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http://hdl.handle.net/10609/132789
Title: | Density-based clustering for X-ray source detection on XMM-Newton EPIC-PN data |
Author: | Rico Gómez, Rodrigo |
Director: | Casas-Roma, Jordi |
Tutor: | Ruiz Dern, Laura |
Abstract: | The main purpose of this work is to explore X-ray astronomical data from EPIC cameras on board XMM-Newton observatory by using machine learning techniques. As a result, and depending on the scientific validation, part of the techniques/algorithmts produced could be implemented in future XMM-Newton processing pipeline versions. XMM-Newton is short for X-ray Multi Mirror observatory, and it is one of the main science missions of the European Space Agency. Data collected by XMM-Newton is sent to a complex set of algorithms and calibrations methods resulting in scientific data products elaborated and distributed by XMM-Newton Science Operations Centre. This work is marked in the last stage of data processing. The data treated in the project has been previously processed so the focus is kept on Machine Learning techniques. Although, as this work will be developed in an astronomical environment and cosupervised by ESA scientists, there is a strong astronomical point of view. |
Keywords: | astronomy machine learning clustering XMM-Newton |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 6-Jun-2021 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
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File | Description | Size | Format | |
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rricogoTFM0621memory.pdf | TFM Memory | 27,91 MB | Adobe PDF | View/Open |
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