Usefulness of several analysing methods for photon-correlation LDA data

Three methods for analyzing photon-correlation LDA data are described, and their applicability is evaluated. The three methods are: (1) the Fourier transform, (2) the linear transform, and (3) Hermite polynomial fit. It is determined that the Fourier transform does not need any a priori supposition to the time domain or velocity distribution; the linear transform needs an a prior supposition of the time domain, but not the velocity distribution; and the Hermite polynomial fit needs a prior supposition of both the time domain and velocity distribution. The three methods are applied to the analysis of analytically generated autocorrelation data and autocorrelation data derived from measurements on a free running water jet and in a stirred vessel. The data reveal that the linear transform method is most effective for analyzing photon-correlation LDA data.