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Fast Algorithmic Self-assembly of Simple Shapes Using Random Agitation

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DNA Computing and Molecular Programming (DNA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8727))

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Abstract

We study the power of uncontrolled random molecular movement in a model of self-assembly called the nubots model. The nubots model is an asynchronous nondeterministic cellular automaton augmented with rigid-body movement rules (push/pull, deterministically and programmatically applied to specific monomers) and random agitations (nondeterministically applied to every monomer and direction with equal probability all of the time). Previous work on nubots showed how to build simple shapes such as lines and squares quickly—in expected time that is merely logarithmic of their size. These results crucially make use of the programmable rigid-body movement rule: the ability for a single monomer to push or pull large objects quickly, and only at a time and place of the programmers’ choosing. However, in engineered molecular systems, molecular motion is largely uncontrolled and fundamentally random. This raises the question of whether similar results can be achieved in a more restrictive, and perhaps easier to justify, model where uncontrolled random movements, or agitations, are happening throughout the self-assembly process and are the only form of rigid-body movement. We show that this is indeed the case: we give a polylogarithmic expected time construction for squares using agitation, and a sublinear expected time construction to build a line. Such results are impossible in an agitation-free (and movement-free) setting and thus show the benefits of exploiting uncontrolled random movement.

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Chen, HL., Doty, D., Holden, D., Thachuk, C., Woods, D., Yang, CT. (2014). Fast Algorithmic Self-assembly of Simple Shapes Using Random Agitation. In: Murata, S., Kobayashi, S. (eds) DNA Computing and Molecular Programming. DNA 2014. Lecture Notes in Computer Science, vol 8727. Springer, Cham. https://doi.org/10.1007/978-3-319-11295-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-11295-4_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11294-7

  • Online ISBN: 978-3-319-11295-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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