The catalogue was created based on the extended candidate catalogue of the Planck clusters (SZcat) and deep learning algorithm, that was trained on the ACT+Planck maps (Naess et al. 2020).
The ComPACT catalogue contains 2,962 candidates. Below we describe columns:
| Column | Description | Units / Notes |
|---|---|---|
| Name | ID of a ComPACT candidate | Unique identifier |
| RA | Right Ascension of maximum pixel | Decimal degrees (J2000) |
| DEC | Declination of maximum pixel | Decimal degrees (J2000) |
| S | Object mask area | Pixels |
| pmax | Maximum probability for an object | Probability score [0, 1] |
| SZcat | Name of the object from SZcat catalogue | Cross-match ID* |
| ACT | Cluster name in the ACT DR5 catalogue | Cross-match ID* |
| PSZ2 | PSZ2 source name | Cross-match ID* |
| Priority | Reliability of candidate based on |
See levels descriprion in arxiv_2309.17077 folder |
*file with this columns in folder arXiv_2309.17077
| Column | Description | Units / Notes |
|---|---|---|
| z | Cluster redshift | |
| zType | Redshift type |
spec (spectroscopic) or phot (photometric) |
| zSource | Source of the cluster redshift | Reference ID (see Data Sources) |
| zCluster_delta |
zCluster density contrast statistic |
see zCluster |
| zCluster_err | Uncertainty in zCluster_delta
|
|
| zZazn_sig1 |
Zaznobin first significance value |
Significance ( |
| zZazn_sig2 |
Zaznobin second significance value |
Significance ( |
| zZazn_err | Uncertainty in Zaznobin redshift |
|
| M500 | Cluster mass ( |
|
| mSource | Source of the mass estimate | Reference ID (see Data Sources) |
For columns we used catalogues:
- SZcatgen: data, Meshcheryakov et al. 2022
- ACT DR5: data, Hilton et al. 2021
- PSZ2: data, Planck Collobaration
- zCluster: github, Hilton et al. 2018
- Zaznobin algorithm: github, Zaznobin et al. 2023
- Redshift/Mass Sources: Detailed references for specific
zSourceandmSourceIDs are provided in the Table 1 of the v3.0 paper.
Cluster calalogue: ComPACT.csv (v2.0)
- v3.0 Measure mass and readshifts. Released accompanying paper:
- v2.0 Add 'Priority' column, which is responsible for subsamples with different purity and completeness characteristics. Also, We keep the nearest object in 5 arcmin window (before all objects in 5 arcmin window). Also, now we cross-match objects from full catalogue with SZcat, before we crop 5 arcmin window from probability map and analyse groups
- v1.1 Negative RA coordinates in catalog are fixed (e.g -152.41666 -> 207.58333)
- v1.0 Initial release (in folder v1.0)
- Bibcode: 2024MNRAS.531.1998V (ADS)
- arXiv: arXiv:2309.17077
- Bibcode:
- arXiv:
- Vizier: ComPACT: J/MNRAS/531/1998