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| SDSSCGB 2111.1 , the SIMBAD biblio (20 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.16CEST15:39:49 |
| 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...405...99M |
3832 | 14 | A search for Low Surface Brightness galaxies in the near-infrared. I. Selection of the sample. | MONNIER-RAGAIGNE D., VAN DRIEL W., SCHNEIDER S.E., et al. | |||||
|
2003A&A...412...45P |
15 | D | 1 | 956189 | 750 | HYPERLEDA. I. Identification and designation of galaxies. | PATUREL G., PETIT C., PRUGNIEL P., et al. | ||
|
2009MNRAS.395..255M |
15 | D | 1 | 397037 | 82 | Compact groups in theory and practice - III. Compact groups of galaxies in the sixth data release of the Sloan Digital Sky Survey. | McCONNACHIE A.W., PATTON D.R., ELLISON S.L., et al. | ||
|
2012MNRAS.421.1569B |
15 | D | 3 | 18458 | 511 | On the fundamental dichotomy in the local radio-AGN population: accretion, evolution and host galaxy properties. | BEST P.N. and HECKMAN T.M. | ||
|
2014ApJ...785..104R |
15 | D | 1 | 72334 | 578 | redMaPPer. I. Algorithm and SDSS DR8 catalog. | RYKOFF E.S., ROZO E., BUSHA M.T., et al. | ||
|
2016ApJS..224....1R |
16 | D | 1 | 670875 | 246 | The redMaPPer galaxy cluster catalog from DES science verification data. | RYKOFF E.S., ROZO E., HOLLOWOOD D., et al. | ||
|
2017MNRAS.466.2570B |
16 | D | 1 | 587 | 84 | SDSS-IV MaNGA - the spatially resolved transition from star formation to quiescence. | BELFIORE F., MAIOLINO R., MARASTON C., et al. | ||
|
2017AJ....154...86W |
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. | ||
|
2018AJ....155..188L |
16 | D | 1 | 13497 | 1 | An analysis framework for understanding the origin of nuclear activity in low-power radio galaxies. | LIN Y.-T., HUANG H.-J. and CHEN Y.-C. | ||
|
2018MNRAS.477.4711G |
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. | ||
|
2018MNRAS.481.5580F |
16 | D | 1 | 280 | 51 | SDSS-IV MaNGA: the formation sequence of S0 galaxies. | FRASER-MCKELVIE A., ARAGON-SALAMANCA A., MERRIFIELD M., et al. | ||
|
2019MNRAS.483.2057F |
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 |
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. | ||
|
2020ApJS..247...53K |
16 | D | 1 | 23378 | 20 | Radio sources associated with Optical Galaxies and having Unresolved or Extended morphologies (ROGUE). I. A catalog of SDSS galaxies with FIRST core identifications. | KOZIEL-WIERZBOWSKA D., GOYAL A. and ZYWUCKA N. | ||
|
2020ApJ...901..159C |
16 | D | 1 | 407 | 26 | A catalog of 406 AGNs in MaNGA: a connection between radio-mode AGNs and star formation quenching. | COMERFORD J.M., NEGUS J., MULLER-SANCHEZ F., et al. | ||
|
2021ApJ...909..120S |
17 | D | 2 | 317 | ~ | SDSS-IV MaNGA: the radial profile of enhanced star formation in close galaxy pairs. | STEFFEN J.L., FU H., COMERFORD J.M., et al. | ||
| 2022A&A...665A.144M | 17 | D | 1 | 534 | 3 | Star formation and AGN feedback in the local Universe: Combining LOFAR and MaNGA. | MULCAHEY C.R., LESLIE S.K., JACKSON T.M., et al. | ||
|
2022ApJS..262...36S |
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. | ||
|
2023ApJS..269....3M |
17 | D | 1 | 356397 | ~ | Siena Galaxy Atlas 2020. | MOUSTAKAS J., LANG D., DEY A., et al. | ||
|
2024NatAs...8.1310A |
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. |