Cl* Berkeley 32 KM 74 , the SIMBAD biblio

Cl* Berkeley 32 KM 74 , the SIMBAD biblio (11 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.17CEST23:33:02


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Title First 3 Authors
1991AcA....41..167K viz 14       D               1 384 27 Photometric study of the old open cluster Be 32. KALUZNY J. and MAZUR B.
2001BASI...29...53R viz 14       D               1 469 12 A study of the old galactic star cluster Berkeley 32. RICHTLER T. and SAGAR R.
2006MNRAS.368..471D viz 15       D               1 439 15 The old anticentre open cluster Berkeley 32: membership and fundamental parameters. D'ORAZI V., BRAGAGLIA A., TOSI M., et al.
2020A&A...633A..99C viz 16       D               1 257585 169 Clusters and mirages: cataloguing stellar aggregates in the Milky Way. CANTAT-GAUDIN T. and ANDERS F.
2020A&A...640A...1C viz 16       D               1 235399 241 Painting a portrait of the Galactic disc with its stellar clusters. CANTAT-GAUDIN T., ANDERS F., CASTRO-GINARD A., et al.
2021A&A...647A..19T viz 17       D               1 24814 55 3D kinematics and age distribution of the open cluster population. TARRICQ Y., SOUBIRAN C., CASAMIQUELA L., et al.
2021MNRAS.503.3279S viz 17       D               1 104620 56 The GALAH survey: tracing the Galactic disc with open clusters. SPINA L., TING Y.-S., DE SILVA G.M., et al.
2022MNRAS.509.1664J viz 17       D               1 14101 25 The Gaia-ESO Survey: Membership probabilities for stars in 63 open and 7 globular clusters from 3D kinematics. JACKSON R.J., JEFFRIES R.D., WRIGHT N.J., et al.
2022ApJ...929...29G viz 17       D               1 8982 ~ Detection of Gravitational Redshift in Open Cluster Nondegenerate Stars. GUTIERREZ C.M. and RAMOS-CHERNENKO N.
2023A&A...676A.129H viz 17       D               1 114943 ~ The Gaia-ESO Survey: Homogenisation of stellar parameters and elemental abundances. HOURIHANE A., FRANCOIS P., WORLEY C.C., et al.
2024A&A...692A.228C viz 18       D               1 49864 ~ Inferring stellar parameters and their uncertainties from high-resolution spectroscopy using invertible neural networks. CANDEBAT N., SACCO G.G., MAGRINI L., et al.

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