After completing a joint program (Double DEC) at Collège de Maisonneuve in Science and Social Science, Maria undertook her undergraduate studies in physics at Université de Montréal (2018-2021). She started her master’s degree in September 2021 under the supervision of Julie Hlavacek-Larrondo and Laurence Perreault-Levasseur with Msc Excellence scholarships from IVADO and FRQNT. Her research focuses on the classification and characterization of galaxy clusters. Depending on the distribution of the intracluster gas, galaxy clusters can be classified into cool-core and non cool-core clusters, and interact differently with the supermassive black hole (SMBH) located at their center. The purpose of the project is to develop a machine learning algorithm that will be able to classify X-ray images of galaxy clusters. The neural network will first be trained on simulated images obtained with the Illustris TNG cosmological hydrodynamical simulations. Once trained and validated, the network will be tested on simulated images as well as on Chandra X-ray data. Working directly with Michael McDonald, Professor of Physics at MIT and collaborator on the project, the algorithm will be applied to a sample of 83 galaxy cluster X-ray images that have been previously studied and analyzed by him. Using machine learning algorithms to classify and characterize galaxy clusters, the project aims to analyze the interaction between the cluster and the SMBH and identify how the SMBH impacts the surrounding gas.
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