A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks

Abstract

Dissipative accounts of structure formation show that the self-organisation of complex structures is thermodynamically favoured, whenever these structures dissipate free energy that could not be accessed otherwise. These structures therefore open transition channels for the state of the universe to move from a frustrated, metastable state to another metastable state of higher entropy. However, these accounts apply as well to relatively simple, dissipative systems, such as convection cells, hurricanes, candle flames, lightning strikes, or mechanical cracks, as they do to complex biological systems. Conversely, interesting computational properties—that characterize complex biological systems, such as efficient, predictive representations of environmental dynamics—can be linked to the thermodynamic efficiency of underlying physical processes. However, the potential mechanisms that underwrite the selection of dissipative structures with thermodynamically efficient subprocesses is not completely understood. We address these mechanisms by explaining how bifurcation-based, work-harvesting processes—required to sustain complex dissipative structures—might be driven towards thermodynamic efficiency. We first demonstrate a simple mechanism that leads to self-selection of efficient dissipative structures in a stochastic chemical reaction network, when the dissipated driving chemical potential difference is decreased. We then discuss how such a drive can emerge naturally in a hierarchy of self-similar dissipative structures, each feeding on the dissipative structures of a previous level, when moving away from the initial, driving disequilibrium.

On Bayesian Mechanics: A Physics of and by Beliefs

“…This equation integrates to (9), and was our previous equation for motion constrained to lie in the gradient of a potential (or, correspondingly, a connection). Indeed, the solution to the parallel transport ODE (10) is the exponential function, p(x) = e −λJ(x) .…”

“…Accordingly, the FEP applies informatively to "things" defined in a particular way, via a sparse causal dependence structure or sparse coupling, which is the key construction from which the rest of the FEP follows [55,3]. 10 In other words, the FEP is a principle that we can apply to specify the mechanics of systems that have a specific, particular partition (i.e., into a thing that is a model and a process that is being modelled). For such a distinction to hold in physical systems, it must be the case the causal coupling between the thing that instantiates the model and generative process evince some kind of sparsity.…”

“…It is often said that systems that are able to preserve their organisation over time, such as living systems, appear to resist the entropic decay and dissipation that are dictated by the second law of thermodynamics (this view is often attributed to Schrödinger, [9]). This is, in fact, untrue, and something of a sleight of hand: self-organising systems, and living systems in particular, not only conform to the second law of thermodynamics, which states that the internal entropy of an isolated system always increases, but conform to it exceptionally well-yet in doing so, they also maintain their structural integrity [4,10]. The foundations of Bayesian mechanics have been laid out by the physics of complex adaptive systems and 1 The fields encompassing Bayesian mechanics, the free energy principle, and the maximum entropy principle are inherently technical ones that presuppose and leverage detailed formal constructs and concepts.…”

“…Indeed, already at this early stage of presentation, the formulation presented here appeals to a separation of timescales: we distinguish between a faster timescale of states or paths that are effectively treated as random fluctuations, and a slower timescale of states or paths that are treated as states or paths per se. This is expanded upon and used to effect in[1] 10. The FEP is not a "theory of everything" in the sense that it could be applied informatively to kind any mathematical system whatsoever.…”

Low-dissipation optimization of the prefrontal cortex in the −12° head-down tilt position: A functional near-infrared spectroscopy study

“…The above discussion corresponds to the dissipative structure in the thermodynamic theory. The dissipative structure constitutes the transition channel in a system from a frustrated metastable state to another metastable state ( Jeffery et al, 2019 ; Ueltzhffer et al, 2021 ), providing a new possibility to achieve energy self-optimization ( Gonzalez-Ayala et al, 2020a , b ). This theory is also applicable in complex biological systems.…”