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A solid-state approach for quantum networks is advantages, as it allows the integration of nanophotonics to enhance the photon emission and the utilization of weakly coupled nuclear spins for long-lived storage. Silicon carbide, specifically point defects within it, shows great promise in this regard due to the easy of availability and well-established nanofabrication techniques. Despite of remarkable progresses made, achieving spin-photon entanglement remains a crucial aspect to be realized. In this paper, we experimentally generate entanglement between a silicon vacancy defect in silicon carbide and a scattered single photon in the zero-phonon line. The spin state is measured by detecting photons scattered in the phonon sideband. The photonic qubit is encoded in the time-bin degree-of-freedom and measured using an unbalanced Mach-Zehnder interferometer. Photonic correlations not only reveal the quality of the entanglement but also verify the deterministic nature of the entanglement creation process. By harnessing two pairs of such spin-photon entanglement, it becomes straightforward to entangle remote quantum nodes at long distance.

Rapid developments in machine vision have led to advances in a variety of industries, from medical image analysis to autonomous systems. These achievements, however, typically necessitate digital neural networks with heavy computational requirements, which are limited by high energy consumption and further hinder real-time decision-making when computation resources are not accessible. Here, we demonstrate an intelligent meta-imager that is designed to work in concert with a digital back-end to off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both angle and polarization multiplexing to create multiple information channels that perform positive and negatively valued convolution operations in a single shot. The meta-imager is employed for object classification, experimentally achieving 98.6% accurate classification of handwritten digits and 88.8% accuracy in classifying fashion images. With compactness, high speed, and low power consumption, this approach could find a wide range of applications in artificial intelligence and machine vision applications.

Photonic moiré superlattice as an emerging platform of flatbands can tightly confine the light inside the cavity and has important applications not only in linear optics but also in nonlinear optics. In this paper, we numerically investigate the third- and fifth-order harmonic generation (THG and FHG) in photonic moiré superlattices fabricated by the nonlinear material silicon. The high conversion efficiency of THG and FHG is obtained at a relatively low intensity of fundamental light, e.g., the maximum conversion efficiency of THG and FHG arrives even up to be $10^{-2}$ and $10^{-9}$ at the fundamental intensity of 30 kW/m2, respectively, in the moiré superlattice of near flat band formed by the twist angle 6.01o. The results indicate the photonic moiré superlattice of a high-quality factor and flatbands is a promising platform for efficient nonlinear processes and advanced photonic devices.

Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision making when computation resources are limited. Here, we demonstrate a meta-optic based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems resulting in a robust classifier that achieves 95% accurate classification of handwriting digits and 94% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine-vision and artificial intelligence.

In this paper, we obtain a Sn-Bi-In-Pb quaternary near eutectic alloy composition from machine learning model. The eutectic points and the alloy composition were evaluated and continuously improved by experimental input. The actual composition is near the result given by machine learning. We conclude that the application of machine learning in solder design has shown the potential to overcome the challenge in searching for the next generation eutectic solders, which will have a broad impact on the industry.

We conduct a combined experimental and theoretical study of the quantum-confined Stark effect in GaAs/AlGaAs quantum dots obtained with the local droplet etching method. In the experiment, we probe the permanent electric dipole and polarizability of neutral and positively charged excitons weakly confined in GaAs quantum dots by measuring their light emission under the influence of a variable electric field applied along the growth direction. Calculations based on the configuration-interaction method show excellent quantitative agreement with the experiment and allow us to elucidate the role of Coulomb interactions among the confined particles and -- even more importantly -- of electronic correlation effects on the Stark shifts. Moreover, we show how the electric field alters properties such as built-in dipole, binding energy, and heavy-light hole mixing of multiparticle complexes in weakly confining systems, underlining the deficiencies of commonly used models for the quantum-confined Stark effect.

Intensity squeezing, i.e., photon number fluctuations below the shot noise limit, is a fundamental aspect of quantum optics and has wide applications in quantum metrology. It was predicted in 1979 that the intensity squeezing could be observed in resonance fluorescence from a two-level quantum system. Yet, its experimental observation in solid states was hindered by inefficiencies in generating, collecting and detecting resonance fluorescence. Here, we report the intensity squeezing in a single-mode fibre-coupled resonance fluorescence single-photon source based on a quantum dot-micropillar system. We detect pulsed single-photon streams with 22.6% system efficiency, which show subshot-noise intensity fluctuation with an intensity squeezing of 0.59 dB. We estimate a corrected squeezing of 3.29 dB at the first lens. The observed intensity squeezing provides the last piece of the fundamental picture of resonance fluorescence; which can be used as a new standard for optical radiation and in scalable quantum metrology with indistinguishable single photons.

An optimal single-photon source should deterministically deliver one and only one photon at a time, with no trade-off between the source's efficiency and the photon indistinguishability. However, all reported solid-state sources of indistinguishable single photons had to rely on polarization filtering which reduced the efficiency by 50%, which fundamentally limited the scaling of photonic quantum technologies. Here, we overcome this final long-standing challenge by coherently driving quantum dots deterministically coupled to polarization-selective Purcell microcavities--two examples are narrowband, elliptical micropillars and broadband, elliptical Bragg gratings. A polarization-orthogonal excitation-collection scheme is designed to minimize the polarization-filtering loss under resonant excitation. We demonstrate a polarized single-photon efficiency of 0.60+/-0.02 (0.56+/-0.02), a single-photon purity of 0.975+/-0.005 (0.991+/-0.003), and an indistinguishability of 0.975+/-0.006 (0.951+/-0.005) for the micropillar (Bragg grating) device. Our work provides promising solutions for truly optimal single-photon sources combining near-unity indistinguishability and near-unity system efficiency simultaneously.

We report the design, construction, and initial commissioning results of a large high pressure gaseous Time Projection Chamber (TPC) with Micromegas modules for charge readout. The detector vessel has an inner volume of about 600 L and an active volume of 270 L. At 10 bar operating pressure, the active volume contains about 20 kg of xenon gas and can image charged particle tracks. Drift electrons are collected by the charge readout plane, which accommodates a tessellation of seven Micromegas modules. Each of the Micromegas covers a square of 20 cm by 20 cm. A new type of Microbulk Micromegas is chosen for this application due to its good gain uniformity and low radioactive contamination. Initial commissioning results with 1 Micromegas module running with 1 bar argon and isobutane gas mixture and 5 bar xenon and trimethylamine (TMA) gas mixture are reported. We also recorded extended background tracks from cosmic ray events and highlighted the unique tracking feature of this gaseous TPC.

The optical selection rules in epitaxial quantum dots are strongly influenced by the orientation of their natural quantization axis, which is usually parallel to the growth direction. This configuration is well suited for vertically emitting devices, but not for planar photonic circuits because of the poorly controlled orientation of the transition dipoles in the growth plane. Here we show that the quantization axis of gallium arsenide dots can be flipped into the growth plane via moderate in plane uniaxial stress. By using piezoelectric strain actuators featuring strain-amplification we study the evolution of the selection rules and excitonic fine-structure in a regime, in which quantum confinement can be regarded as a perturbation compared to strain in determining the symmetry properties of the system. The experimental and computational results suggest that uniaxial stress, may be the right tool to obtain quantum light sources with ideally oriented transition dipoles and enhanced oscillator strengths for integrated quantum photonics.

We fabricated an acousto-optic semiconductor hybrid device for strong optomechanical coupling of individual quantum emitters and a surface acoustic wave. Our device comprises a surface acoustic wave chip made from highly piezoelectric LiNbO$_3$ and a GaAs-based semiconductor membrane with an embedded layer of quantum dots. Employing multi-harmonic transducers, we generated sound waves on LiNbO$_3$ over a wide range of radio frequencies. We monitored their coupling to and propagation across the semiconductor membrane both in the electrical and optical domain. We demonstrate enhanced optomechanical tuning of the embedded quantum dots with increasing frequencies. This effect was verified by finite element modelling of our device geometry and attributed to an increased localization of the acoustic field within the semiconductor membrane. For moderately high acoustic frequencies, our simulations predict strong optomechanical coupling making our hybrid device ideally suited for applications in semiconductor based quantum acoustics.

One of the remaining obstacles to approaching the theoretical efficiency limit of crystalline silicon (c-Si) solar cells is the exceedingly high interface recombination loss for minority carriers at the Ohmic contacts. In ultra-thin-film c-Si solar cells, this contact recombination loss is far more severe than for traditional thick cells due to the smaller volume and higher minority carrier concentration of the former. This paper presents a novel design of an electron passing (Ohmic) contact to n-type Si that is hole-blocking with significantly reduced hole recombination. This contact is formed by depositing a thin titanium dioxide (TiO2) layer to form a silicon metal-insulator-semiconductor (MIS) contact. A 2 \mum thick Si cell with this TiO2 MIS contact achieved an open circuit voltage (Voc) of 645 mV, which is 10 mV higher than that of an ultra-thin cell with a metal contact. This MIS contact demonstrates a new path for ultra-thin-film c-Si solar cells to achieve high efficiencies as high as traditional thick cells, and enables the fabrication of high-efficiency c-Si solar cells at a lower cost.

Quantum photonics holds great promise for future technologies such as secure communication, quantum computation, quantum simulation, and quantum metrology. An outstanding challenge for quantum photonics is to develop scalable miniature circuits that integrate single-photon sources, linear optical components, and detectors on a chip. Plasmonic nanocircuits will play essential roles in such developments. Plasmonic components feature ultracompact geometries and can be controlled more flexibly and more energy-efficiently compared to conventional dielectric components due to strong field confinement and enhancement. Moreover, plasmonic components are compatible with electronic circuits, thanks to their deep subwavelength sizes as well as their electrically conducting materials. However, for quantum plasmonic circuits, integration of stable, bright, and narrow-band single photon sources in the structure has so far not been reported. Here we present a quantum plasmonic nanocircuit driven by a self-assembled GaAs quantum dot. The quantum dot efficiently excites narrow-band single plasmons that are guided in a two-wire transmission line until they are converted into single photons by an optical antenna. Our work demonstrates the feasibility of fully on-chip plasmonic nanocircuits for quantum optical applications.

This paper explores different photo-bending shapes in polydomain nematic glass. The motivation is to explain the phenomenon in experiment [1] under polarized light in which a nematic film curls into an circular arc, like part of a cylindrical surface. Polarized light triggers photo-isomerization and therefore makes liquid crystals (LCs) contract along their directors. We apply the Sachs limit to homogenize the deformation of polydomain LC glass. Photo-strain can be either contraction or expansion through the material. Bending shapes can be anticlastic, bowl-shaped and cylindrical affected by Poisson ratio and illumination intensity. An explanation for the cylindrical bend and ways to observe other shapes are given in a parameter plane.

This paper demonstrates an arbitrary tunable spaser based on double-Fano resonance of a plasmonic nanostructure consisting of two sets of disk-ring (TSDR) nanostructure. TSDR nanostructure supports two Fano resonances, which can be served as the lasing mode and the pumping mode of a spaser. These two mode can be tuned in a very wide wavelength range because of the good tunability of the two nanorings. The tuning range of the lasing mode and the pumping mode can be reached to 710 nm and 620 nm. These results represent a significant step in the pursuit of ultimate spasers and propose a approach to manipulate lasing mode and pumping mode over a broad spectral range.

Silicon single-photon avalanche diode (SPAD) is a core device for single-photon detection in the visible and the near-infrared range, and widely used in many applications. However, due to limits of the structure design and device fabrication for current silicon SPADs, the key parameters of detection befficiency and timing jitter are often forced to compromise. Here, we propose a nanostructured silicon SPAD, which achieves high detection efficiency with excellent timing jitter simultaneously over a broad spectral range. The optical and electric simulations show significant performance enhancement compared with conventional silicon SPAD devices. This nanostructured devices can be easily fabricated and thus well suited for practical applications.

The research in parallel machine scheduling in combinatorial optimization suggests that the desirable parallel efficiency could be achieved when the jobs are sorted in the non-increasing order of processing times. In this paper, we find that the time spending for computing the permanent of a sparse matrix by hybrid algorithm is strongly correlated to its permanent value. A strategy is introduced to improve a parallel algorithm for sparse permanent. Methods for approximating permanents, which have been studied extensively, are used to approximate the permanent values of sub-matrices to decide the processing order of jobs. This gives an improved load balancing method. Numerical results show that the parallel efficiency is improved remarkably for the permanents of fullerene graphs, which are of great interests in nanoscience.