(ANSA) – ROME, APRIL 26 – An international group of scientists, including some from the National Institute of Astrophysics (INAF), has used artificial intelligence to measure the size of galaxies up to about seven billion light years away from the Land. It is the first time that this technique has been applied to data collected from Earth, demonstrating that neural networks are much faster and more accurate than traditional techniques and represent the future for measuring astronomical objects in observation campaigns over large portions of the sky.
Like real “galactic tailors”, the researchers – coordinated by Nicola R. Napolitano, full professor at Sun Yat-sen University (China) – have developed a convolutional neural network to determine the structural parameters of galaxies, in particular the their size. The neural network has the advantage of “measuring” these quantities much faster than traditional methods, which rely on slower computational techniques. It is a fundamental tool for analyzing the enormous amount of data that will arrive in the future from telescopes such as Rubin and Euclid, which will observe a third of the entire celestial vault. The results of this research were published today in The Astrophysical Journal. “Just as a tailor has the eye and the experience to determine a person’s size and then make the perfect suit, so the astronomer needs to know the shape and size of galaxies, which are crucial information to understand their structure. and reconstruct the models to explain their evolutionary history “, says Crescenzo Tortora, researcher at INAF in Naples and co-author of the article. The neural network at the center of this study is called GaLNet (GAlaxy Light profile convolutional neural NETwork). (HANDLE).
Source: Ansa
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