Reducing Tile Complexity for the Self-Assembly of Scaled Shapes Through Temperature Programming
Scott M. Summers

TL;DR
This paper demonstrates how temperature programming can reduce tile complexity in self-assembling scaled shapes, providing new tile sets and proving the necessity of scaling for arbitrary shape assembly.
Contribution
It introduces two constant-size tile sets for scaled shape self-assembly in the multiple temperature model and proves that scaling is necessary for arbitrary shape assembly.
Findings
Two constant-size tile sets enable scaled shape assembly.
One tile set uses an asymptotically optimal temperature sequence.
Scaling is proven necessary for arbitrary shape assembly.
Abstract
This paper concerns the self-assembly of scaled-up versions of arbitrary finite shapes. We work in the multiple temperature model that was introduced by Aggarwal, Cheng, Goldwasser, Kao, and Schweller (Complexities for Generalized Models of Self-Assembly, SODA 2004). The multiple temperature model is a natural generalization of Winfree's abstract tile assembly model, where the temperature of a tile system is allowed to be shifted up and down as self-assembly proceeds. We first exhibit two constant-size tile sets in which scaled-up versions of arbitrary shapes self-assemble. Our first tile set has the property that each scaled shape self-assembles via an asymptotically "Kolmogorov-optimum" temperature sequence but the scaling factor grows with the size of the shape being assembled. In contrast, our second tile set assembles each scaled shape via a temperature sequence whose length is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModular Robots and Swarm Intelligence · Advanced biosensing and bioanalysis techniques · DNA and Biological Computing
