ABSTRACT: Blurred reflection features are commonly observed in the X-ray spectra of accreting black holes. In the presence of high-quality data and with the correct astrophysical model, X-ray reflection spectroscopy can be a powerful tool to probe the strong gravity region of black holes, study the morphology of the accreting matter, measure black hole spins, and even test Einstein's theory of General Relativity in the strong field regime. In the pastyears, there has been significant progress in the development of the analysis of these reflection features, thanks to both more sophisticated theoretical models and new observational data. However, the next generation of X-ray missions (e.g. eXTP, Athena, HEX-P) promises to provide unprecedented high-quality data, which will necessary require more accurate synthetic reflection spectra than those available today. In this talk, I will review the state-of-the-art in reflection modeling and I will present current efforts to develop a new generation of reflection models based on neural networks.
BIO: Cosimo Bambi is currently Xie Xide Junior Chair Professor at the Department of Physics at Fudan University. He received the Laurea degree from Florence University in 2003 and the PhD degree from Ferrara University in 2007. He worked as a postdoctoral research scholar at Wayne State University, IPMU/The University of Tokyo, and LMU Munich. He joined Fudan University as a faculty member at the end of 2012. His main research interests focus on theoretical and observational studies on black holes. He has published about 200 papers on high impact factor refereed journals as first or corresponding author, he has over 10,000 citations, and his h-index is 55 (Google Scholar). He has published several books with Springer, either as author and editor. He has received a number of awards, including the Magnolia Gold Award (上海市白玉兰荣誉奖) in 2022 and the Magnolia Silver Award (上海市白玉兰纪念奖) in 2018 from the Municipality of Shanghai, the International Excellent Young Scientists Award from the National Natural Science Foundation of China in 2022, and the Xu Guangqi Prize from the Embassy of Italy in Beijing in 2018.