4 papers
When Every Simulation Counts: Value-Based Reinforcement Learning for Accelerated Photonics Inverse Design
Longying Wen, Feiyang Wu, Jinglin Yu +3
Photonic-crystal surface-emitting lasers (PCSELs) can combine high-power operation with narrow-divergence surface emission, but optimizing coupled parameters requires costly full-w…
Reliability-Aware Bayesian Optimization of 1310 nm PCSELs with FDTD Verification
Jinglin Yu, Feiyang Wu, Longying Wen +3
Near 1310 nm photonic-crystal surface-emitting lasers (PCSELs) are attractive narrow-beam sources for optical communication and sensing, but their final design refinement is costly…
LLM4Laser: Large Language Models Automate the Design of Lasers
Renjie Li, Ceyao Zhang, Sixuan Mao +4
With the rapid evolution of global autonomous driving technology, the demand for its core sensing hardware, Light Detection and Ranging (LiDAR), is escalating. As the light source…
What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips
Renjie Li, Wenjie Wei, Qi Xin +7
Large language models (LLMs) are rapidly pushing the limits of contemporary computing hardware. For example, training GPT-3 has been estimated to consume around 1300 MWh of electri…