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Last modified by Ricardo Julio Rodríguez Fernández on 2026/06/14 08:33
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1 -Xabier Cid Vidal and María Pereira Martínez
1 +Xabier Cid Vidal and Alejandro Novo Cal
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1 -=== Communicating IGFAE Physics to new audiences ===
2 -==== Supervisor: Manuel Rey Pan
1 +=== Machine Learning for Axion-Like Particles and Quirks Searches at LHCb ===
2 +==== Supervisor: Alejandro Novo Cal
3 3  ====
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5 -This project will explore new ways to communicate IGFAE’s strategic research areas—particle/astroparticle/nuclear physics, as well as Quantum IST, to young audiences. The goal will be to analyse the science communication & outreach on video formats, with some case studies (e.g. CERN, Fermilab, DESY, IFT, among others) to identify which formats, narrative structures and resources are more effective to communicate physics in an engaging way, whilst maintaining academic rigour.
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7 -This analysis will be compared with the IGFAE’s social media activity, with the aim of proposing new ideas & approaches to help improve the Institute’s outreach activities in this area, in line with the 2025–2030 Communication Plan.
5 +The Standard Model requires new theories to explain phenomena such as the universe's baryonic asymmetry or dark matter. Popular proposals include Axion-Like Particles (ALPs) with detectable decay signatures, and exotically signed particles called Quirks that leave characteristic movement patterns in the detectors. The LHCb detector provides the precision needed to study these new particles. In this project, we will develop a Machine Learning algorithm to be applied in a specific search for ALPs and/or Quirks, studying its applicability depending on the mass and lifetime of the ALPs to improve the detection sensitivity of these new physics models.