Machine learning techniques applied to cosmological problems
Phenomenology of the dipolar coupling between dark matter and dark photon
Machine Learning methods for extracting cosmological information
| Grant number: | 19/17182-0 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Start date: | October 01, 2020 |
| End date: | March 31, 2021 |
| Field of knowledge: | Physical Sciences and Mathematics - Physics - Elementary Particle Physics and Fields |
| Principal Investigator: | Oscar José Pinto Eboli |
| Grantee: | Tathagata Ghosh |
| Host Institution: | Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
Abstract In this project, we analyze different Particle Physics facets. We will apply machine learning techniques to the analyses of processes at the Large Hadron Collider (LHC), as well as look for signals of new physics at the LHC. We will also study dark matter signals at the LHC and direct detection experiments. Moreover, we will study the footprints of the baryonic asymmetry in gravitational waves. | |
| News published in Agência FAPESP Newsletter about the scholarship: | |
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