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We demonstrate voltage-tunable thermo-optic bi- and tri-stability in silicon photonic microring resonators with lateral p-i-n junctions and present a technique for characterizing the thermo-optic transient response of integrated optical…
Micro- and nanothermometry enable precise temperature monitoring and control at the micro- and nanoscale, and have become essential diagnostic tools in applications ranging from high-power microelectronics to biosensing and nanomedicine.…
Complete and textured 3D reconstruction of dynamic scenes has been facilitated by mapped RGB and depth information acquired by RGB-D cameras based multi-view systems. One of the most critical steps in such multi-view systems is to determine…
Nanoscale thermometry is paramount to study primary processes of heat transfer in solids and is a subject of hot debate in cell biology. Here we report ultrafast temperature sensing using all-optical thermometry exploiting synthetic…
Microresonator frequency combs (microcombs) hold great potential for precision metrology within a compact form factor, impacting a wide range of applications such as point-of-care diagnostics, environmental monitoring, time-keeping,…
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…
We demonstrate narrowband orthogonally polarized optical RF single sideband generation as well as dual-channel equalization based on an integrated dual-polarization-mode high-Q microring resonator. The device operates in the optical…
Photonic integrated circuit devices can be used as refractometric opto-fluidic sensors to detect the presence of analytes in solution at low concentrations. In this work, we investigate the refractive index sensitivity of silicon nitride…
Photonic signal processing is essential in the optical communication and optical computing. Numerous photonic signal processors have been proposed, but most of them exhibit limited reconfigurability and automaticity. A feature of fully…
Photonic neuromorphic computing offers compelling advantages in power efficiency and parallel processing, but often falls short in realizing scalable nonlinearity and long-term memory. We overcome these limitations by employing silicon…
Neural networks have proven effective for solving many difficult computational problems. Implementing complex neural networks in software is very computationally expensive. To explore the limits of information processing, it will be…
A multi-bit digital weight cell for high-performance, inference-only non-GPU-like neuromorphic accelerators is presented. The cell is designed with simplicity of peripheral circuitry in mind. Non-volatile storage of weights which eliminates…
We report the development of an ultrasensitive optomechanical sensor designed to improve the accuracy and precision of force measurements with atomic force microscopy. The sensors reach quality factors of 4.3x10^6 and force resolution on…
Neuromorphic hardware facilitates rapid and energy-efficient training and operation of neural network models for artificial intelligence. However, existing analog in-memory computing devices, like memristors, continue to face significant…
Deep Neural Networks (DNNs) have gained immense success in cognitive applications and greatly pushed today's artificial intelligence forward. The biggest challenge in executing DNNs is their extremely data-extensive computations. The…
Photonic technologies are emerging as powerful enablers for neuromorphic computing by delivering ultrafast and energy efficient neural functionalities. In this work, we propose and demonstrate a novel all-optical dual micro ring resonator…
Deep neural networks have been demonstrated impressive results in various cognitive tasks such as object detection and image classification. In order to execute large networks, Von Neumann computers store the large number of weight…
We demonstrate first experimental investigation on the performance of a single-node reservoir computer based on a silicon microring resonator (MRR) operating on the digit recognition task. The input layer of the reservoir is composed of a…
In an effort to compete with the brain's efficiency at processing information, neuromorphic hardware combines artificial synapses and neurons using mixed-signal circuits and emerging memories. In ferroelectric resistive weights, the…
We present the required techniques for the successful low loss packaging of integrated photonic devices capable of operating down to 970 mK utilizing photonic wire bonds. This scalable technique is shown to have an insertion loss of less…