Micro-ring resonators can tunably weight wavelength-division-multiplexed signals, but they face high sensitivity to temperature. In this work, we take advantage of micro-ring self-heating to experimentally stabilize a silicon micro-ring weight, nearly halving its thermal sensitivity.

Spiking neurons and neural networks constitute a fundamental building block for brain-inspired computing, which is poised to benefit significantly from photonic hardware implementations. In this work, we experimentally investigate an interconnected optical neuromorphic system based on an ultrafast spiking vertical cavity surface emitting laser (VCSEL) neuron and a silicon photonics (SiPh) integrated micro-ring resonator (MRR). We experimentally demonstrate two different functional arrangements of these devices: first, we show that MRR weight banks can be used in conjunction with the spiking VCSEL-neurons to perform amplitude weighting of sub-ns optical spiking signals. Second, we show that a continuously firing VCSEL-neuron can be directly modulated using a locking signal propagated through a single weighting MRR, and we utilise this functionality to perform optical spike firing rate-coding via thermal tuning of the MRR. Given the significant track record of both integrated weight banks and photonic VCSEL-neurons, we believe these results demonstrate the viability of combining these two classes of devices for use in functional neuromorphic photonic systems.

We report experimental and simulation results of a weighting scheme that encodes the weight imparted on an RF signal in its modulation frequency. This scheme significantly increases the multiply-accumulate compute density of microring-based Photonic Neural Networks and enables the implementation of large weight matrices.

In this talk, we report resonance tuning of a silicon nitride microring resonator structure using photochromic molecules. A slot waveguide structure and back-end compatible light molecule evaporation are used to enhance interaction of the molecules and optical mode. The device is interrogated in the optical C-band where the molecules exhibit low optical loss, but where a change in refractive index is present. Under UV illumination the resonance is observed to redshift, while under visible illumination the resonance blueshifts. Furthermore, the observed index shift is seen to be non-volatile. This constitutes a new way to optically reversibly trim and reconfigure high index contrast photonic integrated circuits for which a plethora of applications have been investigated recently.

Analog photonic information processing can be implemented with low chip area using wavelength-division multiplexed systems, which typically manipulate light using micro-ring resonators. Micro-rings are uniquely susceptible to thermal crosstalk, with negative system performance consequences if not addressed. Existing thermal sensitivity mitigation methods face drawbacks including high complexity, high latency, high digital and analog hardware requirements, and CMOS incompatibility. Here, we demonstrate a passive thermal desensitization mechanism for silicon micro-ring resonators exploiting self-heating resulting from optical absorption. We achieve a 49% reduction in thermal crosstalk sensitivity and 1 µs adaptation latency using a system with no specialized micro-ring engineering, no additional control hardware, and no additional calibration. Our theoretical model indicates the potential for significant further desensitization gains with optimized micro-ring designs. Self-heating desensitization can be combined with active thermal stabilization to achieve both responsiveness and accuracy or applied independently to thermally desensitize large photonic systems for signal processing or neural network inference.

Controlling changes in the optical properties of photonic devices allows photonic integrated circuits (PICs) to perform useful functions, leading to a large breadth of applications in communications, computing, and sensing. Many mechanisms to change optical properties exist, but few allow doing so in a reversible, non-volatile manner. Without such mechanisms, power inefficiencies and use of external memory are inevitable. In this work, we propose and experimentally demonstrate reversible, non-volatile phase actuation of a silicon nitride PIC with thermally stable photochromic organic molecules vapor-deposited within a slot waveguide structure. The use of a high-core-index platform allows the photochemical phase actuation of a planar-resonator-based photonic memory unit, which enables positive and negative signal weighting and permits integrated spectroscopic analysis. We show properties of this all-optical memory for a silicon photonics platform, including low loss in the optical C-band, first-order photokinetics of the photoconversion, bidirectional scalable switching, and continuous tuning. Such features are critical for memories in analog applications such as quantum, microwave, and neuromorphic photonics, where bipolar weights, low loss, and precision are paramount. More generally, this work suggests that back-end-of-line-compatible vapor deposition of organic molecules into silicon photonic circuits is promising to introduce non-silicon-native functionality. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

In this work, we present an optical spike processing architecture based on the combined operation of two types of photonic systems: silicon photonics (SiPh) microring resonator (MRR) weight banks [1] and all-optical spiking artificial neurons based on vertical cavity surface emitting lasers (VCSELs) [2]. These systems have been previously demonstrated as key-enabling building blocks in the rapidly growing field of neuromorphic photonics.

In electronic circuits, memristors have been defined as resistors whose resistance depends on past signals. Such elements have promise as low-power weighting and self-learning elements in electronic neuromorphic circuits. Photonic memristors, elements whose transmission depends on past optical signals, are experiencing renewed study alongside the rise in interest in neuromorphic photonics. One potential route to creating photonic memristors involves incorporating photochromic materials, whose optical properties continuously change with optical illumination, into photonic integrated circuits (PICs). In this manuscript we lay out a theoretical model to study the transmission dynamics of devices incorporating photochromic compounds into SiN planar microring resonators which utilize slot waveguide structure, and show that such devices fulfill the criteria for memristive behaviour. This represents a practical path towards incorporating photonic memristors into a technologically mature material platform with minimal additional fabrication processes.

Spiking neurons and neural networks constitute a fundamental building block for brain-inspired computing, which is posed to benefit significantly from photonic hardware implementations. In this work, we experimentally investigate an interconnected system based on an ultrafast spiking VCSEL-neuron and a silicon photonics (SiPh) integrated micro-ring resonator (MRR) weight bank, and demonstrate two different functional arrangements of these devices. First, we show that MRR weightbanks can be used in conjuction with the spiking VCSEL-neurons to perform amplitude weighting of sub-ns optical spiking signals. Second, we show that a continuous firing VCSEL-neuron can be directly modulated using a locking signal propagated through a single weighting micro-ring, and we utilize this functionality to perform optical spike firing rate-coding via thermal tuning of the micro-ring resonator. Given the significant track record of both integrated weight banks and photonic VCSEL-neurons, we believe these results demonstrate the viability of combining these two classes of devices for use in functional neuromorphic photonic systems.

We propose a device composed of stacked thin film optical microcavities to perform compact reconfigurable weighting of wavelength division-multiplexed (WDM) signals. We validate this concept through transfer-matrix simulations of a concrete system composed of rugate filters and phase-change thin films targeting near infrared optical signals.

Neuromorphic photonic processors based on resonator weight banks are an emerging candidate technology for enabling modern artificial intelligence (AI) in high speed analog systems. These purpose-built analog devices implement vector multiplications with the physics of resonator devices, offering efficiency, latency, and throughput advantages over equivalent electronic circuits. Along with these advantages, however, often come the difficult challenges of compensation for fabrication variations and environmental disturbances. In this paper, we review sources of variation and disturbances from our experiments, as well as mathematically define quantities that model them. Then, we introduce how the physics of resonators can be exploited to weight and sum multiwavelength signals. Finally, we outline automated design and control methodologies necessary to create practical, manufacturable, and high accuracy/precision resonator weight banks that can withstand operating conditions in the field. This represents a road map for unlocking the potential of resonator weight banks in practical deployment scenarios.

Photonic systems have seen a recent explosion of investigation for neuromorphic engineering and the execution of machine learning models, owing to the advantages of optics for communications and performing linear operations. Here, we present a novel architecture for executing reconfigurable multiwavelength photonic multiply-accumulate (MAC) operations based on all-solid-state vertically-integrated tunable cavities. We simulate this weighting action through full transfer-matrix calculations of a realistic candidate filter stack. By efficiently leveraging the out-of-plane dimension, we form a conceptual ‘smart pixel’ device that can achieve higher spectral channel count per area, or equivalently computational density, than comparable subpixel architectures and planar integrated photonic devices. While this technology is of use for neuromorphic photonic information processing, its usefulness extends to applications in sensing and communications by covering, for instance, high spatial resolution hyperspectral filters and reconfigurable routing.

Due to its ability to selectively excite fluorophores near a substrate, Total Internal Reflection Fluorescence (TIRF) microscopy has gained a prominent role in biological imaging and is particularly well-suited for cell membrane studies and in vitro single molecule assays. Similarly, a highly inclined laminated optical sheet (HILO) has been used for high S/N imaging away from the glass-water interface. Although rapid azimuthal scanning of the laser beam has been shown to confer certain advantages, namely fringe reduction and better uniformity of illumination, the effects of optical design on field-of-view and TIRF quality has not been systematically studied. Using commercial ray tracing software, we demonstrate how various choices in the optical system design affect each of these parameters. Using these simulations as a guide, we have built a simple circular scanning microscope for TIRF and HILO imaging using a standard inverted microscope, an XY galvanometer scanner and inexpensive lab-built driver electronics and software. Microscope design was optimized to provide a large field of view without compromising TIRF quality and the performance is demonstrated under demanding conditions (high background fluorescence). Finally, we demonstrate that circle-scanned TIRF is successful for a wide range of applications, including live-cell studies, single molecule assays and super-resolution microscopy.