Collinder 273

(VDBH 147; NGC 5168; MWSC 2129; OCL 905; vdBergh-Hagen 147; ESO 132 10; FSR 1655; FoF 427)

Click to load Aladin Lite
0.97 UTI
0.83
CN
1.0
Cdens
1.0
CC3
1.0
Clit
1.0
Cdup
Stellar density (N50/rad) 58.5 [N/pc2]
  • CN 0.83 Rich
  • Cdens 1.0 Very dense
  • CC3 1.0 Very high quality
  • Clit 1.0 Very well-studied
  • Cdup 1.0 Unique

Overview

ℹ️
Collinder 273 is a rich, very dense object of very high C3 quality. Its parallax locates it at a moderate* distance, above the mid-plane, affected by moderate extinction. It is catalogued as a near-solar metallicity, intermediate-age cluster, but with a large variance across recent sources for the age, metallicity, and mass parameters (see Parameters). It is very well-studied in the literature.

(*): The parallax distance estimate (~3.32 kpc) differs significantly from the median photometric distance (~2.42 kpc).

Note: This object contains blue stragglers according to at least one source.

Almeida et al. (2025)
Mass determination: good fit. Isochrone match: good fit. Gold sample.

Cavallo et al. (2024)
Gold sample.

Data

ℹ️
Reference Year RA [deg] DEC [deg] Plx [mas] pmRA [mas/yr] pmDE [mas/yr] Rv [km/s]
UCC 99999– 202.79 -60.946 0.301 -4.145 -1.444 -34.093
Li et al. 2025 202.791 -60.945 0.28 -4.131 -1.478 –
Hu & Soubiran 2025 202.805 -60.947 – – – –
Almeida et al. 2025 202.792 -60.945 – – – –
Hunt & Reffert 2024 202.793 -60.945 0.301 -4.174 -1.434 -30.253
Cavallo et al. 2024 202.805 -60.947 0.301 – – –
Hunt & Reffert 2023 202.793 -60.945 0.301 -4.174 -1.434 -30.253
Almeida et al. 2023 202.79 -60.945 – – – –
Just et al. 2023 202.758 -60.937 – – – –
Jaehnig et al. 2021 202.796 -60.943 0.314 -4.127 -1.473 –
Rain et al. 2021 202.791 -60.945 0.28 -4.131 -1.478 –
Dias et al. 2021 202.792 -60.945 0.275 -4.112 -1.474 -18.672
Cantat-Gaudin et al. 2020 202.791 -60.945 0.28 -4.131 -1.478 –
SΓ‘nchez et al. 2020 202.775 -60.94 – -4.04 -1.43 –
Cantat-Gaudin & Anders 2020 202.791 -60.945 0.28 -4.131 -1.478 –
Liu & Pang 2019 202.815 -60.946 0.286 -4.164 -1.444 –
Soubiran et al. 2018 202.791 -60.945 – – – -34.38
Bica et al. 2019 202.772 -60.942 – – – –
Cantat-Gaudin et al. 2018 202.791 -60.945 0.28 -4.131 -1.478 –
Loktin & Popova 2017 202.77 -60.94 – -7.063 -1.415 –
Kharchenko et al. 2016 202.758 -60.937 – – – –
Dias et al. 2014 202.775 -60.94 – -3.95 -3.05 –
Kharchenko et al. 2013 202.77 -60.94 – -3.7 -0.86 –
Gozha et al. 2012 202.775 -60.94 – – – –
Piskunov et al. 2008 202.749 -60.934 – – – –
van den Bergh 2006 202.775 -60.945 – – – –
Kharchenko et al. 2005 202.77 -60.94 – -1.29 -0.07 –
Kharchenko et al. 2003 202.8 -60.93 – -1.33 -0.5 –
Dias et al. 2002 202.775 -60.94 – -3.95 -3.05 –

πŸ’‘ Note: The UCC values are estimated from its identified members.

Reference Year Dist [kpc] Av [mag] DAv [mag] Age [Myr] [Fe/H] [dex] Mass [Msun] Bfrac BSS
UCC 99999– 2.42 1.34 1.2 178 0.080 795 0.61 6.0
Li et al. 2025 2.67 1.79 – 681 0.258 – – –
Hu & Soubiran 2025 – – – – -0.120(5) – – –
Almeida et al. 2025 2.42 1.97 – 684 – 1313 – –
Hunt & Reffert 2024 – – – – – 2381(1) – –
Cavallo et al. 2024 2.07 2.16 – 1000 -0.330 – – –
Hunt & Reffert 2023 2.92 1.92 1.20 378 – – – –
Almeida et al. 2023 2.55 1.95 – 705 0.099 795(1) 0.61 –
Just et al. 2023 – – – 178 – 67 – –
Jaehnig et al. 2021 3.19(1) – – – – – – –
Rain et al. 2021 3.24 1.33 – 100 – – – 6
Dias et al. 2021 2.42 1.97 – 684 0.080 – – –
Cantat-Gaudin et al. 2020 2.90 1.45 – 603 – – – –
Cantat-Gaudin & Anders 2020 3.24 – – – – – – –
Liu & Pang 2019 – – – 457 0.250 – – –
Soubiran et al. 2018 3.24 – – – – – – –
Cantat-Gaudin et al. 2018 3.24 – – – – – – –
Loktin & Popova 2017 1.78 1.34 – 100 – – – –
Kharchenko et al. 2016 1.73 1.10 – 178 – – – –
Kharchenko et al. 2013 1.73 1.10 – 178 – – – –
Gozha et al. 2012 1.78 – – 100 0.050 417 – –
Piskunov et al. 2008 1.78 1.02 – 55 – – – –
van den Bergh 2006 1.78 1.33 – 100 – – – –
Kharchenko et al. 2005 1.78 1.02 – 55 – – – –
Kharchenko et al. 2003 1.78 1.33 – – – – – –
Dias et al. 2002 1.78 1.34 – 100 – – – –

(N): Indicates that there are N extra values assigned to this parameter in the corresponding reference.

Visualization

ℹ️