Browsing by Author "Eroğlu, Deniz"
Now showing items 1-4 of 4
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Holocene climate forcings and lacustrine regime shifts in the Indian summer monsoon realm
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Publisher and Date:(Wıley, 2020)Extreme climate events have been identified both in meteorological and long-term proxy records from the Indian summer monsoon (ISM) realm. However, the potential of palaeoclimate data for understanding mechanisms triggering climate extremes over long time scales has not been fully exploited. A distinction between proxies indicating climate change, environment, and ecosystem shift is crucial for enabling a comparison with forcing mechanisms (e.g. El-Nino Southern Oscillation). In this study we ...
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Multifaceted Dynamics of Janus Oscillator Networks
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Publisher and Date:(Amer Physical Soc., 2019)Recent research has led to the discovery of fundamental new phenomena in network synchronization including chimera states explosive synchronization and asymmetry-induced synchronization. Each of these phenomena has thus far been observed only in systems designed to exhibit that one phenomenon which raises the questions of whether they are mutually compatible and if so under what conditions they co-occur. Here we introduce a class of remarkably simple oscillator networks that concurrently exhibit ...
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Network dynamics reconstruction from data
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Publisher and Date:(Scıentıfıc Technıcal Research Councıl Turkey-Tubıtak, 2020)We consider the problem of recovering the model of a complex network of interacting dynamical units from time series of observations. We focus on typical networks which exhibit heterogeneous degrees, i.e. where the number of connections varies widely across the network, and the coupling strength for a single interaction is small. In these networks, the behavior of each unit varies according to their connectivity. Under these mild assumptions, our method provides an effective network reconstruction ...
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Revealing Dynamics, Communities, and Criticality from Data
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Publisher and Date:(Amer Physical Soc, 2020)Complex systems such as ecological communities and neuron networks are essential parts of our everyday lives. These systems are composed of units which interact through intricate networks. The ability to predict sudden changes in the dynamics of these networks, known as critical transitions, from data is important to avert disastrous consequences of major disruptions. Predicting such changes is a major challenge as it requires forecasting the behavior for parameter ranges for which no data on the ...
