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Fun Data Challenge – Mysterious X-Rays from Cygnus X-3 (Intro)
Monday September 7 @ 6:30 PM - 7:00 PM
A fun data challenge exploring real x-ray data from the mysterious Cygnus X-3 binary system deep in space.
Practice your Python, data exploration and research skills!
This is a two-part event:
Monday 7th 6.30pm to 7.00pm – Introduction to the challenge, getting the Python notebook up and running, accessing and exploring the data.
Monday 14th 6.30pm to 7.30pm – Sharing what we found, problems we found, interesting ideas we explored, … and one pattern that was found in the data (and how).
Cygnus X-3? is a mysterious object in deep space. It behaves in ways different to standard objects, like stars, and we don’t know exactly why.
There is lots of evidence that Cygnus X-3 is a binary system. That means there are two objects orbiting around each other.
Astronomers and scientists try to work out what an object is by looking at the radiation that reaches us on Earth or satellites orbiting Earth. Cygnus X-3 is one of the strongest sources of X-rays in the galaxy.
We’ll be looking at some X-Ray data from Cygnus X-3 to see if we can find any pattern or useful information.
This challenge is your chance to practice your python and data exploration skills. You’ll have the chance to do the same detective work that real astrophysicists do as they try to unlock puzzling data from space missions.
The challenge has easy elements, but the main task is not so easy. During the week between the introduction and sharing of solutions/ideas feel free to discuss ideas and problems in the group chat.
If you’re a very new beginner, this challenge is a very good way to learn about Python notebooks, using data frames, manipulating data and visualising it, and also finding and using the many data analytics libraries – just like real data scientists do.
The Google Meet video chat links is as follows. You shouldn’t need to install any software or plugins – it works in all modern browsers:
The step-by-step guide to getting your Python notebooks up and running, accessing the data, and visualising it is here: