University of PennsylvaniaBīnxīfǎníyà Dàxué宾夕法尼亚大学researchersyánjiū rényuán研究人员to make use of / to harnesslìyòng利用light-matterguāng wùzhì光物质hybridhùnhé混合particlelìzǐ粒子significantly / by a large margindàfú大幅to improve / to boosttíshēng提升artificial intelligencerén gōng zhìnéng人工智能computing / calculationjìsuàn计算efficiencyxiàolǜ效率。
May 19, 2026 at 8:00 AM
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Science & TechnologyPenn Researchers Harness Light-Matter Hybrid Particles to Boost AI Computing Efficiency
Physicists at the University of Pennsylvania have created a hybrid light-matter particle that enables AI optical signal switching at extremely low energy, potentially replacing conventional electronic computing steps.
University of Pennsylvania physicists have published their latest research findings in Physical Review Letters.
The research team directed light into nanoscale cavities, causing it to interact with atomic-scale thin materials, thereby producing exciton-polaritons.
These hybrid particles combine the speed of light with the interactivity of matter, enabling optical signal switching.
During testing, this switching operation consumed only about 4 femtojoules of energy, far lower than existing electronic devices.
Currently, many photonic AI chips still need to convert optical signals back to electronic signals when performing nonlinear activation steps, significantly reducing the efficiency advantages of photonic computing.
The novel exciton-polaritons technology promises to solve this bottleneck, enabling the entire computing process to operate at light speed.
The project is led by University of Pennsylvania physicist Bo Zhen, whose team focuses on photonic and quantum materials research.
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