Using Python to Study Black Holes

03:15 PM - 03:40 PM on July 17, 2016, Room CR4

Daniela Huppenkothen

Audience level:


Black holes are among the most fascinating objects in our universe, with hundreds of hours of astronomical observations available in public archives around the world. In this talk I will give a brief overview of why and how we study black holes. I will show how python helps us make sense of our data, leverage modern data analysis methods efficiently and help us understand how black holes form and the role they play in our universe.


Black holes, first predicted by Einstein's Theory of General Relativity, play an important role in the study of our universe. An ever-improving fleet of space telescopes, such as NASA's Hubble, Chandra and Fermi, has given us unprecedented glimpses in the fundamental physical laws that govern these objects. The data sets we accumulate with these telescopes grow at a fast pace and require new data analysis methods and new software to mine the information hidden in them. Python and its existing ecosystem of numerical software and data analysis tools provides an ideal framework to rise to these new challenges. In this talk I will give a broad overview of how and why we study black holes as well as the methods and software tools used to do so. I will focus on our recent efforts to build Stingray, a new python package for time series analysis for astronomy.