Summary
Over the last decades, we have established a standard cosmological paradigm by combining the information from complementary cosmological probes. However, many intriguing questions remain to be answered: the nature of dark energy, the driving mechanisms of the cosmic inflation, and masses of neutrinos. In this proposal, I will focus on the cosmological information content of the large-scale structure (LSS) of the Universe. Different physical processes leave their unique imprints on the clustering pattern of LSS at different scales, and N-point statistics act a bridge between the observables and the underlying physics. In the coming years, new large-volume galaxy surveys will probe the LSS of the Universe with exquisite detail. However, traditional analysis methods, based mostly on 2-point statistics alone, are not adequate for these new surveys and must urgently be revised to ensure their full potential. This proposal aims to maximise the information to be extracted from the upcoming surveys. With the Marie-Curie fellowship, I will carry out a consistent joint analysis of the 2- and 3-point statistics, and develop a complementary but simplified treatment of the N-point statistics. These tools will be applied to the new data to constrain the cosmological models, with special focus in understanding the properties of the primordial signatures and models beyond the standard cosmological paradigm. In the outgoing phase, I will work at Univesity of Florida (US) to benefit from the expertise in the leading algorithms to estimate higher-order statistics, their theoretical modelling, and knowledge about high-performance computing. In the incoming phase, I will work at the Max Planck Institute for Extraterrestrial Physics (Germany), I will delve into the data from the real surveys and understand potential systematic errors. With the help of the experts at MPE, the experience and techniques acquired in the US will be applied to the datasets to extract more precise information.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101025187 |
| Start date: | 01-06-2022 |
| End date: | 31-05-2025 |
| Total budget - Public funding: | 264 669,12 Euro - 264 669,00 Euro |
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Original description
Over the last decades, we have established a standard cosmological paradigm by combining the information from complementary cosmological probes. However, many intriguing questions remain to be answered: the nature of dark energy, the driving mechanisms of the cosmic inflation, and masses of neutrinos. In this proposal, I will focus on the cosmological information content of the large-scale structure (LSS) of the Universe. Different physical processes leave their unique imprints on the clustering pattern of LSS at different scales, and N-point statistics act a bridge between the observables and the underlying physics. In the coming years, new large-volume galaxy surveys will probe the LSS of the Universe with exquisite detail. However, traditional analysis methods, based mostly on 2-point statistics alone, are not adequate for these new surveys and must urgently be revised to ensure their full potential. This proposal aims to maximise the information to be extracted from the upcoming surveys. With the Marie-Curie fellowship, I will carry out a consistent joint analysis of the 2- and 3-point statistics, and develop a complementary but simplified treatment of the N-point statistics. These tools will be applied to the new data to constrain the cosmological models, with special focus in understanding the properties of the primordial signatures and models beyond the standard cosmological paradigm. In the outgoing phase, I will work at Univesity of Florida (US) to benefit from the expertise in the leading algorithms to estimate higher-order statistics, their theoretical modelling, and knowledge about high-performance computing. In the incoming phase, I will work at the Max Planck Institute for Extraterrestrial Physics (Germany), I will delve into the data from the real surveys and understand potential systematic errors. With the help of the experts at MPE, the experience and techniques acquired in the US will be applied to the datasets to extract more precise information.Status
SIGNEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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