Dynamic community detection decouples hierarchical timescale behavior of complex chemical systems


Although community or cluster identification is becoming a standard tool within the simulation community, traditional algorithms are challenging to adapt to time dependent data. Here we introduce temporal community identification using the delta-screening algorithm which has the flexibility to account for varying community compositions, merging and splitting behaviors within dynamically evolving chemical networks. When applied to a complex chemical system whose varying chemical environments cause multiple timescale behavior, delta-screening is able to resolve the hierarchical timescales of temporal communities. This computationally efficient algorithm is easily adapted to a wide range of dynamic chemical systems; flexibility in implementation allows the user to increase or decrease the resolution of temporal features by controlling parameters associated with community composition and fluctuations therein.


Supplementary material

Supplementary Material
Detailed description of analysis of performance; additional supporting figures.