Fusion measurements are a key primitive for linear-optical quantum computing and quantum networks. Type-I and type-II fusion gates are widely used to combine small entangled resource states into larger photonic states, but without ancillary resources their success probability is limited to $1/2$. Existing $3/4$-efficient type-I schemes rely on entangled Bell-pair ancillary states, whose preparation is itself probabilistic and resource-intensive. Here, we propose a boosted type-I fusion gate using only four ancillary single photons and standard linear-optical primitives. For multiqubit GHZ and graph states, the gate succeeds directly with probability $5/8$, while a distillation protocol converts partially entangled outcomes into additional successful events, raising the total success probability to $11/16$ after one stage and asymptotically to $3/4$. We quantify the practical advantage of this scheme by estimating the photonic resources required for generating representative large entangled photonic states and show that the proposed gate significantly reduces the required overhead compared with existing schemes. These results expand the set of resource-efficient linear-optical primitives and enable a substantial reduction in the resource requirements for scalable photonic quantum computing and quantum communication.

Understanding defects in atomically thin van der Waals (vdW) semiconductors is essential for advancing their use in next-generation optoelectronic and photovoltaic devices. Here, we apply a combination of various impedance spectroscopy techniques to two-dimensional (2D) vdW GaSe doped with silicon (Si) to reconstruct deep trap states across the full bandgap. Deep-level transient spectroscopy reveals three distinct deep states, 0.33, 0.68, and 0.24 eV, below the conduction band edge. Complementary deep-level optical spectroscopy and photocapacitance measurements identify two deep states at 1.4 and 1.8 eV below the conduction band edge and one at 2.0 eV above the valence band edge, with thermal admittance spectroscopy providing additional verification and further resolving two trap states at 0.16 eV above the valence band edge and at 0.26 eV below the conduction band edge. By comparing the experimentally extracted ionization energies with the predictions of density functional theory, our results attribute these trap states primarily to Si-related defects and metal vacancies. This work presents a comprehensive defect map of Si-doped GaSe, providing critical insights into carrier trapping mechanisms that are essential for optimizing the design of 2D material-based devices for industrial applications.

Ultraviolet light emitters based on the semiconductor alloy aluminum gallium nitride, (Al,Ga)N, have attracted significant interest in recent years due to their potential for optoelectronic devices. To guide the design of such devices with improved efficiencies, theoretical frameworks based on so-called $\mathbf{k}·\mathbf{p}$ methods have found widespread application in the literature. Given that $\mathbf{k}·\mathbf{p}$ models are empirical in nature, parameters such as effective masses or crystal-field splitting energies of (Al,Ga)N alloys have to be provided as input from first-principles calculations or experiment. Although these parameters are available for GaN and AlN, detailed information on their composition dependence is sparse. Here, we address this question and provide (Al,Ga)N band parameters for widely used multiband $\mathbf{k}·\mathbf{p}$ Hamiltonians. We start from density functional theory (DFT) to sample the electronic structure of (Al,Ga)N alloys over the full composition range. The $\mathbf{k}·\mathbf{p}$ band parameters are treated as free parameters to reproduce the DFT data. For GaN and AlN, the parameters extracted here agree well with literature values. When turning to the composition dependence of the $\mathbf{k}·\mathbf{p}$ parameters, our calculations show that most parameters deviate significantly from a linear interpolation of the GaN and AlN values, an approximation widely made in the literature. Moreover, to describe changes in the band parameters with Al content, composition-dependent bowing parameters have to be considered for an accurate description of the DFT data. Finally, our analysis also provides initial insight into consequences of the nonlinear composition dependence of the $\mathbf{k}·\mathbf{p}$ parameters for the electronic structure of (Al,Ga)N alloys. We find that, in particular, the band ordering is affected by the nonlinear evolution of the crystal-field splitting energy with composition, which is an important aspect for the light polarization characteristics of high Al content (Al,Ga)N alloys.

PulsePol is an elegantly designed pulse-sequence-based quantum control scheme that enables polarization transfer between electron and nuclear spins. However, previous analyses of PulsePol assumed very strong, close to ideal, instantaneous microwave pulses, which is rarely achievable as one goes to higher magnetic fields. We revisit the PulsePol scheme under finite-pulse constraints and show that its performance significantly degrades because of finite-pulse effects. Using bimodal Floquet theory, we identify the symmetry-breaking mechanism responsible for this deteriorating fidelity. By phase adjustment, we reestablish the proper symmetry of the interaction-frame spin Hamiltonian—leading to a sequence called Q-PulsePol, where ‘Q’ reflects the restored quadrature symmetry. Our results demonstrate robustness to finite-pulse effects and improved polarization transfer efficiency, establishing Q-PulsePol as a practical and reliable scheme for bulk hyperpolarization of nuclear spins in solid-state using a single-mode (zero-quantum or double-quantum) transfer. This work bridges idealized quantum control with realistic pulse engineering, establishing design rules for spin-based quantum-control protocols.

2D/3D heterostructures provide a powerful platform for uncovering how reduced dimensionality governs radiation response. While two-dimensional (2D) materials such as graphene, transition metal dichalcogenides, and MXenes have demonstrated notable structural resilience to radiation, fundamental differences in their radiation response compared with bulk three-dimensional (3D) crystals remain largely unverified. Here, we fabricate patterned $a$-${\mathrm{Al}}_2{\mathrm{O}}_3$/graphene/H-intercalated SiC(0001) heterostructures and expose them to fast neutrons (1–2 MeV) across fluences from $1.9\times {10}^{17}$ to $6.5\times {10}^{18}\mathrm{n}/{\mathrm{cm}}^2$. The results reveal a striking disparity: despite the 3D environment, graphene accumulates damage 69–273 times more slowly than SiC, with its resilience further enhanced at high fluences due to early saturation, soft limited to only 0.0064% at $1.3\times {10}^{19}\mathrm{n}/{\mathrm{cm}}^2$. This behavior is attributed to a two-channel defect accumulation model in 2D materials, involving interfacial evolution that dominates the early-stage response when the interface is chemically active, and direct lattice damage from atomic displacements, which persists but remains comparatively weak. These findings establish 2D lattices as fundamentally more radiation-resistant than 3D crystals and demonstrate that their advantages persist in realistic device architectures. Harnessing this resilience offers orders-of-magnitude improvements in structural stability for technologies operating under extreme irradiation, including fusion and fission reactors, particle accelerators, and aerospace systems.

Color-center spins in 4H-SiC offer a rare combination of wafer-scale materials maturity with long spin coherence and chip-level photonics, making them promising building blocks for scalable quantum technologies. In particular, the silicon vacancy hosts an $\mathrm{S}=3/2$ ground state, a native qudit that enables compact encodings and subspace-selective control but also introduces spectator transitions: short, detuned pulses can coherently drive nonaddressed level pairs and create crosstalk. Here we use broadband Ramsey interferometry to reveal and quantify such spectator-transition crosstalk. Experimentally, the Ramsey Fourier spectra display multiple lines beyond the addressed single-quantum transition. Analytically, we map each line to a pairwise energy difference between qudit levels of the rotating-frame Hamiltonian and assign its weight via compact amplitudes set by the prepared state and the microwave pulse parameters, predicting a deterministic six-branch structure. Numerical time-domain propagation with the experimental sampling reproduces the detuning map, and the measured peak positions coincide with the analytic branch lines without frequency fitting. Together these results provide a practical, spectator-aware framework for multilevel control in the silicon-vacancy qudit. The approach offers clear guidance to suppress crosstalk or, conversely, to exploit spectator lines, e.g., as additional constraints for in situ pulse calibration and for phase-sensitive quantum state and process estimation.

The concept of a microwave planar antenna for the excitation of dielectric paramagnetic media is proposed. The shape and size of the electrodes are designed for the generation of a uniform magnetic field parallel to the surfaces of a single- or multilayer dielectric, with a specific resonance frequency and bandwidth. One or both electrodes can be semireflective to allow the optical accessibility of the paramagnetic media and, possibly, to enhance the collection efficiency by beaming the optical emission of quantum emitters. This device is particularly useful in optically detected magnetic resonance due to the large bandwidth of the microwave excitation and favorable conditions for optical excitation and detection. Applications are devised especially in vector magnetometry and microwave spectral analysis because of the paramagnetic quantum properties of emitters such as the nitrogen-vacancy center in diamond.

A concept for microwave (MW) amplification and maser generation in compact planar waveguides embedding a thin layer of paramagnetic color centers is presented. The ground state of the color centers can be optically or electrically spin-polarized, while population inversion is attained by Zeeman shifting of one spin sublevel below the populated state. A signal traveling along the waveguide, if resonant with the spin transition, can be amplified, or a self-sustained MW oscillation can be generated. A general analysis of the conditions for amplification and self-oscillation is developed for nitrogen-vacancy-rich diamond films, together with practical examples of impedance matching and resonator design. The proposed architecture combines near-unity filling factors with relatively low electromagnetic quality factors, enabling operation in strongly coupled configurations and broad frequency tunability through the external magnetic field. The same formalism naturally extends to compact lumped-element resonators operating at a few gigahertz while preserving millimeter-scale dimensions. Compared with the present state of the art of diamond masers, the approach offers reduced size, simplified integration with external electronics, and relaxed requirements on cavity quality factor.

A coupled spintronic-oscillator array has been considered attractive for neuromorphic computing applications. Experimental reports have shown the nanoconstriction geometry to be a relatively easier-to-fabricate platform for implementing such spin oscillators, but most prior reports on training and inference algorithms for neuromorphic computing using spin oscillators have been mostly restricted to the nanopillar geometry. Also, those prior reports involve updating the natural frequency values of the oscillators and moving the synchronization regions onto the data clusters during the offline learning phase, which has associated challenges. In this context, we design and simulate a novel artificial neural network (ANN)—oscillator neural network (ONN)—algorithm wherein, in the offline learning phase, the weight parameters of the ANN are updated such that the data clusters are instead moved to the synchronization regions of spin Hall nanooscillators (SHNOs) in the nanoconstriction geometry, as obtained through micromagnetic simulations. We further simulate the on-chip inference part of the ANN-ONN algorithm, where the ANN is implemented on a crossbar array of domain-wall synapse devices, as simulated here through micromagnetics, and the ONN is implemented on nanoconstriction SHNOs. We show successful data classification for both binary and multiclass classification tasks to demonstrate the generalizability of our proposed scheme.

We propose a broadband Purcell-protection scheme based on a single shared filter integrated directly into the feedline, enabling simultaneous protection of multiple qubits in a compact architecture with minimal hardware overhead. The filter consists of two open-ended stubs connected by an in-line transmission line, forming a $\mathrm{\Pi }$ geometry, and operates via engineered passive microwave interference that suppresses the real part of the environmental admittance over a wide frequency window. Circuit simulations and finite-element modeling show that transmission is suppressed by several orders of magnitude within the target band (the qubits’ frequencies) while preserving the readout mode of the multiplexed architecture. For realistic device parameters, the proposed design yields Purcell-limited relaxation times exceeding 1 ms over a frequency span of approximately 1.5 GHz. Our results establish the $\mathrm{\Pi }$ filter as a compact and scalable solution for broadband impedance engineering in superconducting quantum circuits, compatible with standard dispersive readout protocols.

Near-zero-field magnetometers, particularly the spin-exchange relaxation-free (SERF) magnetometer, despite their exceptional sensitivity, face a fundamental limitation: their accuracy is inherently tied to the precision of precalibrated magnetic coils, creating a circular dependency in calibration. To break this loop, we establish a comprehensive analytical framework to describe the full-sequence free-induction-decay (FID) trajectories of atomic ensembles in the near-zero magnetic field regime. By explicitly incorporating the dynamic evolution of the polarization-dependent slowing-down factor $q(P)$, our model provides a rigorous description of spin precession in ultraweak field environments, enabling the extraction of absolute field components without relying on external coil-based references. The mathematical integrity of the model is confirmed by excellent agreement with direct numerical simulations of the Bloch equations. We demonstrate that a single FID waveform can simultaneously resolve six independent physical parameters through a multiparameter nonlinear estimation process. Experimental results validate that the reconstructed magnetic fields exhibit high fidelity, with a coefficient of determination of approximately 0.99. Under current experimental conditions, this approach achieves a practical reconstruction uncertainty of 0.1 nT for the absolute magnetic field and 5 and $1{\mathrm{s}}^{-1}$ for pumping and relaxation rates, respectively. This work redefines the SERF magnetometer as a calibration-free magnetometer, providing a robust foundation for autonomous quantum sensing in remote or inaccessible environments.

Precise control over deformation behaviors is essential for shape-morphing devices, adaptive actuators, and soft robotics. However, designing materials to achieve the whole user-defined deformation pathway remains a significant challenge. This work introduces a fast, physics-informed approach, namely incremental contrastive learning, for the inverse design of Willis lattice metamaterials capable of achieving desired deformation pathways under prescribed external constraints. We first implement gauge transformation to analytically derive an initial Willis lattice configuration and then leverage contrastive learning to develop a local learning rule on each incremental deformation step so as to design strain-dependent Willis parameters to realize the desired deformation pathway. Numerical simulations are performed to validate the approach and demonstrate its ability to program diverse and complex target deformations prescribed on boundary nodes, internal nodes, or even all nodes. Notably, we demonstrate independent control over both the final deformed shape and the specific pathway taken to achieve it, such as programming “early” versus “delayed” convexity to reach an identical final configuration. The developed framework provides a robust and efficient solution for programming matter, opening new avenues for designing complex morphing structures and tunable systems.

Magnetic anisotropy is a fundamental prerequisite for stabilizing long-range order in two-dimensional (2D) magnets, yet its evaluation via first-principles methods is computationally prohibitive for large-scale material discovery. Here, an octahedral-field-informed machine learning framework is reported, specifically designed to identify 2D magnets with perpendicular magnetic anisotropy (PMA). By incorporating crystal-field-informed descriptors, this model transcends traditional composition-based heuristics, achieving an 89% classification accuracy while accelerating the discovery process by 6 orders of magnitude. High-throughput screening of over 10 000 candidates reveals 15 novel PMA materials, with ${\text{Ba}}_2{\text{VTe}}_2{\mathrm{S}}_2$ identified as a prominent candidate. Specifically, axial elongation along the out-of-plane direction by Ba cations modulates the $d$-orbital splitting, resulting in a giant magnetic anisotropy energy of 5.65 meV per V atom. This work provides an interpretable framework for rapid discovery of 2D PMA magnets and highlights how physics-informed descriptors enable rational design of low-dimensional magnetic materials.

This paper presents a technology for fabricating microstructures based on carbon nanowalls (CNWs) integrated on silicon nitride (${\text{SiN}}_{\mathrm{x}}$) waveguides. The step-by-step fabrication process is described, including chemical mechanical planarization, deposition of molybdenum contacts, selective etching of the upper ${\mathrm{SiO}}_{\mathrm{x}}$ buffer layer relative to ${\text{SiN}}_{\mathrm{x}}$, and plasma-enhanced chemical vapor deposition of CNWs. The photothermoelectric response of the structures was studied in the C-band, near the $1.55\mathrm{\mu }\mathrm{m}$ wavelength. The results demonstrate that the primary mechanism of the response to the laser emission is the Seebeck effect, providing a maximum sensitivity of $0.037\mathrm{V}/\mathrm{W}$ without thermal degradation of the CNWs. Furthermore, the amplitude-frequency response of the structures corresponds to that of a fourth-order Butterworth filter with a cutoff frequency of 13.4 kHz. The utilization of the Joule-heating-assisted enhancement allows for a 21.4-fold increase in the output signal amplitude, but it also reduces the bandwidth. These findings highlight the prospects for CNWs in integrated photonics for near-infrared emission detection.

We propose a time- and wavelength-multiplexed remote atom-atom entanglement generation protocol based on cavity-assisted photon scattering (CAPS). This is designed to achieve a high rate and high fidelity with robustness to operational imperfections, parameter fluctuations, and auxiliary time costs, such as percent-level photon impurity, timing and cavity parameter jitter, and atom shuttling time costs. We benchmark this protocol using comprehensive analytical and numerical modeling of the atom-cavity dynamics, including state-dependent pulse-delay effects, photon temporal impurity, atom-cavity system parameter fluctuations, and crosstalk among atoms through a shared cavity mode. With realistic atom-cavity system performance, we predict $2\times {10}^5{\mathrm{s}}^{-1}$ successful atom-atom Bell pair generation even without in-cavity qubit reset, substantially enhanced from two-photon-interference-based protocols, at a predicted heralded fidelity of 0.999. We further show that the predicted rate scales further by the use of wavelength multiplexing while maintaining the fidelity.

Free-space optical communication based on photonic orbital angular momentum (OAM), including OAM multiplexing and OAM modulation schemes, has the potential to greatly increase information transfer capacity. However, the presence of atmospheric turbulence can severely distort the spatial modes of OAM beams, resulting in modal scattering and distortions. In this study, we theoretically develop a method to control the total OAM of a superimposed OAM beam (total OAM in a superposition state but not the OAM eigenstate in general)—coherent superposition of $N$ OAM eigenstates—propagating through the time-varying atmospheric turbulence by dynamically modulating the complex coefficient of each OAM eigenstate and experimentally demonstrate the total OAM control strategy. Our experimental results show that the control error of total average OAM per photon is around $0.1\hslash$ in a turbulent channel with a scintillation index of 1.03, and the control strategy is effective even in nonunitary turbulent systems. Furthermore, we successfully receive a data packet using two-OAM-eigenstate-superposition beams for two bits per pulse in unitary and nonunitary turbulent channels. Our study offers an effective way to control the OAM of light beams propagating in turbulent media, which will find potential applications in free-space optical communication and remote sensing.

Diffusion is a prominent source of noise affecting nuclear magnetic resonance at the nanometer scale (nano-NMR), preventing high-resolution studies of unpolarized liquid samples and hindering the development of nanofluid devices. Actively managing diffusion noise through sample confinement is likely to unveil alternative noise sources that have so far been disregarded, as they occur in longer timescales and consequently are masked by diffusion. These secondary noise sources could diminish the advantages provided by sample confinement, but they may also yield valuable information about the behavior of the fluid sample and its interactions with the confinement device. In this article, we study in detail two previously unaccounted noise models for confined nano-NMR, namely, surface interactions and porosity, and discuss their implications for typical nano-NMR experiments.