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

Nicolau Jr, D. V., Lard, M., Korten, T., Delft, F. C. M. J. M. v., Persson, M., Bengtsson, E., et al. (2016). Parallel computation with molecular-motor-propelled agents in nanofabricated networks. Proceedings of the National Academy of Sciences of the United States of America, 113(10), 2591-2596.

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 Creators:
Nicolau Jr, Dan V1, Author
Lard, Mercy, Author
Korten, Till2, Author           
Delft, Falco C M J M van, Author
Persson, Malin, Author
Bengtsson, Elina, Author
Månsson, Alf1, Author
Diez, Stefan2, Author           
Linke, Heiner, Author
Nicolau, Dan V, Author
Affiliations:
1Max Planck Society, ou_persistent13              
2Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society, ou_2340692              

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 Abstract: 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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 Dates: 2016
 Publication Status: Issued
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 Rev. Type: -
 Identifiers: eDoc: 732402
Other: 6490
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Title: Proceedings of the National Academy of Sciences of the United States of America
Source Genre: Journal
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Pages: - Volume / Issue: 113 (10) Sequence Number: - Start / End Page: 2591 - 2596 Identifier: -