Sparx: Season 1, Episode 3

Machine Learning & Black Holes

Mathematical genius Maximilian Janisch explains how the interplay of mathematics, machine learning and big data makes it possible to take a photo of a black hole 54 million light years away.

How many gigabytes of data does it require to take a photo of a black hole? This question already makes it clear that you can’t just photograph a black hole like that: To capture it as a whole, you would need a telescope the size of our Earth – a seemingly impossible undertaking.

But not when you add machine learning and big data to the maths: Using thousands of partial photos taken by twelve telescopes in different locations around the world, computers were trained to produce an image of the black hole in the middle of the giant galaxy Messier 87 – a galaxy 54 million light years away from Earth. The amount of data for this is immense! To answer the question posed at the beginning: It takes a total of five million gigabytes of data to produce a photo of this black hole.

Prodigy Maximilian Janisch explains in his “Sparx” talk how Albert Einstein laid the foundation for the discovery of black holes in mathematics over 100 years ago and how computer science makes it possible today to put mathematical concepts into practice.


Maximilian Janisch (born in 2003) is a gifted young man, who took the mathematics matura (A-level) at the age of nine and received top marks. Maximilian, born in Switzerland, will complete his Master’s degree in mathematics at the University of Zurich in 2021 at the age of 17. Various appearances on Swiss television have made Maximilian famous in Switzerland. In addition to mathematics, Maximilian is keen on machine learning, Wiener Schnitzel and delivering good work.

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