Distributed Actors: Cluster Management

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Explores galaxy cluster components, historical discoveries, X-ray and radio emissions, and gravitational lensing effects.

Covers clustering time series data using dynamic time warping, string metrics, and Markov models.

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Covers hybrid programming models, project proposals, thread safety, topology problems, and performance expectations in MPI.

Covers percolation theory, absorbed polymers, giant molecules, phase transition, scaling assumptions, and universal behavior in percolation models.

Explores properties of clusters and colorability threshold in graph coloring, including average connectivity and rigidity.

Explores clustering in high-dimensional space, covering methods like hierarchical clustering, K-means, and DBSCAN.

Covers the Actor Model, emphasizing asynchronous message passing and changing an Actor's behavior.

Covers the Stochastic Block Model for community detection, focusing on the detection of communities, clusters, and groups.