Assembly theory meets statistical mechanics to describe evolving systems
A new preprint from the Cronin Group, available on arXiv, couples assembly theory with statistical mechanics to describe how novelty and complexity emerge in systems far from equilibrium. The approach extends thermodynamic principles to history-dependent processes such as selection, which existing non-equilibrium methods struggle to describe. The team represents assembly pathways as matrices and introduces the assembler, a finite state machine that builds objects contingent on its previous states, allowing the maximum entropy principle to be applied directly to assembly spaces. The resulting ensembles provide a baseline against which selection can be detected, and are linked to the informational work required to construct complex objects. Applied to simulations of charged patchy particles under an oscillating electric field, the framework shows that external driving collapses the accessible phase space, producing long chains with high assembly index and copy number.
Link to preprint on arXiv