Cell migration is essential to cell segregation, playing a central role in tissue formation, wound healing, and tumor evolution. Considering random mixtures of two cell types, it is not clear which
cell characteristics define clustering time scales. The mass of diffusing clusters merging with one another is expected to grow as when the diffusion constant scales with the inverse of the mass.
However, cell segregation experiments deviate from that behavior. Explanations for that could arise from specific microscopic mechanism or form collective effects, typical of active matter. Here we consider
a power law connecting the diffusion constant and the cluster mass to propose an analytic approach to model cell segregation where we explicitly take into account finite size corrections. The results are
compared with active matter model simulations and experiments available in the literature. To investigate the role played by different mechanisms we consider different hypotheses describing
cell-cell interactions: Differential Adhesion Hypothesis (DAH) and the Differential Velocity Hypothesis (DVH). We observed that the simulations yield normal diffusion for long time intervals. Analytic
and simulation results show that: I) cluster evolution clearly tends to a scaling regime, disrupted only at the finite size limits; II) cluster diffusion is greatly enhanced by cell collective behavior;
III) the scaling exponent for cluster growth depends only on the mass-diffusion relation, not on the detailed local segregation mechanism.
" Active Matter Cell Sorting Simulations Described by Mean Field Approximations"