Landauer’s Principle asserts that there is a minimum possible amount of work required to perform an irreversible computational task, such as erasing one bit of information. This lower limit is known as Landauer’s Limit. Based on this principle, a complex computation—comprised of simpler modular components—would require an amount of work equal to the sum of each component’s required work.

Surprisingly, Alec Boyd from the Nanyang Technological University found that the modularity of these calculations yields excess work costs beyond those predicted by Landauer’s Principle. He refers to this as “modularity dissipation.” Thus, in addition to Landauer’s relationship between information and energy, complexity itself has real, well-defined energetic consequences.

The current project will build on Boyd’s prior modularity dissipation results to understand how to mitigate these additional energy costs and design energetically efficient complex computations, illuminating thermodynamic structural principles of complex information processing.

To understand fundamental inefficiencies in conventional computing, the project team will examine digital logic—composed of networks of modular elements—as well as modular thermodynamic computers. Beyond basic research insights into the foundational physical relationships between information, energy, and complexity, the outcomes of this project will also help engineers create better conventional computers at the nanoscale and better understand nature's nano-computing designs, as in living systems.​