Chattopadhyay, UtsaUtsaChattopadhyayCarstens, FlorianFlorianCarstensWienke, AndreasAndreasWienkeHartl, IngmarIngmarHartlAy, NihatNihatAyHeyl, ChristophChristophHeylTünnermann, HenrikHenrikTünnermann2025-09-242025-09-242025Conference on Lasers and Electro Optics Europe and European Quantum Electronics Conference, CLEO 20259798331512521https://hdl.handle.net/11420/57555Ultrafast laser systems critically depend on optical thin film coatings to control dispersion and light propagation, enabling precise shaping of light. Optical thin film coating design represents a complex inverse problem traditionally relying on computationally intensive numerical optimization methods. These conventional approaches, exemplified by the widely used Needle Algorithm [1], require significant computational resources and often rely on expert intervention [2]. We here propose a new approach to these challenges and present a physics-informed machine learning framework based on an autoencoder architecture and use it to design an ultra-broadband dispersive mirror.enComputer Science, Information and General Works::006: Special computer methods::006.3: Artificial IntelligenceTechnology::621: Applied Physics::621.3: Electrical Engineering, Electronic EngineeringConference Paper10.1109/CLEO/EUROPE-EQEC65582.2025.11110889Conference Paper