AI is increasingly enabling the study of cosmic activity. Have you heard of Type Ia supernovae? These are powerful stellar explosions that help astronomers measure distances throughout the universe. So “Riddler” is a new tool we created to help researchers better understand Type Ia supernovae. The tool uses:
Machine LearningThe Riddler uses machine learning to study the spectrum of light – the range of colors emitted by an explosion.
Fitting the modelThese spectra can then be fitted to models based on actual supernova data to help scientists understand the mechanism behind the explosion.
efficiency: This is done more efficiently and accurately than traditional methods.
What is a supernova and why is it important?
These supernovae are known as the explosive events that occur at the end of the life of a white dwarf star, a compact star roughly the mass of the Sun but the size of Earth, that occasionally undergo catastrophic explosions.
These explosions release heavy elements such as calcium and iron, which are essential for life, into space. This is important, but exactly how these explosions happen remains a mystery.
Dr Mark McGehee, from the School of Physics at the University of Warwick, where Riddler was created, explained: “When studying a supernova we analyse its spectrum, which shows the intensity of light at different wavelengths, which is influenced by the elements produced in the supernova. Each element interacts with light at its own wavelength and so leaves its own signature in the spectrum.”
How AI can improve traditional supernova research
The traditional way to analyze supernovae is to create detailed models that compare observational data with theoretical predictions. This is a time-consuming process, with each model taking between 10 and 90 minutes to generate. Researchers often need to compare hundreds or even thousands of these models to fully understand a single supernova event.
Dr. McGehee continues, “In our new research, we move away from this lengthy process: we train a machine learning algorithm on what different types of explosions look like, and then use that to generate models more quickly.”
“Just as we can use AI to generate new artwork or text, now we can use it to generate simulations of supernovae. This means we can generate thousands of models in less than a second, which will give a huge boost to supernova research.”
More about Artificial Intelligence
Using AI in supernova research, scientists can gain a more detailed look at the elements that supernovae release: different types of supernovae produce different amounts of certain elements, which can provide clues about the nature of the explosion and the type of white dwarf star involved.
“Studying the elements released by the supernova is an important step in determining the type of explosion that occurred,” said Dr McGehee. “We can then relate the properties of the explosion to the properties of the supernova's host galaxy, and establish a direct link between how the explosion happened and the type of white dwarf that exploded.”
Will there be further research?
“In the future, we will be able to study a wider range of explosions and supernovae and directly link their characteristics to the properties of the galaxies that host them. Dr. Thomas Kirstein of the University of Turku, who is also involved in the research, spoke about the potential success of achieving and using these advances:
“With our latest survey, we finally have a data set of sufficient size and quality to address some of the key remaining questions in supernova science: how do supernovae explode? Machine learning approaches like this one will enable us to study many more supernovae, in greater detail, and more consistently than previous approaches.”
Main points where this is useful
To summarise how this is good for space technology and research:
Speed and EfficiencyAI will drastically reduce the time required to generate a supernova model from hours to literally seconds.
AccuracyAs the models become more accurate, it becomes easier to determine the true nature of supernova explosions.
Detailed AnalysisThe ability to quickly generate and compare thousands of models opens new avenues for understanding the complex dynamics of supernovae.
