Automatic Detection of Nuclear Spins at Arbitrary Magnetic Fields via Signal-to-Image AI Model.

Quantum sensors leverage matter's quantum properties to enable measurements with unprecedented spatial and spectral resolution. Among these sensors, those utilizing nitrogen-vacancy (NV) centers in diamond offer the distinct advantage of operating at room temperature. Nevertheless, signals received from NV centers are often complex, making interpretation challenging. This is especially relevant in low magnetic field scenarios, where standard approximations for modeling the system fail. Additionally, NV signals feature a prominent noise component. In this Letter, we present a signal-to-image deep learning model capable of automatically inferring the number of nuclear spins surrounding a NV sensor and the hyperfine couplings between the sensor and the nuclear spins. Our model is trained to operate effectively across various magnetic field scenarios, requires no prior knowledge of the involved nuclei, and is designed to handle noisy signals, leading to fast characterization of nuclear environments in real experimental conditions. With detailed numerical simulations, we test the performance of our model in scenarios involving varying numbers of nuclei, achieving an average error of less than 2 kHz in the estimated hyperfine constants.

High-Resolution NMR Spectroscopy at Large Fields with Nitrogen Vacancy Centers.

Ensembles of nitrogen-vacancy (NV) centers are used as sensors to detect nuclear magnetic resonance signals from micron-sized samples at room temperature. In this scenario, the regime of large magnetic fields is especially interesting as it leads to a large nuclear thermal polarization-thus, to a strong sensor response even in low concentration samples-while chemical shifts and J couplings become more accessible. Nevertheless, this regime remains largely unexplored owing to the difficulties of coupling NV-based sensors with high-frequency nuclear signals. In this Letter, we circumvent this problem with a method that maps the relevant energy shifts in the amplitude of an induced nuclear spin signal that is subsequently transferred to the sensor. This stage is interspersed with free-precession periods of the sample nuclear spins where the sensor does not participate. Thus, our method leads to high spectral resolutions ultimately limited by the coherence of the nuclear spin signal.

Tailored ion beam for precise colour centre creation.

We present an invariant-based quantum control scheme leading to a highly monochromatic ion beam from a Paul trap. Our protocol is implementable by supplying the segmented electrodes in the trap with voltages of the order of volts. This mitigates the impact of fluctuations in previous designs and leads to a low-dispersion beam of ions. Moreover, our proposal does not rely on sympathetically cooling ions, which bypasses the need of loading different species in the trap-namely, the propelled ion and, e.g. a [Formula: see text] to exert sympathetic cooling-significantly incrementing the repetition rate of the launching procedure. Our scheme is based on an invariant operator linear in position and momentum, which enables us to control the average extraction energy and the outgoing momentum spread. In addition, we propose a sequential operation to tailor the transversal properties of the beam before the ejection to minimize the impact spot and to increase the lateral resolution of the implantation. This article is part of the theme issue 'Shortcuts to adiabaticity: theoretical, experimental and interdisciplinary perspectives'.