2006/11/17 by Simon L. Harding, Harding, Simon L., Julian F. Miller +3
Computer Science · Engineering · #Advanced Memory and Neural Computing #Cellular Automata and Applications #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Neural Networks and Reservoir Computing #Nonlinear Dynamics and Pattern Formation #Other Condensed Matter (cond-mat.other) #Quantum-Dot Cellular Automata
paper · pdf · doi:10.48550/arxiv.cond-mat/0611462
openalex publication_date 2006/11/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We describe several techniques for using bulk matter for special purpose\ncomputation. In each case it is necessary to use an evolutionary algorithm to\nprogram the substrate on which the computation is to take place. In addition,\nthe computation comes about as a result of nearest neighbour interactions at\nthe nano- micro- and meso-scale. In our first example we describe evolving a\nsaw-tooth oscillator in a CMOS substrate. In the second example we demonstrate\nthe evolution of a tone discriminator by exploiting the physics of liquid\ncrystals. In the third example we outline using a simulated magnetic quantum\ndot array and an evolutionary algorithm to develop a pattern matching circuit.\nAnother example we describe exploits the micro-scale physics of charge density\nwaves in crystal lattices. We show that vastly different resistance values can\nbe achieved and controlled in local regions to essentially construct a\nprogrammable array of coupled micro-scale quasiperiodic oscillators. Lastly we\nshow an example where evolutionary algorithms could be used to control density\nmodulations, and therefore refractive index modulations, in a fluid for optical\ncomputing.\n