Modern large-scale, ground-based stellar spectroscopic surveys produce large datasets of stellar atmospheric parameters, abundances and ages. These datasets are crucial for testing current chemo-dynamical models for the Milky Way and for unraveling its formation history. Two different approaches are usually adopted for deriving stellar parameters and chemistry from stellar spectra: \u201cphysical\u201d spectroscopic pipelines that fit a synthetic spectrum to the observed one, and machine learning methods that derive stellar labels after being trained on spectra of well known stars.\u00a0<\/p>\r\n
How can we ensure the accuracy, precision, and homogeneity of the parameters provided by surveys? Presently, spectroscopic surveys base their homogenization on only thirty-six benchmark stars and, when machine learning is in use, they adopt their own training sample (often with incomplete parameter coverage, especially in the metal-poor regime). As a consequence, abundance zero-points and trends vary from one survey to another, thereby introducing erratic biases when used for characterizing our Galaxy.<\/p>\r\n
Our proposed International Team will remedy this situation lastingly. Using targets with available asteroseismology and targets in clusters, we will build a reference catalogue of ~10\u2075 stars.<\/i> The catalogue will include reliable atmospheric parameters, abundances, and ages that span the required range for Milky Way investigations. Our reference catalogue will have a significant importance for present and future spectroscopic surveys such as e.g. 4MOST<\/a> and MSE<\/a>.<\/strong><\/p>\r\n","protected":false},"excerpt":{"rendered":" Modern large-scale, ground-based stellar spectroscopic surveys produce large datasets of stellar atmospheric parameters, abundances and ages. These datasets are crucial for testing current chemo-dynamical models for the Milky Way and for unraveling its formation history. Two different approaches are usually adopted for deriving stellar parameters and chemistry from stellar spectra: \u201cphysical\u201d spectroscopic pipelines that fit […]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-2","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/pages\/2","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/comments?post=2"}],"version-history":[{"count":6,"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/pages\/2\/revisions"}],"predecessor-version":[{"id":23,"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/pages\/2\/revisions\/23"}],"wp:attachment":[{"href":"https:\/\/teams.issibern.ch\/asterocats\/wp-json\/wp\/v2\/media?parent=2"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}