changes in the prepeak/main peak (L2'/L2) intensity ratio of the Ca L23-edge X-ray absorption spectroscopy (XAS) of Ca-rich particles in skeleton-building cells of sea urchin larva revealed that ACC precipitates through a continuum of states rather than through abrupt phase transitions involving two distinct phases as formerly believed. Using an atomic multiplet code, we show that only a tetragonal or "umbrella-like" distortion of the Ca coordination polyhedron can give rise to the observed continuum of states. We also show on the basis of the structures obtained from previous molecular dynamics simulations of hydrated nanoparticles that the Ca L23-edge is not sensitive to atomic arrangements in the early stages of the transformation process.

Criticality and network structure drive emergent oscillations in a stochastic whole-brain model

Understanding the relation between the structure of brain networks and their functions is a fundamental open question. Simple models of neural activity based on real anatomical networks have proven to be effective in describing features of whole-brain spontaneous activity when tuned at their critical point. In this work, we show that structural networks are indeed a crucial ingredient in the emergence of collective oscillations in a whole-brain stochastic model at criticality. We study analytically a stochastic Greenberg–Hastings cellular automaton in the mean-field limit, showing that it undergoes an abrupt phase transition with a bistable region. In particular, no global oscillations emerge in this limit. Then, we show that by introducing a network structure in the homeostatic normalization regime, the bistability may be disrupted, and the transition may become smooth. Concomitantly, through an interplay between network topology and weights, a large peak in the power spectrum appears around the transition point, signaling the emergence of collective oscillations. Hence, both the structure of brain networks and criticality are fundamental in driving the collective responses of whole-brain stochastic models.

Dynamic Routing of Heterogeneous Users After Traffic Disruptions Under a Mixed Information Framework

This research focuses on reducing traffic congestion using the competing strategies between informed and uninformed drivers. Under a mixed information framework, a navigation app provides within-day route suggestions to informed drivers using predicted information about the time-varying route habits of uninformed drivers. The informed users detour from initially proposed routes to minimize network congestion after traffic disruptions, pushing the system toward optimal equilibrium, while uninformed drivers make day-to-day decisions which push the system toward user equilibrium. Simulations considering varying fractions of informed drivers show that congestion is reduced during abrupt phase transition before reaching equilibrium by approximately 59.2% when 20% of drivers are informed, and is nearly eliminated when 80% of drivers are informed, which could be achieved through connected vehicle technologies. Shared memory multi-core parallelization improved the computational efficiency.

Synchronization on star-like graphs and emerging $\mathbb{Z}_{p}$ symmetries at strong coupling

Abstract We discuss the aspects of synchronization on inhomogeneous star-like graphs with long rays in the Kuramoto model framework. We assume the positive correlation between internal frequencies and degrees for all nodes which supports the abrupt first-order synchronization phase transition. It is found that different ingredients of the graph get synchronized at different critical couplings. Combining numerical and analytic tools, we evaluate all critical couplings for the long star graph. Surprisingly, it is found that at strong coupling there are discrete values of coupling constant that support the synchronized states with emerging $\mathbb{Z}_{p}$ symmetries. The stability of the synchronized phase is discussed, and the interpretation of the phase with emerging $\mathbb{Z}_{p}$ symmetry for the Josephson array on a long star graph is mentioned.

Epidemic spreading in populations of mobile agents with adaptive behavioral response

Despite the advanced stage of epidemic modeling, there is a major demand for methods to incorporate behavioral responses to the spread of a disease, such as social distancing and adoption of prevention methods. Mobility plays an important role on epidemic dynamics and is also affected by behavioral changes, but there are many situations in which real mobility data is incomplete or inaccessible. We present a model for epidemic spreading in temporal networks of mobile agents that incorporates local behavioral responses. Susceptible agents are allowed to move towards the opposite direction of infected agents in their neighborhood. We show that this mechanism considerably decreases the stationary prevalence when the spatial density of agents is low. However, for higher densities, the mechanism causes an abrupt phase transition, where a new bistable phase appears. We develop a semi-analytic approach for the case when the mobility is fast compared to the disease dynamics, and use it to argue that the bistability is caused by the emergence of spatial clusters of susceptible agents. Finally, we characterize the temporal networks formed in the fast mobility regime, showing how the degree distributions and other metrics are affected by the behavioral mechanism. Our work incorporates results previously known from adaptive networks into population of mobile agents, which can be further developed to be used in mobility-driven models.

Semiconductor-metal phase transition in oxides of Magneli series: VO and V-=SUB=-2-=/SUB=-O-=SUB=-3-=/SUB=-

A comparative analysis of the physical parameters of strongly correlated oxides VO and V2O3 has been carried out. It has been established that the semiconductor--metal phase transition in both VO and V2O3 has a complex Mott-Peierls character. Namely, as the temperature increases in both oxides, before the Peierls abrupt structural phase transition, the Mott phase transition, which is extended in temperature, take place. It has been discussed the reason for the fact that, despite the stabilization of the semiconductor phase by high-strength π-dimers or sigma-dimers, the temperatures of phase transitions are low (Tc=126 K (VO) and Tc=140 K (V2O3)). Keywords: Magnelis series, phase transformations, electron-electron correlations.

Network percolation reveals adaptive bridges of the mobility network response to COVID-19.

Human mobility is crucial to understand the transmission pattern of COVID-19 on spatially embedded geographic networks. This pattern seems unpredictable, and the propagation appears unstoppable, resulting in over 350,000 death tolls in the U.S. by the end of 2020. Here, we create the spatiotemporal inter-county mobility network using 10 TB (Terabytes) trajectory data of 30 million smart devices in the U.S. in the first six months of 2020. We investigate the bond percolation process by removing the weakly connected edges. As we increase the threshold, the mobility network nodes become less interconnected and thus experience surprisingly abrupt phase transitions. Despite the complex behaviors of the mobility network, we devised a novel approach to identify a small, manageable set of recurrent critical bridges, connecting the giant component and the second-largest component. These adaptive links, located across the United States, played a key role as valves connecting components in divisions and regions during the pandemic. Beyond, our numerical results unveil that network characteristics determine the critical thresholds and the bridge locations. The findings provide new insights into managing and controlling the connectivity of mobility networks during unprecedented disruptions. The work can also potentially offer practical future infectious diseases both globally and locally.