Overview The Massive and Distant Clusters of WISE Survey 2 (MaDCoWS2) is a new survey designed as the successor of the original MaDCoWS survey. MaDCoWS2 improves upon its predecessor by using deeper optical and infrared data and a more powerful detection algorithm (PZWav). As input to the search, MaDCoWS2 use g⁢r⁢z photometry from DECaLS in combination with W1 and W2 photometry from the CatWISE2020 catalog to derive the photometric redshifts with full redshift probability distribution functions for WISE-selected galaxies. Cluster candidates are detected using the PZWav algorithm to find three-dimensional galaxy overdensities from the sky positions and photometric redshifts. The second data release of the Massive and Distant Clusters of WISE Survey 2 (MaDCoWS2) expands from the equatorial first data release to most of the Dark Energy Camera Legacy Survey area, covering a total area of 6498 deg^2. The catalog consists of 133,036 cluster candidates with S/NP ≥5. The catalog covers redshifts ranging from 0.1 to 2, including 29,764 candidates at z≥1 and 6790 candidates at z>1.5. The catalog consists of name, RA, DEC, photometric redshift (and its error) and the S/N based upon Gaussian (S/NG) and Poisson (S/NP) noise statistics. In addition, it includes the names in the literature of each cluster candidate (and numbers assigned to the referred works) and spectroscopic redshifts derived from external catalogs accompanied by their references. Lastly, the catalog provides the name of any foreground cluster detections in the column Name_fg (see §2.2.1 of MaDCoWS2 DR1) and the CNN probability that a detection a⁢t ⁢z>1 is a genuine cluster PCNN (see §3 of MaDCoWS2 DR2). A foreground detection is defined as a cluster candidate within a projected 500 kpc of a more distant candidate, requiring a redshift at least 0.12 lower than that of the more distant candidate. If you use MaDCoWS2, please cite both the MaDCoWS2 DR1 paper (Thongkham et al., 2024) and the MaDCoWS2 DR2 paper. Table description Byte-by-byte Description of file which is also used for AAS MRT -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 19 A19 --- Name Name of cluster candidate 21- 27 F7.3 deg ra Right ascension in decimal degrees (J2000) 29- 35 F7.3 deg dec ? Declination in decimal degrees (J2000) 37- 41 F5.3 --- zphot Cluster photometric redshift 43- 47 F5.3 --- e_zphot Uncertainty in zphot 49- 52 F4.1 --- SNR_P Signal-to-Noise ratio from Poisson background noise 54- 57 F4.1 --- SNR_G Signal-to-Noise ratio from Gaussian background noise 59- 77 A19 --- NameF Name of foreground cluster detection (1) 79- 83 F5.3 --- CNNprob ? Convolutional Neural Network probability that a detection is not spurious 85-109 A25 --- LitName Name of cluster in literature (2) 111-137 A27 --- r_LitName Reference for LitName (3) 139-143 F5.3 --- zspec ? Cluster spectroscopic redshift (2) 145-146 I2 --- r_zspec ? Literature reference for zspec (3) -------------------------------------------------------------------------------- Note (1): If the foreground and background clusters share identical names, letter A is added to the name of the foreground clusters while letter B is added to the background cluster. Note (2): Literature Names and spectroscopic redshift are names and spectroscopic redshift of clusters in literature that are match to cluster in MaDCoWS2. Note (3): 1 = Abell et al. (1989) [1989ApJS...70....1A]; 2 = Hilton et al. (2021) [2021ApJS..253....3H]; 3 = Bocquet et al. (2019) [2019ApJ...878...55B]; 4 = Planck Collaboration et al. (2016) [2016A&A...594A..27P]; 5 = Gioia et al. (1990) [1990ApJS...72..567G]; 6 = Ebeling et al. (2001) [2001ApJ...553..668E]; 7 = Gladders & Yee (2005) [2005ApJS..157....1G]; 8 = Bulbul et al. (2024) [2024A&A...685A.106B]; 9 = Balogh et al. (2021) [2021MNRAS.500..358B]; 10 = Muzzin et al. (2012) [2012ApJ...746..188M], Balogh et al. (2017) [2017MNRAS.470.4168B]; 11 = Andreon et al. (2009) [2009A&A...507..147A]; 12 = Papovich et al. (2010) [2010ApJ...716.1503P]; 13 = Adami et al. (2018) [2018A&A...620A...5A]; 14 = Liu et al. (2022) [2022A&A...661A...2L]; 15 = Mehrtens et al. (2012) [2012MNRAS.423.1024M]; 16 = Rykoff et al. (2016) [2016ApJS..224....1R]; 17 = Gonzalez et al. (2019) [2019ApJS..240...33G]; 18 = Oguri et al. (2018) [2018PASJ...70S..20O]; 19 = Radovich et al. (2017) [2017A&A...598A.107R]; 20 = Wen et al. (2012) [2012ApJS..199...34W]; 21 = Wen & Han (2015) [2015ApJ...807..178W]; 22 = Wen & Han (2021) [2021MNRAS.500.1003W]; 23 = Wen & Han (2022) [2022MNRAS.513.3946W]; 24 = Wen & Han (2024) [2024ApJS..272...39W]. 15 = Mehrtens et al. (2012) [2012MNRAS.423.1024M]; 16 = Rykoff et al. (2016) [2016ApJS..224....1R]; 17 = Gonzalez et al. (2019) [2019ApJS..240...33G]; 18 = Oguri et al. (2018) [2018PASJ...70S..20O]; 19 = Radovich et al. (2017) [2017A&A...598A.107R]; 20 = Wen et. al (2012) [2012ApJS..199...34W]; 21 = Wen & Han (2015) [2015ApJ...807..178W]; 22 = Wen & Han (2021) [2021MNRAS.500.1003W]; 23 = Wen & Han (2022) [2022MNRAS.513.3946W]; 24 = Wen & Han (2024) [2024ApJS..272...39W]. Note (3): If the foreground and background clusters share identical names, letter A is added to the name of the foreground clusters while letter B is added to the background cluster. Note (4): no data entry for any column is null except for CNNprob and zspec which is -1.000