Paper detail

Evolutionary Kuramoto Dynamics

Common models of synchronizable oscillatory systems consist of a collection of coupled oscillators governed by a collection of differential equations. The ubiquitous Kuramoto models rely on an {\em a priori} fixed connectivity pattern facilitates mutual communication and influence between oscillators. In biological synchronizable systems, like the mammalian suprachaismatic nucleus, enabling communication comes at a cost -- the organism expends energy creating and maintaining the system -- linking their development to evolutionary selection. Here, we introduce and analyze a new evolutionary game theoretic framework modeling the behavior and evolution of systems of coupled oscillators. Each oscillator in our model is characterized by a pair of dynamic behavioral traits: an oscillatory phase and whether they connect and communicate to other oscillators or not. Evolution of the system occurs along these dimensions, allowing oscillators to change their phases and/or their communication strategies. We measure success of mutations by comparing the benefit of phase synchronization to the organism balanced against the cost of creating and maintaining connections between the oscillators. Despite such a simple setup, this system exhibits a wealth of nontrivial behaviors, mimicking different classical games -- the Prisoner's Dilemma, the snowdrift game, and coordination games -- as the landscape of the oscillators changes over time. Despite such complexity, we find a surprisingly simple characterization of synchronization through connectivity and communication: if the benefit of synchronization $B(0)$ is greater than twice the cost $c$, $B(0) > 2c$, the organism will evolve towards complete communication and phase synchronization. Taken together, our model demonstrates possible evolutionary constraints on both the existence of a synchronized oscillatory system and its overall connectivity.

preprint2020arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.