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

Reference

Dan V. Nicolau, Mercy Lard, Till Korten, Falco C. M. J. M. van Delft, Malin Persson, Elina Bengtsson, Alf Månsson, Stefan Diez, Heiner Linke, Dan V. Nicolau, "Parallel computation with molecular-motor-propelled agents in nanofabricated networks", In Proceedings of the National Academy of Sciences, vol. 113, no. 10, pp. 2591-2596, 2016. [doi]

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.

Bibtex

@article{Nicolau08032016,
author = {Nicolau, Dan V. and Lard, Mercy and Korten, Till and van Delft, Falco C. M. J. M. and Persson, Malin and Bengtsson, Elina and Månsson, Alf and Diez, Stefan and Linke, Heiner and Nicolau, Dan V.},
title = {Parallel computation with molecular-motor-propelled agents in nanofabricated networks},
volume = {113},
number = {10},
pages = {2591-2596},
year = {2016},
doi = {10.1073/pnas.1510825113},
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.},
URL = {http://www.pnas.org/content/113/10/2591.abstract},
eprint = {http://www.pnas.org/content/113/10/2591.full.pdf},
journal = {Proceedings of the National Academy of Sciences}
}

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