This work investigates the modulation of x-rays by high-resolution zone plates (ZPs), challenging the limitations of traditional phasor-based theory when volume diffraction effects (VDE) dominate. Using the beam propagation method (BPM), we simulated the optical field dynamics and identified three key causes of efficiency degradation in traditional ZPs with rectangular profiles: amplitude-type modulation, focal spot displacement, and phase mismatch. Experimental validation using a 15 nm outermost-zone ZP fabricated via e-beam lithography and tested at Shanghai Synchrotron Radiation Facility (SSRF) confirms the superior accuracy of BPM over phasor-based theory. Furthermore, slant zone plates incorporating Bragg diffraction mitigate VDE-induced losses, achieving near-ideal phase modulation. Finally, a waveguide-based interpretation provides physical insight into VDE mechanisms, highlighting the potential of geometric innovations to overcome current limitations.

The thermal response of proximity Josephson junctions (JJs) is governed by the temperature ($T$)-dependent occupation of Andreev bound states (ABS), making them promising candidates for sensitive thermal detection. In this study, we systematically engineer ABS to enhance the thermal sensitivity of critical current ($I_{\mathrm{c}}$) of proximity JJs, quantified as $|d{I}_{\mathrm{c}}/dT|$ for the threshold readout scheme and $|d{I}_{\mathrm{c}}/dT·I_{\mathrm{c}}^{-1}|$ for the inductive readout scheme. Using a gate-tunable graphene-based JJ platform, we explore the impact of key parameters—including channel length, transparency, carrier density, and superconducting material—on the thermal response. Our results reveal that the proximity-induced superconducting gap plays a crucial role in optimizing thermal sensitivity. For the threshold scheme, we obtain a width-normalized sensitivity of $|d{J}_{\mathrm{c}}/dT|\approx 0.2\mathrm{\mu }\mathrm{A}{\mathrm{K}}^{-1}\mathrm{\mu }{\mathrm{m}}^{-1}$ at 0.1 K in an aluminum-based graphene JJ. Notably, we see a maximum $|d{I}_{\mathrm{c}}/dT·I_{\mathrm{c}}^{-1}|$ value of $0.6{\mathrm{K}}^{-1}$ at 50 mK with titanium-based graphene JJs. By demonstrating a systematic approach to engineering ABS in proximity JJs, this work establishes a versatile framework for optimizing thermal sensors and advancing the study of ABS-mediated transport.

Multimode superconducting circuits offer a promising platform for engineering robust systems for quantum computation. Previous studies indicate that single-mode devices cannot be engineered to simultaneously exhibit resilience against multiple decoherence sources due to conflicting requirements. In contrast, multimode systems offer increased flexibility and have proven capable of overcoming these fundamental limitations. Here, we present a multimode device optimized for quantum information processing. It features an anharmonicity of a third of the qubit frequency and reduced energy dispersion caused by charge and magnetic flux fluctuations. It exhibits improvements over the fundamental errors limiting transmon and fluxonium coherence and control, achieving ratios between the total coherence time and the gate time $T_2/t_{\mathrm{g}}$ one order of magnitude larger than transmon and two times larger than fluxonium for microwave charge drives, assuming equal dielectric and inductive loss quality factors and limited drive strength. Simulations further demonstrate the device’s robustness to circuit parameter deviations, a known limitation of many multimode devices.

Two-dimensional (2D) van der Waals (vdW) bilayers, with their intrinsic interlayer electric fields for enhanced carrier separation, provide a promising platform for efficient photocatalysis. However, the microscopic mechanisms linking these internal fields to higher photocatalytic activities remain elusive. Here, we construct ${\text{HfN}}_2$ bilayers with different stacking orders to explore how interlayer polarization governs carrier dynamics for higher photocatalytic water-splitting characteristics. First-principles calculations show that the AB stacking, which breaks interlayer symmetry, possesses a spontaneous polarization, leading to an intrinsic type-II band alignment and strongly suppressed electron-hole recombination. Thereby, AB stacking exhibits prolonged carrier lifetimes and enhanced solar-to-hydrogen conversion compared with the ${\text{AA}}^{\prime }$ stacking. Moreover, such spontaneous built-in fields can also generate stronger electron overpotentials, lowering hydrogen evolution reaction barriers and reducing external bias requirements during hydrogen evolution. Via interlayer sliding, the completely reversed interlayer polarization can exchange the oxidation and reduction planes, suggesting a viable route toward their switchable photocatalytic applications. Since the interlayer polarization originates purely from stacking asymmetry, these insights are broadly applicable to other 2D vdW bilayers. Therefore, our findings offer a feasible pathway for the next design and optimal regulation of 2D high-efficient photocatalysts.

Understanding the lattice-dynamical and electronic transport mechanisms of thermoelectric materials is essential for identifying systems that combine intrinsically low lattice thermal conductivity with favorable charge-transport characteristics. We present a comprehensive first-principles investigation of the thermoelectric properties of Li-based chalcopyrite compounds ${\text{LiXTe}}_2(\mathrm{X}=\text{Al},\text{Ga},\text{In})$. By combining the Boltzmann transport equation with self-consistent phonon theory, including bubble-term corrections and both three-phonon and four-phonon scattering, we reveal the microscopic origin of their intrinsically ultralow lattice thermal conductivity. Te-dominated isolated optical soft modes in the low-to-mid-frequency region, together with strong higher-order anharmonicity, substantially enhance phonon scattering. In particular, the inclusion of four-phonon processes reduces the lattice thermal conductivity of ${\text{LiInTe}}_2$ by 45% (41%) along the $c$-axis ($a/b$-axis) at 300 K, demonstrating pronounced anharmonic behavior. Electronic transport is evaluated using the AMSET framework, explicitly incorporating key scattering mechanisms and spin-orbit coupling (SOC) effects. ${\text{LiGaTe}}_2$ exhibits a highly dispersive, multivalley-degenerate band structure that significantly decouples $S\text{–}\sigma \text{–}{\kappa }_e$, leading to outstanding performance with an $n$-type $ZT$ of 2.8 at 800 K (2.2 with SOC). The experimental synthesis of ${\text{LiXTe}}_2$ would confirm the structural stability and practical viability of this family. These results establish ${\text{LiXTe}}_2$ as a promising high-performance thermoelectric system and provide essential microscopic insights for tuning strongly anharmonic semiconductors.

Quantum sensors often consist of packaging, such as dielectric-based vapor cells and metallic electrodes, that reduces and spatially alters the locally observed electromagnetic fields. These effects have been well studied in the optical regime and even in the rf regime over a few GHz. However, there have been few studies in the electrically small regime below 1 GHz. In order to account for or remove the effects of the packaging, more studies are needed across a broad range of frequencies. This paper reports on the complex permittivity and conductivity of several commercially available vapor cells used for Rydberg electric-field sensing from 10 to 300 MHz. A new method using a stripline transmission measurement was performed, and full-wave electromagnetics modeling was used to extract the effective dielectric constitutive parameters from the vapor cells. Additionally, the field reduction inside the vapor cell is reported, and published atomic measurements of the electric field are used to further validate the results presented here. Several observations were made from the measurements, such as the frequency dependencies of the rf dispersion and absorption. Applications of this technique include making precise numerical field corrections or physically designing a more optimal vapor cell via coatings, material changes, or geometric changes to improve field strength and uniformity.

High-fidelity quantum-state preparation is a central task in quantum information science. In practice, it is commonly guided either by full quantum state tomography, which becomes prohibitively resource-intensive as system size grows, or by empirically chosen measurement settings that lack principled optimality. Here, we show that quantum state verification (QSV) can be elevated from a purely diagnostic tool to a prescriptive framework for quantum-state preparation, directly specifying experimentally optimal measurements and quantitative fidelity indicators without full state reconstruction. We experimentally realize this prescriptive paradigm using a three-qubit nonstabilizer $W$ state and a modified homogeneous QSV protocol. The verification measurements not only certify the prepared state with high confidence but also serve as a tomography-free indicator that systematically informs the preparation procedure. Using only nine measurement settings and ${10}^4$ samples, we achieve high-fidelity state preparation consistent with full tomography that requires orders of magnitude more resources. Beyond the present implementation, the prescriptive structure of QSV is naturally compatible with closed-loop feedback control, outlining a pathway toward genuine real-time quantum-state preparation in future low-latency platforms.

Realizing deterministic and bright single-photon sources with minimal two-photon probability at room temperature is essential for quantum communication, computation, and sensing. Solid-state quantum emitters, particularly nitrogen-vacancy (N-$V$) centers in diamond, are prime candidates for single-photon emission and spin addressability but suffer from limited photon extraction efficiency and higher two-photon probability. Here, we demonstrate efficient coupling of single N-$V$ centers in diamond nanowaveguides to guided optical modes, enabling enhanced single-photon outcoupling with low two-photon probability. By optimizing excitation and collection geometry, we achieve a single-photon count rate of approximately $2\text{Mcps}$ along with a low two-photon probability of $g^{(2)}(0)=0.014\pm 0.004$. The nanowaveguide architecture overcomes alignment and bandwidth constraints of resonant cavities, providing a scalable, fabrication-compatible route for bright single-photon sources.

The laser-ranging interferometer (LRI) serves as a core payload for space-based gravitational-wave missions, as well as for gravity recovery missions. In this work, a ground-based simulator reproducing a three-spacecraft formation with six interferometric links is developed to emulate a subset of the on-orbit configuration of space-based missions. The formation is realized on air-bearing platforms forming a 10 m equilateral triangle, thereby providing a dynamic experimental environment. Each spacecraft (S/C) carries a complete set of in-house developed interferometric payloads, including an NPRO laser, a laser frequency stabilization system, two optical benches, and an integrated field programmable gate array (FPGA)-based electronics unit. The FPGA implements key functions, including weak-light phase locking, phasemeter, and differential wavefront sensing (DWS). In experiments, all six laser links are successfully established and operated simultaneously, effectively reproducing the configuration of an on-orbit S/C interferometer. At 4 mHz, the laser frequency stability is better than $80\mathrm{Hz}/\sqrt{\mathrm{Hz}}$, the weak-light phase-locking control noise is below $2\times {10}^{-4}\mathrm{rad}/\sqrt{\mathrm{Hz}}$, and the pointing stability is better than $4\mathrm{\mu }\mathrm{rad}/\sqrt{\mathrm{Hz}}$. The optical bench and the air-bearing platform exhibit displacement noise at the micrometer and sub-millimeter levels, respectively. This work provides a systematic and multi-perspective validation of S/C formation interferometry for space-based gravitational-wave detection, laying an important experimental foundation for future space missions.

The semiconductor chip manufacturing process is complex and lengthy, and potential errors can arise at every stage. Each wafer contains numerous chips, and wafer bin maps can be generated after chip testing. By analyzing the defect patterns on these wafer bin maps, the manufacturing steps at which errors occur can be inferred. In this work, we improve the quantum Bayesian inference algorithm and apply the proposed algorithm to accelerate the identification of error patterns on wafer bin maps, thereby assisting in chip yield analysis. We show the algorithm for error identification and detail the implementation of the improved quantum Bayesian inference. Our results demonstrate the speed advantage of quantum computation over classical algorithms for a real-world problem, highlighting the practical significance of quantum computation for many problems based on Bayesian inference.

We present a countermeasure against the detector-blinding attack (DBA) utilizing statistical analysis of error and double-click events accumulated during a quantum key distribution session under randomized modulation of single-photon avalanche diode (SPAD) detection probabilities via gate voltage manipulation. Building upon prior work demonstrating the ineffectiveness of this countermeasure against continuous-wave (cw) DBA, we extend the analysis to evaluate its performance against pulsed DBA. Our findings reveal an approximately 13 dB increase in the trigger pulse energies difference between default and reduced gate voltage applied under pulsed DBA conditions compared with cw DBA. This heightened difference enables a re-evaluation of the feasibility of utilizing SPAD detection probability variations as a countermeasure and makes it possible to estimate the fraction of bits compromised by an adversary during pulsed DBA.

Optically active spin qubits have emerged as powerful quantum sensors capable of nanoscale magnetometry; yet conventional coherent sensing approaches are ultimately limited by the coherence time of the sensor, typically precluding detection in the sub-MHz regime. We present a broadly applicable fluorescence-encoding method that circumvents coherence-time constraints by transducing time-varying magnetic fields directly into modulated fluorescence signals. Using nitrogen-vacancy centers in diamond as a model system, we demonstrate shot-noise-limited sensitivity for ac magnetic fields spanning near-dc to MHz frequencies, with detection bandwidth tunable via optical excitation power. The technique captures complete spectral information in a single measurement, eliminating the need for point-by-point frequency scanning, and allows phase-sensitive multifrequency detection. This approach transforms quantum sensors into atomic-scale spectrum analyzers, with immediate applications for low-frequency rf communication, zero-field nuclear magnetic resonance, and bioelectronic sensing. Our approach is broadly applicable to the expanding class of optically active spin qubits, including molecular systems and fluorescent proteins, opening new sensing regimes previously inaccessible to coherent techniques.

Quantum transport in atomistic devices is governed by both localized quantum coupling and long-range Coulomb interactions. However, existing deep learning models for device simulation struggle to capture these inherently nonlocal effects. To address this challenge, we propose the Position-Aware Global Attention Network (PGA-Net), a Transformer-based architecture for quantum transport simulation. PGA-Net introduces a multiscale physical field learning framework that integrates local physical encoding with global attention decoding, along with a trainable two-dimensional (2D) positional encoding to enhance spatial structure awareness. By learning an end-to-end mapping from device inputs to the atomistic electrostatic potential outputs, PGA-Net achieves up to a $10\times$ simulation speedup while maintaining consistency with the nonequilibrium Green’s function method. On a dataset of 6015 2D atomistic MOSFET samples, PGA-Net attains a mean absolute error below 0.02 V for potential prediction. Moreover, the learned physical representations can be further used to recover other key transport-related quantities, such as the charge density and the local density of states. Overall, this work provides an efficient route for atomic-scale device simulation under similar physical assumptions and boundary conditions and offers insights into extending physics-aware global attention mechanisms to broader device-level modeling.

Numerical calculus algorithms, which estimate derivatives and integrals from data series acquired either via measurements or by sampling functions, are essential in scientific computing. To date, few quantum algorithms have been developed to perform calculus operations based on closed-form functional inputs; yet, in many practical applications, field variables are numerically described via a series of samples rather than closed-form expressions. This paper presents the theoretical development and the gate-level circuit implementation of quantum algorithms for numerical differentiation and, up to addition of a constant, indefinite integration. The methodology relies on a spectral approach that leverages the computational efficiency of the quantum Fourier transform and the parallel computing capability afforded by quantum superposition to evaluate outputs at all domain points simultaneously. The differentiation approach is also extended to enable gradient estimation, and postprocessing procedures are presented to recover sign information. The primary outputs of the proposed algorithms are quantum state vectors directly proportional to the numerical derivative or integral of the given data; therefore, the correctly signed results are made available to proceeding quantum computations. This result lays the foundation for the proposed algorithms to serve as core subroutines in applied quantum computing operations, such as image processing, data analysis, and machine learning.

Microrheology involves the study of matter’s rheological properties at the microscale and has a wide application in biology, chemistry, and other fields. Exploring the microrheology of intracellular fluids is critical for understanding cell dynamics and related biological processes, and providing insights into cell physiology. Here, we present a label-free, noninvasive microrheology platform that simultaneously integrates holographic optical tweezers for 3D manipulation with double-helix point spread function microscopy for 3D localization. Without using externally labeled particles, an arbitrary endogenous particle within pyroptotic cell can be captured by holographic optical tweezer and moved to desired area in 3D space. Double-helix point spread function microscopy can enhance the imaging contrast of trapped particle and precisely determine its 3D position without prior knowledge of particle size or repeated calibration. The relative viscosity of intracellular fluid is then derived from the trajectory of probe. The label-free microrheology technology was applied to pyroptosis cells for the first time, revealing a relative viscosity gradient from the cell membrane to the nucleus region. This noninvasive approach can avoid external influences on the normal dynamics of cells and provide an in situ platform for the study of intracellular fluid heterogeneity, which will help elucidate the mechanisms of cell death and inflammation.

Zinc oxide (ZnO) has garnered much attention as a promising material for quantum devices due to its unique characteristics. To utilize the potential of ZnO for quantum devices, the development of fundamental technological elements such as high-speed readout and charge sensing capabilities has become essential. In this study, we address these challenges by demonstrating radio-frequency (rf) reflectometry and charge sensing in ZnO quantum dots, thus advancing the potential for qubit applications. A device is fabricated on a high-quality ZnO heterostructure, featuring gate-defined target and sensor quantum dots. The sensor dot, integrated into an rf resonator circuit, enables the detection of single-electron charges in the target dots. Using this setup, we observe the rf-detected charge stability diagram indicating the formation of few-electron double quantum dots and provide the first benchmark of the bandwidth, sensitivity, and readout fidelity of rf reflectometry.