Growth, Cellular, and Network Systems

Adaptive networks and aggregation

• Physarum transport model. Nakagaki, Yamada and Tóth (2001) studies tube morphogenesis and maze paths; Bonifaci et al. (2012) analyses a defined shortest-path solver. Plot: routes, capacities, terminals; inks can separate backbone, redundancy, and nodes.
• DLA. Witten and Sander (1981) defines diffusion-limited aggregation by random walkers attaching to a cluster. Plot: branch skeleton, growth-time bands, walkers versus aggregate.
• Mark J. Stock, Sprawl. Reference page; use as an art example of DLA, not a biological-network model. Plot: regular support grid, aggregate, and optional growth chronology.

Fields, reaction, and cellular systems

• Gray–Scott reaction–diffusion. Gray and Scott (1993) models autocatalytic pattern formation. Plot: threshold contours and field gradients rather than pixels; inks can encode concentrations or time bands.
• Cellular automata. Wolfram (1984) concerns local-rule cellular systems. Plot: boundaries and time-slices; inks can separate state transition and persistent state.
• Perlin gradient noise. Perlin (2002). Plot: scalar values drive contours, seed density, or direction; not a growth model by itself.

Branching, grammar, and fabrication

• Space colonisation. Runions, Lane and Prusinkiewicz connects attractor points to adaptive branching. Plot: branch orders and attractor fields are naturally separable inks.
• L-systems. Prusinkiewicz and Lindenmayer, The Algorithmic Beauty of Plants. Plot: rewrite generations, turtle paths, and grammar variants can be isolated.
• Nervous System. Reference page for differential growth and Kinematics. Plot: fold/mesh/growth-rate layers, clearly labelled as translations.

Open-source and visualisation practice

• CreativeCodingLab / Polyphorm. Repository documents a Monte Carlo Physarum Machine for cosmic-web visualisation. Plot: filaments, sources, and density levels; cite its method as an inspired visualisation.
• Katharina Brunner / generativeart. Reference page; formula/seed logging is useful provenance for any plot series.
• Jon McCormack. Reference page; generative/evolutionary systems are an artistic research lineage, not scientific evidence for a particular mechanism.

Use in Corollaria

Select one declared mechanism per layer, record its inputs and seed, and translate it to measured open paths. Let layer roles differ—source/terminal, field, structure, event, or time—so a multi-ink plot remains legible when separated.