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Title: | Detection of Gravitational Wave signals using Machine Learning methods and Generative Pre-trained Transformers |
Author: | Dana Ruiz, Abel |
Director/Tutor: | Andrade Weber, Tomás Emparan García de Salazar, Roberto A. |
Keywords: | Ones gravitacionals Aprenentatge automàtic Treballs de fi de grau Gravitational waves Machine learning Bachelor's theses |
Issue Date: | Jun-2023 |
Abstract: | We use Machine Learning methods based on Convolutional Neural Networks to search for gravitational waves signals above the background noise distribution for a data set of simulated gravitational waves and real noise signals from three detectors (LIGO Hanford, LIGO Livingston, and Virgo). A training data set is used to train the ML method to classify data streams in two groups: gravitational wave plus noise (label 1) or only noise (label 0). Later, the method predicts if data streams from a testing data set belong to one or an other category. To generate the code that implements the CNN algorithm we use Generative Pre-trained Transformers, specifically ChatGPT based on GPT-3 and compare them to a human-made CNN. The ML methods are capable to detect gravitational waves if we give ChatGPT freedom to create a CNN without specifying the parameters or the architecture, but are not satisfactory if we try to direct ChatGPT to a specific type of code. |
Note: | Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2023, Tutors: Tomás Andrade Weber, Roberto Emparan García de Salazar |
URI: | http://hdl.handle.net/2445/201012 |
Appears in Collections: | Treballs Finals de Grau (TFG) - Física |
Files in This Item:
File | Description | Size | Format | |
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DANA RUÍZ ABEL_7999646.pdf | 448.42 kB | Adobe PDF | View/Open |
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