Quantum support vector machines for aerodynamic classification

Understand

Aerodynamics plays an important role in aviation industry and aircraft design.

• Detecting and minimizing the phenomenon of flow separation from scattered pressure data on airfoil is critical for ensuring stable and efficient aviation.
• However, since it is challenging to understand the mechanics of flow field separation, the aerodynamic parameters are emphasized for the identification and control of flow separation.
• It has been investigated extensively using traditional algorithms and machine learning methods such as the support vector machine (SVM) models.