Positional information trade-offs in boundary-driven reaction-diffusion systems

TL;DR

This paper investigates how boundary-driven reaction-diffusion systems balance the trade-offs between positional information, entropy production, and reaction current, revealing phase transitions in optimal protocols and diminishing returns with increased information.

Contribution

It introduces a framework analyzing Pareto-optimal trade-offs in boundary-driven systems, uncovering phase transitions and protocol shifts in positional information management.

Findings

Existence of Pareto-optimal trade-offs between information, dissipation, and current.

Phase transitions in optimal boundary protocols.

Diminishing returns in information gain with increased dissipation.

Abstract

Individual components such as cells, particles, or agents within a larger system often require detailed understanding of their relative position to act accordingly, enabling the system as a whole to function in an organised and efficient manner. Through the concept of positional information, such components are able to specify their position in order to, e.g., create robust spatial patterns or coordinate specific functionality. Such complex behaviour generally occurs far from thermodynamic equilibrium and thus requires the dissipation of free energy to sustain functionality. We show that in boundary-driven simple exclusion systems with position-dependent Langmuir kinetics, non-trivial Pareto-optimal trade-offs exist between the positional information, rescaled entropy production rate and global reaction current. Phase transitions in the optimal protocols that tune the densities of the system boundaries emerge as a result, showing that distinct protocols are able to exchange global optimality similar to phase coexistence in liquid-gas phase transitions, and that increasing the positional information can lead to diminishing returns when considering increased dissipation.