The rapid development of the Internet of Things and the digital information era has intensified the demand for secure hardware and information systems. Physical unclonable functions (PUFs) provide a hardware-based approach by exploiting fabrication-induced randomness to generate unique, unclonable labels. Concurrently, advances in deterministic nanofabrication increasingly challenge the unclonability of conventional micro- and nanoscale PUFs, motivating the exploration of more fundamental sources of physical randomness. Here, we demonstrate an atomic-scale PUF architecture that leverages intrinsic randomness in solids through lattice and defect engineering. The resulting PUFs exhibit both three-dimensional spatial variability and atomic-scale configurational complexity, yielding extraordinary encoding space and uniqueness. For a characteristic feature size of 1 nanometer, the Shannon entropy is estimated at 17.49, underscoring the encoding capacity. Moreover, the embedded structure ensures intrinsic unclonability and robustness against environmental perturbations. These results establish atomic-scale PUFs as a fundamentally secure and scalable platform for next-generation hardware and information security.

The accelerating growth of global data generation demands data storage platforms that offer high capacity, long lifespan, and low energy consumption beyond the limits of electronic memory technologies. Optical storage provides an attractive alternative. However, its density is fundamentally constrained by the optical diffraction limit and the limited scalability from the point-by-point laser writing, as well as thermal accumulation during high-speed writing. Here, we introduce a large-scale optical data storage scheme that is compatible with the progress in chip fabrication by combining electron-beam lithography (EBL) and ion implantation to deterministically encode high-density data. The approach achieves precise control of ion number and spatial distribution, enabling multi-bit grayscale encoding and wavelength division multiplexing with chip-scale patterning over millimeter areas. Wavelength-selective readout is performed using downconversion and upconversion fluorescence detection, allowing crosstalk-free retrieval of multiplexed data channels. We further develop a neural network-based super-resolution algorithm that reconstructs data beyond the diffraction limit, further increasing the effective storage density. Using this integrated framework, we achieve an optical data density of 10 Gbit/cm^2 with high fidelity. Our results establish a micro/nano-fabrication-compatible route to large-scale, high-density optical memory and provide a foundation for next-generation cold data optical storage technologies.

Scanning nitrogen-vacancy (NV) center electrometry has shown potential for quantitative quantum imaging of electric fields at the nanoscale. However, achieving nanoscale spatial resolution remains a challenge since employing gradiometry to overcome electrostatic screening causes resolution-limiting trade-offs including the averaging effect and the sensor-sample proximity. Here, we demonstrate a scanning NV center protocol that achieves an enhanced spatial resolution of ∼10 nm. We develop an axially symmetric probe with a sub-nanometer oscillating amplitude, which simultaneously provides robust intermittent-contact mode feedback and ensures close engagement between the diamond tip and the sample. As an example, we experimentally demonstrate a 10 nm spatial resolution on ferroelectric lithium niobate. Scanning NV center electrometry with this resolution can directly resolve the nanoscale polar textures and dynamics of emerging ferroelectrics, which commonly arise on the scale of tens of nanometers.

The chemical environment at interfaces plays an important role in controlling the structure, properties, and performance of low-dimensional materials. The water environment and adsorbates on solid surfaces are the most common interface environments that are prevalent in nonultrahigh vacuum conditions. Despite their ubiquitous presence, the structural and dynamic properties of these surface adsorbates are difficult to be directly characterized in situ at the atomic scale. Here, we report a dissection method leveraging shallow nitrogen-vacancy centers to quantitatively characterize nanoscale adsorbate layers on diamond surfaces with distinct structural and dynamical signatures. Our results reveal that under ambient conditions, a tightly bound organic adsorbate layer and an icelike interfacial water layer coexist on diamond surfaces. We further demonstrate that the rigidity of the interfacial water layer originates from its interaction with specific surface adsorption sites, such as the dangling bonds on the diamond surface. These findings establish new insights for investigating the structure and dynamics of low-dimensional adsorbates, as well as surface properties modulated by adsorbates under native conditions.

Mid- to long-wave infrared (MIR-LWIR) microscopy provides a non-invasive and label-free tool to acquire rich spectroscopic and structural information about chemical materials and biomedical samples. However, the lateral resolution is typically limited by severe optical diffraction at long infrared wavelengths, which hinders imaging systems from observing intricate details beyond the diffraction limit. Here, we report a MIR-LWIR to near infrared (NIR) transducer based on a rare-earth-doped crystal, which enables room-temperature MIR-LWIR imaging within a broad spectral coverage of 7-10.6 . The underlying mechanism relies on monitoring fluorescence intensity changes under infrared illumination, thus favoring far-field upconversion operation without suffering from the stringent requirements of polarization control, phase matching, or nanocavity design, commonly encountered in previous upconversion imaging platforms. Moreover, the presented lanthanide-based transducer is compatible with close positioning to nano-/micro-structures, facilitating near-field MIR-LWIR imaging with an improved spatial resolution from 50 to sub-. Notably, hidden objects can be accurately identified with high axial precision owing to the confocal excitation configuration, which enables high-resolution MIR-LWIR depth imaging. In addition, experimental validation using 2D materials such as hexagonal boron nitride reveals distinct MIR-LWIR response characteristics, demonstrating the system's capability for high-resolution imaging and spectroscopic characterization across extended infrared wavelengths.

We propose redan actively correlated Mach-Zehnder interferometer (MZI) based on the Kerr state, aiming to beat the shot noise limit (SNL) of conventional interferometers. Through theoretical analysis, the phase sensitivity of three detection schemes-homodyne detection (HD), single-intensity detection (SID), and total-intensity detection (TID)-is systematically investigated under both lossless and lossy conditions. The results demonstrate that the Kerr state not only significantly improves the phase sensitivity of the interferometer, but also exhibits superior anti-interference ability in practical environments, with performance consistently outperforming that of the coherent state. This work provides a novel theoretical framework for the application of nonlinear quantum optics in precision measurement.

The strong coupling between an emitter and a cavity is significant for advancing quantum networks. Due to their long optical and spin coherence times, rare-earth ions (REIs) represent a compelling platform for quantum networks. However, their inherently weak intra-4f optical transitions typically result in low coupling strength, thus restricting most current achievements to the weak coupling regime. This work proposes a scheme to realize an on-chip quantum network by coupling REIs to high-quality whispering gallery mode (WGM) microcavities. Additionally, we provide numerical validation for a parametric amplification technique to enhance the emitter-cavity coupling strength. As an extension of this approach, the coupled system efficiently achieves the quantum entanglement of local and flying qubits. This study deepens the understanding of emitter-cavity interactions and contributes to realizing REIs-based photonic platforms, which are crucial to distributed quantum computing and developing robust quantum networks.

The ability to control solid-state quantum emitters is fundamental to advancing quantum technologies. The performance of these systems is fundamentally governed by their spin-dependent photodynamics, yet conventional control methods using cavities offer limited access to key non-radiative processes. Here we demonstrate that anisotropic lattice strain serves as a powerful tool for manipulating spin dynamics in solid-state systems. Under high pressure, giant shear strain gradients trigger a complete reversal of the intrinsic spin polarization, redirecting ground-state population from $|0\rangle$ to $|\pm 1\rangle$ manifold. We show that this reprogramming arises from strain-induced mixing of the NV center's excited states and dramatic alteration of intersystem crossing, which we quantify through a combination of opto-magnetic spectroscopy and a theoretical model that disentangles symmetry-preserving and symmetry-breaking strain contributions. Furthermore, the polarization reversal is spatially mapped with a transition region below 120 nm, illustrating sub-diffraction-limit control. Our work establishes strain engineering as a powerful tool for tailoring quantum emitter properties, opening avenues for programmable quantum light sources, high-density spin-based memory, and hybrid quantum photonic devices.

Molecular chirality plays a crucial role in physics, chemistry, life sciences and pharmacology. Nowadays, the chiral discrimination and control at the single-molecule level is urgently needed to reveal the origin of the chirality-relevant phenomena by recovering the information disturbed by the ensemble averaging. The method of magnetic resonance (MR), as one of powerful tools for structure analysis, is blind to the molecular chirality in the absence of a chiral reagent. Here we propose and experimentally demonstrate a direct MR-based method for determining the chirality at the single-molecule level through constructing the symmetry-breaking dynamics of nearby nuclear spins. In principle, the mirror asymmetry of two enantiomers in real space is manifested by breaking the joint symmetry of the mirror reflection and time reversal in spin space under spin dynamics. Experimentally, two enantiomers are indistinguishable from the dynamics of strongly-coupled but unpolarized nuclear spins, but diverge evidently in the dynamical results that break the field-inversion symmetry after spins are polarized. Our method and results will benefit the study of chirality-induced properties in the fields of chemistry and biology.

Accurate characterization of the three-dimensional (3D) spatial radiation characteristics of microwave fields, especially the out-of-plane intensity distribution, remains a critical challenge in advanced microwave technology and diamond nitrogen-vacancy (NV) center-based quantum sensing. In this work, a high-precision three-dimensional microwave magnetic field measurement system based on a fiber-integrated NV center scanning probe is developed. The system enables high-spatial-resolution characterization of electromagnetic fields on the surface of miniaturized microwave antennas. The core of the system is a mechanically polished tapered optical fiber with a 26.5° taper angle, integrated with a diamond nanopillar containing ensemble NV centers at the fiber tip. This tapered structure conforms more closely to the diamond nanopillars, thereby enabling high-sensitivity electromagnetic imaging on the chip surface. We perform microwave magnetic field measurements on a standard Ω-ring radiating structure: in-plane measurements at 100 and 500 μm from the ring edge verify excellent field uniformity in the central region of the Ω-ring radiating structure, while out-of-plane characterization from 0 to 500 μm above the ring center identifies an effective radiation distance of 500 μm for the structure. This system realizes non-destructive, high-precision on-chip electromagnetic field characterization and can be extended to diverse quantum magnetometry applications requiring 3D measurement capability.

Quantum relaxometry based on nitrogen-vacancy (NV) centers in diamond is an easy-to-use technique that detects magnetic noise by measuring the longitudinal relaxation of NV centers. It is favored in chemical and biological applications due to the robustness against imperfect spin control. By tuning the energy level, NV relaxometry can detect magnetic noise generated by other spins and obtain magnetic resonance spectra through cross relaxation. However, the inhomogeneous broadening of NV centers greatly limits the spectral resolution of cross-relaxation spectra. Here we demonstrate a hole-burning technique to remove the inhomogeneous broadening. We utilize a weak pump field to deplete specific NV centers during the relaxation measurement, which contribute a reverse signal in the cross-relaxation spectra with a much narrower linewidth. Our method retains the convenience and sensitivity of NV relaxometry, opening up new avenues for high-resolution magnetic resonance spectroscopy in complex scenarios.

Detecting individual spins-including stable and metastable states-represents a fundamental challenge in quantum sensing, with broad applications across condensed matter physics1,2, quantum chemistry3 and single-molecule magnetic resonance imaging4,5. Although nitrogen-vacancy (NV) centres in diamond have emerged as powerful nanoscale sensors, their performance for single-spin detection remains constrained by substantial environmental noise and restricted sensing volume6,7. Here we propose and demonstrate an entanglement-enhanced sensing protocol that overcomes these limitations through the strategic use of entangled NV pairs. Our approach achieves a 3.4-fold enhancement in sensitivity and a 1.6-fold improvement in spatial resolution relative to single NV centres under ambient conditions. The protocol uses carefully engineered entangled states that amplify target spin signals through quantum interference while suppressing environmental noise. Crucially, we extend these capabilities to resolve metastable single-spin dynamics, directly observing stochastic transitions between different spin states by identifying state-dependent coupling strengths. This dual functionality enables simultaneous detection of static and dynamic spin species for studying complex quantum systems. The achieved performance establishes entanglement-enhanced sensing as a viable pathway towards atomic-scale characterization of quantum materials and interfaces.

The nitrogen-vacancy (NV) center can serve as a magnetic sensor for electron paramagnetic resonance (EPR) measurements. Benefiting from its atomic size, the diamond chip can integrate a tremendous amount of NV centers to improve the magnetic-field sensitivity. However, EPR spectroscopy using NV ensembles is less efficient due to inhomogeneities in both sensors and targets. Spectral line broadening induced by ensemble averaging is even detrimental to spectroscopy. Here we show a kind of cross-relaxation EPR spectroscopy at zero field, where the sensor is tuned by an amplitude-modulated control field to match the target. The modulation makes detection robust to the sensors inhomogeneity, while zero-field EPR is naturally robust to the targets inhomogeneity. We demonstrate an efficient EPR measurement on an ensemble of ∼30 000  NV centers. Our method shows the ability to not only acquire unambiguous EPR spectra of free radicals, but also monitor their spectroscopic dynamics in real time.

The nanoscale charge environment critically influences semiconductor physics and device performance. While conventional bulk characterization techniques provide volume-averaged defect properties, they lack the spatial resolution to resolve nanoscale charge heterogeneity and identify microscopic noise sources. Here, we utilize single PL5 centers in 4H-SiC as room-temperature broadband quantum sensors to fill in the gap. We report the first real-time, nanoscale observation of singlecharge tunneling dynamics in a commercial semiconductor at room temperature, by monitoring the random telegraph noise using optically detected magnetic resonance (ODMR). This capability enables an electrical noise imaging technique, showing distinct noise variations across different wafer substrates. By employing dynamical decoupling, we extend noise spectroscopy from near-DC to MHz frequencies, uncovering significant noise spectral density correlations across frequency bands. Finally, we probe MHz-GHz noise and identify its origin via T1 relaxation spectroscopy, obtaining the first nanoscale electron paramagnetic resonance (EPR) spectroscopic fingerprint of charge defects in SiC. These techniques open avenues for characterizing noise environments in semiconductor devices, providing critical insights for optimizing SiC fabrication processes, defect control, and advancing quantum technologies.

The one-dimensional side gate based on graphene edges shows a significant capability of reducing the channel length of field-effect transistors, further increasing the integration density of semiconductor devices. The nanoscale electric field distribution near the edge provides the physical limit of the effective channel length; however, its imaging under ambient conditions is still lacking, which is a critical aspect for the practical deployment of semiconductor devices. Here, we used scanning nitrogen-vacancy (N-V) microscopy to investigate the electric field distribution near edges of single-layer graphene. Realspace scanning maps of photocharged floating graphene flakes were acquired with a spatial resolution of approximately 10 nm, and the electric edge effect was quantitatively studied by analyzing the N-V spin energy-level shifts due to the electric Stark effect. Since the graphene flakes are isolated from external electric sources, we brought out a theory based on the photothermionic effect to explain the charge transfer from graphene to the oxygen-terminated diamond probe with a disordered distribution of charge traps. Real-time tracing of electric fields detected the photothermionic emission process and the recombination process of the emitted electrons. This study provides a perspective for graphene-based one-dimensional gates and optoelectronics with nanoscale real-space imaging and, moreover, offers a method to tune the chemical environment of diamond surfaces based on optical charge transfer.

Sea surface temperature (SST) is critically important for understanding ocean dynamics and supporting various marine activities, making accurate short-term SST forecasting highly significant. However, accurately modeling the multiscale variability of SST remains challenging for existing deep learning (DL) models. This study introduces the coupled Transformer-CNN network (CoTCN), a hybrid architecture designed to leverage the multiscale variability of SST. The CoTCN combines the strengths of Transformers and convolutional neural networks (CNNs), significantly enhancing SST forecasts' spatial continuity and predictive accuracy. Compared to five state-of-the-art DL models based on Transformers or CNNs that include convolutional long short-term memory (ConvLSTM), ConvGRU, adaptive Fourier neural operator (AFNO), PredRNN, and SwinLSTM, the CoTCN demonstrates superior performance in global and local areas of SST forecasting. At 1-day lead time, the CoTCN reduces the global average root-mean-square error (RMSE) by over 15%, with forecast errors ranging from 0.20 C-degrees to 0.53 C-degrees across 1-10-day lead times. Moreover, the CoTCN effectively mitigates the checkerboard artifacts inherent to the Vision Transformer (ViT) architecture. These findings highlight the effectiveness of the CoTCN in capturing SST's multiscale features and underscore the promising potential of hybrid architectures for future DL models.

Ensemble nitrogen-vacancy (NV) centers in diamond are promising platforms for quantum sensing due to their exceptional magnetic sensitivity. This sensitivity is critically governed by the NV ensemble's yield, which determines the number of active sensors and their coherence properties. A high yield is essential for simultaneously achieving a high NV density and long spin coherence time. However, the complex process of NV formation remains quantitatively poorly understood. In this study, we systematically optimize the electron irradiation dose to maximize the yield of NV ensembles in chemical vapor deposition (CVD) diamond. We quantitatively characterize the concentrations of key nitrogen-related defects, including vacancies and electron donors, under varying conditions. Our results identify the initial P1 center (nitrogen) concentration, the vacancy yield, and the availability of electron donors as the primary factors controlling the final NV yield. These findings provide crucial insights for defect engineering strategies to enhance NV center production, paving the way for more sensitive and efficient quantum sensors.

Critical fluctuations play a crucial role in determining spin orders in low-dimensional magnetic materials. However, experimentally linking these fluctuations to scaling theory-and thereby uncovering insights into spin interaction models-remains a challenge. Here, we utilize a nitrogen-vacancy center-based quantum decoherence imaging technique to probe critical fluctuations in the van der Waals magnet Fe3GeTe2. Our data reveal that critical fluctuations produce a random magnetic field, with noise spectra undergoing significant changes near the critical temperature. To explain this phenomenon, we developed a theoretical framework showing that the spectral density exhibits 1/f noise characteristics near the critical temperature, transitioning to white noise behavior away from this regime. By experimentally adjusting the sample-to-diamond distance, we identified the crossover temperature between these two noise types. These findings offer an approach to studying phase transition dynamics through critical fluctuations, enabling precise determination of critical exponents associated with long-range correlations. This methodology holds promise for advancing our understanding of critical phenomena across diverse physical systems.

Combining optical tweezers with fluorescence microscopy is a powerful tool for single-cell analysis, playing a pivotal role in disease diagnosis, cell sorting, and the investigation of cellular dynamics. However, fluorescence detection faces challenges such as blinking, photobleaching and autofluorescence in biotissues. To address these limitations, we developed a magnetic detection strategy by integrating quantum magnetometry using nitrogen-vacancy centers into optical tweezers,demonstrating precise trapping and manipulation of individual cells in microfluidic environment. We detected a magnetic signal of 89 μT from a single cell labeled with magnetic nanoparticles, compared to a noise floor of 3.9 μT observed in unlabeled cells. This platform provides a promising approach for high-precision single-cell analysis and holds significant potential for probing cellular activities within biological microenvironments.