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arXiv · 1807.09753

Magnetic-field-learning using a single electronic spin in diamond with one-photon-readout at room temperature

Raffaele Santagati·Antonio A. Gentile·Sebastian Knauer·Simon Schmitt·Stefano Paesani·Christopher Granade·Nathan Wiebe·Christian Osterkamp·Liam P. McGuinness·Jianwei Wang·Mark G. Thompson·John G. Rarity·Fedor Jelezko·Anthony Laing
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Abstract

Nitrogen-vacancy (NV) centres in diamond are appealing nano-scale quantum sensors for temperature, strain, electric fields and, most notably, for magnetic fields. However, the cryogenic temperatures required for low-noise single-shot readout that have enabled the most sensitive NV-magnetometry reported to date, are impractical for key applications, e.g. biological sensing. Overcoming the noisy readout at room-temperature has until now demanded repeated collection of fluorescent photons, which increases the time-cost of the procedure thus reducing its sensitivity. Here we show how machine learning can process the noisy readout of a single NV centre at room-temperature, requiring on average only one photon per algorithm step, to sense magnetic field strength with a precision comparable to those reported for cryogenic experiments. Analysing large data sets from NV centres in bulk diamond, we report absolute sensitivities of $60$ nT s$^{1/2}$ including initialisation, readout, and computational overheads. We show that dephasing times can be simultaneously estimated, and that time-dependent fields can be dynamically tracked at room temperature. Our results dramatically increase the practicality of early-term single spin sensors.

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Raffaele Santagati, Antonio A. Gentile, Sebastian Knauer, Simon Schmitt, Stefano Paesani, Christopher Granade, Nathan Wiebe, Christian Osterkamp, Liam P. McGuinness, Jianwei Wang, Mark G. Thompson, John G. Rarity, Fedor Jelezko, Anthony Laing. 2018-07-25. Magnetic-field-learning using a single electronic spin in diamond with one-photon-readout at room temperature. https://doi.org/10.1103/physrevx.9.021019

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