October 10, 2024, by Anna Walter
Photo: UHH/H. fox
Gregor Kasieczka is Professor of Machine Learning in Particle Physics at the University of Hamburg.
This year’s Nobel Prize in Physics goes to John J. Hopkins from Princeton University in the USA and Geoffrey E. Hinton from the University of Toronto in Canada. They are honored for research work that led to the invention of so-called artificial neural networks. Prof. Dr. Gregor Kasieczka explains how research at the Cluster of Excellence Quantum Universe at the University of Hamburg builds on the pioneering work of the two Nobel Prize winners.
“Neural networks are the technology that is used wherever artificial intelligence is developed, for example in chatbots, autonomous cars, AI-generated images or even in automated art and music. Hinton and Hopfield did the preparatory work that made all of this possible,” says Prof. Dr. Gregor Kasiezcka, Professor of Machine Learning in Particle Physics at the University of Hamburg and senior scientist at the Cluster of Excellence Quantum Universe.
Based on neural networks, machine learning has developed explosively in the last fifteen to twenty years. What is less known is that the method has long been important for research. It is used in particular for sorting and analyzing huge amounts of data, such as those generated by the large particle detectors at CERN in Switzerland.
“Machine learning methods help in the search for new particles, because data evaluation based on machine learning proves to be much faster than conventional methods, reduces the computing effort and therefore also saves energy,” explains Kasieczka. Machine learning played a crucial role in the discovery of the Higgs boson in 2012. Similarly, astrophysics also benefits from machine learning when processing data from telescopes. The technology is also used to reduce noise when measuring gravitational waves from colliding black holes.
Basic physical research, such as that carried out at the Cluster of Excellence Quantum Universe at the University of Hamburg, also benefits from the technology. The Cluster of Excellence is all about fundamental questions about the origin, development and composition of the universe. Scientists in the Cluster of Excellence use generative models, for example, to accelerate the simulation of extremely large data sets. Or they use algorithms optimized with the help of neural networks that can filter out interesting events from data chaos in microseconds.
In one Interview with the Tagesschau Gregor Kasieczka provides insights into how the research and inventions of John J. Hopkins and Geoffrey E. Hinton pioneered the development of artificial intelligence and led to its application in modern physics.
