Nitrogen-vacancy (NV) center in diamond is a promising quantum metrology tool finding applications across disciplines. The spin sensor measures magnetic fields, electric fields and temperature with nano-scale precision and is fully operable under ambient conditions. Moreover, it achieves precision scaling inversely with total measurement time σB ∝ 1/T (Heisenberg scaling) rather than as the inverse of the square root of T, with σB = √T the Shot-Noise limit. This scaling can be achieved by means of phase estimation algorithms (PEAs), in combination with single-shot read-out. Despite their accuracy, the range of applicability of PEAs is limited to sensing single frequencies with negligible temporal fluctuations. Nuclear Magnetic Resonance (NMR) signals from molecules often contain multifrequency components and sensing them using PEA is ruled out. Here we propose an alternative method for precision magnetometry in frequency multiplexed signals via compressive sensing (CS) techniques focusing on nanoscale NMR. We show that CS can provide for precision scaling approximately as σB ≈ 1/T, as well as for a 5-fold increase in sensitivity over dynamic-range gain, in addition to reducing the total number of resources required. We illustrate our method by taking model solid-state spectra of Glycine acquired under Magic Angle Spinning conditions.
Nitrogen-vacancy (NV) center in diamond is a promising quantum metrology tool finding applications across disciplines. The spin sensor measures magnetic fields, electric fields and temperature with nano-scale precision and is fully operable under ambient conditions. Moreover, it achieves precision scaling inversely with total measurement time σB ∝ 1/T (Heisenberg scaling) rather than as the inverse of the square root of T, with σB = √T the Shot-Noise limit. This scaling can be achieved by means of phase estimation algorithms (PEAs), in combination with single-shot read-out. Despite their accuracy, the range of applicability of PEAs is limited to sensing single frequencies with negligible temporal fluctuations. Nuclear Magnetic Resonance (NMR) signals from molecules often contain multifrequency components and sensing them using PEA is ruled out. Here we propose an alternative method for precision magnetometry in frequency multiplexed signals via compressive sensing (CS) techniques focusing on nanoscale NMR. We show that CS can provide for precision scaling approximately as σB ≈ 1/T, as well as for a 5-fold increase in sensitivity over dynamic-range gain, in addition to reducing the total number of resources required. We illustrate our method by taking model solid-state spectra of Glycine acquired under Magic Angle Spinning conditions.
Quantum sensors based on single Nitrogen-Vacancy (NV) defects in diamond are state-of-the-art tools for nano-scale magnetometry with precision scaling inversely with total measurement time σB∝1/T (Heisenberg scaling) rather than as the inverse of the square root of T, with σB=1/T the Shot-Noise limit. This scaling can be achieved by means of phase estimation algorithms (PEAs) using adaptive or non-adaptive feedback, in combination with single-shot readout techniques. Despite their accuracy, the range of applicability of PEAs is limited to periodic signals involving single frequencies with negligible temporal fluctuations. In this Letter, we propose an alternative method for precision magnetometry in frequency multiplexed signals via compressive sensing (CS) techniques. We show that CS can provide for precision scaling approximately as σB≈1/T, both in the case of single frequency and frequency multiplexed signals, as well as for a 5-fold increase in sensitivity over dynamic-range gain, in addition to reducing the total number of resources required.
We propose a protocol to estimate magnetic fields using a single nitrogen-vacancy (N-V) center in diamond, where the estimate precision scales inversely with time, $\ensuremath{\delta}B~1/T$, rather than the square-root of time, $\ensuremath{\delta}B~1/\sqrt{T}$. The method is based on converting the task of magnetometry into phase estimation, performing quantum phase estimation on a single N-V nuclear spin using either adaptive or nonadaptive feedback control, and the recently demonstrated capability to perform single-shot readout within the N-V [P. Neumann et al., Science 329, 542 (2010)]. We present numerical simulations to show that our method provides an estimate whose precision scales close to 1/T (T the total estimation time), and moreover will give an unambiguous estimate of the static magnetic field experienced by the N-V. By combining this protocol with recent proposals for scanning magnetometry using an N-V, our protocol will provide a significant decrease in signal acquisition time while providing an unambiguous spatial map of the magnetic field.
In modern-day quantum metrology, quantum sensors are widely employed to detect weak magnetic fields or nanoscale signals. Quantum devices, exploiting quantum coherence, are inevitably connected to physical constants and can achieve accuracy, repeatability, and precision approaching fundamental limits. As a result, these sensors have shown utility in a wide range of research domains spanning both science and technology. A rapidly emerging quantum sensing platform employs atomic-scale defects in crystals. In particular, magnetometry using nitrogen-vacancy (NV) color centers in diamond has garnered increasing interest. NV systems possess a combination of remarkable properties, optical addressability, long coherence times, and biocompatibility. Sensors based on NV centers excel in spatial resolution and magnetic sensitivity. These diamond-based sensors promise comparable combination of high spatial resolution and magnetic sensitivity without cryogenic operation. The above properties of NV magnetometers promise increasingly integrated quantum measurement technology, as a result, they have been extensively developed with various protocols and find use in numerous applications spanning materials characterization, nuclear magnetic resonance (NMR), condensed matter physics, paleomagnetism, neuroscience and living systems biology, and industrial vector magnetometry. In this chapter, NV centers are explored for magnetic sensing in a number of contexts. In general, we introduce novel regimes for magnetic-field probes with NV ensembles. Specifically, NV centers are developed for sensitive magnetometers for applications where microwaves (MWs) are prohibitively invasive and operations need to be carried out under zero ambient magnetic field. The primary goal of our discussion is to improve the utility of these NV center-based magnetometers.
Single nitrogen vacancy (NV) centers in diamond have been used extensively for high-sensitivity nanoscale sensing, but conventional approaches use confocal microscopy to measure individual centers sequentially, limiting throughput and access to nonlocal physical properties, where simultaneous, high-fidelity measurement of multiple centers is required. Here, we design and implement a multiplexed NV sensing platform that allows us to read out many single NV centers simultaneously using a low-noise camera. Using this platform, we coherently manipulate and read out the spin states of hundreds of individual NV centers in parallel, achieving comparable magnetic field sensitivity to confocal measurements. We also implement a parallelized version of spin-to-charge-conversion readout for low NV center spin state readout noise and use it to demonstrate multiplexed covariance magnetometry, in which we measure ten two-point magnetic field correlators from five NV centers simultaneously. From these measurements, we demonstrate the quantitative reconstruction of spatially varying magnetic correlations arising from a current-carrying wire. The number of correlators we can measure is limited only by the available laser power, opening the door to massively multiplexed covariance magnetometry. In contrast to scanning probes for imaging spatially varying magnetic fields, our approach measures the temporal dynamics of the magnetic field at many precisely defined positions simultaneously, from which the local noise spectrum and nonlocal properties such as correlation functions can be computed. This high-fidelity readout platform will find immediate applications in studying condensed matter phenomena that are characterized by the noise spectrum or correlation functions, including quantum phase transitions, dynamics far from equilibrium, magnetic order, and correlated electron phenomena.
Quantum sensing using nitrogen-vacancy (NV) centers in diamond has emerged as a powerful platform for detecting ultra-low magnetic fields under ambient conditions. Owing to their long spin coherence times, optical addressability, and compatibility with aqueous environments, it has found widespread applications in biosensing and bio-imaging. This review presents the fundamental principles and recent advances in NV-based quantum magnetometry for biosensing applications, with a particular focus on measurements in aqueous medium and at cellular and molecular length scales. We discuss the underlying spin physics of NV centers and highlight two primary detection modalities: optically detected magnetic resonance (ODMR) and T1 relaxometry-based sensing and how these approaches aids in the detection of both static magnetic fields and dynamic magnetic noise arising from biological processes. The review explores key application areas, including nanoscale nuclear magnetic resonance (NMR), monitoring of neural activity, detection of abnormal or rogue cells using NV-based platforms etc. In addition, strategies for enhancing sensitivity, such as surface functionalization of nanodiamonds, femtosecond (fs) laser-written photonic structures, and integration with microfluidic and lab-on-chip systems have also been discussed in depth. We also address the critical challenges, including surface-induced decoherence, charge-state instability, and signal-to-noise limitations in biofluids associated with NV-based biosensing applications. Finally, we outline future prospects, highlighting how NV-based magnetic biosensing provides a promising pathway for translating quantum sensing technologies into practical biomedical applications.
Quantum technologies are expected to significantly change our world in the next decades and the possible applications are diverse – ranging from quantum computation and encryption to metrology with unprecedented sensitivity. This thesis focuses on quantum sensing and imaging based on single nitrogen-vacancy (NV) centres in diamond to measure magnetic fields. Its electronic spin qualifies this point defect as a highly sensitive quantum sensor and its atomic size offers nanoscale spatial resolution. The simple optical initialisation and readout, together with the relatively long coherence time at ambient conditions, make NV centres promising candidates for biological applications and in particular for nuclear magnetic resonance (NMR) on the nanoscale. Recording the spectral information on the nanoscale allows to determine the structure of single or just a few molecules. However, the current main problems and challenges include insufficient spectral resolution, artificial signals and overall poor performance. In this thesis new spectroscopic techniques which tackle these issues are presented. First, it is shown that by randomisation of control pulse phases spurious harmonic signals can be suppressed, which otherwise complicate spectrum interpretation and can lead to false signal identification. At the same time the effects of pulse imperfections are mitigated. Furthermore, a protocol allowing to measure with a coherence independent spectral resolution is presented. It is demonstrated that linewidths below 1mHz are possible, which is an improvement of more than seven orders of magnitude compared to traditional methods. Due to its simple implementation, the protocol is relevant for many applications. Initially developed to measure signals oscillating up to several megahertz, it is further shown that modifications allow to extend the frequency range into the gigahertz domain. Finally, quantum frequency discrimination with the task to differentiate between two frequency distributions using a quantum sensor is analysed. An optimised protocol is introduced and the influences of different readout strategies are discussed with respect to the probability to make an incorrect decision. These findings are useful for diagnostic tests in NMR.