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. 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 can decrease the shielding and damping requirements significantly. Thereby, the relevant matter-wave characteristics and perturbation parameters could be extracted from the correlation analysis of a "washed-out" interference pattern and the 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 is analyzed. The influence of noise on the correlation function and amplitude spectrum is calculated and numerically cross-checked by a comparison of our theory with numerical single-particle simulations. 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.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.