Second-order correlations in single-particle interferometry

Abstract

Interferometers with single particles are susceptible for dephasing perturbations from the environment, such as electromagnetic oscillations or mechanical vibrations. On the one hand, this limits sensitive quantum phase measurements as it reduces the interference contrast in the signal. On the other hand, it enables single-particle interferometers to be used as sensitive sensors for electromagnetic and mechanical perturbations. Recently, it was demonstrated experimentally, that a second-order correlation analysis of the spatial and temporal detection signal can decrease the electromagnetic shielding and vibrational damping requirements significantly. Thereby, the relevant matter-wave characteristics and the perturbation parameters could be extracted from the correlation analysis of a spatially ‘washed-out’ interference pattern and the original undisturbed interferogram could be reconstructed. This method can be applied to all interferometers that produce a spatial fringe pattern on a detector with high spatial and temporal single-particle resolution. In this article, we present and discuss in detail the used two-dimensional second-order correlation theory for multifrequency perturbations. The derivations of an explicit and approximate solution of the correlation function and corresponding amplitude spectra are provided. It is explained, how the numerical correlation function is extracted from the measurement data. Thereby, the influence of the temporal and spatial discretization step size on the extracted parameters, as contrast and perturbation amplitude, is analyzed. The influence of noise on the correlation function and corresponding amplitude spectrum is calculated and numerically cross-checked by a comparison of our theory with numerical single-particle simulations of a perturbed interference pattern. Thereby, an optimum spatial discretization step size is determined to achieve a maximum signal-to-noise ratio, which was used in former experiments to identify the perturbation caused by the electrical network. Our method can also be applied for the analysis of broad-band frequency noise, dephasing the interference pattern. Using Gaussian distributed noise in the simulations, we demonstrate that the relevant matter-wave parameters and the applied perturbation spectrum can be revealed by our correlation analysis.