LEDA 1159233 , the SIMBAD biblio

LEDA 1159233 , the SIMBAD biblio (19 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.14CEST19:27:24

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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
2003A&A...412...45P viz 15       D               1 956189 750 HYPERLEDA. I. Identification and designation of galaxies. PATUREL G., PETIT C., PRUGNIEL P., et al.
2010ApJS..186..427N viz 15       D               1 14033 346 A catalog of detailed visual morphological classifications for 14,034 galaxies in the Sloan Digital Sky Survey. NAIR P.B. and ABRAHAM R.G.
2014ApJ...788...45T viz 15       D               1 224166 54 Luminosity and redshift dependence of the covering factor of active galactic nuclei viewed with WISE and Sloan Digital Sky Survey. TOBA Y., OYABU S., MATSUHARA H., et al.
2017AJ....154...86W viz 16       D               2 4614 272 The SDSS-IV MaNGA sample: design, optimization, and usage considerations. WAKE D.A., BUNDY K., DIAMOND-STANIC A.M., et al.
2018MNRAS.476.1765L viz 16       D               1 2080 86 SDSS-IV MaNGA: global stellar population and gradients for about 2000 early-type and spiral galaxies on the mass-size plane. LI H., MAO S., CAPPELLARI M., et al.
2018MNRAS.477.4711G viz 16       D               1 2755 110 SDSS-IV MaNGA: stellar angular momentum of about 2300 galaxies: unveiling the bimodality of massive galaxy properties. GRAHAM M.T., CAPPELLARI M., LI H., et al.
2019MNRAS.483.2057F viz 16       D               1 4600 64 SDSS-IV MaNGA PyMorph Photometric and Deep Learning Morphological Catalogues and implications for bulge properties and stellar angular momentum. FISCHER J.-L., DOMINGUEZ SANCHEZ H. and BERNARDI M.
2019ApJS..244....3D viz 16       D               1 23803 ~ Circumventing the effects of projection and dust using inclination-independent infrared galaxy structure measurements: method, error analysis, and a new public catalog of near-infrared galaxy structures. DEVOUR B.M. and BELL E.F.
2019MNRAS.487.5572M viz 16       D               1 4573 ~ Connecting galaxy structure and star formation: the role of environment in formation of S0 galaxies. MISHRA P.K., WADADEKAR Y. and BARWAY S.
2020MNRAS.492.4680W viz 16       D               1 2726 44 Ionized gas outflow signatures in SDSS-IV MaNGA active galactic nuclei. WYLEZALEK D., FLORES A.M., ZAKAMSKA N.L., et al.
2020MNRAS.493...87T viz 16       D               1 988 46 A physically motivated definition for the size of galaxies in an era of ultradeep imaging. TRUJILLO I., CHAMBA N. and KNAPEN J.H.
2020MNRAS.495.4820L viz 16       D               1 1340 ~ SDSS-IV MaNGA: stellar population correlates with stellar root-mean-square velocity Vrms gradients or total-density-profile slopes at fixed effective velocity dispersion σe. LU S., CAPPELLARI M., MAO S., et al.
2022MNRAS.509.3966W viz 17       D               1 89291 61 Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies. WALMSLEY M., LINTOTT C., GERON T., et al.
2022MNRAS.511.4223A viz 17       D               1 370 2 Cool outflows in MaNGA: a systematic study and comparison to the warm phase. AVERY C.R., WUYTS S., FORSTER SCHREIBER N.M., et al.
2022ApJS..262...36S viz 17       D               1 10075 23 SDSS-IV MaNGA: pyPipe3D Analysis Release for 10,000 Galaxies. SANCHEZ S.F., BARRERA-BALLESTEROS J.K., LACERDA E., et al.
2022A&A...667A..87C viz 17       D               1 615 6 The edges of galaxies: Tracing the limits of star formation. CHAMBA N., TRUJILLO I. and KNAPEN J.H.
2023A&A...674A..85A viz 17       D               1 6495 2 Classifying the full SDSS-IV MaNGA Survey using optical diagnostic diagrams: Presentation of AGN catalogs in flexible apertures. ALBAN M. and WYLEZALEK D.
2023ApJS..269....3M viz 17       D               1 356397 ~ Siena Galaxy Atlas 2020. MOUSTAKAS J., LANG D., DEY A., et al.
2024NatAs...8.1310A viz 18       D               1 10075 ~ Constraints on the in situ and ex situ stellar masses in nearby galaxies obtained with artificial intelligence. ANGELOUDI E., FALCON-BARROSO J., HUERTAS-COMPANY M., et al.

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