Electron-matter interactions produce elastic and inelastic scattering, forming the basis for imaging and spectroscopy in electron microscopy. However, integrating electron energy-loss spectroscopy (EELS) with 4D-STEM and ptychography remains challenging due to detector geometry conflicts. Hollow ptychography introduced by Song et al., which uses a central aperture to allow low-angle electrons into the EELS spectrometer, suffers from multiple scattering in thicker samples. We propose multislice hollow ptychography (MHP), which incorporates a multislice model to address dynamical scattering and enables robust high-resolution imaging from hollow diffraction patterns while supporting simultaneous EELS acquisition. MHP achieves sub-ångström lateral resolution at intermediate doses (${10}^4–{10}^8{\mathrm{e}}^{-}/{Å}^2$) and enables full three-dimensional (3D) atomic-layer reconstruction at ultrahigh doses ($\ge {10}^8{\mathrm{e}}^{-}/{Å}^2$), limited only by lattice vibrations. Of note, up to 70% of electrons remain available for spectroscopy. This flexible and dose-efficient framework supports correlative 3D imaging and chemical mapping, opening new possibilities for analyzing complex energy and quantum materials.

Quantum heuristics have shown promise in solving various optimization problems, including lattice protein folding. Equally relevant is the inverse problem, protein design, where one seeks sequences that fold to a given target structure. The latter problem is often split into two steps: (i) searching for sequences that minimize the energy in the target structure, and (ii) testing whether the generated sequences fold to the desired structure. Here, we investigate the utility of variational quantum algorithms for the first of these two steps on today’s noisy intermediate-scale quantum devices. We focus on the sequence optimization task, which is less resource-demanding than folding computations. We test the quantum approximate optimization algorithm and variants of it, with problem-informed quantum circuits, as well as the hardware-efficient ansatz, with problem-agnostic quantum circuits. While the former approach, with a careful choice of mixer, yields good results in noiseless simulations (success probability $\ge 0.95$ in all instances), its performance drops drastically under noise. With the problem-agnostic circuits, which are more compatible with hardware constraints, improved performance is observed in noisy simulations, compared to their problem-informed counterparts. When running the problem-agnostic circuits on a real quantum device, with parameters taken from simulations, we obtain a significant success probability ($\ge 0.2$) in most instances.

In a typical Rydberg mixer, modulated communication signals are detected using a radio frequency (rf) heterodyne technique. The mixer outputs an intermediate frequency, which must be filtered and mixed down to baseband. In this work, we apply an rf-homodyne technique to simultaneously demonstrate baseband I/Q readout and angle-of-arrival determination of standard communication signals using a dual-ladder Rydberg receiver (DLRR). We also provide a systematic comparison with a conventional Rydberg receiver (CRR) (i.e., with a heterodyne-based receiver). While the signal amplitude of the DLRR does not decay with increasing symbol rate as in a CRR, direct conversion receivers are highly sensitive to low-frequency noise. As a result, the DLRR’s performance is degraded relative to a CRR when subjected to substantial pink noise. We show that both systems behave comparably once pink noise effects have been accounted for.

Integrated plasmonics is advancing rapidly, enabling a wide range of functionalities to be incorporated onto a single chip. Applications span information processing, computation, quantum sensing, and dark matter detection. This progress has driven the development of integrated nonreciprocal devices, which are essential for preventing unwanted feedback that can degrade system performance. While nonreciprocal devices have been realized in edge magnetoplasmon (EMP) materials via classical interference effects, their operation is often limited by the input power range. Here, we demonstrate that topological circulators utilizing asymmetric coupling offer improved input power range, isolation, and insertion loss. In this configuration, we demonstrate that the coupling between a chiral edge magnetoplasmonic resonator and a pair of LC resonators is well described by an effective non-Hermitian two-site Hatano–Nelson model with asymmetric directional couplings, resulting in nonreciprocal behavior. The coherent photon-plasmon interaction enables a circulator with up to $50\mathrm{dB}$ of isolation across a broad range of excitation power. These results suggest that magnetic topological insulators provide a promising platform for realizing asymmetric non-Hermitian couplings at radio frequencies and for exploring regimes of strong directional suppression and possible exceptional-point physics. More broadly, they highlight the potential of topological-material-based microwave devices for future integration with superconducting quantum information platforms.

Two-dimensional (2D) multiferroic materials with polarization-tunable electronic properties provide unprecedented opportunities for designing high-performance ferroelectric tunnel junctions (FTJs). In this work, we focus on ${\text{InCrS}}_3$, a 2D multiferroic derived from ferroelectric ${\text{In}}_2{\mathrm{S}}_3$ via Cr substitution, which exhibits a distinct polarization-modulated electronic phase transition, half-metallic in one polarization state and semiconducting in the other. Using density functional theory combined with the nonequilibrium Green’s function method, we reveal that the transport performance of ${\text{InCrS}}_3$-based FTJs is strongly dependent on the choice of electrode materials, originating from a momentum-selective coupling effect between the electronic states of electrodes and ${\text{InCrS}}_3$. When graphene is used as the electrode, the system exhibits an abnormal transport behavior: the metallic state shows ultralow transmittance due to momentum-space mismatch near the $\mathrm{K}$ point, while the semiconducting state shows much higher transmittance. In contrast, using metallic ${\text{NbS}}_2$ as the electrode restores normal transport behavior, as the electronic states overlap in momentum space around the $\mathrm{\Gamma }$ point. Our findings highlight that electrode selection can fundamentally alter the switching behavior of 2D FTJs and establish momentum matching as a key design principle for achieving high-contrast tunneling electroresistance in ferroelectric memory devices.

In the antenna community, there has always been a fundamental question: how can we control antenna behavior, e.g., resonant frequency, bandwidth, and mutual coupling in an array, solely by changing materials surrounding the radiating current? To answer this, we analyze the role of a magneto-dielectric substrate/superstrate in controlling the stored energy, impedance, and radiation properties, showing that the bandwidth of the antennas can be substantially increased by reducing the substrate permittivity or permeability, respectively, in magnetic- and electric-current-driven antennas. These theoretical findings are validated through numerical simulations. The same conceptual framework is applied to investigate the problem of mutual coupling between closely spaced elements. The results show that loading magnetic-current antennas with a magnetic superstrate effectively suppresses surface waves and thereby reduces interelement coupling, whereas for electric-current antennas, a dielectric superstrate provides the most efficient coupling reduction.

We have developed two modular dilution refrigerators with a cooling power on the order of 1 mW at 100 mK and $20\mathrm{\mu }\mathrm{W}$ at 20 mK, and further carried out joint operation by integrating the two modular units. In the integrated configuration, the base temperatures of the mixing chamber cold plates of both refrigerators remained below 10 mK and within the same temperature range; the combined cooling power essentially doubles that of a single module. In this way, a concurrent increase in both cooling power and available experimental space has been realized through the implementation of the modular integration, and the integrated prototype is already being used to conduct superconducting quantum computing experiments. We experimentally verified that, under integrated operation, the load condition of one module has only a negligible effect on the temperature and cooling power of the other refrigerator, demonstrating a certain degree of independence between the two modular units. Finally, we also point out the challenges that the proposed modular integration scheme may face in its further evolution and suggest possible improvement approaches. This study provides a reference for the future development and application of high-cooling power dilution refrigerators. The scalability demonstrated in cooling power and experimental space is expected to offer solutions for future large-scale quantum computing applications.

Systematic Rabi-amplitude and detuning errors remain important sources of infidelity in high-fidelity quantum gates. We develop a robust pulse-engineering scheme for nonadiabatic holonomic quantum computing in a three-level $\mathrm{\Lambda }$-type qutrit, combining inverse engineering with time-dependent perturbative analysis. Pulse shaping eliminates the leading second-order Rabi-amplitude contribution, while static detuning introduces a distinct population-mediated channel that cannot be removed within a single control loop. We therefore introduce a compensation loop that exactly cancels the dominant second-order $O_{13}^{\delta }$ contribution, with the residual $O_{12}^{\delta }$ channel further suppressed by pulse shaping. Using the logical average gate fidelity over the complete computational subspace, the optimized composite sequence reaches closed-system fidelities of 99.88%–99.99% for four representative single-qubit gates at $ϵ=0.2$ and $\delta /2\pi =2\mathrm{MHz}$. With phenomenological decoherence at $T_1=T_2=30\mathrm{\mu }\mathrm{s}$, the NOT and S gates retain fidelities of 99.72% and 99.79%, respectively, with a coherence-time crossover near $0.58\mathrm{\mu }\mathrm{s}$. These results identify the regime in which systematic-error suppression outweighs the decoherence cost of the additional control loop.

This study addresses the persistent multifidelity gap between numerical simulations and experimental observations in the design of elastic metamaterials, specifically focusing on wave transmission spectra of the triply periodic minimal surface lattices. We propose the Dual Elastic Alignment Network (DEAN), a learning framework that uses elastic functional data analysis (EFDA) to separate transmission responses into spectral amplitude and frequency-warping components. DEAN employs a shared geometric encoder with dual probabilistic heads to separately model resonance morphology and frequency shifts across topologies and between fidelity levels. To mitigate experimental data sparsity, we introduce an augmented transfer learning strategy in which the model is first trained on a large set of low-fidelity (LF) simulations and subsequently fine-tuned using a combined dataset of high-fidelity (HF) experimental data and EFDA-generated augmented data. The study uses 72 experimentally evaluated designs together with 510 simulated designs, resulting in a highly sparse experimental regime relative to the broader simulation design space. The baseline discrepancy between the LF and HF datasets corresponds to a normalized mean absolute error (NMAE) of 0.142 and a coefficient of determination ($R^2$) of 0.355. Under the augmented transfer learning strategy, DEAN achieves the strongest aggregate global accuracy among the evaluated models, with the level-set variant reaching a test-set NMAE of 0.055 and an $R^2$ of 0.858, while the multihot variant remains close with an NMAE of 0.059 and $R^2$ of 0.843. Fisher-Rao distance analysis and joint-density evaluation of peak deviations demonstrate improved preservation of resonance morphology and peak characteristics when using the DEAN framework. These findings indicate that explicitly modeling amplitude and frequency-warping variability enhances predictive reliability under sparse experimental data conditions. The proposed framework provides a structured, experimentally grounded surrogate for data-efficient modeling and candidate screening of elastic metamaterials under uncertain constitutive and manufacturing conditions.

Random pulse sequences are a powerful method for qubit noise spectroscopy, enabling efficient reconstruction of sparse noise spectra. Here, we advance this method in two complementary directions. First, we extend the method using a regularizer based on the total generalized variation norm in order to reconstruct a larger class of noise spectra, namely, piecewise-linear noise spectra, which more realistically model many physical systems. We show through numerical simulations that the new method resolves finer spectral features, while maintaining an order-of-magnitude speedup over conventional approaches to noise spectroscopy. Second, we simplify the experimental implementation of the method by introducing Rademacher measurements for reconstructing sparse noise spectra. These measurements use pseudorandom pulse sequences that can be generated in real time from a short random seed, reducing experimental complexity without compromising reconstruction accuracy. Together, these developments broaden the reach of random pulse sequences for accurate and efficient noise characterization in realistic quantum systems.

We present the fabrication of nanoscale superconducting quantum interference devices (SQUIDs) at the apex of wireframe tips on self-aligned superconducting cantilever probes. The probes are made on silicon wafers using molding techniques in combination with corner lithography, which results in a nanowire frame tip with a tunable apex structure. A shadow-effect deposition using magnetron sputtering of niobium creates self-aligned superconducting wireframes on cantilevers with accompanying device circuitry. Superconducting weak links are realized at the apex of the wireframes with the use of focused ion beam nanopatterning. The realized SQUIDs have effective diameters ranging from several micrometers down to 100 nm and can be operated in magnetic fields up to 1 T. Furthermore, the nanowires in the wireframe can be used to flux modulate the SQUID locally. This fabrication process enables the production of wafer-scale templates for probes based on on-tip superconducting devices.

In the transmitter of a quantum key distribution (QKD) system, a wavelength-division multiplexer (WDM) is typically used to combine quantum and synchronization signals and is directly connected to the quantum channel. As a result, it becomes the first optical component exposed to laser-injection attacks. Therefore, understanding the behavior of WDMs under such attacks is essential for assessing the practical security of QKD systems. In this work, we systematically investigate the characteristics of WDMs under high-power laser illumination. Our experimental results show that certain WDM samples exhibit pronounced changes in their spectral features once the injected laser power surpasses a specific threshold. Taking the Trojan-horse attack as an illustrative example, we further perform a theoretical analysis of the resulting spectral side channel and show that it can reduce the maximum secure transmission distance to below 66.9% of its original value. By combining experimental observations with theoretical modeling, this study advances the understanding of the influence of WDMs on the practical security of QKD systems.

We present a low size, weight, and power (SWaP), low-complexity, ytterbium magneto-optical trap (MOT). We demonstrate trapping of $1.4\times {10}^6$ ${}^{171}\mathrm{Yb}$ atoms on the $|{{}^{1}S}_0,F=1/2⟩\leftrightarrow |{{}^{1}P}_1,F^{\prime }=3/2⟩$ transition directly from a hot thermal beam. We explore the effect of trap detuning and oven temperature on trap number, density, loading rate, and sample temperature. The low SWaP and low-complexity design presents a realistic pathway toward portable ytterbium MOTs, allowing cold atom ytterbium systems to escape the confines of the laboratory and perform precision measurements in field environments.

Noisy intermediate-scale quantum (NISQ) devices impose dual challenges on quantum circuit execution: limited qubit connectivity requires extensive SWAP-gate routing, while time-dependent decoherence progressively degrades quantum information. Existing qubit-mapping algorithms optimize for hardware topology and static calibration metrics but systematically neglect transverse relaxation dynamics ($T_2$), creating a fundamental gap between compiler decisions and evolving noise characteristics. We present transverse relaxation time–aware qubit-mapping (TRAM), a coherence-guided compilation framework that elevates decoherence mitigation to a primary optimization objective. TRAM integrates calibration-informed community detection to construct noise-resilient qubit partitions, generates time-weighted initial mappings that anticipate coherence decay, and dynamically schedules SWAP operations to minimize cumulative error accumulation. Evaluated on Qiskit-based simulators with realistic noise models, TRAM outperforms SABRE by 3.29% in fidelity, reduces gate count by 11.47%, and shortens circuit depth by 12.29%, establishing coherence-aware optimization as essential for practical quantum compilation in the NISQ era.

The hot carrier solar cell exhibits a photovoltaic conversion efficiency limit of 85.4%. Among the idealizations necessary to achieve this efficiency, it has traditionally been considered essential that the electrons absorbing sunlight do not end up transferring the captured energy to the crystal lattice. In this work, we argue that such a requirement is not necessary if the absorber is thermally insulated. In our analysis, we also consider the possibility of Ohmic losses in the absorber due to finite electrical conductivity. We also demonstrate that such losses, delivered as heat, can be partially recycled into electrical work with an efficiency that is given by the Carnot factor. The high efficiencies reported here are thermodynamic limits obtained with ideal energy-selective contacts and negligible parasitic contact conductance, not projections of practical device efficiency. Our work includes a sensitivity analysis for finite contact-mediated heat leakage, and the results are presented as design targets.