|
other query modes : |
Identifier query |
Coordinate query |
Criteria query |
Reference query |
Basic query |
Script submission |
TAP |
Output options |
Object types |
Help |
| BD+40 3689 , the SIMBAD biblio (15 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.14CEST23:42:56 |
| Bibcode/DOI | Score |
in Title|Abstract| Keywords |
in a table | in teXt, Caption, ... | Nb occurence | Nb objects in ref |
Citations (from ADS) |
Title | First 3 Authors |
|---|---|---|---|---|---|---|---|---|---|
| 2011AcA....61..325B | 15 | D | 1 | 87 | 13 | Mt. Suhora Survey - Searching for pulsating M dwarfs in Kepler Public Dataset. | BARAN A.S., FOX-MACHADO L., LYKKE J., et al. | ||
|
2012A&A...543A.160T |
15 | D | 1 | 92 | 66 | Atmospheric parameters of 82 red giants in the Kepler field. | THYGESEN A.O., FRANDSEN S., BRUNTT H., et al. | ||
|
2013MNRAS.434.1422M |
15 | D | 2 | 399 | 81 | Atmospheric parameters of 169 F-, G-, K- and M-type stars in the Kepler field. | MOLENDA-ZAKOWICZ J., SOUSA S.G., FRASCA A., et al. | ||
|
2016A&A...591A.118S |
16 | D | 5 | 31408 | 141 | The PASTEL catalogue: 2016 version. | SOUBIRAN C., LE CAMPION J.-F., BROUILLET N., et al. | ||
|
2016A&A...594A..39F |
55 | D | X | 2 | 51408 | 86 | Activity indicators and stellar parameters of the Kepler targets. An application of the ROTFIT pipeline to LAMOST-Kepler stellar spectra. | FRASCA A., MOLENDA-ZAKOWICZ J., DE CAT P., et al. | |
|
2016A&A...594A.120B |
16 | D | 1 | 142 | 7 | The Gaia-ESO Survey: Hydrogen lines in red giants directly trace stellar mass. | BERGEMANN M., SERENELLI A., SCHONRICH R., et al. | ||
|
2014ASPC..485..223B |
15 | D | 1 | 465820 | 45 | The JMMC stellar diameters catalog v2 (JSDC): a new release based on SearchCal improvements | BOURGES L., LAFRASSE S., MELLA G., et al. | ||
|
2017MNRAS.469.4578H |
16 | D | 1 | 8666 | 48 | Deep learning classification in asteroseismology. | HON M., STELLO D. and YU J. | ||
|
2018MNRAS.475.3633W |
16 | D | 1 | 3727 | 38 | Mass and age of red giant branch stars observed with LAMOST and Kepler. | WU Y., XIANG M., BI S., et al. | ||
|
2018MNRAS.476.3233H |
16 | D | 1 | 15009 | 17 | Deep learning classification in asteroseismology using an improved neural network: results on 15 000 Kepler red giants and applications to K2 and TESS data. | HON M., STELLO D. and YU J. | ||
|
2018ApJS..236...42Y |
16 | D | 1 | 16097 | 158 | Asteroseismology of 16,000 Kepler red giants: global oscillation parameters, masses, and radii. | YU J., HUBER D., BEDDING T.R., et al. | ||
| 2018A&A...620A.203M | 136 | D | X | 4 | 16 | 2 | Asteroseismic potential of CHEOPS. | MOYA A., BARCELO FORTEZA S., BONFANTI A., et al. | |
|
2019MNRAS.490.3158C |
16 | D | 1 | 465839 | 28 | A catalogue of stellar diameters and fluxes for mid-infrared interferometry. | CRUZALEBES P., PETROV R.G., ROBBE-DUBOIS S., et al. | ||
|
2021AJ....161..170S |
17 | D | 1 | 16187 | ~ | The Swan: data-driven inference of stellar surface gravities for cool stars from photometric light curves. | SAYEED M., HUBER D., WHEELER A., et al. | ||
|
2022A&A...663A...4S |
17 | D | 1 | 14206 | 7 | Assessment of [Fe/H] determinations for FGK stars in spectroscopic surveys. | SOUBIRAN C., BROUILLET N. and CASAMIQUELA L. |