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21	21	The decays of the pseudoscalar resonances eta and eta' may play a crucial role in refining theoretical predictions for g_mu - 2, which is one of the significant discrepancies between the Standard Model of Particle Physics and experimental measurements. Notably, the decay eta' -> mu mu has not yet been observed. Achieving this observation would be a landmark accomplishment for the field and the experiment that accomplishes it.
22	22	Current analysis of data collected by the LHCb experiment at CERN shows promising signs of observing evidence of this decay with a significance greater than 3 sigmas. Improving this sensitivity could significantly benefit from a more effective multivariate classifier, which can better differentiate between background-like and signal-like data. This project aims to fine-tune the classifier to achieve optimal performance.
23	23	For this, we will be trying with different input variables in the dataset, testing how much each one contributes to the overall result. We will also fine-tune the hyperparameters of the training algorithm using the Python optimization framework Optuna, which allows us to efficiently test different strategies and choose the best result.
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	27	+=== Neural networks for LLP discovery
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	30	+LLPs are an exciting avenue to discover new physics, but they are also known to be very challenging to detect, specifically in the context of hadronic colliders with large backgrounds. Detectors such as LHCb have been trying to find one of such particles, with no success so far.
	31	+In this project we will make use of the capabilities of Neural Networks, which can deal with high-dimensional feature spaces, to make the most of the information provided by the detector.