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Parallel computation with molecular-motor-propelled agents in nanofabricated networks

OPEN Proceedings of the National Academy of Sciences of the United States of America | 24 Feb 2016

DV Nicolau, M Lard, T Korten, FC van Delft, M Persson, E Bengtsson, A MÃ¥nsson, S Diez, H Linke and DV Nicolau
The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.
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Problem solving, Quantum computer, Computation, Elementary mathematics, Knapsack problem, Computational complexity theory, Computer, Mathematics
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