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Now showing 1 - 10 of 54
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    Universality in spectral condensation
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Pavithran, Induja; Unni, Vishnu R.; Varghese, Alan J.; Premraj, D.; Sujith, R. I.; Vijayan, C.; Saha, Abhishek; Marwan, Norbert; Kurths, Jürgen
    Self-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study its occurrence in fluid mechanical, optical and electronic systems. We define a set of spectral measures to quantify this condensation spanning several dynamical systems. Further, we uncover an inverse power law behaviour of spectral measures with the power corresponding to the dominant peak in the power spectrum in all the aforementioned systems.
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    Dynamic Network Characteristics of Power-electronics-based Power Systems
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Ji, Yuxi; He, Wei; Cheng, Shijie; Kurths, Jürgen; Zhan, Meng
    Power flow studies in traditional power systems aim to uncover the stationary relationship between voltage amplitude and phase and active and reactive powers; they are important for both stationary and dynamic power system analysis. With the increasing penetration of large-scale power electronics devices including renewable generations interfaced with converters, the power systems become gradually power-electronics-dominant and correspondingly their dynamical behavior changes substantially. Due to the fast dynamics of converters, such as AC current controller, the quasi-stationary state approximation, which has been widely used in power systems, is no longer appropriate and should be reexamined. In this paper, for a better description of network characteristics, we develop a novel concept of dynamic power flow and uncover an explicit dynamic relation between the instantaneous powers and the voltage vectors. This mathematical relation has been well verified by simulations on transient analysis of a small power-electronics-based power system, and a small-signal frequency-domain stability analysis of a voltage source converter connected to an infinitely strong bus. These results demonstrate the applicability of the proposed method and shed an improved light on our understanding of power-electronics-dominant power systems, whose dynamical nature remains obscure.
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    Multiscale Spatiotemporal Analysis of Extreme Events in the Gomati River Basin, India
    (Basel : MDPI, 2021) Kalyan, AVS; Ghose, Dillip Kumar; Thalagapu, Rahul; Guntu, Ravi Kumar; Agarwal, Ankit; Kurths, Jürgen; Rathinasamy, Maheswaran
    Accelerating climate change is causing considerable changes in extreme events, leading to immense socioeconomic loss of life and property. In this study, we investigate the characteristics of extreme climate events at a regional scale to ‐understand these events’ propagation in the near fu-ture. We have considered sixteen extreme climate indices defined by the World Meteorological Or-ganization’s Expert Team on Climate Change Detection and Indices from a long‐term dataset (1951– 2018) of 53 locations in Gomati River Basin, North India. We computed the present and future spatial variation of theses indices using the Sen’s slope estimator and Hurst exponent analysis. The periodicities and non‐stationary features were estimated using the continuous wavelet transform. Bivariate copulas were fitted to estimate the joint probabilities and return periods for certain com-binations of indices. The study results show different variation in the patterns of the extreme climate indices: D95P, R95TOT, RX5D, and RX showed negative trends for all stations over the basin. The number of dry days (DD) showed positive trends over the basin at 36 stations out of those 17 stations are statistically significant. A sustainable decreasing trend is observed for D95P at all stations, indi-cating a reduction in precipitation in the future. DD exhibits a sustainable decreasing trend at almost all the stations over the basin barring a few exceptions highlight that the basin is turning drier. The wavelet power spectrum for D95P showed significant power distributed across the 2–16‐year bands, and the two‐year period was dominant in the global power spectrum around 1970–1990. One interest-ing finding is that a dominant two‐year period in D95P has changed to the four years after 1984 and remains in the past two decades. The joint return period’s resulting values are more significant than values resulting from univariate analysis (R95TOT with 44% and RTWD of 1450 mm). The difference in values highlights that ignoring the mutual dependence can lead to an underestimation of extremes. © 2021 by the author. Licensee MDPI, Basel, Switzerland.
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    Novel fixed-time stabilization of quaternion-valued BAMNNs with disturbances and time-varying coefficients
    (Springfield, MO : AIMS Press, 2020) Wei, Ruoyu; Cao, Jinde; Kurths, Jürgen
    In this paper, with the quaternion number and time-varying coefficients introduced into traditional BAMNNs, the model of quaternion-valued BAMNNs are formulated. For the first time, fixed-time stabilization of time-varying quaternion-valued BAMNNs is investigated. A novel fixed-time control method is adopted, in which the choice of the Lyapunov function is more general than in most previous results. To cope with the noncommutativity of the quaternion multiplication, two different fixed-time control methods are provided, a decomposition method and a non-decomposition method. Furthermore, to reduce the control strength and improve control efficiency, an adaptive fixed-time control strategy is proposed. Lastly, numerical examples are presented to demonstrate the effectiveness of the theoretical results. © 2020 the Author(s), licensee AIMS Press.
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    Interacting tipping elements increase risk of climate domino effects under global warming
    (Göttingen : Copernicus, 2021) Wunderling, Nico; Donges, Jonathan F.; Kurths, Jürgen; Winkelmann, Ricarda
    With progressing global warming, there is an increased risk that one or several tipping elements in the climate system might cross a critical threshold, resulting in severe consequences for the global climate, ecosystems and human societies. While the underlying processes are fairly well-understood, it is unclear how their interactions might impact the overall stability of the Earth's climate system. As of yet, this cannot be fully analysed with state-of-the-art Earth system models due to computational constraints as well as some missing and uncertain process representations of certain tipping elements. Here, we explicitly study the effects of known physical interactions among the Greenland and West Antarctic ice sheets, the Atlantic Meridional Overturning Circulation (AMOC) and the Amazon rainforest using a conceptual network approach. We analyse the risk of domino effects being triggered by each of the individual tipping elements under global warming in equilibrium experiments. In these experiments, we propagate the uncertainties in critical temperature thresholds, interaction strengths and interaction structure via large ensembles of simulations in a Monte Carlo approach. Overall, we find that the interactions tend to destabilise the network of tipping elements. Furthermore, our analysis reveals the qualitative role of each of the four tipping elements within the network, showing that the polar ice sheets on Greenland and West Antarctica are oftentimes the initiators of tipping cascades, while the AMOC acts as a mediator transmitting cascades. This indicates that the ice sheets, which are already at risk of transgressing their temperature thresholds within the Paris range of 1.5 to 2 ∘C, are of particular importance for the stability of the climate system as a whole.
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    Complex network approach for detecting tropical cyclones
    (Berlin ; Heidelberg : Springer, 2021) Gupta, Shraddha; Boers, Niklas; Pappenberger, Florian; Kurths, Jürgen
    Tropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.
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    Path integral solutions for n-dimensional stochastic differential equations under α-stable Lévy excitation
    (College Park, Md : [Verlag nicht ermittelbar], 2023) Zan, Wanrong; Xu, Yong; Kurths, Jürgen
    In this paper, the path integral solutions for a general n-dimensional stochastic differential equations (SDEs) with α-stable Lévy noise are derived and verified. Firstly, the governing equations for the solutions of n-dimensional SDEs under the excitation of α-stable Lévy noise are obtained through the characteristic function of stochastic processes. Then, the short-time transition probability density function of the path integral solution is derived based on the Chapman-Kolmogorov-Smoluchowski (CKS) equation and the characteristic function, and its correctness is demonstrated by proving that it satisfies the governing equation of the solution of the SDE, which is also called the Fokker-Planck-Kolmogorov equation. Besides, illustrative examples are numerically considered for highlighting the feasibility of the proposed path integral method, and the pertinent Monte Carlo solution is also calculated to show its correctness and effectiveness.
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    Epidemics with mutating infectivity on small-world networks
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Rüdiger, Sten; Plietzsch, Anton; Sagués, Francesc; Sokolov, Igor M.; Kurths, Jürgen
    Epidemics and evolution of many pathogens occur on similar timescales so that their dynamics are often entangled. Here, in a first step to study this problem theoretically, we analyze mutating pathogens spreading on simple SIR networks with grid-like connectivity. We have in mind the spatial aspect of epidemics, which often advance on transport links between hosts or groups of hosts such as cities or countries. We focus on the case of mutations that enhance an agent’s infection rate. We uncover that the small-world property, i.e., the presence of long-range connections, makes the network very vulnerable, supporting frequent supercritical mutations and bringing the network from disease extinction to full blown epidemic. For very large numbers of long-range links, however, the effect reverses and we find a reduced chance for large outbreaks. We study two cases, one with discrete number of mutational steps and one with a continuous genetic variable, and we analyze various scaling regimes. For the continuous case we derive a Fokker-Planck-like equation for the probability density and solve it for small numbers of shortcuts using the WKB approximation. Our analysis supports the claims that a potentiating mutation in the transmissibility might occur during an epidemic wave and not necessarily before its initiation. © 2020, The Author(s).
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    Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics
    (Bristol : IOP Publ., 2023) Bianconi, Ginestra; Arenas, Alex; Biamonte, Jacob; Carr, Lincoln D; Kahng, Byungnam; Kertesz, Janos; Kurths, Jürgen; Lü, Linyuan; Masoller, Cristina; Motter, Adilson E; Perc, Matjaž; Radicchi, Filippo; Ramaswamy, Ramakrishna; Rodrigues, Francisco A; Sales-Pardo, Marta; San Miguel, Maxi; Thurner, Stefan; Yasseri, Taha
    The 2021 Nobel Prize in Physics recognized the fundamental role of complex systems in the natural sciences. In order to celebrate this milestone, this editorial presents the point of view of the editorial board of JPhys Complexity on the achievements, challenges, and future prospects of the field. To distinguish the voice and the opinion of each editor, this editorial consists of a series of editor perspectives and reflections on few selected themes. A comprehensive and multi-faceted view of the field of complexity science emerges. We hope and trust that this open discussion will be of inspiration for future research on complex systems.
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    Evolving climate network perspectives on global surface air temperature effects of ENSO and strong volcanic eruptions
    (Berlin ; Heidelberg : Springer, 2021) Kittel, Tim; Ciemer, Catrin; Lotfi, Nastaran; Peron, Thomas; Rodrigues, Francisco; Kurths, Jürgen; Donner, Reik V.
    Episodically occurring internal (climatic) and external (non-climatic) disruptions of normal climate variability are known to both affect spatio-temporal patterns of global surface air temperatures (SAT) at time-scales between multiple weeks and several years. The magnitude and spatial manifestation of the corresponding effects depend strongly on the specific type of perturbation and may range from weak spatially coherent yet regionally confined trends to a global reorganization of co-variability due to the excitation or inhibition of certain large-scale teleconnectivity patterns. Here, we employ functional climate network analysis to distinguish qualitatively the global climate responses to different phases of the El Niño–Southern Oscillation (ENSO) from those to the three largest volcanic eruptions since the mid-20th century as the two most prominent types of recurrent climate disruptions. Our results confirm that strong ENSO episodes can cause a temporary breakdown of the normal hierarchical organization of the global SAT field, which is characterized by the simultaneous emergence of consistent regional temperature trends and strong teleconnections. By contrast, the most recent strong volcanic eruptions exhibited primarily regional effects rather than triggering additional long-range teleconnections that would not have been present otherwise. By relying on several complementary network characteristics, our results contribute to a better understanding of climate network properties by differentiating between climate variability reorganization mechanisms associated with internal variability versus such triggered by non-climatic abrupt and localized perturbations.