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Turning machines

  • Irina Kostitsyna
  • , Cai Wood
  • , Damien Woods

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

Molecular robotics is challenging, so it seems best to keep it simple. We consider an abstract molecular robotics model based on simple folding instructions that execute asynchronously. Turning Machines are a simple 1D to 2D folding model, also easily generalisable to 2D to 3D folding. A Turning Machine starts out as a line of connected monomers in the discrete plane, each with an associated turning number. A monomer turns relative to its neighbours, executing a unit-distance translation that drags other monomers along with it, and through collective motion the initial set of monomers eventually folds into a programmed shape. We fully characterise the ability of Turning Machines to execute line rotations, and to do so efficiently: computing an almost-full line rotation of 5π/3 radians is possible, yet a full 2π rotation is impossible. We show that such line-rotations represent a fundamental primitive in the model, by using them to efficiently and asynchronously fold arbitrarily large zig-zag-rastered squares and y-monotone shapes.

Originele taal-2Engels
Titel26th International Conference on DNA Computing and Molecular Programming, DNA 2020
RedacteurenCody Gear, Matthew J. Patitz
UitgeverijSchloss Dagstuhl - Leibniz-Zentrum für Informatik
ISBN van elektronische versie9783959771634
DOI's
StatusGepubliceerd - 1 sep 2020
Evenement26th International Conference on DNA Computing and Molecular Programming, DNA 2020 - Oxford, Verenigd Koninkrijk
Duur: 14 sep 202017 sep 2020

Publicatie series

NaamLeibniz International Proceedings in Informatics, LIPIcs
Volume174
ISSN van geprinte versie1868-8969

Congres

Congres26th International Conference on DNA Computing and Molecular Programming, DNA 2020
Land/RegioVerenigd Koninkrijk
StadOxford
Periode14/09/2017/09/20

Financiering

Funding Authors C. Wood and D. Woods are supported by European Research Council (ERC) award number 772766 and Science foundation Ireland (SFI) grant 18/ERCS/5746 (this manuscript reflects only the authors’ view and the ERC is not responsible for any use that may be made of the information it contains).

FinanciersFinanciernummer
European Union’s Horizon Europe research and innovation programme772766
European Union’s Horizon Europe research and innovation programme
Science Foundation Ireland - SFI18/ERCS/5746

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