The high precision and scalable technology offered by atom interferometry has the opportunity to profoundly affect gravity surveys, enabling the detection of features of either smaller size or greater depth. While such systems are already starting to enter into the commercial market, significant reductions are required in order to reach the size, weight and power of conventional devices. In this article, the potential for atom interferometry based gravimetry is assessed, suggesting that the key opportunity resides within the development of gravity gradiometry sensors to enable drastic improvements in measurement time. To push forward in realizing more compact systems, techniques have been pursued to realize a highly portable magneto-optical trap system, which represents the core package of an atom interferometry system. This can create clouds of 107 atoms within a system package of 20 l and 10 kg, consuming 80 W of power.This article is part of the themed issue ‘Quantum technology for the 21st century’.

The sensing of gravity has emerged as a tool in geophysics applications such as engineering and climate research1–3, including the monitoring of temporal variations in aquifers4 and geodesy5. However, it is impractical to use gravity cartography to resolve metre-scale underground features because of the long measurement times needed for the removal of vibrational noise6. Here we overcome this limitation by realizing a practical quantum gravity gradient sensor. Our design suppresses the effects of micro-seismic and laser noise, thermal and magnetic field variations, and instrument tilt. The instrument achieves a statistical uncertainty of 20 E (1 E = 10−9 s−2) and is used to perform a 0.5-metre-spatial-resolution survey across an 8.5-metre-long line, detecting a 2-metre tunnel with a signal-to-noise ratio of 8. Using a Bayesian inference method, we determine the centre to ±0.19 metres horizontally and the centre depth as (1.89 −0.59/+2.3) metres. The removal of vibrational noise enables improvements in instrument performance to directly translate into reduced measurement time in mapping. The sensor parameters are compatible with applications in mapping aquifers and evaluating impacts on the water table7, archaeology8–11, determination of soil properties12 and water content13, and reducing the risk of unforeseen ground conditions in the construction of critical energy, transport and utilities infrastructure14, providing a new window into the underground.

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signal processing techniques for the detection of highly localised gravity anomalies using quantum interferometry technology," Proc. SPIE 9992, Emerging Imaging and Sensing Technologies, 99920M (

We demonstrate a method of inverting gravity data, based on profiled singular-function expansions. It is well known that the inverse problem of determining underground density variations from gravity data is severely ill-posed and prior knowledge is needed to restrict the range of possible solutions. Viewed as a linear inverse problem, various standard methods, all of which produce solutions approximating the generalised solution, tend to give density variations concentrated near the surface. To overcome this potentially undesirable trait, various authors have introduced depth weighting. In this paper we carry this idea a step further and introduce a method based on a profiled singular-function expansion which uses the prior knowledge that the underground object is centred at a particular depth. The use of an appropriate depth-weighting profile leads to a solution at the correct depth. Furthermore, we show that if the depth of the object is unknown, a range of solutions at different depths can be produced, allowing other prior knowledge, such as object size or density, to be introduced to determine which solution is the most plausible. The truncation point of the profiled singular-function expansion is determined by the level of noise on the data. We examine how the achievable horizontal resolution varies with this truncation point. A notable property of our approach is that when the centre of the profile corresponds to the true object depth, the solution appears, in a certain sense, to be the most focussed one. Finally we consider a gravimetry example using real data.