FAQ

Please contact me for any comments/suggestions or any other questions not listed here.

What is the UCC?

The acronym UCC stands for Unified Cluster Catalogue. It is the largest catalogue of open clusters in existence. It consists of comprehensive and homogeneous data for an ever expanding number of entries, taken from the latest published articles combined with data from the Gaia survey.

Catalogued OCs in the literature

What objects are included in the UCC?

The UCC lists any object that was catalogued as an open cluster in the literature. This object might be classified differently in other articles (e.g.: moving group, association, etc.) but it will remain listed in the UCC because at least one article at some point indicated that it was an open cluster.

The UCC is regularly updated to include new research. If your article is not listed in the database, you can contact me with the details and I will add it as soon as possible.

How are member stars selected?

Membership is obtained through the fastMP method described in Sect. 3 of Perren et al. (2023). The fastMP membership estimation method has been incorporated into the ASteCA package (see details here).

How is the duplicate probability estimated?

To estimate the probability of an object being a duplicate of a previous entry, we simply find the overlap between members. If two objects share a significant number of members, it is likely that they are the same object catalogued twice under different names.

The probability of being a duplicate is calculated as:

P_dup = max(shared_members_percent) / 100

where shared_members_percent is the percentage of common members between objects (since a given object can be compared to many others, we take the maximum value found). The object presented earlier in the literature is considered the original, while the later one is considered the duplicate.

The P_dup value is equivalent to 1 - C_dup, where C_dup is the factor used in the UTI calculation (see What is the UTI parameter?).

What is the C3 parameter?

The C3 parameter is the combined C1 and C2 classes, described in Sect. 4.3 of Perren et al. (2023) where the UCC was initially introduced. The C1 and C2 classes can be described as:

C1: A density-based metric that quantifies the contrast between the spatial distribution of cluster member stars and that of the surrounding field stars within the five-dimensional parameter space defined by celestial coordinates, proper motions, and parallax.

C2: A photometric metric that estimates the likelihood that the observed stellar sequence of the candidate members is statistically indistinguishable from a sequence randomly drawn from the field star population.

Each one takes values [A, B, C, D] where A is best and D is worst.

Classification of OCs in the literature

What is the UTI parameter?

The UTI (UCC Trust Index) is a measure of the reliability of the cluster detection, ranging from 0 (worst) to 1 (best). It is calculated based on factors such as the number of members, stellar density, the C3 parameter, the presence of the object in the literature, and the probability of the object being a duplicate of a previous entry. It is estimated via the relation:

UTI = 0.2 * (C_N + C_dens + C_C3 + 2*C_lit) * C_dup

where the C factors have values in the [0, 1] range (1 is best) representing normalized estimates of:

  • C_N: number of members (0=very few members, 1=many members)
  • C_dens: stellar density in pc^2 (0=very sparse object, 1=dense object)
  • C_C3: C3 parameter (0=DD class, 1=AA class)
  • C_lit: presence in literature (0=rarely mentioned in the literature, 1=frequently mentioned in the literature)
  • C_dup: likelihood of uniqueness (0=very likely a duplicate entry, 1=not a duplicate entry)

UTI values for OCs in the literature

How are objects flagged as likely not real?

Objects are flagged as likely not real (or non-clusters) when they meet the following conditions:

- C_dup > 0.75 (not a duplicate)
- C_lit < 0.3 (rarely mentioned in the literature)
- UTI < 0.25 (low UTI parameter)

The Search page allows you to hide these objects by selecting the Hide likely non-clusters option.

How are parameters transformed?

The UCC provides a table of fundamental parameters for the OCs listed (when available). These parameters are sometimes transformed to maintain homogeneity. The transformations are as follows:

Metallicity: We use the Bressan et al. (2012) z_sun=0.0152 coefficient as:

[Fe/H]=log10(z/z_sun)

Age: Ages are always given in [Myr]. When ages are provided in [log(age/yr)], we apply:

Age [Myr] = 10^(log(age/yr)/1e6)

Absorption / Extinction: The UCC lists Av absorption. To transform E(B-V) we use the standard value:

Av = 3.1 * E(B-V)

In cases where Ag is present, it is always assumed to be Gaia’s G band. The transformation coefficient to Av is:

Av = 1.2 * Ag

Conversion from E(V-I) assumes Cousin’s I band and is expressed as:

Av = 2.5 * E(V-I)

All approximate coefficients can be estimated for example using the dust_extinction package.

How are the galactocentric plots generated?

The Sun and the Galactic center are represented by the yellow star and the black X, respectively. The spiral arms are taken from Momany et al (2006). The (X_GC, Y_GC, Z_GC) values are estimated applying a -0.02 parallax zero-point offset position of -0.02 [mas] (taken as a reasonable average, see e.g. Ding et al. (2025)). The minimum accepted parallax value is 0.035 (~29 Kpc). Radial velocities are used when available and set to 0.0 Km/s when they are not.

How can I cite the UCC?

If you found the UCC useful for your research, please reference its original article Perren et al. (2023). You can use the following text:

“This research has made use of the Unified Cluster Catalogue (UCC)~\cite{Perren_2023}”

BibTeX entry for the original article:

@ARTICLE{Perren_2023,
       author = {{Perren}, Gabriel I. and {Pera}, Mar{\'\i}a S. and {Navone}, Hugo D. and {V{\'a}zquez}, Rub{\'e}n A.},
        title = "{The Unified Cluster Catalogue: towards a comprehensive and homogeneous data base of stellar clusters}",
      journal = {\mnras},
     keywords = {methods: data analysis, catalogues, open clusters and associations: general, Astrophysics - Astrophysics of Galaxies},
         year = 2023,
        month = dec,
       volume = {526},
       number = {3},
        pages = {4107-4119},
          doi = {10.1093/mnras/stad2826},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2023MNRAS.526.4107P}
}