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Universal Shape Replication via Self-Assembly with Signal-Passing Tiles (Extended Abstract)

Authors Andrew Alseth , Daniel Hader, Matthew J. Patitz

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Author Details

Andrew Alseth
  • University of Arkansas, Fayetteville, AR, USA
Daniel Hader
  • University of Arkansas, Fayetteville, AR, USA
Matthew J. Patitz
  • University of Arkansas, Fayetteville, AR, USA

Funding

This work was supported in part by NSF grant CAREER-1553166.

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Andrew Alseth, Daniel Hader, and Matthew J. Patitz. Universal Shape Replication via Self-Assembly with Signal-Passing Tiles (Extended Abstract). In 28th International Conference on DNA Computing and Molecular Programming (DNA 28). Leibniz International Proceedings in Informatics (LIPIcs), Volume 238, pp. 2:1-2:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.DNA.28.2

Abstract

In this paper, we investigate shape-assembling power of a tile-based model of self-assembly called the Signal-Passing Tile Assembly Model (STAM). In this model, the glues that bind tiles together can be turned on and off by the binding actions of other glues via "signals". In fact, we prove our positive results in a version of the model in which it is slightly more difficult to work (where tiles are allowed to rotate) but show that they also hold in the standard STAM. Specifically, the problem we investigate is "shape replication" wherein, given a set of input assemblies of arbitrary shape, a system must construct an arbitrary number of assemblies with the same shapes and, with the exception of size-bounded junk assemblies that result from the process, no others. We provide the first fully universal shape replication result, namely a single tile set capable of performing shape replication on arbitrary sets of any 3-dimensional shapes without requiring any scaling or pre-encoded information in the input assemblies. Our result requires the input assemblies to be composed of signal-passing tiles whose glues can be deactivated to allow deconstruction of those assemblies, which we also prove is necessary by showing that there are shapes whose geometry cannot be replicated without deconstruction. Additionally, we modularize our construction to create systems capable of creating binary encodings of arbitrary shapes, and building arbitrary shapes from their encodings. Because the STAM is capable of universal computation, this then allows for arbitrary programs to be run within an STAM system, using the shape encodings as input, so that any computable transformation can be performed on the shapes.

Subject Classification

ACM Subject Classification
  • Theory of computation → Models of computation
Keywords
  • Algorithmic self-assembly
  • Tile Assembly Model
  • shape replication

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References

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