diff --git a/frb/surveys/catalog_utils.py b/frb/surveys/catalog_utils.py
index de99058d..9d993a04 100644
--- a/frb/surveys/catalog_utils.py
+++ b/frb/surveys/catalog_utils.py
@@ -160,9 +160,10 @@ def summarize_catalog(frbc, catalog, summary_radius, photom_column, magnitude):
     return summary_list
 
 
-def xmatch_catalogs(cat1:Table, cat2:Table, skydist:units.Quantity = 5*units.arcsec,
+def xmatch_catalogs(cat1:Table, cat2:Table, dist:units.Quantity = 5*units.arcsec,
                      RACol1:str = "ra", DecCol1:str = "dec",
                      RACol2:str = "ra", DecCol2:str = "dec",
+                     distcol1:str = None, distcol2:str = None,
                      return_match_idx:bool=False)->tuple:
     """
     Cross matches two astronomical catalogs and returns
@@ -171,15 +172,21 @@ def xmatch_catalogs(cat1:Table, cat2:Table, skydist:units.Quantity = 5*units.arc
         cat1, cat2: astropy Tables
             Two tables with sky coordinates to be
             matched.
-        skydist: astropy Quantity, optional
+        dist: astropy Quantity, optional
             Maximum separation for a valid match.
-            5 arcsec by default.
+            5 arcsec by default. Can be length units
+            if distcol1 and distcol2 are provided.
         RACol1, RACol2: str, optional
             Names of columns in cat1 and cat2
             respectively that contain RA in degrees.
         DecCol1, DecCol2: str, optional
             Names of columns in cat1 and cat2
             respectively that contain Dec in degrees.
+        distcol1, distcol2: str, optional
+            Names of columns in cat1 and cat2
+            respectively that contain the radial distance
+            as floats in Mpc. If None, 2D cross-matches
+            are returned.
         return_match_idx: bool, optional
             Return the indices of the matched entries with
             with the distance instead?
@@ -193,19 +200,31 @@ def xmatch_catalogs(cat1:Table, cat2:Table, skydist:units.Quantity = 5*units.arc
     assert isinstance(cat1, (Table, QTable))&isinstance(cat1, (Table, QTable)), "Catalogs must be astropy Table instances."
     assert (RACol1 in cat1.colnames)&(DecCol1 in cat1.colnames), " Could not find either {:s} or {:s} in cat1".format(RACol1, DecCol1)
     assert (RACol2 in cat2.colnames)&(DecCol2 in cat2.colnames), " Could not find either {:s} or {:s} in cat2".format(RACol2, DecCol2)
+    do_3d = (distcol1 is not None)&(distcol2 is not None)
+    if do_3d:
+        assert (distcol1 in cat1.colnames)&(distcol2 in cat2.colnames), "Could not find either {:s} or {:s} in cat1".format(distcol1, distcol2)
+        dist1 = cat1[distcol1]*units.Mpc
+        dist2 = cat2[distcol2]*units.Mpc
+    else:
+        dist1 = None
+        dist2 = None
     # Get corodinates
-    cat1_coord = SkyCoord(cat1[RACol1], cat1[DecCol1], unit = "deg")
-    cat2_coord = SkyCoord(cat2[RACol2], cat2[DecCol2], unit = "deg")
+    cat1_coord = SkyCoord(cat1[RACol1]*units.deg, cat1[DecCol1]*units.deg, distance=dist1)
+    cat2_coord = SkyCoord(cat2[RACol2]*units.deg, cat2[DecCol2]*units.deg, distance=dist2)
 
     # Match 2D
-    idx, d2d, _ = cat1_coord.match_to_catalog_sky(cat2_coord)
+    idx, d2d, d3d = cat1_coord.match_to_catalog_sky(cat2_coord)
 
     # Get matched tables
-    match1 = cat1[d2d < skydist]
-    match2 = cat2[idx[d2d < skydist]]
+    if do_3d:
+        separation = d3d
+    else:
+        separation = d2d
+    match1 = cat1[separation < dist]
+    match2 = cat2[idx[separation < dist]]
 
     if return_match_idx:
-        return idx, d2d
+        return idx, d2d, d3d
     else:
         return match1, match2
 
diff --git a/frb/surveys/cluster_search.py b/frb/surveys/cluster_search.py
index 1b4738c4..2402ac1f 100644
--- a/frb/surveys/cluster_search.py
+++ b/frb/surveys/cluster_search.py
@@ -8,6 +8,7 @@
 from frb.defs import frb_cosmo
 from astropy.coordinates import SkyCoord
 from astropy import units as u
+from astropy.table import Table
 
 try:
     from astroquery.vizier import Vizier
@@ -22,11 +23,11 @@ class VizierCatalogSearch(surveycoord.SurveyCoord):
     """
 
 
-    def __init__(self, coord, radius = 90*u.deg, catalog = None, cosmo=None, **kwargs):
+    def __init__(self, coord, radius = 90*u.deg, survey=None, viziercatalog = None, cosmo=None, **kwargs):
         # Initialize a SurveyCoord object
-        surveycoord.SurveyCoord.__init__(self, coord, radius, **kwargs)
-        self.survey = None # Name
-        self.catalog = catalog # Name of the Vizier table to draw from.
+        super(VizierCatalogSearch, self).__init__(coord, radius, **kwargs)
+        self.survey = survey # Name
+        self.viziercatalog = viziercatalog # Name of the Vizier table to draw from.
         self.coord = coord # Location around which to perform the search
         self.radius = radius.to('deg').value # Radius of cone search
         if cosmo is None: # Use the same cosmology as elsewhere in this repository unless specified.
@@ -34,13 +35,46 @@ def __init__(self, coord, radius = 90*u.deg, catalog = None, cosmo=None, **kwarg
         else:
             self.cosmo = cosmo
     
-
-    def get_catalog(self, query_fields=None, transverse_distance_cut = 5*u.Mpc, **kwargs):
+    def clean_catalog(self, catalog):
+        """
+        This will be survey specific.
+        """
         pass
 
-        
+    def _transverse_distance_cut(self, catalog, transverse_distance_cut, distance_column='Dist'):
+        # Apply a transverse distance cut
+        angular_dist = self.coord.separation(SkyCoord(catalog['ra'], catalog['dec'], unit='deg')).to('rad').value
+        transverse_dist = catalog[distance_column]*np.sin(angular_dist)
+        catalog = catalog[transverse_dist<transverse_distance_cut]
+        return catalog
+
+    def _get_catalog(self, query_fields=None, **kwargs):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+            If no objects found, returns an empty table with fields ['ra','dec', and 'z'].
+        """
+        if query_fields is None:
+            query_fields = ['**'] # Get all.
+
+        # Query Vizier
+        v = Vizier(catalog = self.viziercatalog, columns=query_fields, row_limit= -1, **kwargs) # No row limit
+        result = v.query_region(self.coord, radius=self.radius*u.deg)
+        if len(result) == 0:
+            print("No objects found within the given radius.")
+            return Table(names = ('ra','dec','z'))
+        else:
+            result = result[0]
+        return result
 
-class TullyGroupCat(surveycoord.SurveyCoord):
+# Tully 2015
+class TullyGroupCat(VizierCatalogSearch):
     """
     A class to query sources within the Tully 2015
     group/cluster catalog.
@@ -49,18 +83,26 @@ class TullyGroupCat(surveycoord.SurveyCoord):
 
     def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
         # Initialize a SurveyCoord object
-        surveycoord.SurveyCoord.__init__(self, coord, radius, **kwargs)
-        self.survey = 'Tully_2015' # Name
-        self.catalog = "J/AJ/149/171/table5" # Name of the Vizier table to draw from.
-        self.coord = coord # Location around which to perform the search
-        self.radius = radius.to('deg').value # Radius of cone search
-        if cosmo is None: # Use the same cosmology as elsewhere in this repository unless specified.
-            self.cosmo = frb_cosmo
-        else:
-            self.cosmo = cosmo
+        super(TullyGroupCat, self).__init__(coord, radius,
+                                            survey="Tully+2015",
+                                            viziercatalog="J/AJ/149/171/table5",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+
+        catalog.rename_columns(['_RA.icrs', '_DE.icrs', 'Nmb'], ['ra', 'dec', 'Ngal']) # Rename the columns to match the SurveyCoord class
+        
+        # Convert distances from h^-1 Mpc to Mpc based on the cosmology being used.
+        catalog['Dist'] /=self.cosmo.h
+        rec_velocity = catalog['Dist'].value*self.cosmo.H0.value
+        c_kms = 299792.458
+        redshift = ((1+rec_velocity/c_kms)/(1-rec_velocity/c_kms))**0.5-1
+        catalog['Dist'] = self.cosmo.angular_diameter_distance(redshift).value
+        return catalog
     
 
-    def get_catalog(self, query_fields=None, transverse_distance_cut = np.inf*u.Mpc, richness_cut = 5):
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc, richness_cut = 5):
         """
         Get the catalog of objects
         Args:
@@ -71,21 +113,413 @@ def get_catalog(self, query_fields=None, transverse_distance_cut = np.inf*u.Mpc,
         Returns:
             A table of objects within the given limits.
         """
-        if query_fields is None:
-            query_fields = ['**'] # Get all.
-        # Query Vizier
-        v = Vizier(catalog = self.catalog, columns=query_fields, row_limit= -1) # No row limit
-        result = v.query_region(self.coord, radius=self.radius*u.deg)[0] # Just get the first (and only table here)
-        result.rename_columns(['_RA.icrs', '_DE.icrs'], ['ra', 'dec']) # Rename the columns to match the SurveyCoord class
+        result = super(TullyGroupCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+            # Apply a transverse distance cut
+            if transverse_distance_cut<np.inf*u.Mpc:
+                result = super(TullyGroupCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+            result = result[result['Ngal']>=richness_cut]
+        self.catalog = result
+
+        return self.catalog
+    
+# Wen+2024
+class WenGroupCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Wen+2024
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 0.2*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(WenGroupCat, self).__init__(coord, radius,
+                                            survey="Wen+2024",
+                                            viziercatalog="J/ApJS/272/39/table2",
+                                            cosmo=cosmo,  **kwargs)
         
-        # Convert distances from h^-1 Mpc to Mpc based on the cosmology being used.
-        result['Dist'] /=self.cosmo.h
+    def clean_catalog(self, catalog):
+        try:
+            catalog.rename_columns(['RAJ2000'],['ra'])
+        except KeyError:
+            assert 'ra' in catalog.keys()
+        try:
+            catalog.rename_columns(['DEJ2000'],['dec'])
+        except KeyError:
+            assert 'dec' in catalog.keys()
+        try:
+            catalog.rename_columns(['zCl'],['z'])
+        except KeyError:
+            assert 'z' in catalog.keys()
+
+        
+        # Add a distance estimate in Mpc using the given cosmology
+        catalog['Dist'] = self.cosmo.angular_diameter_distance(catalog['z']).value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc, richness_cut = 5):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(WenGroupCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+            # Apply a transverse distance cut
+            if transverse_distance_cut<np.inf*u.Mpc:
+                result = super(TullyGroupCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+            result = result[result['Ngal']>=richness_cut]
+        self.catalog = result
+        return self.catalog
+    
+# Bahk and Hwang 2024 (Updated Planck+2015)
+class UPClusterSZCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Bahk and Hwang 2024
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(UPClusterSZCat, self).__init__(coord, radius,
+                                            survey="UPClusterSZ",
+                                            viziercatalog="J/ApJS/272/7/table2",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            try:
+                catalog.rename_columns(['RAJ2000', 'DEJ2000'], ['ra', 'dec']) # Rename the columns to match the SurveyCoord class
+            except KeyError:
+                print(catalog.keys())
+
+                assert 'ra' in catalog.keys() and 'dec' in catalog.keys()
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(catalog['z']).value
+
+        return catalog
+
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(UPClusterSZCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+        # Apply a transverse distance cut
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(UPClusterSZCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+        self.catalog = result
+        return self.catalog
+    
+# Xu+2022 (ROSAT X ray cluster)
+
+class ROSATXClusterCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Xu+2022
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(ROSATXClusterCat, self).__init__(coord, radius,
+                                            survey="ROSATXCluster",
+                                            viziercatalog="J/A+A/658/A59/table3",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            catalog.rename_columns(['RAJ2000', 'DEJ2000'], ['ra', 'dec']) # Rename the columns to match the SurveyCoord class
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(catalog['z']).value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(ROSATXClusterCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+        # Apply a transverse distance cut
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(ROSATXClusterCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+        self.catalog = result
+        return self.catalog
+    
+# Tempel+2018
+
+class TempelClusterCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Tempel+2018
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(TempelClusterCat, self).__init__(coord, radius,
+                                            survey="TempelCluster",
+                                            viziercatalog="J/A+A/618/A81/2mrs_gr",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            catalog.rename_columns(['RAJ2000', 'DEJ2000', 'zcmb'], ['ra', 'dec', 'z']) # Rename the columns to match the SurveyCoord class
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(catalog['z']).to('Mpc').value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(TempelClusterCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+        # Apply a transverse distance cut
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(TempelClusterCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+        self.catalog = result
+        return self.catalog
+
+
+# Klein+ 2023 RASS-MCMF (Rosat All Sky Survey Multi Component Matched Filter)
+
+class RASSClusterCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Klein+ 2023
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(RASSClusterCat, self).__init__(coord, radius,
+                                            survey="RASSCluster",
+                                            viziercatalog="J/MNRAS/526/3757/catalog",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            catalog.rename_columns(['RAJ2000', 'DEJ2000','zsp1'], ['ra', 'dec','z']) # Rename the columns to match the SurveyCoord class
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(catalog['z']).value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(RASSClusterCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+        # Apply a transverse distance cut
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(RASSClusterCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+        self.catalog = result
+        return self.catalog
+
+    
+# Rykoff+ 2014 Clusters identified in SDSS8 using red mapper algorithm
+
+class RedMapperClusterCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Rykoff+ 2014
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(RedMapperClusterCat, self).__init__(coord, radius,
+                                            survey="RedMapperCluster",
+                                            viziercatalog="J/ApJ/785/104/table1",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            catalog.rename_columns(['RAJ2000', 'DEJ2000','zspec'], ['ra', 'dec','z']) # Rename the columns to match the SurveyCoord class
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            redshift = catalog['z']
+            redshift[redshift<0] = catalog['zlambda'][redshift<0]
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(redshift).value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(RedMapperClusterCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
 
         # Apply a transverse distance cut
-        angular_dist = self.coord.separation(SkyCoord(result['ra'], result['dec'], unit='deg')).to('rad').value
-        transverse_dist = result['Dist']*np.sin(angular_dist)
-        result = result[transverse_dist<transverse_distance_cut]
-        result = result[result['Nmb']>=richness_cut]
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(RedMapperClusterCat, self)._transverse_distance_cut(result, transverse_distance_cut)
         self.catalog = result
+        return self.catalog
+
+    
+# Klein+ 2024 Clusters identified in ACT data release 5
+
+class ACTDR5ClusterCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Klein+ 2024
+    group/cluster catalog.
+    """
+
 
-        return self.catalog
\ No newline at end of file
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(ACTDR5ClusterCat, self).__init__(coord, radius,
+                                            survey="ACTDR5Cluster",
+                                            viziercatalog="J/A+A/690/A322/catalog",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            catalog.rename_columns(['RAJ2000', 'DEJ2000', 'z1C'], ['ra', 'dec','z']) # Rename the columns to match the SurveyCoord class
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            redshift = catalog['z']
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(redshift).value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(ACTDR5ClusterCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+        # Apply a transverse distance cut
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(ACTDR5ClusterCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+        self.catalog = result
+        return self.catalog
+
+    
+# Kluge+ 2024 Clusters identified in eRosita x-ray all sky survey
+
+class ERASSClusterCat(VizierCatalogSearch):
+    """
+    A class to query sources within the Kluge+ 2024
+    group/cluster catalog.
+    """
+
+
+    def __init__(self, coord, radius = 90*u.deg, cosmo=None, **kwargs):
+        # Initialize a SurveyCoord object
+        super(ERASSClusterCat, self).__init__(coord, radius,
+                                            survey="ERASSCluster",
+                                            viziercatalog="J/A+A/688/A210/tablee1",
+                                            cosmo=cosmo,  **kwargs)
+        
+    def clean_catalog(self, catalog):
+        if len(catalog) > 0:
+            catalog.rename_columns(['RAJ2000', 'DEJ2000', 'Bestz'], ['ra', 'dec','z']) # Rename the columns to match the SurveyCoord class
+            
+            # Add a distance estimate in Mpc using the given cosmology
+            redshift = catalog['z']
+            catalog['Dist'] = self.cosmo.angular_diameter_distance(redshift).value
+
+        return catalog
+    
+    def get_catalog(self, query_fields=None,
+                    transverse_distance_cut = np.inf*u.Mpc):
+        """
+        Get the catalog of objects
+        Args:
+            z_lim (float): The maximum redshift of the objects to include in the catalog.
+            transverse_distance_cut (Quantity): The maximum impact parameter of the objects to include in the catalog.
+            richness_cut (int): The minimum number of members in any group/cluster returned.
+            query_fields (list): The fields to include in the catalog. If None, all fields are used.
+        Returns:
+            A table of objects within the given limits.
+        """
+        result = super(ERASSClusterCat, self)._get_catalog(query_fields=query_fields)
+        if len(result) > 0:
+            result = self.clean_catalog(result)
+
+        # Apply a transverse distance cut
+        if transverse_distance_cut<np.inf*u.Mpc:
+            result = super(ERASSClusterCat, self)._transverse_distance_cut(result, transverse_distance_cut)
+        self.catalog = result
+        return self.catalog