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Research

My main research focus is to understand the nature of dark matter. For this, I work in the intersection between particle physics and cosmology, modelling and analyzing data from the Large Hadron Collider, and comparing it to cosmological observations from other experiments. In my research, I also use various scientific computing techniques, mainly artificial intelligence models, to try to explain and predict new results.

In the following I provide a summary of my main research projects and a list of selected publications.

Projects

  • 🔝 Measurement of t \bar t production cross section

    We aim to measure the t \bar t \to Z cross section performing a maximum likelihood fit on the output distribution of a DNN using a Python framework for NanoAODs datafiles. This analysis are being performed in two parts, tackling both dileptonic and semileptonic t\bar t decay channels. We use data from LHC Run 2 (138 fb^−1) as well as from Run 3.

    Analysis GitLab (CERN internal)

  • MACAXEIRA - A ML Framework

    The MACAXEIRA framework is being developed to help physicists to train ML models in a easier way, from .root or .h5 datafiles, straight to parameter optimization and likelihood fits of the model. It’s well parallelized and work fine in HPC environments through HTCondor or SLURM.

    Framework Repository (CERN internal)

  • AxiTop

    The main scientific objective of this research is the search for the production of axion-like particles from proton-proton collisions at \sqrt{s} = 13.6 TeV at the CERN LHC, using the data collected by the CMS detector. In summary, we propose to use LHC Run 3 data to search for axion-like particles as a viable DM candidate in production and decay that was never explored before experimentally. The success of the project relies on innovative analysis techniques to tackle the triggering, signal reconstruction, and estimation of background processes, through a joint effort of UGent and UNESP.

    Reference

  • DM resonance production in the s-channel

    The search for new mediators within the dark sector in accelerators, such as LHC, aims to evaluate the data for new interactions, where processes of new physics, if observed, must incorporate cosmological and astrophysical constraints to be identified as originating from DM. This research investigates a simplified interaction model, which aligns with current SM physics but introduces a new spin-1 and spin-0 mediator to interact with three potential particles that could constitute some or all of the DM relic abundance in the Universe.

    Part of the code used in this research is avaible on my GitHub

Papers

  • Resonant production of vector dm states characterized by monophoton isr at high-energy colliders. de SOUZA, M. & SILVEIRA, G. G. (2024). Brazilian Journal of Physics, 54(5). DOI: 10.1007/s13538-024-01545-4

  • Investigation of scalar and fermion dark matter in mono-photon production at high-energy colliders. de SOUZA, M. & SILVEIRA, G. G. (2023). Eur. Phys. J. C, 84(2), 181. DOI: 10.1140/epjc/s10052-024-12528-9.

  • Investigation of spin-dependent dark matter in mono-photon production at high-energy colliders.de Souza, M. & SILVEIRA, G. G. (2023). E-print: arXiv:2308.03680

  • Investigation of the nature of a massive vector mediator for dark matter through e^+e^- collisions. MATEUS, Marcio, & da SILVEIRA, G. G. [Gustavo Gil]. (2021). Astron. Nachr., 342(1-2), 411–415. DOI: 10.1002/asna.202113943

PhD Thesis

  • Resonant dark matter production through a new spin-1 massive mediator. de Sousa Mateus Junior, M. (2024). Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil. Retrieved from https://www.lume.ufrgs.br/handle/10183/276460

Master Dissertation

  • Investigação da natureza de um mediador vetorial massivo para a matéria escura por meio de colisões e^+e^-. JUNIOR, M. de S. M.; SILVEIRA, G. G. da. MSc. Dissertation — Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil, 2020. Avaible at: https://lume.ufrgs.br/handle/10183/211546 (🇧🇷 PT-BR).