Precise Characterization of a Waveguide Fiber Interface in Silicon Carbide.

Spin-active optical emitters in silicon carbide are excellent candidates toward the development of scalable quantum technologies. However, efficient photon collection is challenged by undirected emission patterns from optical dipoles, as well as low total internal reflection angles due to the high refractive index of silicon carbide. Based on recent advances with emitters in silicon carbide waveguides, we now demonstrate a comprehensive study of nanophotonic waveguide-to-fiber interfaces in silicon carbide. We find that across a large range of fabrication parameters, our experimental collection efficiencies remain above 90%. Further, by integrating silicon vacancy color centers into these waveguides, we demonstrate an overall photon count rate of 181 kilo-counts per second, which is an order of magnitude higher compared to standard setups. We also quantify the shift of the ground state spin states due to strain fields, which can be introduced by waveguide fabrication techniques. Finally, we show coherent electron spin manipulation with waveguide-integrated emitters with state-of-the-art coherence times of T 2 ∼ 42 µs. The robustness of our methods is very promising for quantum networks based on multiple orchestrated emitters.

Tunable phononic coupling in excitonic quantum emitters.

Engineering the coupling between fundamental quantum excitations is at the heart of quantum science and technologies. An outstanding case is the creation of quantum light sources in which coupling between single photons and phonons can be controlled and harnessed to enable quantum information transduction. Here we report the deterministic creation of quantum emitters featuring highly tunable coupling between excitons and phonons. The quantum emitters are formed in strain-induced quantum dots created in homobilayer WSe2. The colocalization of quantum-confined interlayer excitons and terahertz interlayer breathing-mode phonons, which directly modulates the exciton energy, leads to a uniquely strong phonon coupling to single-photon emission, with a Huang-Rhys factor reaching up to 6.3. The single-photon spectrum of interlayer exciton emission features a single-photon purity >83% and multiple phonon replicas, each heralding the creation of a phonon Fock state in the quantum emitter. Due to the vertical dipole moment of the interlayer exciton, the phonon-photon interaction is electrically tunable to be higher than the exciton and phonon decoherence rate, and hence promises to reach the strong-coupling regime. Our result demonstrates a solid-state quantum excitonic-optomechanical system at the atomic interface of the WSe2 bilayer that emits flying photonic qubits coupled with stationary phonons, which could be exploited for quantum transduction and interconnection.

Programmable black phosphorus image sensor for broadband optoelectronic edge computing.

Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT's electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing.

Long-range transport of 2D excitons with acoustic waves.

Excitons are elementary optical excitation in semiconductors. The ability to manipulate and transport these quasiparticles would enable excitonic circuits and devices for quantum photonic technologies. Recently, interlayer excitons in 2D semiconductors have emerged as a promising candidate for engineering excitonic devices due to their long lifetime, large exciton binding energy, and gate tunability. However, the charge-neutral nature of the excitons leads to weak response to the in-plane electric field and thus inhibits transport beyond the diffusion length. Here, we demonstrate the directional transport of interlayer excitons in bilayer WSe2 driven by the propagating potential traps induced by surface acoustic waves (SAW). We show that at 100 K, the SAW-driven excitonic transport is activated above a threshold acoustic power and reaches 20 µm, a distance at least ten times longer than the diffusion length and only limited by the device size. Temperature-dependent measurement reveals the transition from the diffusion-limited regime at low temperature to the acoustic field-driven regime at elevated temperature. Our work shows that acoustic waves are an effective, contact-free means to control exciton dynamics and transport, promising for realizing 2D materials-based excitonic devices such as exciton transistors, switches, and transducers up to room temperature.

Harnessing optoelectronic noises in a photonic generative network.

Integrated optoelectronics is emerging as a promising platform of neural network accelerator, which affords efficient in-memory computing and high bandwidth interconnectivity. The inherent optoelectronic noises, however, make the photonic systems error-prone in practice. It is thus imperative to devise strategies to mitigate and, if possible, harness noises in photonic computing systems. Here, we demonstrate a photonic generative network as a part of a generative adversarial network (GAN). This network is implemented with a photonic core consisting of an array of programable phase-change memory cells to perform four-element vector-vector dot multiplication. The GAN can generate a handwritten number ("7") in experiments and full 10 digits in simulation. We realize an optical random number generator, apply noise-aware training by injecting additional noise, and demonstrate the network's resilience to hardware nonidealities. Our results suggest the resilience and potential of more complex photonic generative networks based on large-scale, realistic photonic hardware.

Surface Modification of Black Phosphorus with Group 13 Lewis Acids for Ambient Protection and Electronic Tuning.

Herein we introduce a facile, solution-phase protocol to modify the Lewis basic surface of few-layer black phosphorus (bP) and demonstrate its effectiveness at providing ambient stability and tuning of electronic properties. Commercially available group 13 Lewis acids that range in electrophilicity, steric bulk, and Pearson hard/soft-ness are evaluated. The nature of the interaction between the Lewis acids and the bP lattice is investigated using a range of microscopic (optical, atomic force, scanning electron) and spectroscopic (energy dispersive, X-ray photoelectron) methods. Al and Ga halides are most effective at preventing ambient degradation of bP (>84 h for AlBr3 ), and the resulting field-effect transistors show excellent IV characteristics, photocurrent, and current stability, and are significantly p-doped. This protocol, chemically matched to bP and compatible with device fabrication, opens a path for deterministic and persistent tuning of the electronic properties in bP.

Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network.

Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics for machine learning algorithms, such as neural networks of various types. Integrated photonic networks are particularly powerful in performing analog computing of matrix-vector multiplication (MVM) as they afford unparalleled speed and bandwidth density for data transmission. Incorporating nonvolatile phase-change materials in integrated photonic devices enables indispensable programming and in-memory computing capabilities for on-chip optical computing. Here, we demonstrate a multimode photonic computing core consisting of an array of programable mode converters based on on-waveguide metasurfaces made of phase-change materials. The programmable converters utilize the refractive index change of the phase-change material Ge2Sb2Te5 during phase transition to control the waveguide spatial modes with a very high precision of up to 64 levels in modal contrast. This contrast is used to represent the matrix elements, with 6-bit resolution and both positive and negative values, to perform MVM computation in neural network algorithms. We demonstrate a prototypical optical convolutional neural network that can perform image processing and recognition tasks with high accuracy. With a broad operation bandwidth and a compact device footprint, the demonstrated multimode photonic core is promising toward large-scale photonic neural networks with ultrahigh computation throughputs.

Midinfrared Electro-optic Modulation in Few-Layer Black Phosphorus.

Black phosphorus stands out from the family of two-dimensional materials as a semiconductor with a direct, layer-dependent bandgap spanning the visible to mid-infrared (mid-IR) spectral range. It is, therefore, a very promising material for various optoelectronic applications, particularly in the important mid-IR range. While mid-IR technology has been advancing rapidly, both photodetection and electro-optic modulation in the mid-IR rely on narrow-band compound semiconductors, which are difficult and expensive to integrate with the ubiquitous silicon photonics. For mid-IR photodetection, black phosphorus has already been proven to be a viable alternative. Here, we demonstrate electro-optic modulation of mid-IR absorption in few-layer black phosphorus. Our experimental and theoretical results find that, within the doping range obtainable in our samples, the quantum confined Franz-Keldysh effect is the dominant mechanism of electro-optic modulation. A spectroscopic study on samples with varying thicknesses reveals strong layer dependence in the interband transition between specific pairs of sub-bands. Our results show that black phosphorus is a very promising material to realizing efficient mid-IR modulators.

Three-Dimensional Integration of Black Phosphorus Photodetector with Silicon Photonics and Nanoplasmonics.

We demonstrate the integration of a black phosphorus photodetector in a hybrid, three-dimensional architecture of silicon photonics and metallic nanoplasmonics structures. This integration approach combines the advantages of the low propagation loss of silicon waveguides, high-field confinement of a plasmonic nanogap, and the narrow bandgap of black phosphorus to achieve high responsivity for detection of telecom-band, near-infrared light. Benefiting from an ultrashort channel (∼60 nm) and near-field enhancement enabled by the nanogap structure, the photodetector shows an intrinsic responsivity as high as 10 A/W afforded by internal gain mechanisms, and a 3 dB roll-off frequency of 150 MHz. This device demonstrates a promising approach for on-chip integration of three distinctive photonic systems, which, as a generic platform, may lead to future nanophotonic applications for biosensing, nonlinear optics, and optical signal processing.

Ultrahigh-performance inverters based on CdS nanobelts.

We report ultrahigh-performance inverters, each consisting of two top-gate metal-oxide-semiconductor field-effect transistors based on n-CdS nanobelts. High-kappa HfO(2) dielectrics are used as the top-gate oxide layers. The inverters have a large supply voltage (V(DD)) range (from 50 mV to 10 V) and very high voltage gain ( approximately 10, 100, and 1000 at V(DD) = 0.2, 1, and 10 V, respectively). Current consumption is less than 7 nA at V(DD) = 1 V, corresponding to a power consumption of less than 7 nW. The high and low output voltages are close to full rail. The inverters also exhibit good dynamic behavior with square wave input at frequencies up to 1 kHz. The operation of the inverters is analyzed in detail. The inverters are promising for future low power high performance logic circuit applications.