The radiation transfer equation is widely used for simulations, for example, heat transfer in engineering, diffuse optical tomography in healthcare, and radiation hydrodynamics in astrophysics. By combining the lattice Boltzmann method, we propose a quantum algorithm for radiative transfer. This algorithm encompasses all the essential physical processes of radiative transfer: absorption, scattering, and emission. Although a sufficient number of measurements are required to precisely estimate the quantum state, and the initial encoding of the quantum state remains a challenging problem, our quantum algorithm exponentially accelerates radiative-transfer calculations compared to classical algorithms. In order to verify the quantum algorithm, we perform quantum circuit simulation using IBM Qiskit Aer and find good agreement between our numerical result and the exact solution. The algorithm paves the way for applications, such as fault-tolerant quantum computers for plasma engineering, telecommunications, nuclear-fusion technology, healthcare, and astrophysics.

Classifying skyrmionic textures and extracting magnetic Hamiltonian parameters represent crucial and challenging pursuits within the realm of two-dimensional (2D) spintronics. In this study, we leverage micromagnetic simulation and machine learning (ML) to theoretically achieve the recognition of nine distinct skyrmionic textures and the extraction of magnetic Hamiltonian parameters from extensive spin texture images in a 2D Heisenberg model. For texture classification, a deep neural network (DNN) trained through transfer learning is proposed to enable the accurate discrimination of nine diverse skyrmionic textures. In parallel, for parameter extraction, based on the textures generated by different Heisenberg exchange stiffnesses ($J$), Dzyaloshinskii-Moriya strengths ($D$), and anisotropy constants ($K$), we employ a multi-input single-output (MISO) deep learning model (handling both images and parameters) and a support vector regression (SVR) model (dealing with Fourier features) to extract the parameters embedded in the spin textures. Our models for classification and extraction demonstrate significant success, achieving an accuracy of 98% (DNN), and R-squared ($R^2$) of 0.90 (MISO) and 0.8 (SVR). Notably, our ML methods prove their effectiveness in distinguishing skyrmionic textures with blurred phase boundaries, thereby contributing to a more nuanced understanding of these textures. Additionally, our models establish a mapping relationship between spin texture images and magnetic parameters, thus validating the feasibility of extracting microscopic mechanisms from experimental images. This finding offers significant guidance for spintronics experiments, emphasizing the potential of ML methods in elucidating intricate details from practical observations.

This study employs first-principles density-functional-theory (DFT) calculations and ab initio molecular dynamic (AIMD) simulations to investigate the stability, electronic properties, and oxygen-reduction reaction (ORR) activity of $M$ adatoms ($M=\text{Fe},\text{Co}$) on free-standing bilayer borophene (BB) with different coverages. Our findings indicate that metals strongly bind to the BB surface, particularly at the hollow sites, inducing metallicity. We analyze the dissociation energy of ${\text{O}}_2$ and $\mathrm{OOH}$ after the adsorption on the metal center of BBM while ORR activity was assessed through the free-energy adsorption of their intermediates. The stability of the systems at electrochemical conditions was investigated by Pourbaix analysis as well as by AIMD simulations, which include explicit solvents. Our results suggest that $\mathrm{BBCo}$ in a low-coverage adatom configuration would exhibit competitive ORR activity, with a theoretical overpotential of around 1 V. However, this activity would only be feasible in alkaline environments where the stability $\mathrm{BBCo}$ is preserved. Hubbard-$U$ corrections and the hybrid functional approaches within DFT are taken into consideration, and subsequent results are compared.

Metalenses have been widely studied and used because of their high design freedom and ultrathin configurations. For various practical applications, such as geological exploration, energy harvesting, and structural health monitoring, it is highly desirable to maximize the focusing efficiency of elastic waves. However, it is a great challenge to realize both high-efficiency focusing and subdiffraction resolution for elastic waves, especially when the mode coupling and conversion between longitudinal and transverse elastic waves is ubiquitous and inevitable. Here, we adopt a hybrid design approach for an elastic metalens to realize a high-efficiency (54.6%) and subdiffraction resolution (0.39λ) focusing performance with a large numerical aperture (NA = 0.931). The hybrid metalens is composed of a gradient metasurface in the central region and metagratings in the peripheral region to achieve a dramatic lensing functionality, where 112.5 times enhancement of wave intensity is attained at the focal spot. The high-efficiency, large-NA, and superresolution characteristics of the focusing performance, together with the planar and compact configuration of the metalens, are expected to find potential applications in various fields.

Using orthogonally crossed moving lattices, we demonstrate the continuous transport of ${}^{88}\mathrm{Sr}$ atoms in the long-lived metastable ${}^3{P}_0$ and ${}^3{P}_2$ states to a region free from scattered laser-cooling light, while two-stage cooling on the ${}^1{S}_0–{}^1{P}_1$ and ${}^3{P}_2–{}^3{D}_3$ transitions is being conducted. The transfer efficiency between the crossed lattices was close to unity when laser cooling was applied in the crossed region. For a clock laser propagating along the lattice axis, such a lattice-trapped atomic beam enables continuous interrogation of the clock transition free from the Doppler effect arising from the thermal motion of atoms.

Randomness extraction is an essential postprocessing step in practical quantum cryptography systems. When statistical fluctuations are taken into consideration, the requirement of large-input data size could heavily penalize the speed and resource consumption of the randomness-extraction process, thereby limiting the overall system performance. In this work, we propose a sampled subblock hashing approach to circumvent this problem by randomly dividing the large-input block into multiple subblocks and processing them individually. Through simulations and experiments, we demonstrate that our method achieves an order-of-magnitude increase in system throughput while keeping the resource utilization low. Furthermore, our proposed approach is applicable to a generic class of quantum cryptographic protocols that satisfy the generalized entropy-accumulation framework, presenting a highly promising and general solution for high-speed postprocessing in quantum cryptographic applications such as quantum key distribution and quantum random number generation.

High time-bandwidth product signal and idler pulses comprised of independent identically distributed two-mode squeezed vacuum (TMSV) states are readily produced by spontaneous parametric down-conversion. These pulses are virtually unique among entangled states in that they offer quantum performance advantages—over their best classical-state competitors—in scenarios whose loss and noise break their initial entanglement. Broadband TMSV states’ quantum advantage derives from its signal and idler having a strongly nonclassical phase-sensitive cross correlation, which leads to information-bearing signatures in lossy, noisy scenarios stronger than what can be obtained from classical-state systems of the same transmitted energy. Previous broadband TMSV receiver architectures focused on converting phase-sensitive cross correlation into phase-insensitive cross correlation, which can be measured in second-order interference. In general, however, these receivers fail to deliver broadband TMSV states’ full quantum advantage, even if they are implemented with ideal equipment. This paper introduces the correlation-to-displacement receiver—an alternative architecture comprised of a correlation-to-displacement converter, a programmable mode selector, and a coherent-state information extractor—that can be configured to achieve quantum optimal performance in known sensing and communication protocols for which broadband TMSV provides quantum advantage that is robust against entanglement-breaking loss and noise.

Conversion of chemical energy into mechanical work is the fundamental mechanism of several natural phenomena at the nanoscale, like molecular machines and Brownian motors. Quantum mechanical effects are relevant for optimizing these processes and to implement them at the atomic scale. This paper focuses on engines that transform chemical work into mechanical work through energy and particle exchanges with thermal sources at different chemical potentials. Irreversibility is introduced by modeling the engine transformations with finite-time dynamics generated by a time-dependent quantum master equation. Quantum degenerate gases provide maximum efficiency for reversible engines, whereas the classical limit implies small efficiency. For irreversible engines, both the output power and the efficiency at maximum power are much larger in the quantum regime than in the classical limit. The analysis of ideal homogeneous gases grasps the impact of quantum statistics on the above performances, which are expected to persist in the presence of interactions and more general trapping. The performance dependence on different types of Bose-Einstein condensates (BECs) is also studied. The BECs under consideration are standard BECs with a finite fraction of particles in the ground state, and generalized BECs where eigenstates with parallel momenta, or those with coplanar momenta, are macroscopically occupied according to the confinement anisotropy. Quantum gases are therefore a resource for enhanced performances of converting chemical into mechanical work.

The main technological obstacle hampering the dissemination of modern optoelectronic devices operating with large light-matter coupling strength $\mathrm{\Omega }$ is an in-depth comprehension of the carrier current extraction and injection from and into strongly coupled light-matter states, the so-called polaritonic states. The main challenge lies in modeling the interaction between excitations of a different nature, namely bosonic excitations [the plasmonic intersubband (ISB) excitations] with fermionic excitations (the electrons within the extraction or injection subband). In this work, we introduce a comprehensive quantum framework that encompasses both the ISB plasmonic mode and the extractor and injector mode, with a specific emphasis on accurately describing the coherent nature of transport. This reveals inherent selection rules dictating the interaction between the ISB plasmon and the extraction and injection subband. To incorporate the dynamics of the system, this framework is combined to a density-matrix model and a quantum master equation, which have the key property to distinguish intra- and intersubband mechanisms. These theoretical developments are confronted to experimental photocurrent measurements from midinfrared quantum cascade detectors ($\lambda =10\text{μ}\mathrm{m}$) embedded in metal-semiconductor-metal microcavities, operating at the onset of the strong light-matter coupling regime ($2\mathrm{\Omega }=9.3\mathrm{meV}$). We are able to reproduce the different features of the photocurrent spectra, notably the relative amplitude evolution of the polaritonic peaks with respect to the voltage bias applied to the structure. These results on extraction allow us to elucidate the possibility to effectively inject electronic excitations into ISB plasmonic states, and thus polaritonic states.

In this study, we explore the magnetothermoelectric power (MTP) of ${\mathrm{Zr}\mathrm{Te}}_5$, a canonical Dirac semimetal, through a photothermal technique. Unlike conventional thermoelectric studies that rely on on-chip heaters and are limited by fabrication processes, especially for stress-sensitive materials, our approach utilizes photothermal effects to induce temperature gradients. Our experiments, applying a magnetic field approximately parallel and transverse to the photocurrent detection direction, reveal that the photothermal method efficiently and reliably extracts both diagonal and off-diagonal components of the thermoelectric coefficient of ${\mathrm{Zr}\mathrm{Te}}_5$. We observe that the longitudinal MTP reproduces features previously reported in thermal transport studies, while the photoinduced transverse MTP confirms the anomalous Nernst effect. This photothermal measurement technique opens avenues for investigating transport properties in a wide range of quantum materials, in both three-dimensional and two-dimensional systems.

We develop a compact four-port superconducting switch with tunable operating frequency in the range from 4.8 to 7.3 GHz. Isolation between channels exceeds 20 dB over a bandwidth of several hundred megahertz, exceeding 40 dB at some frequencies. The footprint of the device is $80\times 420\text{μ}{\mathrm{m}}^2$. The tunability requires only a global flux bias without either permanent magnets or microelectromechanical structures. As the switch is superconducting, the heat dissipation during operation is negligible. The device can operate at up to $-80\mathrm{dBm}$, which corresponds to $2.5\times {10}^6$ photons per microsecond at a frequency of 6 GHz. The device shows the possibility to be operated as a beam splitter with tunable splitting ratio.

We experimentally investigate inductively shunted transmon-type artificial atoms as an alternative to address the challenges of low anharmonicity and the need for strong charge dispersion in superconducting quantum systems. We characterize several devices with varying geometries and parameters (Josephson energies and capacitances), and find a good agreement with calculations. Our approach allows us to retain the benefits of transmon qubit engineering and fabrication technology and high coherence, while potentially increasing anharmonicity. The approach offers an alternative platform for the development of scalable multiqubit systems in quantum computing.

A setup that simulates ground states of spin graphs would allow one to solve computationally hard optimization problems efficiently. Current optical setups to this goal have difficulties decoupling the amplitude and phase degrees of freedom of each effective spin, which risks that the resultant mapping will be invalid, a problem known as amplitude heterogeneity. Here, we propose a setup with coupled active optical cavity modes, where this problem is eliminated through their particular geometric arrangement. Acting as an effective Monte Carlo solver, the ground state can be found exactly. By tuning a parameter, the setup solves $XY$ or Ising problems.

An understanding of the origins of power loss in superconducting interconnects is essential for the energy efficiency and scalability of superconducting digital logic. At microwave frequencies, power dissipates in both the superconducting wires and the dielectric and these losses can be of comparable magnitude. We describe an approach to accurately disentangle such losses by exploiting their frequency dependence in a multimode transmission-line resonator. This is supported by the concept of a resonator geometric factor extracted from the Ansys High Frequency Structure Simulator (hfss), a commercial three-dimensional finite-element method (FEM) that we adopt for solving a superconductor interior. Using the technique, we have optimized a planarized fabrication process of reciprocal quantum logic (RQL) for the minimum interconnect loss at 4.2 K and gigahertz frequencies. The microstrip interconnects are composed of niobium ($\mathrm{Nb}$) insulated by silicon dioxide ($\mathrm{Si}\mathrm{O}$${}_2$) made from a tetraethoxysilane (TEOS) precursor. Two process generations use damascene fabrication and the third one uses Cloisonné fabrication. For all three, $\mathrm{Si}\mathrm{O}$${}_2$ exhibits a dielectric loss tangent $\tan \delta =0.0012\pm 0.0001$, independent of the $\mathrm{Nb}$ wire width over 0.25–4 $\text{μ}\mathrm{m}$. The intrinsic microwave resistance $R_s$ of $\mathrm{Nb}$ varies with both the process and the wire width. For damascene fabrication, scanning transmission electron microscopy (STEM) and energy-dispersive x-ray spectroscopy (EDS) reveal that plasma oxidation and grain-growth orientation increase $R_s$ above the Bardeen-Cooper-Schrieffer (BCS) resistance $R_{\mathrm{BCS}}\approx 17\text{μ}\mathrm{\Omega }$ at 10 GHz. For Cloisonné fabrication, we demonstrate $R_s=13\pm 1.4\text{μ}\mathrm{\Omega }$ down to $0.25\text{μ}\mathrm{m}$ wire width, which is below $R_{\mathrm{BCS}}$ and arguably the lowest microwave resistance reported for $\mathrm{Nb}$ at 4.2 K.

Far-field wave imaging and inversion of objects with dimension and spacing much smaller than the wavelength are very difficult because of the well-known diffraction limit. The task becomes more challenging for quantitative shape reconstruction of closely spaced subwavelength impenetrable scatterers. Apart from the classic resolution limit, complex wave interaction including evanescent waves among impenetrable objects can be strong, but it is difficult to be fully utilized for correct shape inversion although it contains critical resolution information. Here we tackle this problem by proposing a level-set-based geometrical full-waveform inversion method. It makes full use of wave physics to directly reconstruct subwavelength objects of arbitrary shapes separated within half a wavelength. Shape reconstruction is controlled by the geometrical boundary gradient calculated from the finite-element formulation, and the important role of wave interaction among objects in the inversion is demonstrated. The boundaries of the objects are represented using the level-set method, allowing for reconstruction of multiple objects simultaneously. Numerical examples and experiments of ultrasonic waves in solid samples demonstrate that the method successfully reconstructs closely spaced subwavelength objects with far-field measurements, and the resolution is shown to be within a fraction of wavelength. This level of accuracy can be very useful in subsurface imaging applications such as ultrasonic nondestructive evaluation, medical diagnosis, and electromagnetic sensing.

The near-field radiative heat transfer (NFRHT) between one-dimensional metamaterials comprised of phonon dielectric multilayers was investigated experimentally. Large-size (1 × 1 ${\mathrm{cm}}^2$) near-field samples were fabricated using $\mathrm{Si}\mathrm{C}$, ${\mathrm{Si}\mathrm{O}}_2$, and $\mathrm{Ge}$ layers at a certain gap distance, and the effects of layer-stacking order and phonon-resonance quality on NFRHT were examined. The measured results show good agreement with the theoretical results obtained by employing the transmission-matrix method. Super-Planckian thermal radiation was observed between emitters and receivers with identical structures. The failure of effective-medium theory (EMT) at predicting the near-field heat flux has been evidenced by measurements, particularly in the presence of bounded surface modes, such as the epsilon-near-zero mode. Additionally, analyses have shown that, in specific scenarios, the EMT can offer reasonable physical insights into the underlying coupling process from the perspective of homogenized media. Furthermore, the conditions for applying the EMT in the near-field regime were also touched upon.

Nitrogen-vacancy ($\mathrm{N}$-V) centers in diamond are promising quantum sensors due to their ultralong coherence time under ambient conditions and multimodal sensing capability. $\mathrm{N}$-V centers are strongly coupled to magnetic fields, leading to unprecedented sensitivity in magnetic field sensing. However, the coupling strengths between $\mathrm{N}$-V centers and other crucial parameters, such as temperature and pressure, are not as strong as that of the magnetic field, resulting in a relative low sensitivity. A previous study showed that the temperature sensitivity of a diamond quantum sensor could be largely improved by magnetic criticality enhancement. Here, we propose and demonstrate a hybrid quantum thermometer composed of bulk diamond with ensemble $\mathrm{N}$-V centers and a gadolinium magnetic flux concentrator. In addition to the magnetic criticality enhancement of gadolinium, our scheme leverages the magnetic flux concentration and ensemble $\mathrm{N}$-V centers, achieving a temperature sensitivity of about $251.5\text{nK}/\sqrt{\text{Hz}}$. Near the critical point, the spin resonance to temperature $(\mathrm{\partial }{f}_{\pm }/\mathrm{\partial }T)$ reached $57.3\text{MHz}/\text{K}$ under an external magnetic field of 1.213 G, which is about 774 times enhanced compared with that of bare $\mathrm{N}$-V centers. The submicrokelvin temperature resolution of our hybrid thermometer can be used in the calibration of a reference point of temperature, integrated marine environmental surveys, laser-frequency stabilization, aerospace high-stability temperature-control systems, and many other practical applications on a macroscopic scale.