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Inferring the properties of exoplanets from their atmospheres, while confronting low resolution and low signal-to-noise in the context of the quantities we want to derive, poses rigorous demands upon the data collected from observation.…

Earth and Planetary Astrophysics · Physics 2022-07-27 Theresa Fisher , Hyunju Kim , Camerian Millsaps , Michael Line , Sara Imari Walker

Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) acquired tens of millions of low-resolution stellar spectra. The large amount of the spectra result in the urgency to explore automatic atmospheric parameter estimation…

Instrumentation and Methods for Astrophysics · Physics 2022-07-14 Xiangru Li , Si Zeng , Zhu Wang , Bing Du , Xiao Kong , Caixiu Liao

As a typical data-driven method, deep learning becomes a natural choice for analysing astronomical data nowadays. In this study, we built a deep convolutional neural network to estimate basic stellar parameters $T\rm{_{eff}}$, log g,…

Astrophysics of Galaxies · Physics 2022-08-03 Zhuohan Li , Gang Zhao , Yuqin Chen , Xilong Liang , Jingkun Zhao

We aim to prepare the machine-learning ground for the next generation of spectroscopic surveys, such as 4MOST and WEAVE. Our goal is to show that convolutional neural networks can predict accurate stellar labels from relevant spectral…

We design an uncertainty-aware cost-sensitive neural network (UA-CSNet) to estimate metallicities from dereddened and corrected Gaia BP/RP (XP) spectra for giant stars. This method accounts for both stochastic errors in the input spectra…

Solar and Stellar Astrophysics · Physics 2025-05-09 Lin Yang , Haibo Yuan , Bowen Huang , Ruoyi Zhang , Timothy C. Beers , Kai Xiao , Shuai Xu , Yang Huang , Maosheng Xiang , Meng Zhang , Jinming Zhang

Distances from the Gaia mission will no doubt improve our understanding of stellar physics by providing an excellent constraint on the luminosity of the star. However, it is also clear that high precision stellar properties from, for…

Solar and Stellar Astrophysics · Physics 2012-12-07 O. L. Creevey , F. Thévenin

We investigate how the constraints on cosmological and astrophysical parameters ($\Omega_{\rm m}$, $\sigma_{8}$, $A_{\rm SN1}$, $A_{\rm SN2}$) vary when exploiting information from multiple fields in cosmology. We make use of a…

Cosmology and Nongalactic Astrophysics · Physics 2023-07-05 Sambatra Andrianomena , Sultan Hassan

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low Resolution Spectroscopic Survey (LRS) provides massive spectroscopic data of M-type stars, and the derived stellar parameters could bring vital help to various…

Accurate determination of stellar atmospheric parameters and elemental abundances is crucial for Galactic archeology via large-scale spectroscopic surveys. In this paper, we estimate stellar atmospheric parameters -- effective temperature…

Stellar physical and dynamical properties are essential knowledge to understanding the structure, formation, and evolution of our Galaxy. We produced an all-sky uniformly derived catalog of stellar astrophysical parameters (APs; age, mass,…

Astrophysics of Galaxies · Physics 2022-07-06 M. Fouesneau , R. Andrae , T. Dharmawardena , J. Rybizki , C. A. L. Bailer-Jones , M. Demleitner

Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a…

The determination of atmospheric parameters depends on the use of radiative transfer codes (among other elements such as model atmospheres) to compute synthetic spectra and/or derive abundances from equivalent widths. However, it is common…

This work investigates the spectrum parameterization problem using deep neural networks (DNNs). The proposed scheme consists of the following procedures: first, the configuration of a DNN is initialized using a series of autoencoder neural…

Solar and Stellar Astrophysics · Physics 2019-03-20 Xiangru Li , Ruyang Pan

Analyses of stellar spectra often begin with the determination of a number of parameters that define a model atmosphere. This work presents a prototype for an automated spectral classification system that uses a 15 nm-wide region around…

Astrophysics · Physics 2016-08-30 C. Allende Prieto

Gaia Data Release 3 (DR3) provides a wealth of new data products for the astronomical community to exploit, including astrophysical parameters for a half billion stars. In this work we demonstrate the high quality of these data products and…

Solar and Stellar Astrophysics · Physics 2023-06-21 Gaia Collaboration , O. L. Creevey , L. M. Sarro , A. Lobel , E. Pancino , R. Andrae , R. L. Smart , G. Clementini , U. Heiter , A. J. Korn , M. Fouesneau , Y. Frémat , F. De Angeli , A. Vallenari , D. L. Harrison , F. Thévenin , C. Reylé , R. Sordo , A. Garofalo , A. G. A. Brown , L. Eyer , T. Prusti , J. H. J. de Bruijne , F. Arenou , C. Babusiaux , M. Biermann , C. Ducourant , D. W. Evans , R. Guerra , A. Hutton , C. Jordi , S. A. Klioner , U. L. Lammers , L. Lindegren , X. Luri , F. Mignard , C. Panem , D. Pourbaix , S. Randich , P. Sartoretti , C. Soubiran , P. Tanga , N. A. Walton , C. A. L. Bailer-Jones , U. Bastian , R. Drimmel , F. Jansen , D. Katz , M. G. Lattanzi , F. van Leeuwen , J. Bakker , C. Cacciari , J. Castañeda , C. Fabricius , L. Galluccio , A. Guerrier , E. Masana , R. Messineo , N. Mowlavi , C. Nicolas , K. Nienartowicz , F. Pailler , P. Panuzzo , F. Riclet , W. Roux , G. M. Seabroke , G. Gracia-Abril , J. Portell , D. Teyssier , M. Altmann , M. Audard , I. Bellas-Velidis , K. Benson , J. Berthier , R. Blomme , P. W. Burgess , D. Busonero , G. Busso , H. Cánovas , B. Carry , A. Cellino , N. Cheek , Y. Damerdji , M. Davidson , P. de Teodoro , M. Nuñez Campos , L. Delchambre , A. Dell'Oro , P. Esquej , J. Fernández-Hernández , E. Fraile , D. Garabato , P. García-Lario , E. Gosset , R. Haigron , J. -L. Halbwachs , N. C. Hambly , J. Hernández , D. Hestroffer , S. T. Hodgkin , B. Holl , K. Janßen , G. Jevardat de Fombelle , S. Jordan , A. Krone-Martins , A. C. Lanzafame , W. Löffler , O. Marchal , P. M. Marrese , A. Moitinho , K. Muinonen , P. Osborne , T. Pauwels , A. Recio-Blanco , M. Riello , L. Rimoldini , T. Roegiers , J. Rybizki , C. Siopis , M. Smith , A. Sozzetti , E. Utrilla , M. van Leeuwen , U. Abbas , P. Ábrahám , A. Abreu Aramburu , C. Aerts , J. J. Aguado , M. Ajaj , F. Aldea-Montero , G. Altavilla , M. A. Álvarez , J. Alves , F. Anders , R. I. Anderson , E. Anglada Varela , T. Antoja , D. Baines , S. G. Baker , L. Balaguer-Núñez , E. Balbinot , Z. Balog , C. Barache , D. Barbato , M. Barros , M. A. Barstow , S. Bartolomé , J. -L. Bassilana , N. Bauchet , U. Becciani , M. Bellazzini , A. Berihuete , M. Bernet , S. Bertone , L. Bianchi , A. Binnenfeld , S. Blanco-Cuaresma , T. Boch , A. Bombrun , D. Bossini , S. Bouquillon , A. Bragaglia , L. Bramante , E. Breedt , A. Bressan , N. Brouillet , E. Brugaletta , B. Bucciarelli , A. Burlacu , A. G. Butkevich , R. Buzzi , E. Caffau , R. Cancelliere , T. Cantat-Gaudin , R. Carballo , T. Carlucci , M. I. Carnerero , J. M. Carrasco , L. Casamiquela , M. Castellani , A. Castro-Ginard , L. Chaoul , P. Charlot , L. Chemin , V. Chiaramida , A. Chiavassa , N. Chornay , G. Comoretto , G. Contursi , W. J. Cooper , T. Cornez , S. Cowell , F. Crifo , M. Cropper , M. Crosta , C. Crowley , C. Dafonte , A. Dapergolas , P. David , P. de Laverny , F. De Luise , R. De March , J. De Ridder , R. de Souza , A. de Torres , E. F. del Peloso , E. del Pozo , M. Delbo , A. Delgado , J. -B. Delisle , C. Demouchy , T. E. Dharmawardena , P. Di Matteo , S. Diakite , C. Diener , E. Distefano , C. Dolding , H. Enke , C. Fabre , M. Fabrizio , S. Faigler , G. Fedorets , P. Fernique , F. Figueras , Y. Fournier , C. Fouron , F. Fragkoudi , M. Gai , A. Garcia-Gutierrez , M. Garcia-Reinaldos , M. García-Torres , A. Gavel , P. Gavras , E. Gerlach , R. Geyer , P. Giacobbe , G. Gilmore , S. Girona , G. Giuffrida , R. Gomel , A. Gomez , J. González-Núñez , I. González-Santamaría , J. J. González-Vidal , M. Granvik , P. Guillout , J. Guiraud , R. Gutiérrez-Sánchez , L. P. Guy , D. Hatzidimitriou , M. Hauser , M. Haywood , A. Helmer , A. Helmi , M. H. Sarmiento , S. L. Hidalgo , N. Hładczuk , D. Hobbs , G. Holland , H. E. Huckle , K. Jardine , G. Jasniewicz , A. Jean-Antoine Piccolo , Ó. Jiménez-Arranz , J. Juaristi Campillo , F. Julbe , L. Karbevska , P. Kervella , S. Khanna , G. Kordopatis , Á Kóspál , Z. Kostrzewa-Rutkowska , K. Kruszyńska , M. Kun , P. Laizeau , S. Lambert , A. F. Lanza , Y. Lasne , J. -F. Le Campion , Y. Lebreton , T. Lebzelter , S. Leccia , N. Leclerc , I. Lecoeur-Taibi , S. Liao , E. L. Licata , H. E. P. Lindstrøm , T. A. Lister , E. Livanou , A. Lorca , C. Loup , P. Madrero Pardo , A. Magdaleno Romeo , S. Managau , R. G. Mann , M. Manteiga , J. M. Marchant , M. Marconi , J. Marcos , M. M. S. Marcos Santos , D. Marín Pina , S. Marinoni , F. Marocco , D. J. Marshall , L. Martin Polo , J. M. Martín-Fleitas , G. Marton , N. Mary , A. Masip , D. Massari , A. Mastrobuono-Battisti , T. Mazeh , P. J. McMillan , S. Messina , D. Michalik , N. R. Millar , A. Mints , D. Molina , R. Molinaro , L. Molnár , G. Monari , M. Monguió , P. Montegriffo , A. Montero , R. Mor , A. Mora , R. Morbidelli , T. Morel , D. Morris , T. Muraveva , C. P. Murphy , I. Musella , Z. Nagy , L. Noval , F. Ocaña , A. Ogden , C. Ordenovic , J. O. Osinde , C. Pagani , I. Pagano , L. Palaversa , P. A. Palicio , L. Pallas-Quintela , A. Panahi , S. Payne-Wardenaar , X. Peñalosa Esteller , A. Penttilä , B. Pichon , A. M. Piersimoni , F. -X. Pineau , E. Plachy , G. Plum , E. Poggio , A. Prša , L. Pulone , E. Racero , S. Ragaini , M. Rainer , C. M. Raiteri , P. Ramos , M. Ramos-Lerate , P. Re Fiorentin , S. Regibo , P. J. Richards , C. Rios Diaz , V. Ripepi , A. Riva , H. -W. Rix , G. Rixon , N. Robichon , A. C. Robin , C. Robin , M. Roelens , H. R. O. Rogues , L. Rohrbasser , M. Romero-Gómez , N. Rowell , F. Royer , D. Ruz Mieres , K. A. Rybicki , G. Sadowski , A. Sáez Núñez , A. Sagristà Sellés , J. Sahlmann , E. Salguero , N. Samaras , V. Sanchez Gimenez , N. Sanna , R. Santoveña , M. Sarasso , M. Schultheis , E. Sciacca , M. Segol , J. C. Segovia , D. Ségransan , D. Semeux , S. Shahaf , H. I. Siddiqui , A. Siebert , L. Siltala , A. Silvelo , E. Slezak , I. Slezak , O. N. Snaith , E. Solano , F. Solitro , D. Souami , J. Souchay , A. Spagna , L. Spina , F. Spoto , I. A. Steele , H. Steidelmüller , C. A. Stephenson , M. Süveges , J. Surdej , L. Szabados , E. Szegedi-Elek , F. Taris , M. B. Taylor , R. Teixeira , L. Tolomei , N. Tonello , F. Torra , J. Torra , G. Torralba Elipe , M. Trabucchi , A. T. Tsounis , C. Turon , A. Ulla , N. Unger , M. V. Vaillant , E. van Dillen , W. van Reeven , O. Vanel , A. Vecchiato , Y. Viala , D. Vicente , S. Voutsinas , M. Weiler , T. Wevers , Ł. Wyrzykowski , A. Yoldas , P. Yvard , H. Zhao , J. Zorec , S. Zucker , T. Zwitter

The GAIA Galactic survey satellite will obtain photometry in 15 filters of over 10^9 stars in our Galaxy across a very wide range of stellar types. No other planned survey will provide so much photometric information on so many stars. I…

Astrophysics · Physics 2009-11-07 C. A. L. Bailer-Jones

We present a unified framework to derive fundamental stellar parameters by combining all available observational and theoretical information for a star. The algorithm relies on the method of Bayesian inference, which for the first time…

Solar and Stellar Astrophysics · Physics 2015-06-18 Ralph Schönrich , Maria Bergemann

Gaia will observe more than one billion objects brighter than V=20, including stars, asteroids, galaxies and quasars. As Gaia performs real time detection (i.e. without an input catalogue) the intrinsic properties of most of these objects…

Astrophysics · Physics 2007-05-23 C. A. L. Bailer-Jones