大学物理 ›› 2026, Vol. 45 ›› Issue (08): 108-.doi: 10.16854/j.cnki.1000-0712.250568

• AI赋能 智教新探 • 上一篇    下一篇

人工智能赋能微纳光学器件设计能力培养

柴真,刘婧双,李青原,黄馨瑶   

  1. 1.北京航空航天大学 仪器科学与光电工程学院,北京100191;2. 北京航空航天大学 大科学装置研究院,北京100191;
    3. 北京航空航天大学 物理学院,北京102206
  • 收稿日期:2025-10-11 接受日期:2025-12-19 出版日期:2026-10-10 发布日期:2026-10-20
  • 作者简介:柴真(1990—),女,河南开封人,北京航空航天大学仪器科学与光电工程学院副研究员,博士,主要从事芯片化量子传感器、微纳光学及器件.

  • 基金资助:
    北京航空航天大学2025年校级教育教学改革研究项目(JGXY2025054C)资助

design capabilities in micronano optical devices

CHAI Zhen1,2, LIU Jingshuang1,2, LI Qingyuan1, HUANG Xinyao3   

  1. 1. School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China;
    2. Institute of LargeScale Scientific Facility, Beihang University, Beijing 100191, China;
    3. School of Physics, Beihang University, Beijing 102206, China
  • Received:2025-10-11 Accepted:2025-12-19 Online:2026-10-10 Published:2026-10-20

摘要: 在量子传感器领域的微纳光学器件设计中,现有研究生培养体系普遍存在跨学科知识壁垒、理论-实践转化困难的问题.针对这些痛点,本文提出了一种人工智能赋能的“设计-仿真-优化”闭环式、项目驱动型量子传感器专业研究生创新能力培养模式.该模式以解决真实科研问题为导向,引导学生利用人工智能算法进行微纳光学器件的设计与优化.本文以一项“基于深度学习的相位调控超透镜设计”的研究生课题为实践案例,指导学生逐步利用深度学习实现对超透镜的设计与优化.实践结果表明,该培养模式不仅可以有效提升学生在面对复杂工程问题时的跨学科能力与系统性思维,更提升其科研创新效率,为数智时代量子技术领域培育高水平人才提供了思路.


关键词: 量子传感, 人工智能, 微纳光学器件设计, 教学模式创新

Abstract: In the field of quantum sensing, the design of micronano optical devices in graduate education is often hindered by interdisciplinary barriers and difficulties in bridging theory and practice. To address these challenges, this paper proposes an AIenabled, projectdriven training model that integrates “designsimulationoptimization” in a closed loop. The model orients students toward real research problems and guides them in applying AI algorithms to the design and optimization of micronano optical devices. A case study on deep learningbased phase modulation metasurface lens design illustrates how students progressively employ deep learning for device design and optimization. Results show that this approach enhances interdisciplinary competence, systems thinking, and research efficiency, thereby offering a pathway for cultivating highlevel talent in quantum technologies in the era of digital intelligence.


Key words: quantum sensing, artificial intelligence, micronano optical device design, innovation in teaching models