Z 87-45 , the SIMBAD biblio

Z 87-45 , the SIMBAD biblio (21 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.14CEST16:12:42

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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
1996A&AS..117..467G viz 22339 19 An image database. II. Catalogue between δ=-0deg and δ=70deg. GARNIER R., PATUREL G., PETIT C., 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.
2011MNRAS.416.2840L viz 15       D               1 72558 178 The 2M++ galaxy redshift catalogue. LAVAUX G. and HUDSON M.J.
2012ApJS..199...26H viz 15       D               1 48926 517 The 2MASS Redshift Survey - Description and data release. HUCHRA J.P., MACRI L.M., MASTERS K.L., 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.
2015AJ....149..171T viz 16       D               1 49219 119 Galaxy groups: a 2MASS catalog. TULLY R.B.
2016A&A...588A..14T viz 16       D               2 84079 35 Friends-of-friends galaxy group finder with membership refinement. TEMPEL E., KIPPER R., TAMM A., 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.
2018A&A...618A..81T viz 16       D               1 50420 14 Bayesian group finder based on marked point processes. Method and feasibility study using the 2MRS data set. TEMPEL E., KRUUSE M., KIPPER R., 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.
2019ApJ...882....9S viz 16       D               1 735 32 Characterizing the local relation between star formation rate and gas-phase metallicity in MaNGA spiral galaxies. SANCHEZ-MENGUIANO L., SANCHEZ ALMEIDA J., MUNOZ-TUNON C., et al.
2020ApJ...903...52S viz 16       D               1 666 ~ Local and global gas metallicity versus stellar age relation in MaNGA galaxies. SANCHEZ-MENGUIANO L., SANCHEZ ALMEIDA J., MUNOZ-TUNON C., et al.
2021ApJ...914..121A viz 17       D               1 43541 20 The NANOGrav 11 yr data set: limits on supermassive black hole binaries in galaxies within 500 Mpc. ARZOUMANIAN Z., BAKER P.T., BRAZIER A., 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.
2022ApJ...935..170A viz 17       D               1 44067 26 Arrival Directions of Cosmic Rays above 32 EeV from Phase One of the Pierre Auger Observatory. ABREU P., AGLIETTA M., ALBURY J.M., et al.
2022MNRAS.516.2337W viz 17       D               1 113 ~ H I content of massive red spiral galaxies observed by FAST. WANG L., ZHENG Z., HAO C.-N., 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.
2024MNRAS.527.7438R viz 18       D               1 4215 ~ The Tully-Fisher relation from SDSS-MaNGA: physical causes of scatter and variation at different radii. RISTEA A., CORTESE L., FRASER-MCKELVIE 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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