improve the docs - we have two vectorized queries
@@ -22,8 +22,9 @@ vary, but you should not submit more than ~5-10 queries per second.
If you want to perform large queries, we suggest using vectorized queries
when possible. You can pass `~astroquery.simbad.Simbad.query_region`
-a vector of coordinates, and SIMBAD will treat this as one query.
-See `query regions <Query Regions>`_ below.
+a vector of coordinates or `~astroquery.simbad.Simbad.query_objects`
+a list of object names, and SIMBAD will treat this submission as a single
+query. See `vectorized queries <Vectorized Queries>`_ below.
Query an Identifier
-------------------
@@ -222,8 +223,8 @@ to 2000.0. So here is a query with all the options utilized:
TYC 607-418-1 00 49 09.636 ... 2000A&A...355L..27H
-Query Regions
--------------
+Vectorized Queries
+------------------
You can query multiple regions at once using vectorized queries.
Each region must have the same radius.
@@ -253,6 +254,23 @@ Each region must have the same radius.
SDSS J004422.75+110104.3 00 44 22.753 +11 01 04.34 7 7 -- -- 0 C O 2017A&A...597A..79P
TYC 607-628-1 00 44 05.6169 +11 05 41.195 14 14 0.047 0.033 90 A O 2018yCat.1345....0G
+You can do the same based on IDs:
+
+ >>> from astroquery.simbad import Simbad
+ >>> result_table = Simbad.query_objects(["m1","m2","m3","m4"])
+ >>> print(result_table)
+
+However, note that missing data will result in missing lines:
+
+ >>> from astroquery.simbad import Simbad
+ >>> result_table = Simbad.query_objects(["m1","notanobject","m2","m1000"])
+ >>> print(result_table)
+
+Only the results for m1 and m2 are included. As of May 2019, there is a
+feature request in place with SIMBAD to return blank rows with the queried
+identifier indicated.
+
+
Query a catalogue
-----------------
