Summary
An epoch of “big data” mining just started for high redshift astronomy. State-of-the-art photometric surveys observed millions of objects on sky, and next-generation telescopes will provide statistically significant samples even for the rarest galaxy types. However, standard techniques (e.g., methods to fit galaxies' spectral energy distribution) are not optimal to analyse this data, preventing a true scientific breakthrough. Indeed some of the most urgent questions in this research field, concerning the evolution of rare ultra-massive galaxies, may remain unsolved. As the Cosmic Dawn Center (University of Copenhagen) is collecting an unprecedented large sample of photometric and spectroscopic data, this is the best time to devise new tools for a full exploitation of such unique observations.
The proposed project will devise an original machine learning software to efficiently extract information from the Cosmic Dawn Survey database, and an advanced statistical analysis will result in unprecedented demographics (e.g., stellar mass function) of high redshift (z>3), massive (>5e10 Msol) galaxies. By interpreting these measurements through theoretical models, the project will shed light on the physical mechanisms driving star formation in such extreme galaxies, which are thought to contain most of the stellar mass in the early universe. Besides the unparalleled data set, the expertise of S. Toft (host supervisor) and the other members of the Cosmic Dawn Center will be crucial to achieve these goals.
The proposed project will devise an original machine learning software to efficiently extract information from the Cosmic Dawn Survey database, and an advanced statistical analysis will result in unprecedented demographics (e.g., stellar mass function) of high redshift (z>3), massive (>5e10 Msol) galaxies. By interpreting these measurements through theoretical models, the project will shed light on the physical mechanisms driving star formation in such extreme galaxies, which are thought to contain most of the stellar mass in the early universe. Besides the unparalleled data set, the expertise of S. Toft (host supervisor) and the other members of the Cosmic Dawn Center will be crucial to achieve these goals.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/896225 |
| Start date: | 26-06-2020 |
| End date: | 25-06-2022 |
| Total budget - Public funding: | 207 312,00 Euro - 207 312,00 Euro |
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Original description
An epoch of “big data” mining just started for high redshift astronomy. State-of-the-art photometric surveys observed millions of objects on sky, and next-generation telescopes will provide statistically significant samples even for the rarest galaxy types. However, standard techniques (e.g., methods to fit galaxies' spectral energy distribution) are not optimal to analyse this data, preventing a true scientific breakthrough. Indeed some of the most urgent questions in this research field, concerning the evolution of rare ultra-massive galaxies, may remain unsolved. As the Cosmic Dawn Center (University of Copenhagen) is collecting an unprecedented large sample of photometric and spectroscopic data, this is the best time to devise new tools for a full exploitation of such unique observations.The proposed project will devise an original machine learning software to efficiently extract information from the Cosmic Dawn Survey database, and an advanced statistical analysis will result in unprecedented demographics (e.g., stellar mass function) of high redshift (z>3), massive (>5e10 Msol) galaxies. By interpreting these measurements through theoretical models, the project will shed light on the physical mechanisms driving star formation in such extreme galaxies, which are thought to contain most of the stellar mass in the early universe. Besides the unparalleled data set, the expertise of S. Toft (host supervisor) and the other members of the Cosmic Dawn Center will be crucial to achieve these goals.
Status
CLOSEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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