Distributed network of optically pumped magnetometers for space weather monitoring.

Spatial variation in the intensity of magnetospheric and ionospheric fluctuations during solar storms creates ground-induced currents, of importance in both infrastructure engineering and geophysical science. This activity is presently measured using a network of ground-based magnetometers, typically consisting of extensive installations at established observatory sites. We show that this network can be enhanced by the addition of remote quantum magnetometers which combine high sensitivity with intrinsic calibration.

A cold-atom Ramsey clock with a low volume physics package.

We demonstrate a Ramsey-type microwave clock interrogating the 6.835 GHz ground-state transition in cold [Formula: see text]Rb atoms loaded from a grating magneto-optical trap (GMOT) enclosed in an additively manufactured loop-gap resonator microwave cavity. A short-term stability of [Formula: see text] is demonstrated, in reasonable agreement with predictions from the signal-to-noise ratio of the measured Ramsey fringes.

Optimal binary gratings for multi-wavelength magneto-optical traps.

Grating magneto-optical traps are an enabling quantum technology for portable metrological devices with ultracold atoms. However, beam diffraction efficiency and angle are affected by wavelength, creating a single-optic design challenge for laser cooling in two stages at two distinct wavelengths - as commonly used for loading, e.g.

Free-induction-decay magnetic field imaging with a microfabricated Cs vapor cell.

Magnetic field imaging is a valuable resource for signal source localization and characterization. This work reports an optically pumped magnetometer (OPM) based on the free-induction-decay (FID) protocol, that implements microfabricated cesium (Cs) vapor cell technology to visualize the magnetic field distributions resulting from various magnetic sources placed close to the cell. The slow diffusion of Cs atoms in the presence of a nitrogen (N) buffer gas enables spatially independent measurements to be made within the same vapor cell by translating a 175 μm diameter probe beam over the sensing area.

Automated Machine Learning Strategies for Multi-Parameter Optimisation of a Caesium-Based Portable Zero-Field Magnetometer.

Machine learning (ML) is an effective tool to interrogate complex systems to find optimal parameters more efficiently than through manual methods. This efficiency is particularly important for systems with complex dynamics between multiple parameters and a subsequent high number of parameter configurations, where an exhaustive optimisation search would be impractical. Here we present a number of automated machine learning strategies utilised for optimisation of a single-beam caesium (Cs) spin exchange relaxation free (SERF) optically pumped magnetometer (OPM).