{"id":2,"date":"2025-02-05T15:25:02","date_gmt":"2025-02-05T15:25:02","guid":{"rendered":"https:\/\/teams.issibern.ch\/asteroshop\/?page_id=2"},"modified":"2025-03-12T09:58:26","modified_gmt":"2025-03-12T09:58:26","slug":"home","status":"publish","type":"page","link":"https:\/\/teams.issibern.ch\/asteroshop\/","title":{"rendered":"Home"},"content":{"rendered":"<p><span style=\"font-size: 14pt\"><b><span style=\"color: #073763\"><span style=\"font-family: Times New Roman, serif\">About the project<\/span><\/span><\/b><\/span><\/p>\n<p align=\"justify\"><span style=\"font-family: Times New Roman, serif\"><i>In modern Galactic astronomy, stellar spectroscopy has a pivotal role in complementing large photometric and astrometric surveys, such as Gaia, PLATO and TESS. Spectroscopic observations provide crucial data on stellar parameters, chemical compositions, and radial velocities, enabling deeper insights into the chemical evolution and chemo-dynamical mechanisms of the Milky Way and its satellites. Several large spectroscopic surveys have already provided data for millions of stars, with many more underway, promising to significantly expand our understanding of the formation and the evolution of our Galactic environment.<\/i><\/span><\/p>\n<p align=\"justify\"><span style=\"font-family: Times New Roman, serif\"><i>Despite the wealth of data from these surveys, systematic differences in derived spectroscopic parameters raise challenges. Efforts to harmonize these surveys onto a common scale are essential to maximize their scientific legacy. Machine learning techniques offer promising avenues for <!-- I disagree that ML is helping as calibration, it is rather propagation of everything we know for small samples into large samples. Calibration is improving stellar physics, and that is still a bit detached from ML. --><!-- I'd say the promising is for precision and efficiency in dealing with the large and complex data gathered with current facilities --><!-- I believe that ML will be helpful for putting\u00a0surveys on the same scale. I have been trying Auto-Encoders since a few weeks now, and the results are promising. -->homogenizing spectroscopic surveys on the same base, but they require addressing issues such as parameter space coverage of the training set and the compatibility of different survey methodologies. Additionally, the creation of benchmark catalogues and the development of common metrics are critical steps in evaluating and improving homogenization methods.<\/i><\/span><\/p>\n<p align=\"justify\"><a name=\"yynkcmj31cu9\"><\/a> <span style=\"font-family: Times New Roman, serif\"><i>The project brings together experts with different backgrounds<!-- in what? Stellar, ML? --> to tackle these challenges collaboratively. Through discussions and collaborative efforts, the team aims to establish a comprehensive understanding of the homogenization process and develop new methodologies to ensure the compatibility and accuracy of spectroscopic surveys. By defining the applicability domain of homogenization methods and developing common metrics, the project aims to provide valuable guidance for future spectroscopic surveys, maximizing their scientific impact and ensuring their seamless integration with other surveys.<\/i><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>About the project In modern Galactic astronomy, stellar spectroscopy has a pivotal role in complementing large photometric and astrometric surveys, such as Gaia, PLATO and TESS. Spectroscopic observations provide crucial data on stellar parameters, chemical compositions, and radial velocities, enabling deeper insights into the chemical evolution and chemo-dynamical mechanisms of the Milky Way and its [&hellip;]<\/p>\n","protected":false},"author":151,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/pages\/2","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/users\/151"}],"replies":[{"embeddable":true,"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/comments?post=2"}],"version-history":[{"count":6,"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/pages\/2\/revisions"}],"predecessor-version":[{"id":42,"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/pages\/2\/revisions\/42"}],"wp:attachment":[{"href":"https:\/\/teams.issibern.ch\/asteroshop\/wp-json\/wp\/v2\/media?parent=2"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}