Coping with diffraction effects in protein-based computing through a specialized approximation algorithm with constant overhead

One of the current research directions in biological nanotechnology is the use of bacteriorhodopsin in the fabrication of protein-based photonic devices. Bacteriorhodopsin, with its unique light-activated photocycle, nanoscale size, cyclicity (>107), and natural resistance to harsh environmental conditions, provides for protein-based memories that have a comparative advantage over magnetic and optical data storage devices. However, the construction of protein-based memories has been severely limited by fundamental issues that exist with such devices, such as unwanted diffraction effects. In this paper, we propose an approximation algorithm for coping with diffraction effects, that improves over previously proposed algorithms.