旋光法
计算机科学
代表(政治)
穆勒微积分
极化(电化学)
光子学
对象(语法)
点(几何)
光学
物理
人工智能
数学
散射
几何学
政治
政治学
法学
化学
物理化学
作者
Chao He,Jintao Chang,Patrick S. Salter,Yuanxing Shen,Ben Dai,Pengcheng Li,Yihan Jin,Samlan Chandran Thodika,Mengmeng Li,Tariq Aziz,Jingyu Wang,Jacopo Antonello,Yang Dong,Ji Qi,Jianyu Lin,Daniel S. Elson,Min Zhang,Honghui He,Hui Ma,Martin J. Booth
出处
期刊:Advanced photonics
[SPIE - International Society for Optical Engineering]
日期:2022-03-10
卷期号:4 (02)
被引量:57
标识
DOI:10.1117/1.ap.4.2.026001
摘要
Advances in vectorial polarization-resolved imaging are bringing new capabilities to applications ranging from fundamental physics through to clinical diagnosis. Imaging polarimetry requires determination of the Mueller matrix (MM) at every point, providing a complete description of an object’s vectorial properties. Despite forming a comprehensive representation, the MM does not usually provide easily interpretable information about the object’s internal structure. Certain simpler vectorial metrics are derived from subsets of the MM elements. These metrics permit extraction of signatures that provide direct indicators of hidden optical properties of complex systems, while featuring an intriguing asymmetry about what information can or cannot be inferred via these metrics. We harness such characteristics to reveal the spin Hall effect of light, infer microscopic structure within laser-written photonic waveguides, and conduct rapid pathological diagnosis through analysis of healthy and cancerous tissue. This provides new insight for the broader usage of such asymmetric inferred vectorial information.
科研通智能强力驱动
Strongly Powered by AbleSci AI