Computation in Self-assembled Nanometre Scale Arrays

TL;DR

This paper proposes a method for using self-assembled nanoarrays with bistable units to perform robust, efficient, and programmable computation driven by optical pulses, tolerant to defects through evolutionary optimization.

Contribution

It introduces a novel approach to harness self-assembled nanoarrays for computation, demonstrating defect tolerance and programmability without detailed defect mapping.

Findings

Arrays can compute robustly with simple optical control.

Evolutionary algorithms effectively handle array defects.

The approach works across various physical interactions.

Abstract

Ordered nanoarrays, i.e. regular patterns of quantum structures at the nanometre scale, have recently been synthesized in a wide range of systems. Here I explore a possible route to technological exploitation: assuming a simple form of bistability for the individual units, I find that arrays can compute in a way that is robust, efficient, programmable and highly defect tolerant. The nanoarray would need to be 'wired' to conventional technologies only at its boundary; its internal dynamics are driven simply by applying optical pulses to the entire structure indiscriminately. Any self-assembled array would have a unique set of defects, therefore I employ an ab initio evolutionary process to subsume such flaws without any need to determine their location or nature. The approach succeeds for various forms of physical interaction within the array.