Parallel computation with molecularmotorpropelled agents in nanofabricated networks.
(2016) In Proceedings of the National Academy of Sciences 113(10). p.25912596 Abstract
 The combinatorial nature of many important mathematical problems, including nondeterministicpolynomialtime (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 parallelcomputation approaches in the past, for example: DNA computation, quantum computation, and microfluidicsbased 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 parallelcomputation system in which a given combinatorial problem is encoded into a graphical, modular network that is... (More)
 The combinatorial nature of many important mathematical problems, including nondeterministicpolynomialtime (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 parallelcomputation approaches in the past, for example: DNA computation, quantum computation, and microfluidicsbased 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 parallelcomputation 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, molecularmotorpropelled 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 proofofconcept 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 NPcomplete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/record/8821971
 author
 Nicolau, Dan V; Lard, Mercy ^{LU} ; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner ^{LU} and Nicolau, Dan V
 organization
 publishing date
 20160222
 type
 Contribution to journal
 publication status
 published
 subject
 in
 Proceedings of the National Academy of Sciences
 volume
 113
 issue
 10
 pages
 2591  2596
 publisher
 National Acad Sciences
 external identifiers

 pmid:26903637
 scopus:84960532489
 wos:000372013300025
 ISSN
 10916490
 DOI
 10.1073/pnas.1510825113
 language
 English
 LU publication?
 yes
 id
 8db589fe4bdc4a32905c91b93a7423f9 (old id 8821971)
 date added to LUP
 20160304 09:39:50
 date last changed
 20171001 03:09:12
@article{8db589fe4bdc4a32905c91b93a7423f9, abstract = {The combinatorial nature of many important mathematical problems, including nondeterministicpolynomialtime (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 parallelcomputation approaches in the past, for example: DNA computation, quantum computation, and microfluidicsbased 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 parallelcomputation 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, molecularmotorpropelled 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 proofofconcept 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 NPcomplete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.}, 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}, issn = {10916490}, language = {eng}, month = {02}, number = {10}, pages = {25912596}, publisher = {National Acad Sciences}, series = {Proceedings of the National Academy of Sciences}, title = {Parallel computation with molecularmotorpropelled agents in nanofabricated networks.}, url = {http://dx.doi.org/10.1073/pnas.1510825113}, volume = {113}, year = {2016}, }