The increasing sophistication of research and data quality has revealed a complex interplay between the internal and external environments of galaxies. While galaxies are demonstrably connected to their cosmic ecosystems, their interiors are also comprised of diverse components with intricate interactions, forming a "galaxy ecosystem". Stars and the interstellar medium (ISM) are two crucial constituents of this ecosystem, engaging in a complex interaction. Stars form within the densest and coldest ISM, and their feedback processes influence the physical and chemical properties of the ISM. Therefore, understanding the interaction between stars and the ISM is paramount for understanding galaxy formation and evolution. Despite recent advancements in observational instrumentation that have yielded vast datasets, the direct comparison between observations and theoretical models (including simulations) is often hampered by ubiquitous and non-trivial observational effects. Consequently, developing customized methods to bridge the gap between observation and theory is fundamental to unlocking the full potential of observational data. In talk, speaker will present his recent works on the star-ISM interaction and the connection between observation and theory. Specifically, it will include: case study of shocked clouds at extremely high spatial resolution (~1000 au), the origin of gas-rich quenched regions and feedback from low mass evolved stars, regression techniques for handling astronomical data with complex behavior, and post-processing of hydrodynamic simulations.
BIO
Tao Jing (荆韬) graduated from Xiamen University in 2020. He is currently a PhD student at Tsinghua University. His research focuses on stellar populations, the interstellar medium, and their interactions. He is also interested in developing statistical methods for analyzing astronomical data and applying machine learning techniques to astrophysical problems.
