Category: Network Sci.

Summary: Mapping how cultural-feature count and trait diversity shift the critical noise rate for order-disorder transitions in the Axelrod model.

The Axelrod model captures cultural similarity and social influence, but random noise can destabilize local agreement and produce a transition between ordered and multicultural states. This experiment asks how that critical noise rate depends jointly on the number of cultural features and the number of traits available per feature.

The simulation runs the model on square lattices for several system sizes while sweeping noise, feature count, and trait count. Finite-size comparisons are then used to trace the phase boundary and test whether the nature of the transition changes across the parameter plane.

That goes beyond the common practice of fixing one structural parameter and varying only the other. The project aims to build a fuller phase diagram for how social diversity and random perturbation interact.

Method: Finite-size sweeps of the Axelrod cultural-dissemination model on 2D lattices across noise rate, feature count, and trait count.

What is measured: Critical noise rate, phase boundary across feature and trait counts, ordered versus multicultural outcomes, and finite-size evidence about transition character.