Z 300-18 , the SIMBAD biblio

Z 300-18 , the SIMBAD biblio (23 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.15CEST16:21:05

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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
1983Afz....19..631Y 17 ~ The morphology of the galaxies with UV excess. YEGIAZARIAN A.A.
1990IRASF.C......0M viz 14       D               1 26192 130 IRAS Faint Source Catalogue, version 2.0. MOSHIR M., et al.
1991PNAOJ...2....7T viz 459 8 Kiso survey for ultraviolet-excess galaxies. XII. TAKASE B. and MIYAUCHI-ISOBE N.
1996Ap.....39..245K 580 1 Morphological classification of new galaxies with a UV excess. KAZARIAN M.A.
1999PASP..111..438F viz 14       D               1 19407 418 The updated Zwicky catalog (UZC). FALCO E.E., KURTZ M.J., GELLER M.J., et al.
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.
2003Ap.....46..164K 643 1 Physical coupling of Kazarian galaxies with surrounding galaxies. KAZARIAN M.A. and MARTIROSIAN J.R.
2006AJ....132..231P viz 15       D               1607 44 An MMT hectospec redshift survey of 24 µm sources in the Spitzer first look survey. PAPOVICH C., COOL R., EISENSTEIN D., et al.
2009MNRAS.398..109W viz 15       D               1 22041 37 The imperial IRAS-FSC redshift catalogue. WANG L. and ROWAN-ROBINSON M.
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.
2007ChJAA...7..187W 74               F     1 21 11 Mid-to-Far Infrared Spectral Energy Distribution of Galaxies in the Spitzer First Look Survey Field. WEN X.-Q., WU H., CAO C., et al.
2010Ap.....53...57K viz 15       D               1 703 11 A catalog of Kazarian galaxies. KAZARIAN M.A., ADIBEKYAN V.Zh., McLEAN B., et al.
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.
2017MNRAS.471.2687B viz 16       D               1 7831 45 On the interdependence of galaxy morphology, star formation and environment in massive galaxies in the nearby Universe. BAIT O., BARWAY S. and WADADEKAR Y.
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.
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.
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.
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.
2024ApJ...973..116D 90             C       2 16 ~ The Strength of Bisymmetric Modes in SDSS-IV/MaNGA Barred Galaxy Kinematics. DIGIORGIO ZANGER B., WESTFALL K.B., BUNDY K., 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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