A Miniaturized Metalens‐Based Spin Defect Quantum Sensor

Achieving fast, sensitive, and parallel measurement of a large number of quantum particles is an essential task in building large‐scale quantum platforms for different quantum information processing applications such as sensing, computation, simulation, and communication. Current quantum platforms in experimental atomic and optical physics based on CMOS sensors and charged coupled device cameras are limited by either low sensitivity or slow operational speed. Here an array of single‐photon avalanche diodes is integrated with solid‐state spin defects in diamond to build a fast wide‐field quantum sensor, achieving a frame rate up to 100 kHz. The design of the experimental setup to perform spatially resolved imaging of quantum systems is presented. A few exemplary applications, including sensing DC and AC magnetic fields, temperature, strain, local spin density, and charge dynamics, are experimentally demonstrated using a nitrogen‐vacancy ensemble diamond sample. The developed photon detection array is broadly applicable to other platforms such as atom arrays trapped in optical tweezers, optical lattices, donors in silicon, and rare earth ions in solids.

Magnonic devices are extensively studied for energy‐efficient information processing. High spatial resolution and high accuracy measurement is required to characterize the excitation and distribution of magnons. Here, sensing and imaging of magnons in the magnetic insulator (YIG) is realized with negatively charged boron vacancy () spin defects in 2D hexagonal boron nitride (hBN). Thermal magnon noise is studied through spin relaxometry, illustrating the nanometers proximity of the 2D quantum sensor over a large area. The small probe‐sample standoff distance helps to detect weak signals with diffraction‐limited spatial resolution. The uniform out‐of‐plane symmetry axis of is further utilized to study perpendicular magnetic anisotropy (PMA). It effectively extracts the stray field of microwave‐excited magnons from the direct stripline field. The distributions of propagating and localized magnons in different structures are subsequently imaged and analyzed. The work provides the strategy for utilizing the distinctive advantages of the van der Waals quantum sensor in magnetic imaging. The results will promote the development of magnonic devices for diverse applications.

Quantum sensing with spin defects in diamond, such as the nitrogen vacancy (NV) center, enables the detection of various chemical species on the nanoscale. Molecules or ions with unpaired electronic spins are typically probed by their influence on the NV center's spin relaxation. Whereas it is well-known that paramagnetic ions reduce the NV center's relaxation time (T1), here we report on the opposite effect for diamagnetic ions. We demonstrate that millimolar concentrations of aqueous diamagnetic electrolyte solutions increase the T1 time of near-surface NV center ensembles compared to pure water. To elucidate the underlying mechanism of this surprising effect, single and double quantum NV experiments are performed, which indicate a reduction of magnetic and electric noise in the presence of diamagnetic electrolytes. In combination with ab initio simulations, we propose that a change in the interfacial band bending due to the formation of an electric double layer leads to a stabilization of fluctuating charges at the interface of an oxidized diamond. This work not only helps to understand noise sources in quantum systems but could also broaden the application space of quantum sensors toward electrolyte sensing in cell biology, neuroscience, and electrochemistry.

Magnetic imaging with ultrahigh spatial resolution is crucial to exploring the magnetic textures of emerging quantum materials. We propose a novel magnetic imaging protocol that achieves angstrom-scale resolution by combining spin defects in van der Waals materials and terahertz (THz) scattering scanning near-field optical microscopy. Spin defects in the atomic monolayer enable the probe-to-sample distance diving into angstrom range where the exchange interactions between the probe and sample spins become predominant. This exchange interaction leads to energy splitting of the probe spin in the order of meV, corresponding to THz frequencies. With THz optics and the spin-dependent fluorescence of the probe spin, the interaction energy can be resolved entirely through optical methods. Our proposed all-optical magnetic imaging protocol holds significant promise for investigating magnetic textures in condensed matter physics due to its excellent compatibility and high spatial resolution.

Understanding the physical and chemical properties of aqueous interfaces is important in diverse fields of science, ranging from biology and chemistry to materials science. In spite of crucial progress in surface sensitive spectroscopic techniques over the past decades, the microscopic properties of aqueous interfaces remain difficult to measure. Here, we explore the use of noise spectroscopy to characterize interfacial properties, specifically of quantum sensors hosted in two-dimensional materials in contact with water. We combine molecular dynamics simulations of water interfaced with a model two-dimensional substrate and the calculation of the dynamical properties of a spin defect, representing a quantum sensor, and we investigate the impact of interfacial water and simple ions on the decoherence time of the defect. We show that the Hahn echo coherence time of the quantum sensor is sensitive to motional narrowing and to the hydrogen bonding arrangement and the dynamical properties of water and ions at the interface. We present results as a function of the liquid temperature, strength of the water-surface interaction, and varied monovalent and divalent ions, highlighting the broad applicability of near-surface quantum sensors to gain insight into the properties of aqueous interfaces.

Electronic defects in semiconductors form the basis for emerging quantum technologies, but many defect centers are difficult to access at the single-particle level. A method for probing optically inactive spin defects would reveal semiconductor physics at the atomic scale and advance the study of new quantum systems. We exploit the intrinsic correlation between the charge and spin states of defect centers to measure the charge populations and dynamics of single substitutional nitrogen spin defects in diamond. By probing their steady-state spin population, read out at the single-defect level with a nearby nitrogen vacancy center, we directly measure the defect ionization-corroborated by first-principles calculations-an effect we do not have access to with traditional coherence-based quantum sensing.

Optically active spin defects in van der Waals materials are promising platforms for modern quantum technologies. Here we investigate the coherent dynamics of strongly interacting ensembles of negatively charged boron-vacancy ({{{{{{{{rm{V}}}}}}}}}_{{{{{{{{rm{B}}}}}}}}}^{-}) centers in hexagonal boron nitride (hBN) with varying defect density. By employing advanced dynamical decoupling sequences to selectively isolate different dephasing sources, we observe more than 5-fold improvement in the measured coherence times across all hBN samples. Crucially, we identify that the many-body interaction within the {{{{{{{{rm{V}}}}}}}}}_{{{{{{{{rm{B}}}}}}}}}^{-} ensemble plays a substantial role in the coherent dynamics, which is then used to directly estimate the concentration of {{{{{{{{rm{V}}}}}}}}}_{{{{{{{{rm{B}}}}}}}}}^{-}. We find that at high ion implantation dosage, only a small portion of the created boron vacancy defects are in the desired negatively charged state. Finally, we investigate the spin response of {{{{{{{{rm{V}}}}}}}}}_{{{{{{{{rm{B}}}}}}}}}^{-} to the local charged defects induced electric field signals, and estimate its ground state transverse electric field susceptibility. Our results provide new insights on the spin and charge properties of {{{{{{{{rm{V}}}}}}}}}_{{{{{{{{rm{B}}}}}}}}}^{-}, which are important for future use of defects in hBN as quantum sensors and simulators.

Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T2*-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T2* and resonance frequency. The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm(3) and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16-24 h). High contrast T2*-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at -7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.

Spin defects in solid-state materials are strong candidate systems for quantum information technology and sensing applications. Here we explore in details the recently discovered negatively charged boron vacancies (VB−) in hexagonal boron nitride (hBN) and demonstrate their use as atomic scale sensors for temperature, magnetic fields and externally applied pressure. These applications are possible due to the high-spin triplet ground state and bright spin-dependent photoluminescence of the VB−. Specifically, we find that the frequency shift in optically detected magnetic resonance measurements is not only sensitive to static magnetic fields, but also to temperature and pressure changes which we relate to crystal lattice parameters. We show that spin-rich hBN films are potentially applicable as intrinsic sensors in heterostructures made of functionalized 2D materials.

Most modern satellites can provide two types of images: 1) panchromatic (PAN) image and 2) multispectral (MS) image. The former has high spatial resolution and low spectral resolution, while the latter has high spectral resolution and low spatial resolution. To obtain images with both high spectral and spatial resolution, pansharpening has emerged to fuse the spatial information of the PAN image and the spectral information of the MS image. However, most pansharpening methods fail to preserve spatial and spectral information simultaneously. In this article, we propose a framelet-based convolutional neural network (CNN) for pansharpening which makes it possible to pursue both high spectral and high spatial resolution. Our network consists of three subnetworks: 1) feature embedding net; 2) feature fusion net; and 3) framelet prediction net. Different from conventional CNN methods directly inferring high-resolution MS images, our approach learns to predict their framelet coefficients from available PAN and MS images. The introduction of multilevel feature aggregation and hybrid residual connection makes full use of spatial information of PAN image and spectral information of MS image. Quantitative and qualitative experiments at reduced- and full-resolution demonstrate that the proposed method achieves more appealing results than other state-of-the-art pansharpening methods. The source code and trained models are available at https://github.com/TingMAC/FrMLNet.

Hyperspectral images (HSI) have high spectral and low spatial resolutions. However, multispectral images (MSI) usually have low spectral and high spatial resolutions. In various applications HSI with high spectral and spatial resolutions are required. In this paper, a new method for spatial resolution enhancement of HSI using high resolution MSI based on sparse coding and linear spectral unmixing (SCLSU) is introduced. In the proposed method (SCLSU), high spectral resolution features of HSI and high spatial resolution features of MSI are fused. In this case, the sparse representation of some high resolution MSI and linear spectral unmixing (LSU) model of HSI and MSI is simultaneously used in order to construct high resolution HSI (HRHSI). The fusion process of HSI and MSI is formulated as an ill-posed inverse problem. It is solved by the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) and an orthogonal matching pursuit (OMP) algorithm. Finally, the proposed algorithm is applied to the Hyperion and ALI datasets. Compared with the other state-of-the-art algorithms such as Coupled Nonnegative Matrix Factorization (CNMF) and local spectral unmixing, the SCLSU has significantly increased the spatial resolution and in addition the spectral content of HSI is well maintained.

With a rising trend to use optical fiber in both short-reach and long-haul network applications, it has become necessary to detect faults with high spatial resolution, sensitivity, and dynamic range in industry. Unfortunately, the most widely used diagnostic technique, optical time-domain reflectometry (OTDR), has an inherent trade-off between the above mentioned figures of merit. Consequently, traditional OTDR systems can either be used in short-reach applications with high spatial resolution or long-haul applications with high dynamic range. Both OTDR and optical frequency-domain reflectometry systems have been proposed in the past which can arguably close the gap between the two extremes, but they also have a trade-off with the cost, form-factor, and complexity. Recently, researchers have demonstrated an input/output (I/O) interface integrated OTDR (iOTDR), which uses digital I/O ports to perform OTDR measurements with high spatial and voltage resolution. The iOTDR eliminates the necessity of using high-end analog-to-digital converters and demonstrates its potential to be fully integrated in an optical switch with minimum hardware modification. Additionally, the iOTDR is also reconfigurable and software-defined, making it a power- and resource-efficient solution. Thus, it is especially attractive for short-distance communication links, such as those in a datacenter, where computational resources are limited. This manuscript expands upon the advantages brought upon by the iOTDR to propose and demonstrate a new versatile iOTDR that can achieve high spatial resolution, sensitivity, and dynamic range for both short-reach and long-haul networks thanks to its highly reconfigurable design.

Momentum‐resolved electron energy loss spectroscopy (MREELS) probes the momentum (q) dependence (dispersion) of energy losses from characteristic excitations such as excitons, plasmon, and interband excitations thus probing bandstructures, indirect excitations, and dipole‐forbidden excitations. 1 However, the ability to obtain momentum‐resolved spectra both at high spatial and momentum resolutions has remained difficult. As such, layer‐resolved momentum spectra from ultra‐thin films, heterostructures as well as from nanostructures has not been widely reported. We present an experimental approach that enables the acquisition of momentum resolved spectra at high spatial resolution down to 2 nm using a nano‐beam electron diffraction approach. 2 Through this approach we have obtained momentum resolved spectra from individual, differently‐oriented nano‐domains in an ultra thin (12 nm) PrNiO 3 layer as well as spectra from different positions in a LaNiO 3 thin film (70 nm). Figure 1(a) displays a Z‐contrast image of the LaNiO 3 thin layer grown on a LaSrAlO 4 substrate. A nano‐beam electron diffraction pattern from the LaNiO 3 layer is shown in Figure 1(b). A slit is used to select the 200, ‐200 set of diffraction spots (shown by the red rectangle) allowing electrons that have been scattered to certain scattering angles into the spectrometer. This corresponds to the Г‐X direction of the Brillouin zone in the pseudo‐cubic symmetry of LaNiO 3 . The resulting image (ω‐q map) shown in figure 1(c) displays energy losses as function of momentum transfer along the Г‐X (q// [100] ) direction in the reciprocal space. The presented approach will enable the acquisition of momentum resolved spectra from nano‐structured materials, thin films, interfaces, surfaces, and heterostructures at high spatial, energy, and momentum resolutions.

To design a more accurate and reproducible technique for the measurement of blood-brain barrier (BBB) permeability in gadolinium-enhancing multiple sclerosis (MS) lesions. Four MS patients were scanned using a new dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) protocol based on an uninterrupted two-part acquisition consisting of an initial part at high temporal and low spatial resolutions and a second part at low temporal and high spatial resolutions. The method preserves both the high spatial resolution needed for the often small size of lesions and the high temporal resolution required during the first minute after injection to sufficiently sample the first-pass bolus. Simulations compared the performance of this new protocol with the conventional one at low temporal and high spatial resolutions throughout. The BBB permeability estimates changed by up to 33% between the two protocols. The new protocol led to simulated error on K(trans) of 7%-10%, versus 7%-30% with the conventional protocol, and was more robust with respect to offsets between acquisition and injection start times, differences in shape of the first-pass peak, and permeability values. The dual-temporal resolution protocol produces improved BBB permeability estimates and provides a more complete view of active inflammatory MS lesion pathology.

Comparison of visible and multi-satellite global inundation datasets at high-spatial resolution