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Programmable feedforward photonic meshes of Mach–Zehnder interferometers are computational optical circuits that have many classical and quantum computing applications including machine learning, sensing, and telecommunications. Such devices can form the basis of energy-efficient photonic neural networks, which solve complex tasks using photonics-accelerated matrix multiplication on a chip, and which may require calibration and training mechanisms. Such training can benefit from internal optical power monitoring and physical gradient measurement for optimizing controllable phase shifts to maximize some task merit function. Here, we design and experimentally verify a new architecture capable of power monitoring any waveguide segment in a feedforward photonic circuit. Our scheme is experimentally realized by modulating phase shifters in a 6 × 6 triangular mesh silicon photonic chip, which can non-invasively (i.e., without any internal “power taps”) resolve optical powers in a 3 × 3 triangular mesh based on response measurements in only two output detectors. We measure roughly 3% average error over 1000 trials in the presence of systematic manufacturing and environmental drift errors and verify scalability of our procedure to more modes via simulation.

This paper describes the characterization and testing of a temperature-compensated optical fiber platform for silicon sensors. Our sensor platform consists of standard optical fiber hardware for optically-balanced and wavelength-multiplexed reflection measurements. We show that thermal effects in silicon sensors are significant for operational temperatures from 275-315 K but can be compensated using a collocated nano-fabricated temperature sensor. Our silicon temperature sensor is a $150~\mu \text{m}$ wide and $5~\mu \text{m}$ thick disk that is fabricated on the wafer-scale with a 3 mK/ $\sqrt {Hz}$ resolution and a 1.7 s thermal time constant in air. Our temperature-compensated platform has sufficient sensitivity and bandwidth to reduce thermal signals in silicon pressure sensors and microphones by more than an order of magnitude.

As blockchain technology and cryptocurrency become increasingly mainstream, photonic computing has emerged as an efficient hardware platform that reduces ever-increasing energy costs required to verify transactions in decentralized cryptonetworks. To reduce sensitivity of these verifications to photonic hardware error, we propose and experimentally demonstrate a cryptographic scheme, LightHash, that implements robust, low-bit precision matrix multiplication in programmable silicon photonic networks. We demonstrate an error mitigation scheme to reduce error by averaging computation across circuits, and simulate energy-efficiency-error trade-offs for large circuit sizes. We conclude that our error-resistant and efficient hardware solution can potentially generate a new market for decentralized photonic blockchain.

This paper describes the design, characterization, and testing of a compact hydrophone capable of measuring acoustic signals from cardiomyocytes. Our hydrophone consists of a nanofabricated photonic-crystal diaphragm externally-mounted to the facet of an optical fiber to form a pressure-sensitive Fabry-Pérot cavity. Our hydrophone can operate in small liquid volumes less than 5 mm deep and incorporates a microchannel to vent air during immersion. The venting channel is designed to optimize bandwidth and sensitivity. Modeling and experimental results in water show a bandwidth from 50 Hz to 18 kHz and a minimum detectable pressure of $3~\mu Pa/ \sqrt {Hz}$ . We demonstrate the sensitivity to simulated bio-acoustic sources with nanometer-scale displacements.

Multiple microelectromechanical system (MEMS) phased arrays in optical conjugation enable scanning over extended angular ranges beyond what is possible with a single device. We demonstrate this method for random access beam steering at 250 kHz using a MEMS phased array and a switchable grating modulator, achieving 4,352 resolvable lines from 2,176 line pairs over a field of view (FOV) of ±3.74° in the Fourier plane. With projection optics, this is extended to a far-field FOV of ±24.7° without reduction of the number of resolvable lines.

This paper describes the design, fabrication, and characterization of the smallest pressure sensors with the required sensitivity, bandwidth, and robustness for turbulent airflow measurements. These fiber-facet monolithic silicon optical pressure sensors consist of a silicon diaphragm above a sealed cavity contained within a $125~\mu \text{m}$ wide by $5~\mu \text{m}$ thick silicon disk mounted directly onto a single-mode optical fiber facet. The fiber-mounted sensors form pressure-sensitive interferometric cavities with 1.6 MHz bandwidth, 4 nm/kPa deflection, and up to 0.07 V/kPa sensitivity. The short length of the optical cavity makes the sensors optically efficient and optically broadband, allowing multiplexing using standard optical communications equipment. This is demonstrated experimentally by optically-multiplexing three fiber-facet sensors with up to 161 kPa dynamic ranges and 2 Pa noise floors. These balanced-detection pressure-sensing arrays provide a small-footprint, high-resolution alternative to traditional turbulence measurement equipment.

Reconfigurable photonic mesh networks of tunable beamsplitter nodes can linearly transform $N$ -dimensional vectors representing input modal amplitudes of light for applications such as energy-efficient machine learning hardware, quantum information processing, and mode demultiplexing. Such photonic meshes are typically programmed and/or calibrated by tuning or characterizing each beam splitter one-by-one, which can be time-consuming and can limit scaling to larger meshes. Here we introduce a graph-topological approach that defines the general class of feedforward networks and identifies columns of non-interacting nodes that can be adjusted simultaneously. By virtue of this approach, we can calculate the necessary input vectors to program entire columns of nodes in parallel by simultaneously nullifying the power in one output of each node via optoelectronic feedback onto adjustable phase shifters or couplers. This parallel nullification approach is robust to fabrication errors, requiring no prior knowledge or calibration of node parameters and reducing programming time by a factor of order $N$ to being proportional to the optical depth (number of node columns). As a demonstration, we simulate our programming protocol on a feedforward optical neural network model trained to classify handwritten digit images from the MNIST dataset with up to 98% validation accuracy.

Linear phased arrays enable simultaneous tunable focusing and scanning. Using an electrostatically actuated, high-speed linear phased array of MEMS mirrors, we demonstrate cylindrical focusing with 90% optical efficiency up to 0.008 numerical aperture (NA) with simultaneous beam steering. Single focus scanning is demonstrated up to an NA of 0.013, at which point the focus splits, creating a multifocal response. The array refresh rate is only limited by the speed of the elements, allowing random-access axial and lateral scanning up to 350 kHz.

We present software-based methods for automatic phase control and for mosaicing high-speed, Lissajous-scanned images. To achieve imaging speeds fast enough for mosaicing, we first increase the image update rate tenfold from 3 to 30 Hz, then vertically interpolate each sparse image in real-time to eliminate fixed pattern noise. We validate our methods by imaging fluorescent beads and automatically maintaining phase control over the course of one hour. We then image fixed mouse brain tissues at varying update rates and compare the resulting mosaics. Using reconstructed image data as feedback for phase control eliminates the need for phase sensors and feedback controllers, enabling long-term imaging experiments without additional hardware. Mosaicing subsampled images results in video-rate imaging speeds, nearly fully recovered spatial resolution, and millimeter-scale fields of view.

Fiber-tip interferometric pressure sensors offer high resolution over broad frequency and dynamic ranges with minimal device footprint. We fabricate a $100~\mu \text{m}$ wide monolithic silicon pressure-sensing diaphragm and reference cavity as a unit on the wafer-scale, simplifying the packaging. The $1.0~\mu \text{m}$ thick diaphragm and $1~\mu \text{m}$ thick cavity form a pressure-sensitive optical resonator which we interrogate over an optical fiber with a polished turning mirror. Our sensors function at pressures up to 3.5 atm, and have tunable dynamic ranges and sensitivities through choice of operational wavelength. We demonstrate 0.002 atm resolution over a 0.9 atm dynamic range using 1544 nm light for atmospheric pressure testing. We introduce an optical model for fiber-tip Fabry-Perot sensors with diffraction-loss and show good agreement with experimental results. We test the devices in a wind-tunnel environment and demonstrate broad-bandwidth operation and resolution competitive with standard micro-electromechanical sensors.

Immersion optics enable creation of systems with improved optical concentration and coupling by taking advantage of the fact that the luminance of light is proportional to the square of the refractive index in a lossless optical system. Immersion graded index optical concentrators, that do not need to track the source, are described in terms of theory, simulations, and experiments. We introduce a generalized design guide equation which follows the Pareto function and can be used to create various immersion graded index optics depending on the application requirements of concentration, refractive index, height, and efficiency. We present glass and polymer fabrication techniques for creating broadband transparent graded index materials with large refractive index ranges, (refractive index ratio)^2 of ~2, going many fold beyond what is seen in nature or the optics industry. The prototypes demonstrate 3x optical concentration with over 90% efficiency. We report via functional prototypes that graded-index-lens concentrators perform close to the theoretical maximum limit and we introduce simple, inexpensive, design-flexible, and scalable fabrication techniques for their implementation., Comment: AGILE featured on the journal cover, accompanying manuscript, and supplementary information

We experimentally demonstrate in situ backpropagation in a programmable nanophotonic interferometer network, achieving inference accuracies matching digital implementations. Error gradients are computed by simultaneously measuring optical interference at intermediate network components, eliminating expensive digital computations.

We report a silicon-photonics process for MEMS-tunable phase shifters that leverages orthogonal optical modes. A phase shifter with -0.63dB insertion loss and π phase shift and a preliminary tunable directional coupler are demonstrated.

We propose LightHash, the first feasible photonic cryptographic hash function for blockchain technology using programmable photonic networks. We experimentally evaluate LightHash and assess whether photonic circuits can outperform digital competitors in latency and energy efficiency.

Compressing electron pulses is important in many applications of electron beam systems. In this study, we propose to use optical beat notes to compress electron pulses. The beat frequency is chosen to match the initial electron pulse duration, which enables the compression of electron pulses with a wide range of durations. This functionality extends the optical control of electron beams, which is important in compact electron beam systems such as dielectric laser accelerators. We also find that the dominant frequency of the electron charge density changes continuously along its drift trajectory, which may open up new opportunities in coherent interaction between free electrons and quantum or classical systems.

Two-dimensional, resonant scanners have been utilized in a large variety of imaging modules due to their compact form, low power consumption, large angular range, and high speed. However, resonant scanners have problems with non-optimal and inflexible scanning patterns and inherent phase uncertainty, which limit practical applications. Here we propose methods for optimized design and control of the scanning trajectory of two-dimensional resonant scanners under various physical constraints, including high frame-rate and limited actuation amplitude. First, we propose an analytical design rule for uniform spatial sampling. We demonstrate theoretically and experimentally that by including non-repeating scanning patterns, the proposed designs outperform previous designs in terms of scanning range and fill factor. Second, we show that we can create flexible scanning patterns that allow focusing on user-defined Regions-of-Interest (RoI) by modulation of the scanning parameters. The scanning parameters are found by an optimization algorithm. In simulations, we demonstrate the benefits of these designs with standard metrics and higher-level computer vision tasks (LiDAR odometry and 3D object detection). Finally, we experimentally implement and verify both unmodulated and modulated scanning modes using a two-dimensional, resonant MEMS scanner. Central to the implementations is high bandwidth monitoring of the phase of the angular scans in both dimensions. This task is carried out with a position-sensitive photodetector combined with high-bandwidth electronics, enabling fast spatial sampling at ~ 100Hz frame-rate., 16 pages, 11 figures

Complex monolithic Si MEMS can be created using a single mask by extending the empty-space-in-silicon (ESS) or silicon-on-nothing (SON) technology. The fabrication combines isotropic and anisotropic etching with selective removal of passivation layers followed by hydrogen annealing. The resulting expanded design space includes multilayer structures and embedded cavities. The MEMS formation by the hydrogen annealing is simulated both at large scales and microscopic scales that together predict the shape of the finished MEMS. We demonstrate the accuracy of our process and simulations by fabricating single- and double-layer evacuated silicon voids that form Fabry-Perot optical pressure sensors with the sealed voids as pressure references. We also create multi-layered sensors with an integrated photonic crystals sensing diaphragm for improved optical readout. The sensors have a calculated 6.7 $\mu \text{V}$ /Pa sensitivity and low noise over a dynamic range of over 70.9 kPa. [2019-0091]

We demonstrate a compact technique to compress electron pulses to attosecond length, while keeping the energy spread reasonably small. The technique is based on Dielectric Laser Acceleration (DLA) in nanophotonic silicon structures. Unlike previous ballistic optical microbunching demonstrations, we use a modulator-demodulator scheme to compress phase space in the time and energy coordinates. With a second stage, we show that these pulses can be coherently accelerated, producing a net energy gain of $1.5\pm0.1$ keV, which is significantly larger than the remaining energy spread of $0.88 \,_{-0.2}^{+0.0}$ keV FWHM. We show that by linearly sweeping the phase between the two stages, the energy spectrum can be coherently moved in a periodic manner, while keeping the energy spread roughly constant. After leaving the buncher, the electron pulse is also transversely focused, and can be matched into a following accelerator lattice. Thus, this setup is the prototype injector into a scalable DLA based on Alternating Phase Focusing (APF).

We demonstrate the first laser acceleration based on novel dielectric materials (Al2O3 and Ga2O3) with high laser damage thresholds, opening a new venue for perfor- mance optimization of dielectric laser accelerators.

We fabricate, assemble, and characterize a compact, robust, and scalably-fabricated photonic crystal hydrophone capable of measuring acoustic signals from single cardiomyocytes with a minimum detectable pressure of 3 µPa/√Hz and a 19 kHz band-width.

We study dispersion models and design variations for programmable MEMS photonic networks to analyze scalability of parallel matrix-vector multiplication, which is a core element of commercially viable and energy-efficient photonic neural network accelerator chips.

Through phase controlling a 2D MEMS scanner, we achieve fast and flexible spatial information sampling for use in LiDAR systems. The scanning pattern is designed for desired operational characteristics, e.g. data collection frame time, actuation amplitude, sampling efficiency and Regions-of-Interest (roi) focus. A hardware prototype with wide-band phase control is also demonstrated. This system facilitates fast LiDAR operation at ~ 100hz frame rate.

We present two compact ultrafast electron injector designs with integrated focusing that provide high peak brightness of up to $1.9*10^{12} A/m^2Sr^2$ with 10s of electrons per laser pulse using silicon carbide electrodes and silicon nanotip emitters. We demonstrate a few centimeter scale 96 keV immersion lens electron source and a 57 keV immersion lens electron source with a 19 kV/mm average acceleration gradient, nearly double the typical 10 kV/mm used in DC electron sources. The brightness of the electron sources is measured alongside start-to-end simulations including space charge effects. These sources are suitable for dielectric laser accelerator experiments, ultrafast electron diffraction, and other applications where a compact high brightness electron source is required., Comment: 8 pages, 5 figures

In this work, we present a comprehensive theoretical description of the Lorentz force in dual-grating dielectric laser accelerators (DLA). Here we examine the dual-grating DLA under arbitrary illumination conditions, both single-side and dual-side drive. We improve upon previous descriptions of these forces by providing a unified description of all possible operating modes of these devices, and classify the modes into three categories. In particular, we predict the existence of the previously observed ``line modes'' and a novel ``elliptical mode'', provide an experimental demonstration of this new mode, and suggest a possible application for it in improving the resolution of attosecond-scale streak cameras. Finally, we examine several complementary methods of tuning a dual-grating DLA to a desired operating mode---particularly dual-drive phase rotation and translational offset of the grating teeth.

We present the first demonstration of a waveguide-integrated dielectric laser accelerator. This structure and associated grating coupler are designed using a gradient-based inverse design approach. A waveguide is directly interfaced with an accelerator structure which is patterned with sub-wavelength features to produce near-fields phase-matched to electrons travelling through a 250 nm gap in the structure. We have experimentally demonstrated these waveguide-integrated accelerators by showing acceleration of subrelativistic electrons of initial energy 83.5 keV. We observe a maximum energy modulation of 1.19 keV over 30 μm. These results represent a significant step toward scalable and integrable on-chip dielectric laser accelerators for applications in ultrafast, medical, and high-energy technologies.

We reveal quantum features in laser acceleration arising from the underlying wave nature of the accelerated electron, and we present the first accelerator on-chip operated inside a transmission electron microscope.

To be useful for most scientific and medical applications, compact particle accelerators will require much higher average current than enabled by current architectures. For this purpose, we propose a photonic crystal architecture for a dielectric laser accelerator, referred to as a multi-input multi-output silicon accelerator (MIMOSA), that enables simultaneous acceleration of multiple electron beams, increasing the total electron throughput by at least one order of magnitude. To achieve this, we show that the photonic crystal must support a mode at the $\Gamma$ point in reciprocal space, with a normalized frequency equal to the normalized speed of the phase matched electron. We show that the figure of merit of the MIMOSA can be inferred from the eigenmodes of the corresponding infinitely periodic structure, which provides a powerful approach to design such devices. Additionally, we extend the MIMOSA architecture to electron deflectors and other electron manipulation functionalities. These additional functionalities, combined with the increased electron throughput of these devices, permit all-optical on-chip manipulation of electron beams in a fully integrated architecture compatible with current fabrication technologies, which opens the way to unconventional electron beam shaping, imaging, and radiation generation.

A buried photonic element fabrication technique is used to create a broadband optical fiber-facet absolute pressure sensor in a 1 50 /i m wide by 5 /im thick crystalline silicon disk with 50 /iatm pressure resolution at 1 atm.

Single-crystal silicon is an excellent optical and mechanical material, but its properties are compromised by the incorporation of other materials required for functionality or structural support. Here, we describe a monolithic silicon acoustic sensor based on a sensing diaphragm with an integrated photonic crystal (PC) mirror. Diaphragm deflection is measured in a Fabry–Perot resonator formed between the PC mirror and a gold coated single-mode fiber. The sensors are fabricated on standard silicon wafers by standard CMOS processing technologies, yielding monolithic, low-stress sensing diaphragms. The packaged sensor exhibits a minimum detectable pressure of $10~\mathrm {\mu }$ Pa/ $\mathrm {\sqrt {Hz}}$ in the 8–17-kHz frequency range.