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

Ensembles of nitrogen-vacancy (NV) centers are used as sensors to detect NMR 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 polarisation -- 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 to couple NV-based sensors with high-frequency nuclear signals. In this work, 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.Comment: 6 pages, 3 figure

Tailored Ion Beam for Precise Color Center Creation

We present a unitary quantum control scheme that produces a highly monochromatic ion beam from a Paul trap. Our protocol is implementable by supplying the segmented electrodes with voltages of the order of Volts, which mitigates the impact of fluctuating voltages in previous designs and leads to a low-dispersion beam of ions. Moreover, our proposal does not rely on sympathetically cooling the ions, which bypasses the need of loading different species in the trap -- namely, the propelled ion and, e.g., a $^{40}$Ca$^+$ atom able to exert sympathetic cooling -- 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

Amplified Nanoscale Detection of Labelled Molecules via Surface Electrons on Diamond

The detection of individual molecules and their dynamics has been a long-standing challenge in the field of nanotechnology. In this work, we present a method that utilizes a nitrogen vacancy (NV) center and a dangling-bond on the diamond surface to measure the coupling between two electronic targets tagged on a macromolecule. To achieve this, we design a multi-tone dynamical decoupling sequence that leverages the strong interaction between the nitrogen vacancy center and the dangling bond. In addition, this sequence minimizes the impact of decoherence finally resulting in an increased signal-to-noise ratio. This proposal has the potential to open up new avenues for fundamental research and technological innovation in distinct areas such as biophysics and biochemistry.Comment: 9 pages, 6 figure

Dynamical decoupling methods in nanoscale NMR

Nuclear magnetic resonance (NMR) schemes can be applied to micron-, and nanometer-sized samples by the aid of quantum sensors such as nitrogen vacancy (NV) color centers in diamond. These minute devices allow for magnetometry of nuclear spin ensembles with high spatial and frequency resolution at ambient conditions, thus having a clear impact in different areas such as chemistry, biology, medicine, and material sciences. In practice, NV quantum sensors are driven by microwave (MW) control fields with a twofold objective: On the one hand, MW fields bridge the energy gap between NV and nearby nuclei which enables a coherent and selective coupling among them while, on the other hand, MW fields remove environmental noise on the NV leading to enhanced interrogation time. In this work we review distinct MW radiation patterns, or dynamical decoupling techniques, for nanoscale NMR applications

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

Publisher Copyright: © 2024 American Physical Society.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.Peer reviewe