Project description DEENESFRITPL New software to extract info from Cosmic Dawn Survey database This is where astronomy meets big data mining. While new telescopes are powerful enough to capture the rarest galaxy types, it is a challenge to analyse this data. The EU-funded BESTTIME project will design machine learning software to extract information from the Cosmic Dawn Survey database. Specifically, it will conduct an advanced statistical analysis in unprecedented demographics, such as stellar mass function, of high redshift (z>3), massive (>5e10 Msol) galaxies. The findings will improve our understanding of the physical mechanisms driving star formation in such extreme galaxies, which are thought to contain most of the stellar mass in the early universe. Show the project objective Hide the project objective Objective 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. Fields of science natural sciencescomputer and information sciencesdatabasesnatural sciencescomputer and information sciencesdata sciencebig datanatural sciencescomputer and information sciencesdata sciencedata miningnatural sciencesphysical sciencesastronomyastrophysicsblack holesnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2019 - Individual Fellowships Call for proposal H2020-MSCA-IF-2019 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator KOBENHAVNS UNIVERSITET Net EU contribution € 207 312,00 Address NORREGADE 10 1165 Kobenhavn Denmark See on map Region Danmark Hovedstaden Byen København Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 207 312,00
