Optimizing NN reduction in an atom interferometer network for GW detection

The sensitivity of an atom gradiometer aiming to detect gravitational waves (GW) is impacted by fluctuations of Earth's gravity field also called Newtonian Noise (NN). Sensor arrays have proved to be a promising technique for NN reduction. In our study, we further investigate the benefits of Atom Interferometer (AI) networks by improving their geometry and the extraction of the GW signal. We focus on Seismic Newtonian Noise in the frequency band from 0.1 to 10 Hz. On one hand, we show that using a specific detector geometry, a better NN rejection can occur optimizing the number of gradiometers in the network. On the other hand, we show that carrying out optimization in sub frequency bands - which results in using various detector geometries from a common network - allows even higher NN rejection while keeping a similar number of interferometers.