Related papers: Scaling on-chip photonic neural processors using a…
Plastic self-adaptation, nonlinear recurrent dynamics and multi-scale memory are desired features in hardware implementations of neural networks, because they enable them to learn, adapt and process information similarly to the way…
There exists a significant scale gap between photonic neural network integrated chips and neural networks, which hinders the deployment and application of photonic neural network. Here, we propose hardware-aware lightweight spiking neural…
Polymers have appealing optical, biochemical, and mechanical qualities, including broadband transparency, ease of functionalization, and biocompatibility. However, their low refractive indices have precluded wavelength-scale optical…
We demonstrate an integrated photonic circuit based on feed forward photonic meshes that can be programmed and reconfigured to perform arbitrary spectral filter functions. We investigate a subset of the available filter functions,…
Programmable optical neural networks (ONNs) can offer high-throughput and energy-efficient solutions for accelerating artificial intelligence (AI) computing. However, existing ONN architectures, typically based on cascaded unitary…
We present waveguides with photonic crystal cores, supporting energy propagation in subwavelength regions with a mode structure similar to that in telecom fibers. We design meta-materials for near-, mid-, and far-IR frequencies, and…
Programmable photonic integrated circuits (PPICs) offer a versatile platform for implementing diverse optical functions on a generic hardware mesh. However, the scalability of PPICs faces critical power consumption barriers. Therefore, we…
Deep neural networks with applications from computer vision and image processing to medical diagnosis are commonly implemented using clock-based processors, where computation speed is limited by the clock frequency and the memory access…
A hallmark of biological intelligence is neural reuse,the ability to preserve past learning and repurpose it for new tasks and changing environments. Photonic neural hardware offers high-bandwidth, low-latency computation, but current…
We present an optical circuit switch design for programmable integrated photonics (PIPs). Our solution finds the correct and optimal set of matchings that provides all-to-all network connectivity and demonstrates scalability to 32 ports.
Optical interconnects are the most promising solution to address the data-movement bottleneck in data centers. Silicon microdisks, benefiting from their compact footprint, low energy consumption, and wavelength division multiplexing (WDM)…
Spiking neural networks (SNN) provide a new computational paradigm capable of highly parallelized, real-time processing. Photonic devices are ideal for the design of high-bandwidth, parallel architectures matching the SNN computational…
Photonic integrated circuits utilize planar waveguides to process light on a chip, encompassing functions like generation, routing, modulation, and detection. Similar to the advancements in the electronics industry, photonics research is…
Efficient on-chip integration of single-photon emitters imposes a major bottleneck for applications of photonic integrated circuits in quantum technologies. Resonantly excited solid-state emitters are emerging as near-optimal quantum light…
On-chip implementation of optical nonlinear activation functions (NAFs) is essential for realizing large-scale photonic neural chips. To implement different neural processing and machine learning tasks with optimal performances, different…
Photonic Neural Network implementations have been gaining considerable attention as a potentially disruptive future technology. Demonstrating learning in large scale neural networks is essential to establish photonic machine learning…
Wireless Network-on-Chip (WNoC) appears as a promising alternative to conventional interconnect fabrics for chip-scale communications. The WNoC paradigm has been extensively analyzed from the physical, network and architecture perspectives…
The ever-increasing demand for processing data with larger machine learning models requires more efficient hardware solutions due to limitations such as power dissipation and scalability. Optics is a promising contender for providing lower…
Integrated photonics computing has emerged as a promising approach to overcome the limitations of electronic processors in the post-Moore era, capitalizing on the superiority of photonic systems. However, present integrated photonics…
Integrated nanophotonic biosensors offer a promising route toward future biomedical detection applications that may enable inexpensive, portable, and sensitive diagnosis of diseases with a small amount of biological samples for convenient…