This work is part of an effort to develop smart composite materials that monitor their own health using embedded micro-sensors and local network communication nodes. Here we address the issue of data management through the development of localized processing algorithms. We demonstrate that the two-dimensional Fast Fourier Transform (FFT) is a useful algorithm due to its hierarchical structure and ability to determine the relative magnitudes of different spatial wavelengths in a material. We investigate different algorithms for implementing the distributed FFT and compare them in terms of computational requirements within a low-power, low-bandwidth network of microprocessors.
We consider the problem of locating a template as a subimage of a larger image. Computing the maxima of the correlation function solves this problem classically. Since the correlation can be calculated with the Fourier transform this problem is a good candidate for a superior quantum algorithmic solution. We outline how such an algorithm would work.
Alternating two fair coin flipping games can create a winning game. Such a Parrondo game is a discrete model for a thermal ratchet. Recently we have constructed quantum versions of these coin flipping games that display the same 'paradoxical' behavior. In this paper we add noise to these quantum Parrondo games in order that they can be compared with continuum models of quantum ratchets. Simulation of these models reproduces one of the most interesting features of quantum ratchets: current inversion.