Since around 1995 there has been a considerable impetus of research to discern when, how, and why evolutionary techniques can be useful in electronics design [17,7,18,13,26,12,19]. In particular, a sequence of experiments at the University of Sussex, UK (summarised in [23,22]) provides the basis for our evolution of single-electron designs to follow. These experiments were designed to determine how radically different evolved circuits can be from those produced by conventional design methods (see also [10]).
In practice, there are many important differences between evolutionary design and conventional methods. The most fundamental is that evolution proceeds through the accumulated action of the variation operators (such as crossover and mutation), and these can be largely blind. For example, a typical mutation operator considers each part of the design in turn, and with a small probability applies a random change to it. The consequences of the variation do not need to be predicted in advance; evolution works by taking account of the resulting changes induced into the measured performance of the system. Although it is possible to introduce context-sensitive or heuristic variation operators, it is this essentially stochastic and cumulative action of the variation operators that distinguishes evolution from other forms of heuristic search, and even from the iterative loop of design and testing often present in bottom-up electronics design.
Hence, circuits can be designed through evolution even when there is no feasible way of analysing how the individual interactions of the components give rise to the overall behaviour. This may be because the dynamics of the interactions are too complex, or simply because a tractable analytical model of the components is not available. For example, when one evolved microelectronic circuit was investigated [21], it was found that it had ingeniously exploited the semiconductor physics of the reconfigurable FPGA chip on which it was evaluated, even aspects that were not part of the chip's normal operation, and which were unknown to the investigators. By doing so, through ingeniously subtle means and a complex dynamics, the circuit was very much smaller than would normally be expected. This was possible because none of the conventional restrictive design rules were applied, since evolution does not have the same need for simplifying constraints. A decisive conclusion of the sequence of experiments [23,22] was: Evolution can explore beyond the scope of conventional design.
Adaptive control algorithms (which could be evolutionary) have been proposed for the on-line tuning of nanoelectronic circuit parameters [16]. Evolutionary algorithms have also been applied to the characterisation of fabricated nanoelectronic devices [8], but not to the design of nanoelectronic systems. Through an initial exploratory case-study, this paper aims to illustrate that the abilities of evolutionary design identified above may have particular impact in this area. The findings will be summarised in the concluding section.