5 papers
A Machine-Verified Proof of a Quantum-Optimization Conjecture
Uri Kol, Maor Ben-Shahar, Kfir Sulimany +1
We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture that depth- Quantum Approx…
Quantization-aware Photonic Homodyne computing for Accelerated Artificial Intelligence and Scientific Simulation
Lian Zhou, Kaiwen Xue, Amirhossein Fallah +14
Modern problems in high-performance computing, ranging from training and inferencing deep learning models in computer vision and language models to simulating complex physical syst…
Machine Intelligence on Wireless Edge Networks
Sri Krishna Vadlamani, Kfir Sulimany, Zhihui Gao +2
Machine intelligence on edge devices enables low-latency processing and improved privacy, but is often limited by the energy and delay of moving and converting data. Current system…
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency
Zhihui Gao, Sri Krishna Vadlamani, Kfir Sulimany +2
Modern edge devices, such as cameras, drones, and Internet-of-Things nodes, rely on deep learning to enable a wide range of intelligent applications, including object recognition,…
Single-Shot Matrix-Matrix Multiplication Optical Tensor Processor for Deep Learning
Chao Luan, Ronald Davis, Zaijun Chen +2
The ever-increasing data demand craves advancements in high-speed and energy-efficient computing hardware. Analog optical neural network (ONN) processors have emerged as a promisin…