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N. Molkenthin

Publications and source records attributed to N. Molkenthin.

3 recordsLinked to original sources

Node-weighted recurrence analysis for path dynamics on networks

Trajectories of units moving on networks are relevant for nonlinear dynamical systems as diverse as polymers, ocean drifters, and human mobility. Although RQA is a well-researched tool with applications in many areas, it has rarely been used for spatial trajectories on networks. Here, we explore the use of RQA for paths on networks. We find that path dynamics on networks display recurrence patterns that are not often described in other applications of recurrence analysis. In particular, the combination of diagonal lines and perpendicular diagonal lines, indicates backtracking paths. We find that recurrence analysis for path dynamics on networks can be helpful to a) better understand the network structure if dynamic and recurrence plots are known, b) better understand the dynamics if network and recurrence plots are known, and c) understand the interaction between path dynamics and the underlying network.

physics.soc-ph

Emergence and co-existence of periodic and unstructured motion in future-avoiding random walks

Self-avoiding random walks on graphs can be seen as walkers interacting with their own past history. This letter considers a complementary class of dynamics: Mutual future avoiding random walks (MFARWs), where stochastically driven walkers are avoiding each others planned future trajectories. Such systems arise naturally in conceptual models of shared mobility. We show that periodic behavior emerges spontaneously in such MFARWs, and that periodic and unstructured behavior coexist, providing a first example of Chimera style behavior of non-oscillatory paths on networks. Further, we analytically describe and predict the onset of structure. We find that the phase transition from unstructured to periodic behavior is driven by a novel mechanism of self-amplifying coupling to the periodic components of the stochastic drivers of the system. In the context of shared mobility applications, these Chimera states imply a regime of naturally stable co-existence between flexible and line-based public transport.

nlin.AO

Selection of radio pulsar candidates using artificial neural networks

Radio pulsar surveys are producing many more pulsar candidates than can be inspected by human experts in a practical length of time. Here we present a technique to automatically identify credible pulsar candidates from pulsar surveys using an artificial neural network. The technique has been applied to candidates from a recent re-analysis of the Parkes multi-beam pulsar survey resulting in the discovery of a previously unidentified pulsar.

astro-ph.IM