The program-size complexity of self-assembled squares (extended abstract)
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Running time and program size for self-assembled squares
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Combinatorial optimization problems in self-assembly
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Algorithmic self-assembly of dna
Algorithmic self-assembly of dna
DNA'04 Proceedings of the 10th international conference on DNA computing
Optimization of supply diversity for the self-assembly of simple objects in two and three dimensions
Natural Computing: an international journal
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Speed of computation and power consumption are the two main parameters of conventional computing devices implemented in microelectronic circuits. As performance of such devices approaches physical limits, new computing paradigms are emerging. Two paradigms receiving great attention are quantum and DNA-based molecular computing. This paper focuses on DNA-based computing. This concept can be abstracted to growth models where computational elements called tiles are self-assembled one by one, subject to some simple hierarchical rules, to fill a given template encoding a Boolean formula. While DNA-based computational devices are known to be extremely energy efficient, little is known concerning the fundamental question of computation times. In particular, given a function, we study the time required to determine its value for a given input. In the simplest instance, the analysis has interesting connections with interacting particle systems and variational problems.