On the performance and programming of reversible molecular computers

TL;DR

This paper explores the principles and limits of reversible molecular computing, emphasizing thermodynamic constraints, and proposes a model to optimize performance within these physical bounds.

Contribution

It refines performance bounds for reversible molecular computers considering thermodynamics and interactions, proposing a model suited for exploiting these constraints.

Findings

Reversible computing can surpass traditional performance limits.

Thermodynamic constraints significantly influence molecular computer design.

Scaling laws for performance depend on system volume and interactions.

Abstract

If the 20th century was known for the computational revolution, what will the 21st be known for? Perhaps the recent strides in the nascent fields of molecular programming and biological computation will help bring about the 'Coming Era of Nanotechnology' promised in Drexler's 'Engines of Creation'. Though there is still far to go, there is much reason for optimism. This thesis examines the underlying principles needed to realise the computational aspects of such 'engines' in a performant way. Its main body focusses on the ways in which thermodynamics constrains the operation and design of such systems, and it ends with the proposal of a model of computation appropriate for exploiting these constraints. These thermodynamic constraints are approached from three different directions. The first considers the maximum possible aggregate performance of a system of computers of given volume, $V$, with a given supply of free energy. From this perspective, reversible computing is imperative in order to circumvent the Landauer limit. A result of Frank is refined and strengthened, showing that the adiabatic regime reversible computer performance is the best possible for any computer - quantum or classical. This therefore shows a universal scaling law governing the performance of compact computers of $\sim V^{5/6}$, compared to $\sim V^{2/3}$ for conventional computers. For the case of molecular computers, it is shown how to attain this bound. The second direction extends this performance analysis to the case where individual computational particles or sub-units can interact with one another. The third extends it to interactions with shared, non-computational parts of the system. It is found that accommodating these interactions in molecular computers imposes a performance penalty that undermines the earlier scaling result. Nonetheless, scaling superior to that of irreversible computers can be...