Quantumnas: Noise-adaptive search for robust quantum circuits
Quantum noise is the key challenge in Noisy Intermediate-Scale Quantum (NISQ)
computers. Previous work for mitigating noise has primarily focused on gate-level or pulse …
computers. Previous work for mitigating noise has primarily focused on gate-level or pulse …
Design automation of photonic resonator weights
Neuromorphic photonic processors based on resonator weight banks are an emerging
candidate technology for enabling modern artificial intelligence (AI) in high speed analog …
candidate technology for enabling modern artificial intelligence (AI) in high speed analog …
Light in ai: toward efficient neurocomputing with optical neural networks—a tutorial
In the post Moore's era, conventional electronic digital computing platforms have
encountered escalating challenges to support massively parallel and energy-hungry …
encountered escalating challenges to support massively parallel and energy-hungry …
Parity–time symmetric optical neural networks
H Deng, M Khajavikhan - Optica, 2021 - opg.optica.org
Optical neural networks (ONNs), implemented on an array of cascaded Mach–Zehnder
interferometers (MZIs), have recently been proposed as a possible replacement for …
interferometers (MZIs), have recently been proposed as a possible replacement for …
Neurolight: A physics-agnostic neural operator enabling parametric photonic device simulation
Optical computing has become emerging technology in next-generation efficient artificial
intelligence (AI) due to its ultra-high speed and efficiency. Electromagnetic field simulation is …
intelligence (AI) due to its ultra-high speed and efficiency. Electromagnetic field simulation is …
Integrated multi-operand optical neurons for scalable and hardware-efficient deep learning
Optical neural networks (ONNs) are promising hardware platforms for next-generation
neuromorphic computing due to their high parallelism, low latency, and low energy …
neuromorphic computing due to their high parallelism, low latency, and low energy …
[HTML][HTML] Tempo: efficient time-multiplexed dynamic photonic tensor core for edge AI with compact slow-light electro-optic modulator
M Zhang, D Yin, N Gangi, A Begović, A Chen… - Journal of Applied …, 2024 - pubs.aip.org
Electronic–photonic computing systems offer immense potential in energy-efficient artificial
intelligence (AI) acceleration tasks due to the superior computing speed and efficiency of …
intelligence (AI) acceleration tasks due to the superior computing speed and efficiency of …
Integrated plasmonic full adder based on cascaded rectangular ring resonators for optical computing
A novel and integrated plasmonic full adder based on cascaded rectangular ring resonators
for optical computing is presented. This full adder consists of cascaded rectangular ring …
for optical computing is presented. This full adder consists of cascaded rectangular ring …
Physics-aware differentiable discrete codesign for diffractive optical neural networks
Diffractive optical neural networks (DONNs) have attracted lots of attention as they bring
significant advantages in terms of power efficiency, parallelism, and computational speed …
significant advantages in terms of power efficiency, parallelism, and computational speed …
SqueezeLight: A multi-operand ring-based optical neural network with cross-layer scalability
Optical neural networks (ONNs) are promising hardware platforms for next-generation
artificial intelligence acceleration with ultrafast speed and low-energy consumption …
artificial intelligence acceleration with ultrafast speed and low-energy consumption …