Discovery of brown dwarfs mining the 2MASS and SDSS databases

Discovery of brown dwarfs mining the 2MASS and SDSS databases#

F. Jiménez-Esteban¹, K. A. Lutz², E. Solano¹

Spanish Virtual Observatory
Université de Strasbourg, CNRS, Observatoire Astronomique de Strasbourg, UMR 7550, F-67000, Strasbourg, France

This tutorial is based on the EURO-VO tutorial of the same name: http://www.euro-vo.org/sites/default/files/documents/tutorial-brown-dwarfs_2019Apr.pdf .

Introduction#

Brown dwarfs are objects occupying the gap between the least massive stars and the most massive planets. They are intrinsically faint objects. Hence, heir detection is not straightforward and, in fact, was almost impossible until the advent of global surveys at deep optical and near-infrared bands like SDSS, 2MASS or DENIS. We propose here to mine the 2MASS point source catalogue (2MASS-PSC) and SDSS-DR9 databases to identify T-type brown dwarfs through an appropriate combination of colors in the optical and the infrared, an approach that perfectly fits into the Virtual Observatory.

In this use case, we explore different ways to do the same tasks with different VO tools. These tasks include:

obtaining data from the SDSS and 2MASS catalogues in a given sky region,
crossmatching the results of these searches,
filtering the resulting table for brown dwarfs, and
verifying our sample of brown dwarfs.

Software packages needed for this tutorial are Aladin, TOPCAT, STILTS and Python (or you may just use the Binder in your web browser).

# Standard Library
from pathlib import Path

# Astronomy tools
from astropy import units as u
from astropy.coordinates import SkyCoord

# Access astronomical databases
import pyvo
from astroquery.simbad import Simbad
from astroquery.vizier import Vizier
from astroquery.xmatch import XMatch

# Sky visualization
from ipyaladin import Aladin

Step #1: Discovery#

We start by searching for the 2MASS point source catalogue (2MASS-PSC) and the SDSS data release 9 catalogue (SDSS DR9). To find and query catalogues, there are two packages we can use: pyVO and astroquery. We will show pyVO for searching the 2MASS-PSC and astroquery for SDSS DR9.

With the pyVo package we are using the TAP service of VizieR. TAP is a Virtual Observatory protocol to query databases of tables. The language we use to compile the query is called ADQL and is similar to SQL. For more details on ADQL see also the dedicated VO tutorial (http://docs.g-vo.org/adql-gaia/html/).

tap_vizier = pyvo.dal.TAPService("https://tapvizier.cds.unistra.fr/TAPVizieR/tap")

query = """
SELECT  * 
FROM tables
WHERE description LIKE '%2MASS%Cutri%'
"""

mass_psc_set = tap_vizier.search(query).to_table()
mass_psc_set["table_name", "description"]

Table length=13

table_name	description
object	object
J/ApJ/569/23/table1	Optical polarimetry of 2MASS Red QSOs ( Smith P.S., Schmidt G.D., Hines D.C., Cutri R.M., Nelson B.O.)
II/281/2mass6x	2MASS-6X catalog ( Cutri R.M., Skrutskie M.F., Van Dyk S., et al.)
J/ApJ/780/92/2mass	2MASS JHKs photometry (table5) ( Szabo R., Ivezic Z., Kiss L.L., Kollath Z., Jones L., Sesar B., Becker A.C., Davenport J.R.A., Cutri R.M.)
II/246/out	2MASS Point Source Catalogue, output (on a total of 470,992,970 sources) ( Cutri R.M., Skrutskie M.F., Van Dyk S., et al.)
J/ApJ/564/421/table3	2MASS IDR2 Sources Unconfirmed in Second Epoch Imaging ( Burgasser A.J., Kirkpatrick J.D., Brown M.E., Reid I.N., Burrows A., Liebert J., Matthews K., Gizis J.E., Dahn C.C., Monet D.G., Cutri R.M., Skrutskie M.F.)
VII/233/xsc	*The 2MASS Extended Catalog (2MASX) ( Skrutskie M.F., Cutri R.M., Stiening R., et al.)
II/241/out	2MASS Point Source Catalogue, 2MASS 2000 Second Incremental Release ( Skrutskie M.F., Schneider S.E., Stiening R., Strom S.E., Weinberg M.D., Beichman C., Chester T., Cutri R., Lonsdale C., Elias J., Elston R., Capps R., Carpenter J., Huchra J., Liebert J., Monet D., Price S., Seitzer P.)
J/ApJ/569/23/table3	Galactic interstellar polarization detected in the fields of 2MASS AGNs ( Smith P.S., Schmidt G.D., Hines D.C., Cutri R.M., Nelson B.O.)
J/ApJ/569/23/table2	Optical polarimetry of other AGN found by 2MASS ( Smith P.S., Schmidt G.D., Hines D.C., Cutri R.M., Nelson B.O.)
J/AJ/126/63/table1	2MASS sample and measurements ( Hutchings J.B., Maddox N., Cutri R.M., Nelson B.O.)
J/ApJS/190/100/table1	List of 2MASS proper motion candidates ( Kirkpatrick J.D., Looper D.L., Burgasser A.J., Schurr S.D., Cutri R.M., Cushing M.C., Cruz K.L., Sweet A.C., Knapp G.R., Barman T.S., Bochanski J.J., Roellig T.L., McLean I.S., McGovern M.R., Rice E.L.)
J/ApJ/564/421/table5	Comparison of NIRC Spectrophotometric colors to 2MASS photometry ( Burgasser A.J., Kirkpatrick J.D., Brown M.E., Reid I.N., Burrows A., Liebert J., Matthews K., Gizis J.E., Dahn C.C., Monet D.G., Cutri R.M., Skrutskie M.F.)
J/ApJ/564/421/table6	New T Dwarfs Identified in the 2MASS Catalog ( Burgasser A.J., Kirkpatrick J.D., Brown M.E., Reid I.N., Burrows A., Liebert J., Matthews K., Gizis J.E., Dahn C.C., Monet D.G., Cutri R.M., Skrutskie M.F.)

As mentioned above we are interested in the 2MASS-pSC, which has the table_name II/246/out in VizieR. Before we move on to construct a more complicated query, we have a quick look at the 2MASS-PSC table and all the available columns. We do so by downloading the first 5 rows:

query = 'SELECT TOP 5 * FROM "II/246/out" '
mass_psc_head = tap_vizier.search(query).to_table()
mass_psc_head

Table length=5

RAJ2000	DEJ2000	errMaj	errMin	errPA	2MASS	Jmag	Jcmsig	e_Jmag	Jsnr	Hmag	Hcmsig	e_Hmag	Hsnr	Kmag	Kcmsig	e_Kmag	Ksnr	Qflg	Rflg	Bflg	Cflg	Ndet	prox	pxPA	pxCntr	Xflg	Aflg	Cntr	Hemis	Date	Scan	GLON	GLAT	Xscan	JD	Jpsfchi	Hpsfchi	Kpsfchi	Jstdap	e_Jstdap	Hstdap	e_Hstdap	Kstdap	e_Kstdap	edgeNS	edgeEW	edge	dup	use	opt	Dopt	PAopt	Bmag	Rmag	Nopt	extKey	scanKey	coaddKey	coadd
deg	deg	arcsec	arcsec	deg		mag	mag	mag		mag	mag	mag		mag	mag	mag							arcsec	deg								deg	deg	arcsec	d				mag	mag	mag	mag	mag	mag	arcsec	arcsec					arcsec	deg	mag	mag
float64	float64	float32	float32	int16	object	float32	float32	float32	float64	float32	float32	float32	float64	float32	float32	float32	float64	object	object	object	object	object	float32	int16	int64	int16	int16	int64	str1	object	int16	float32	float32	float32	float64	float32	float32	float32	float32	float32	float32	float32	float32	float32	int32	int16	object	int16	int16	str1	float32	int16	float32	float32	int16	int32	int32	int32	int16
44.996055	0.005565	0.17	0.16	76	02595905+0000200	16.376	0.097	0.097	11.3	15.77	0.139	0.14	8.2	15.258	0.141	0.141	7.6	ABB	222	111	000	060606	44.5	230	1290669337	0	0	1290669325	s	1998-09-28	112	176.951	-48.902	-138.9	2451084.8062	0.75	1.21	1.13	16.651	0.221	15.434	0.134	15.478	0.434	521	114	ne	1	1	U	0.7	156	17.9	16.9	1	--	69347	1594959	9
45.004857	0.019806	0.06	0.06	90	03000116+0001113	12.529	0.021	0.024	389.8	11.954	0.029	0.03	273.7	11.874	0.027	0.029	172.5	AAA	222	111	000	666666	4.8	330	1290669298	0	0	1290669300	s	1998-09-28	112	176.945	-48.885	-170.6	2451084.8062	1.15	1.31	1.97	12.508	0.019	11.91	0.025	11.852	0.008	469	82	ne	1	1	U	1.5	72	15.0	13.8	1	--	69347	1594959	9
45.004193	0.020956	0.06	0.06	90	03000100+0001154	14.845	0.055	0.056	46.2	14.223	0.077	0.077	33.9	14.016	0.055	0.055	24.0	AAA	222	111	ccc	666666	4.8	150	1290669300	0	0	1290669298	s	1998-09-28	112	176.943	-48.885	-168.2	2451084.8062	0.86	0.89	1.11	13.889	0.101	13.035	0.126	12.97	0.043	465	84	ne	1	1	0	--	--	--	--	0	--	69347	1594959	9
44.995074	0.038204	0.38	0.31	0	02595881+0002175	16.746	0.133	0.134	8.0	15.814	0.139	0.14	7.8	16.125	0.324	0.324	3.4	BBD	222	111	000	060606	70.2	152	1290669298	0	0	1290669276	s	1998-09-28	112	176.914	-48.88	-135.4	2451084.8062	1.22	0.84	0.69	17.047	0.414	15.5	0.229	17.513	1.964	403	117	ne	0	1	0	--	--	--	--	0	--	69347	1594959	9
44.963851	0.043587	0.22	0.17	95	02595132+0002369	16.476	0.112	0.113	10.3	16.057	0.175	0.175	6.3	15.564	--	--	--	BCU	220	110	000	060600	89.4	207	1290669295	0	0	1290669271	s	1998-09-28	112	176.875	-48.898	-23.0	2451084.8062	1.13	1.07	--	17.113	0.34	18.739	3.527	--	--	384	229	ne	1	1	U	0.4	161	18.7	17.7	1	--	69347	1594959	9

As in the original tutorial, we only want to get data within a 14arcmin radius of RA=08h30m00s, Dec=01d30m00s. ADQL has a function, which allows to run an astronomical cone search query. From the quick inital inspection of the table we now know that we will need the columns RAJ2000 and DEJ2000 to only get sources at a certain location. Since we want to get colours for our Brown Dwarf candidates, we will also want to get the Jmag, Hmag and Kmag columns. For a different analysis you might want to choose other columns.

coord = SkyCoord(ra="08:30:00", dec="01:30:00", unit=(u.hourangle, u.deg))

query = """
SELECT * 
FROM \"II/246/out\" as tm_psc 
WHERE 1=CONTAINS(POINT(\'ICRS\', tm_psc.RAJ2000, tm_psc.DEJ2000),
                 CIRCLE(\'ICRS\', {:.3f}, {:.3f}, 14/60))
""".format(
    coord.ra.value,
    coord.dec.value,
)

mass_psc = tap_vizier.search(query).to_table()
mass_psc

Table length=683

RAJ2000	DEJ2000	errMaj	errMin	errPA	2MASS	Jmag	Jcmsig	e_Jmag	Jsnr	Hmag	Hcmsig	e_Hmag	Hsnr	Kmag	Kcmsig	e_Kmag	Ksnr	Qflg	Rflg	Bflg	Cflg	Ndet	prox	pxPA	pxCntr	Xflg	Aflg	Cntr	Hemis	Date	Scan	GLON	GLAT	Xscan	JD	Jpsfchi	Hpsfchi	Kpsfchi	Jstdap	e_Jstdap	Hstdap	e_Hstdap	Kstdap	e_Kstdap	edgeNS	edgeEW	edge	dup	use	opt	Dopt	PAopt	Bmag	Rmag	Nopt	extKey	scanKey	coaddKey	coadd
deg	deg	arcsec	arcsec	deg		mag	mag	mag		mag	mag	mag		mag	mag	mag							arcsec	deg								deg	deg	arcsec	d				mag	mag	mag	mag	mag	mag	arcsec	arcsec					arcsec	deg	mag	mag
float64	float64	float32	float32	int16	object	float32	float32	float32	float64	float32	float32	float32	float64	float32	float32	float32	float64	object	object	object	object	object	float32	int16	int64	int16	int16	int64	str1	object	int16	float32	float32	float32	float64	float32	float32	float32	float32	float32	float32	float32	float32	float32	int32	int16	object	int16	int16	str1	float32	int16	float32	float32	int16	int32	int32	int32	int16
127.509154	1.269173	0.2	0.15	87	08300219+0116090	15.963	0.095	0.096	12.5	15.546	0.121	0.122	9.0	14.93	0.144	0.144	8.1	ABB	222	111	000	160606	14.2	340	804040589	0	0	804040599	s	2000-01-30	58	223.554	22.408	178.5	2451573.6815	0.89	1.01	0.92	15.939	0.235	15.899	0.319	14.69	0.124	4589	74	sw	0	1	0	--	--	--	--	0	--	43956	1010984	221
127.507779	1.272875	0.12	0.11	86	08300186+0116223	15.594	0.083	0.084	17.6	15.563	0.117	0.117	8.9	15.272	0.181	0.182	5.9	ABC	222	111	000	360606	14.2	160	804040599	0	0	804040589	s	2000-01-30	58	223.55	22.408	183.4	2451573.6814	1.64	0.82	1.47	15.432	0.153	15.81	0.424	14.992	0.114	4602	69	sw	0	1	U	0.2	270	17.1	16.5	1	--	43956	1010984	221
127.514167	1.277495	0.23	0.21	51	08300340+0116389	16.553	0.17	0.171	7.3	16.179	0.194	0.194	5.0	15.894	--	--	--	CCU	220	110	000	060600	28.4	234	804040589	0	0	804040577	s	2000-01-30	58	223.549	22.416	160.4	2451573.6814	0.69	1.58	--	16.335	0.139	18.014	3.36	--	--	4619	92	sw	0	1	U	0.0	13	18.0	17.3	1	--	43956	1010984	221
127.463251	1.271903	0.07	0.07	0	08295118+0116188	15.844	0.076	0.077	14.0	15.11	0.095	0.096	13.5	15.029	0.138	0.138	7.4	AAB	222	111	000	260606	41.0	160	804019559	0	0	804019587	s	2000-01-30	57	223.528	22.369	-87.9	2451573.6739	1.78	0.8	1.14	15.935	0.238	15.077	0.164	15.197	0.438	4593	164	se	0	1	U	1.0	281	20.0	18.4	1	--	43955	1010947	56
127.463023	1.2864	0.06	0.06	0	08295112+0117110	14.093	0.029	0.032	70.0	13.652	0.033	0.035	51.7	13.553	0.042	0.043	28.9	AAA	222	111	000	666635	52.2	179	804019587	0	0	804019616	s	2000-01-30	57	223.514	22.376	-87.0	2451573.674	0.75	0.97	0.91	14.077	0.023	13.576	0.05	13.692	0.14	4646	165	se	0	1	U	0.4	160	16.3	14.6	1	--	43955	1010947	56
127.48465	1.271192	0.06	0.06	0	08295631+0116162	13.848	0.026	0.029	87.8	13.177	0.02	0.022	80.0	12.932	0.023	0.024	51.1	AAA	222	111	000	666655	15.7	12	804019600	0	0	804019585	s	2000-01-30	57	223.54	22.387	-164.9	2451573.6739	0.88	0.87	0.95	13.813	0.042	13.143	0.051	13.009	0.056	4591	87	se	0	1	U	0.2	244	18.8	16.7	1	--	43955	1010947	56
127.485565	1.275456	0.2	0.17	4	08295653+0116316	16.26	0.112	0.112	9.5	15.908	0.172	0.172	6.5	15.264	0.184	0.184	6.0	BCC	222	111	000	160606	15.7	192	804019585	0	0	804019600	s	2000-01-30	57	223.536	22.39	-168.2	2451573.674	0.84	1.3	0.8	16.125	0.291	15.529	0.253	15.21	0.246	4606	84	se	0	1	U	0.4	232	18.1	17.4	1	--	43955	1010947	56
127.494339	1.280734	0.15	0.15	145	08295864+0116506	16.317	0.119	0.12	9.0	15.818	0.141	0.141	7.0	15.099	--	--	--	BBU	220	110	000	060600	36.9	239	804019600	0	0	804019605	s	2000-01-30	57	223.536	22.4	-199.8	2451573.674	0.96	1.62	--	16.264	0.088	16.219	0.553	--	--	4625	52	se	1	1	0	--	--	--	--	0	--	43955	1010947	56
127.494645	1.296204	0.07	0.07	17	08295871+0117463	15.25	0.05	0.051	24.1	15.062	0.077	0.078	14.1	14.87	0.114	0.114	8.6	AAB	222	111	000	660506	47.1	299	804019652	0	0	804019639	s	2000-01-30	57	223.521	22.408	-200.9	2451573.674	0.98	0.89	1.01	15.178	0.064	15.195	0.302	14.779	0.326	4681	51	se	1	1	U	0.4	185	16.8	16.1	1	--	43955	1010947	56
127.483247	1.302628	0.06	0.06	0	08295597+0118094	13.484	0.025	0.027	122.7	12.862	0.02	0.022	106.9	12.807	0.033	0.034	57.4	AAA	222	111	000	665555	27.9	314	804019667	0	0	804019652	s	2000-01-30	57	223.509	22.401	-159.8	2451573.674	1.06	0.7	1.1	13.457	0.027	12.875	0.06	12.777	0.069	4704	92	se	0	1	U	2.0	195	16.3	14.5	1	--	43955	1010947	56
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
127.471749	1.699981	0.15	0.15	145	08295321+0141599	16.278	0.12	0.121	9.4	15.646	0.138	0.138	8.2	15.792	--	--	--	BBU	220	110	000	060600	21.5	111	804020536	0	0	804020539	s	2000-01-30	57	223.127	22.583	-118.5	2451573.6743	0.82	0.93	--	16.158	0.12	15.666	0.136	--	--	6134	134	se	0	1	U	0.5	178	18.2	17.1	1	--	43955	1010949	80
127.485472	1.701631	0.07	0.07	17	08295651+0142058	15.286	0.047	0.049	23.3	14.805	0.069	0.069	17.9	14.59	0.102	0.102	11.1	AAA	222	111	000	361506	32.4	245	804020536	0	0	804020544	s	2000-01-30	57	223.132	22.596	-167.8	2451573.6743	1.03	1.1	1.02	15.41	0.107	14.79	0.127	14.331	0.225	6140	84	se	0	1	U	0.5	227	17.9	16.6	1	--	43955	1010949	80
127.50233	1.707568	0.06	0.06	90	08300055+0142272	13.442	0.023	0.026	127.5	12.837	0.024	0.026	109.4	12.652	0.029	0.03	66.2	AAA	222	111	000	666655	24.1	173	804039600	0	0	804039583	s	2000-01-30	58	223.135	22.614	203.0	2451573.6811	1.13	0.79	1.5	13.483	0.018	12.913	0.029	12.71	0.045	6167	50	sw	1	1	U	1.1	262	17.2	15.1	1	--	43956	1010982	198
127.469423	1.71372	0.12	0.11	101	08295266+0142493	16.124	0.097	0.098	10.8	15.408	0.101	0.102	10.3	15.34	0.186	0.186	5.6	AAC	222	111	000	060606	50.2	170	804020539	0	0	804020569	s	2000-01-30	57	223.112	22.588	-110.1	2451573.6743	0.99	0.99	0.93	16.256	0.269	15.929	0.347	15.574	0.328	6184	142	se	0	1	0	--	--	--	--	0	--	43955	1010949	80
127.451948	1.721205	0.06	0.06	0	08294846+0143163	12.459	0.019	0.023	315.4	12.056	0.024	0.026	224.7	11.969	0.023	0.024	124.1	AAA	222	111	000	666666	48.4	192	804020559	0	0	804020588	s	2000-01-30	57	223.096	22.576	-47.2	2451573.6743	0.74	0.74	0.86	12.47	0.019	12.038	0.046	11.973	0.029	6211	205	se	0	1	U	1.3	176	14.8	13.5	1	--	43955	1010949	80
127.395474	1.69711	0.34	0.32	88	08293491+0141495	16.551	0.164	0.164	7.3	15.907	0.207	0.207	6.5	15.795	0.274	0.275	3.7	CED	222	111	000	060506	53.7	338	804020566	0	0	804020535	s	2000-01-30	57	223.089	22.515	156.0	2451573.6743	0.85	10.93	0.72	16.461	0.216	16.1	0.268	16.146	0.828	6125	97	sw	0	1	0	--	--	--	--	0	--	43955	1010949	80
127.432292	1.717116	0.07	0.06	96	08294375+0143016	14.569	0.032	0.035	45.2	14.299	0.055	0.056	28.5	14.219	0.084	0.084	15.6	AAA	222	111	000	665614	22.8	14	804020593	0	0	804020581	s	2000-01-30	57	223.09	22.557	23.5	2451573.6743	0.9	1.15	0.65	14.552	0.05	14.172	0.086	14.225	0.229	6197	229	sw	0	1	U	0.3	198	16.4	15.3	1	--	43955	1010949	80
127.433857	1.723263	0.07	0.07	17	08294412+0143237	15.678	0.08	0.081	16.3	15.207	0.105	0.105	12.3	14.965	0.138	0.138	7.9	AAB	222	111	ccc	665616	4.5	317	804020596	0	0	804020593	s	2000-01-30	57	223.085	22.561	17.9	2451573.6743	1.14	0.83	1.22	14.517	0.097	14.072	0.112	14.179	0.144	6219	235	sw	0	1	U	4.0	139	15.8	14.4	1	--	43955	1010949	80
127.531902	1.729757	0.06	0.06	90	08300765+0143471	14.155	0.033	0.036	66.1	13.84	0.032	0.033	43.4	13.806	0.048	0.049	22.9	AAA	222	111	000	666646	14.1	82	804039539	0	0	804039541	s	2000-01-30	58	223.13	22.65	96.6	2451573.6811	1.03	0.88	1.01	14.136	0.051	13.972	0.048	13.85	0.118	6247	156	sw	0	1	U	0.2	230	15.8	15.0	1	--	43956	1010982	198
127.53577	1.730293	0.37	0.35	45	08300858+0143490	17.047	0.231	0.231	4.6	16.123	0.19	0.19	5.3	15.872	0.302	0.303	3.4	DCD	222	111	000	060605	14.1	262	804039541	0	0	804039539	s	2000-01-30	58	223.131	22.654	82.7	2451573.6811	0.95	0.74	0.98	16.537	0.399	17.529	1.515	16.04	0.705	6249	170	sw	0	1	0	--	--	--	--	0	--	43956	1010982	198

Now that we have all the data we want from the 2MASS-PSC, we move on to query SDSS DR9 with astroquery. First we want to find out which tables are available:

catalog_list_sdss = Vizier.find_catalogs("SDSS DR9")
for catalog_ID, catalog in catalog_list_sdss.items():
    print(catalog_ID, ": ", catalog.description)

/home/manon.marchand/.conda/envs/build-jupybook/lib/python3.11/site-packages/astroquery/vizier/core.py:769: UserWarning: VOTABLE parsing raised exception: 1092:32: not well-formed (invalid token)
  warnings.warn("VOTABLE parsing raised exception: {0}".format(ex))

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astroquery/vizier/core.py:767, in parse_vizier_votable(data, verbose, invalid, get_catalog_names)
    766 try:
--> 767     vo_tree = votable.parse(tf, verify='warn', invalid='exception')
    768 except Exception as ex:

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/utils/decorators.py:604, in deprecated_renamed_argument.<locals>.decorator.<locals>.wrapper(*args, **kwargs)
    602         warnings.warn(msg, warning_type, stacklevel=2)
--> 604 return function(*args, **kwargs)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/table.py:177, in parse(source, columns, invalid, verify, chunk_size, table_number, table_id, filename, unit_format, datatype_mapping, _debug_python_based_parser)
    174 with iterparser.get_xml_iterator(
    175     source, _debug_python_based_parser=_debug_python_based_parser
    176 ) as iterator:
--> 177     return tree.VOTableFile(config=config, pos=(1, 1)).parse(iterator, config)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/tree.py:3900, in VOTableFile.parse(self, iterator, config)
   3899 if start:
-> 3900     tag_mapping.get(tag, self._add_unknown_tag)(
   3901         iterator, tag, data, config, pos
   3902     )
   3903 elif tag == "DESCRIPTION":

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/tree.py:3780, in VOTableFile._add_resource(self, iterator, tag, data, config, pos)
   3779 self.resources.append(resource)
-> 3780 resource.parse(self, iterator, config)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/tree.py:3576, in Resource.parse(self, votable, iterator, config)
   3564 tag_mapping = {
   3565     "TABLE": self._add_table,
   3566     "INFO": self._add_info,
   (...)
   3573     "DESCRIPTION": self._ignore_add,
   3574 }
-> 3576 for start, tag, data, pos in iterator:
   3577     if start:

ValueError: 1092:32: not well-formed (invalid token)

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astroquery/vizier/core.py:699, in VizierClass._parse_result(self, response, get_catalog_names, verbose, invalid)
    698 try:
--> 699     return parse_vizier_votable(
    700         response.content, verbose=verbose, invalid=invalid,
    701         get_catalog_names=get_catalog_names)
    702 except Exception as ex:

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astroquery/vizier/core.py:770, in parse_vizier_votable(data, verbose, invalid, get_catalog_names)
    769         warnings.warn("VOTABLE parsing raised exception: {0}".format(ex))
--> 770         vo_tree = votable.parse(tf, verify='warn', invalid='mask')
    771 elif invalid == 'exception':

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/utils/decorators.py:604, in deprecated_renamed_argument.<locals>.decorator.<locals>.wrapper(*args, **kwargs)
    602         warnings.warn(msg, warning_type, stacklevel=2)
--> 604 return function(*args, **kwargs)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/table.py:177, in parse(source, columns, invalid, verify, chunk_size, table_number, table_id, filename, unit_format, datatype_mapping, _debug_python_based_parser)
    174 with iterparser.get_xml_iterator(
    175     source, _debug_python_based_parser=_debug_python_based_parser
    176 ) as iterator:
--> 177     return tree.VOTableFile(config=config, pos=(1, 1)).parse(iterator, config)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/tree.py:3900, in VOTableFile.parse(self, iterator, config)
   3899 if start:
-> 3900     tag_mapping.get(tag, self._add_unknown_tag)(
   3901         iterator, tag, data, config, pos
   3902     )
   3903 elif tag == "DESCRIPTION":

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/tree.py:3780, in VOTableFile._add_resource(self, iterator, tag, data, config, pos)
   3779 self.resources.append(resource)
-> 3780 resource.parse(self, iterator, config)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astropy/io/votable/tree.py:3576, in Resource.parse(self, votable, iterator, config)
   3564 tag_mapping = {
   3565     "TABLE": self._add_table,
   3566     "INFO": self._add_info,
   (...)
   3573     "DESCRIPTION": self._ignore_add,
   3574 }
-> 3576 for start, tag, data, pos in iterator:
   3577     if start:

ValueError: 1092:32: not well-formed (invalid token)

During handling of the above exception, another exception occurred:

TableParseError                           Traceback (most recent call last)
Cell In[5], line 1
----> 1 catalog_list_sdss = Vizier.find_catalogs("SDSS DR9")
      2 for catalog_ID, catalog in catalog_list_sdss.items():
      3     print(catalog_ID, ": ", catalog.description)

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astroquery/vizier/core.py:235, in VizierClass.find_catalogs(self, keywords, include_obsolete, verbose, max_catalogs, return_type)
    231 if 'STOP, Max. number of RESOURCE reached' in response.text:
    232     raise ValueError("Maximum number of catalogs exceeded.  Try "
    233                      "setting max_catalogs to a large number and"
    234                      " try again")
--> 235 result = self._parse_result(response, verbose=verbose,
    236                             get_catalog_names=True)
    238 # Filter out the obsolete catalogs, unless requested
    239 if include_obsolete is False:

File ~/.conda/envs/build-jupybook/lib/python3.11/site-packages/astroquery/vizier/core.py:705, in VizierClass._parse_result(self, response, get_catalog_names, verbose, invalid)
    703         self.response = response
    704         self.table_parse_error = ex
--> 705         raise TableParseError("Failed to parse VIZIER result! The "
    706                               "raw response can be found in "
    707                               "self.response, and the error in "
    708                               "self.table_parse_error. The attempted "
    709                               "parsed result is in "
    710                               "self.parsed_result.\n Exception: " +
    711                               str(self.table_parse_error))
    712 elif response.content[:5] == b'#\n#  ':
    713     return parse_vizier_tsvfile(response.content, verbose=verbose)

TableParseError: Failed to parse VIZIER result! The raw response can be found in self.response, and the error in self.table_parse_error. The attempted parsed result is in self.parsed_result.
 Exception: 1092:32: not well-formed (invalid token)

We want to get data from the catalogue called V/139. As before let’s have a look at a few rows (per default Vizier.get_catalogs gives you 50 rows) of the code to figure out, which ones are most interesting for us.

test_sdss = Vizier.get_catalogs("V/139")
print(test_sdss)
test_sdss[0]

TableList with 1 tables:
	'0:V/139/sdss9' with 21 column(s) and 50 row(s) 

Table length=50

mode	q_mode	cl	SDSS9	m_SDSS9	Im	RA_ICRS	DE_ICRS	ObsDate	Q	umag	e_umag	gmag	e_gmag	rmag	e_rmag	imag	e_imag	zmag	e_zmag	zsp
						deg	deg	yr		mag	mag	mag	mag	mag	mag	mag	mag	mag	mag
uint8	str1	uint8	str19	str1	str2	float64	float64	float64	uint8	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float64
2		6	J025955.29+000252.0	*	Im	44.980386	0.047779	2003.8093	3	23.450	0.580	22.345	0.101	21.948	0.104	22.044	0.163	21.474	0.404	--
2		3	J025956.07+000300.0	*	Im	44.983649	0.050016	1998.8264	3	24.432	1.374	24.266	0.627	22.859	0.314	21.240	0.119	21.032	0.430	--
2		3	J025956.06+000259.9	*	Im	44.983619	0.049995	2002.7581	3	25.964	0.601	24.082	0.489	23.250	0.415	21.666	0.146	20.346	0.189	--
2		3	J025956.06+000259.7	*	Im	44.983618	0.049940	2003.7384	3	25.593	0.783	24.345	0.567	22.358	0.174	21.124	0.084	20.942	0.310	--
2		3	J025956.06+000259.9	*	Im	44.983616	0.049976	2001.7179	3	23.097	0.818	23.954	0.721	21.839	0.188	20.827	0.102	20.139	0.238	--
2		3	J025956.06+000259.9	*	Im	44.983614	0.049984	2007.8858	3	25.534	1.705	24.458	1.282	23.156	0.451	21.522	0.119	20.811	0.229	--
2		3	J025956.06+000259.9	*	Im	44.983607	0.049985	2002.8508	3	24.403	1.152	23.370	0.273	22.722	0.261	21.445	0.148	20.530	0.285	--
2		3	J025956.06+000259.9	*	Im	44.983606	0.049981	1998.7254	3	23.421	0.462	24.430	0.472	22.850	0.206	21.512	0.091	21.022	0.241	--
2		6	J025956.06+000300.0	*	Im	44.983596	0.050026	2003.9076	3	25.992	0.686	24.375	0.762	22.527	0.225	21.520	0.120	20.665	0.249	--
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
2		3	J025953.59+000242.0		Im	44.973316	0.045001	2008.0006	3	25.346	0.929	24.308	0.658	22.173	0.155	21.577	0.145	20.721	0.197	--
2		3	J025953.59+000241.9	*	Im	44.973304	0.044976	2002.8318	3	25.538	0.713	23.713	0.314	22.173	0.128	21.500	0.104	21.093	0.306	--
2		3	J025953.60+000242.0		Im	44.973350	0.045004	2007.8858	3	22.152	0.532	23.801	0.939	22.174	0.220	21.527	0.135	21.110	0.331	--
2		3	J025953.59+000241.9	*	Im	44.973294	0.044997	2003.9076	3	25.201	1.364	22.889	0.282	21.843	0.151	21.168	0.108	21.248	0.493	--
2		3	J025953.59+000241.9	*	Im	44.973291	0.044981	1998.8837	3	22.888	0.400	23.120	0.240	21.758	0.124	21.315	0.136	21.443	0.637	--
2		3	J025953.58+000241.8	*	Im	44.973286	0.044946	2001.7179	3	23.654	0.892	23.592	0.389	22.294	0.201	21.424	0.121	22.125	0.781	--
1	+	3	J025953.58+000241.9		Im	44.973284	0.044973	2003.8857	3	23.519	0.529	23.650	0.298	22.182	0.123	21.591	0.112	21.892	0.522	--
2		3	J025953.58+000241.9	*	Im	44.973274	0.044992	2003.8093	3	22.861	0.445	23.391	0.291	21.886	0.128	21.564	0.138	21.315	0.452	--
2		3	J025953.58+000241.9	*	Im	44.973274	0.044986	2001.8653	3	24.442	1.263	23.405	0.307	21.929	0.137	21.142	0.100	21.122	0.373	--
2		3	J025952.90+000248.4		Im	44.970415	0.046785	2002.8318	3	26.385	0.522	24.003	0.538	22.335	0.221	22.723	0.444	21.606	0.667	--

Again we want to get the coordinates of the source as well as magnitudes at all five SDSS bands (u, g, r, i and z), and a classification (cl). Do restrict the query to returning these columns and to get more than 50 rows returned, we create a custom Vizier object and then use this object to again query within 14arcmin of RA=08h30m00s, Dec=01d30m00s.

custom_vizier = Vizier(
    row_limit=-1,
    columns=["RA_ICRS", "DE_ICRS", "umag", "gmag", "rmag", "imag", "zmag", "cl"],
)
coord = SkyCoord(ra="08:30:00", dec="01:30:00", unit=(u.hourangle, u.deg))
sdss_results = custom_vizier.query_region(coord, radius=14 * u.arcmin, catalog="V/139")
sdss_results

TableList with 1 tables:
	'0:V/139/sdss9' with 8 column(s) and 12405 row(s) 

So we have one table in the resulting lists of tables. It is called V/139/sdss9. Let’s have a look at it:

sdss_results[0]

Table length=12405

RA_ICRS	DE_ICRS	umag	gmag	rmag	imag	zmag	cl
deg	deg	mag	mag	mag	mag	mag
float64	float64	float32	float32	float32	float32	float32	uint8
127.267366	1.512930	21.853	19.732	18.870	18.564	18.379	6
127.267372	1.512928	22.250	19.697	18.855	18.568	18.306	6
127.267372	1.512928	22.047	19.751	18.879	18.549	18.383	6
127.267727	1.495873	22.879	22.223	21.492	21.122	20.872	3
127.267754	1.495933	22.972	22.431	21.465	21.162	21.009	3
127.267831	1.500005	23.816	24.462	22.470	20.754	20.033	6
127.267836	1.495947	22.638	22.051	21.045	20.627	20.785	3
127.267853	1.499961	24.527	24.690	22.381	20.670	20.016	6
127.267955	1.499932	24.332	24.996	23.056	20.649	19.976	6
...	...	...	...	...	...	...	...
127.721086	1.454952	25.206	22.518	21.180	20.003	19.220	6
127.721092	1.454942	24.141	22.402	21.299	19.986	19.388	6
127.721106	1.454915	25.321	22.688	21.179	20.001	19.185	6
127.721135	1.433421	24.965	23.102	21.848	21.408	20.790	6
127.721294	1.428704	23.008	22.731	22.155	21.610	22.793	3
127.721770	1.431717	24.914	22.575	21.113	20.438	20.019	6
127.721857	1.451469	22.933	22.365	21.472	21.923	20.895	3
127.722534	1.455524	23.442	23.378	22.518	22.918	21.866	3
127.722635	1.433612	24.813	23.994	22.453	21.173	20.798	3
127.722672	1.455765	22.961	25.752	22.950	22.003	23.070	6

Step #2: Cross-matching#

In this next step, we find common sources in the 2MASS-PSC and SDSS-DR9 catalogues. One simple way to do this using the CDS XMatch service, which can also be reached with astroquery. The most reliable way to quuery XMatch is by uploading one of the tables (which will also make sure we stay in our region of interest) and crossmatching it to a table available in VizieR.

mass_psc.write("Data/2MASS_PSC.vot", format="votable", overwrite=True)
sdss_results[0].write("Data/SDSS_DR9.vot", format="votable", overwrite=True)

sdss_mass = XMatch.query(
    cat1=Path("Data/2MASS_PSC.vot").open(),
    cat2="vizier:V/139/sdss9",
    max_distance=4 * u.arcsec,
    colRA1="RAJ2000",
    colDec1="DEJ2000",
)
sdss_mass

Table length=717

angDist	RAJ2000	DEJ2000	errMaj	errMin	errPA	2MASS	Jmag	Jcmsig	e_Jmag	Jsnr	Hmag	Hcmsig	e_Hmag	Hsnr	Kmag	Kcmsig	e_Kmag	Ksnr	Qflg	Rflg	Bflg	Cflg	Ndet	prox	pxPA	pxCntr	Xflg	Aflg	Cntr	Hemis	Date	Scan	GLON	GLAT	Xscan	JD	Jpsfchi	Hpsfchi	Kpsfchi	Jstdap	e_Jstdap	Hstdap	e_Hstdap	Kstdap	e_Kstdap	edgeNS	edgeEW	edge	dup	use	opt	Dopt	PAopt	Bmag	Rmag	Nopt	extKey	scanKey	coaddKey	coadd	SDSS9	RAdeg	DEdeg	errHalfMaj	errHalfMin	errPosAng	umag	gmag	rmag	imag	zmag	e_umag	e_gmag	e_rmag	e_imag	e_zmag	objID	cl	q_mode	flags	Q	ObsDate	pmRA	e_pmRA	pmDE	e_pmDE	SpObjID	zsp	e_zsp	f_zsp	spType	spCl	subClass
float64	float64	float64	float64	float64	int64	str16	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	str3	int64	int64	str3	int64	float64	int64	int64	int64	int64	int64	str1	str10	int64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	int64	int64	str2	int64	int64	str1	float64	int64	float64	float64	int64	int64	int64	int64	int64	str19	float64	float64	float64	float64	int64	float64	float64	float64	float64	float64	float64	float64	float64	float64	float64	int64	int64	int64	str16	int64	float64	int64	int64	int64	int64	int64	int64	int64	int64	int64	int64	int64
0.352101	127.509154	1.269173	0.2	0.15	87	08300219+0116090	15.963	0.095	0.096	12.5	15.546	0.121	0.122	9.0	14.93	0.144	0.144	8.1	ABB	222	111	000	160606	14.2	340	804040589	0	0	804040599	s	2000-01-30	58	223.554	22.408	178.5	2451573.6815	0.89	1.01	0.92	15.939	0.235	15.899	0.319	14.69	0.124	4589	74	sw	0	1	0	--	--	--	--	0	--	43956	1010984	221	J083002.21+011608.9	127.509248	1.269146	0.01	0.009	90	23.712	20.876	19.402	18.068	17.338	0.67	0.034	0.015	0.009	0.015	1237653664712163908	6	1	0000201010000110	3	2000.9155	-53	5	-43	5	0	--	--	--	--	--	--
0.152435	127.507779	1.272875	0.12	0.11	86	08300186+0116223	15.594	0.083	0.084	17.6	15.563	0.117	0.117	8.9	15.272	0.181	0.182	5.9	ABC	222	111	000	360606	14.2	160	804040599	0	0	804040589	s	2000-01-30	58	223.55	22.408	183.4	2451573.6814	1.64	0.82	1.47	15.432	0.153	15.81	0.424	14.992	0.114	4602	69	sw	0	1	U	0.2	270	17.1	16.5	1	--	43956	1010984	221	J083001.86+011622.2	127.507749	1.272845	0.002	0.002	90	18.394	17.213	16.806	16.674	16.623	0.014	0.004	0.004	0.005	0.01	1237653664712163358	6	1	0000001010000000	3	2000.9155	-3	3	2	3	0	--	--	--	--	--	--
0.217574	127.514167	1.277495	0.23	0.21	51	08300340+0116389	16.553	0.17	0.171	7.3	16.179	0.194	0.194	5.0	15.894	--	--	--	CCU	220	110	000	60600	28.4	234	804040589	0	0	804040577	s	2000-01-30	58	223.549	22.416	160.4	2451573.6814	0.69	1.58	--	16.335	0.139	18.014	3.36	--	--	4619	92	sw	0	1	U	0.0	13	18.0	17.3	1	--	43956	1010984	221	J083003.39+011638.8	127.514129	1.277448	0.003	0.003	90	19.513	18.189	17.714	17.559	17.485	0.028	0.006	0.006	0.007	0.016	1237653664712163741	6	1	0000001010000000	3	2000.9155	2	3	1	3	0	--	--	--	--	--	--
0.048922	127.463251	1.271903	0.07	0.07	0	08295118+0116188	15.844	0.076	0.077	14.0	15.11	0.095	0.096	13.5	15.029	0.138	0.138	7.4	AAB	222	111	000	260606	41.0	160	804019559	0	0	804019587	s	2000-01-30	57	223.528	22.369	-87.9	2451573.6739	1.78	0.8	1.14	15.935	0.238	15.077	0.164	15.197	0.438	4593	164	se	0	1	U	1.0	281	20.0	18.4	1	--	43955	1010947	56	J082951.17+011618.8	127.463238	1.271907	0.005	0.005	90	21.976	19.794	18.386	17.54	17.048	0.176	0.016	0.008	0.007	0.012	1237653664712098290	6	1	0000001010000000	3	2000.9155	-19	4	8	4	0	--	--	--	--	--	--
0.023156	127.463023	1.2864	0.06	0.06	0	08295112+0117110	14.093	0.029	0.032	70.0	13.652	0.033	0.035	51.7	13.553	0.042	0.043	28.9	AAA	222	111	000	666635	52.2	179	804019587	0	0	804019616	s	2000-01-30	57	223.514	22.376	-87.0	2451573.674	0.75	0.97	0.91	14.077	0.023	13.576	0.05	13.692	0.14	4646	165	se	0	1	U	0.4	160	16.3	14.6	1	--	43955	1010947	56	J082951.12+011711.0	127.463018	1.286396	0.001	0.001	90	17.223	15.796	15.259	15.074	14.993	0.008	0.003	0.003	0.003	0.005	1237653664712098015	6	1	0000201090020010	3	2000.9155	5	3	-5	3	0	--	--	--	--	--	--
0.102852	127.48465	1.271192	0.06	0.06	0	08295631+0116162	13.848	0.026	0.029	87.8	13.177	0.02	0.022	80.0	12.932	0.023	0.024	51.1	AAA	222	111	000	666655	15.7	12	804019600	0	0	804019585	s	2000-01-30	57	223.54	22.387	-164.9	2451573.6739	0.88	0.87	0.95	13.813	0.042	13.143	0.051	13.009	0.056	4591	87	se	0	1	U	0.2	244	18.8	16.7	1	--	43955	1010947	56	J082956.31+011616.3	127.484625	1.271206	0.002	0.002	90	21.011	18.359	16.959	15.814	15.169	0.081	0.007	0.004	0.004	0.005	1237653664712098324	6	1	0000001010000000	3	2000.9155	-3	3	4	3	0	--	--	--	--	--	--
0.385255	127.485565	1.275456	0.2	0.17	4	08295653+0116316	16.26	0.112	0.112	9.5	15.908	0.172	0.172	6.5	15.264	0.184	0.184	6.0	BCC	222	111	000	160606	15.7	192	804019585	0	0	804019600	s	2000-01-30	57	223.536	22.39	-168.2	2451573.674	0.84	1.3	0.8	16.125	0.291	15.529	0.253	15.21	0.246	4606	84	se	0	1	U	0.4	232	18.1	17.4	1	--	43955	1010947	56	J082956.55+011631.7	127.485664	1.275497	0.003	0.003	90	20.245	18.34	17.584	17.343	17.185	0.046	0.007	0.005	0.006	0.013	1237653664712098328	6	1	0000001010000000	3	2000.9155	5	3	2	3	0	--	--	--	--	--	--
0.18744	127.494339	1.280734	0.15	0.15	145	08295864+0116506	16.317	0.119	0.12	9.0	15.818	0.141	0.141	7.0	15.099	--	--	--	BBU	220	110	000	60600	36.9	239	804019600	0	0	804019605	s	2000-01-30	57	223.536	22.4	-199.8	2451573.674	0.96	1.62	--	16.264	0.088	16.219	0.553	--	--	4625	52	se	1	1	0	--	--	--	--	0	--	43955	1010947	56	J082958.64+011650.4	127.494341	1.280682	0.009	0.008	90	22.545	20.673	19.202	18.184	17.586	0.275	0.029	0.013	0.009	0.017	1237653664712098411	6	1	0000901010020000	3	2000.9155	7	5	-6	5	0	--	--	--	--	--	--
0.038231	127.494645	1.296204	0.07	0.07	17	08295871+0117463	15.25	0.05	0.051	24.1	15.062	0.077	0.078	14.1	14.87	0.114	0.114	8.6	AAB	222	111	000	660506	47.1	299	804019652	0	0	804019639	s	2000-01-30	57	223.521	22.408	-200.9	2451573.674	0.98	0.89	1.01	15.178	0.064	15.195	0.302	14.779	0.326	4681	51	se	1	1	U	0.4	185	16.8	16.1	1	--	43955	1010947	56	J082958.71+011746.3	127.494638	1.296212	0.002	0.001	90	17.968	16.737	16.304	16.182	16.107	0.012	0.004	0.004	0.004	0.007	1237653664712098075	6	1	0000201010021010	3	2000.9155	1	3	-6	3	0	--	--	--	--	--	--
0.125123	127.483247	1.302628	0.06	0.06	0	08295597+0118094	13.484	0.025	0.027	122.7	12.862	0.02	0.022	106.9	12.807	0.033	0.034	57.4	AAA	222	111	000	665555	27.9	314	804019667	0	0	804019652	s	2000-01-30	57	223.509	22.401	-159.8	2451573.674	1.06	0.7	1.1	13.457	0.027	12.875	0.06	12.777	0.069	4704	92	se	0	1	U	2.0	195	16.3	14.5	1	--	43955	1010947	56	J082955.98+011809.3	127.483254	1.302594	0.001	0.001	90	17.956	15.896	15.035	14.727	14.511	0.012	0.003	0.003	0.003	0.004	1237653664712098036	6	1	0000201090020010	3	2000.9155	-9	3	-41	3	0	--	--	--	--	--	--
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
0.231895	127.471749	1.699981	0.15	0.15	145	08295321+0141599	16.278	0.12	0.121	9.4	15.646	0.138	0.138	8.2	15.792	--	--	--	BBU	220	110	000	60600	21.5	111	804020536	0	0	804020539	s	2000-01-30	57	223.127	22.583	-118.5	2451573.6743	0.82	0.93	--	16.158	0.12	15.666	0.136	--	--	6134	134	se	0	1	U	0.5	178	18.2	17.1	1	--	43955	1010949	80	J082953.20+014159.8	127.471686	1.699968	0.003	0.003	90	19.801	18.25	17.648	17.445	17.292	0.034	0.006	0.006	0.006	0.015	1237653665248969172	6	1	0000001010000000	3	2000.9155	0	3	-6	3	0	--	--	--	--	--	--
0.108018	127.485472	1.701631	0.07	0.07	17	08295651+0142058	15.286	0.047	0.049	23.3	14.805	0.069	0.069	17.9	14.59	0.102	0.102	11.1	AAA	222	111	000	361506	32.4	245	804020536	0	0	804020544	s	2000-01-30	57	223.132	22.596	-167.8	2451573.6743	1.03	1.1	1.02	15.41	0.107	14.79	0.127	14.331	0.225	6140	84	se	0	1	U	0.5	227	17.9	16.6	1	--	43955	1010949	80	J082956.51+014205.7	127.485483	1.701603	0.002	0.002	90	19.856	17.73	16.86	16.541	16.35	0.036	0.005	0.004	0.004	0.009	1237653665249034558	6	1	0000001010020000	3	2000.9155	-4	3	-4	3	0	--	--	--	--	--	--
0.033205	127.50233	1.707568	0.06	0.06	90	08300055+0142272	13.442	0.023	0.026	127.5	12.837	0.024	0.026	109.4	12.652	0.029	0.03	66.2	AAA	222	111	000	666655	24.1	173	804039600	0	0	804039583	s	2000-01-30	58	223.135	22.614	203.0	2451573.6811	1.13	0.79	1.5	13.483	0.018	12.913	0.029	12.71	0.045	6167	50	sw	1	1	U	1.1	262	17.2	15.1	1	--	43956	1010982	198	J083000.56+014227.2	127.502332	1.707559	0.001	0.001	90	19.461	16.829	15.524	14.976	14.692	0.027	0.004	0.004	0.003	0.005	1237653665249034586	6	1	0000201010020010	3	2000.9155	-22	3	1	3	0	--	--	--	--	--	--
0.127126	127.469423	1.71372	0.12	0.11	101	08295266+0142493	16.124	0.097	0.098	10.8	15.408	0.101	0.102	10.3	15.34	0.186	0.186	5.6	AAC	222	111	000	60606	50.2	170	804020539	0	0	804020569	s	2000-01-30	57	223.112	22.588	-110.1	2451573.6743	0.99	0.99	0.93	16.256	0.269	15.929	0.347	15.574	0.328	6184	142	se	0	1	0	--	--	--	--	0	--	43955	1010949	80	J082952.66+014249.2	127.469418	1.713685	0.009	0.008	90	23.472	20.755	19.283	18.181	17.503	0.594	0.029	0.014	0.009	0.017	1237653665248969263	6	1	0000001010000100	3	2000.9155	-13	5	3	5	0	--	--	--	--	--	--
0.029366	127.451948	1.721205	0.06	0.06	0	08294846+0143163	12.459	0.019	0.023	315.4	12.056	0.024	0.026	224.7	11.969	0.023	0.024	124.1	AAA	222	111	000	666666	48.4	192	804020559	0	0	804020588	s	2000-01-30	57	223.096	22.576	-47.2	2451573.6743	0.74	0.74	0.86	12.47	0.019	12.038	0.046	11.973	0.029	6211	205	se	0	1	U	1.3	176	14.8	13.5	1	--	43955	1010949	80	J082948.46+014316.3	127.451955	1.721201	0.047	0.042	90	16.125	14.47	13.785	13.755	13.493	0.006	0.003	0.006	0.002	0.004	1237653665248968970	6	0	0000B81092061010	3	2000.9155	2	3	-24	3	0	--	--	--	--	--	--
0.475815	127.395474	1.69711	0.34	0.32	88	08293491+0141495	16.551	0.164	0.164	7.3	15.907	0.207	0.207	6.5	15.795	0.274	0.275	3.7	CED	222	111	000	60506	53.7	338	804020566	0	0	804020535	s	2000-01-30	57	223.089	22.515	156.0	2451573.6743	0.85	10.93	0.72	16.461	0.216	16.1	0.268	16.146	0.828	6125	97	sw	0	1	0	--	--	--	--	0	--	43955	1010949	80	J082934.93+014149.9	127.395566	1.697205	0.017	0.016	90	23.316	21.506	20.041	18.676	17.902	0.557	0.054	0.024	0.013	0.023	1237653665248969283	6	1	0100F01010021010	3	2000.9155	--	--	--	--	0	--	--	--	--	--	--
0.063468	127.432292	1.717116	0.07	0.06	96	08294375+0143016	14.569	0.032	0.035	45.2	14.299	0.055	0.056	28.5	14.219	0.084	0.084	15.6	AAA	222	111	000	665614	22.8	14	804020593	0	0	804020581	s	2000-01-30	57	223.09	22.557	23.5	2451573.6743	0.9	1.15	0.65	14.552	0.05	14.172	0.086	14.225	0.229	6197	229	sw	0	1	U	0.3	198	16.4	15.3	1	--	43955	1010949	80	J082943.75+014301.6	127.432309	1.717121	0.001	0.001	90	17.453	16.137	15.683	15.532	15.469	0.009	0.003	0.004	0.004	0.006	1237653665248968924	6	1	0000001010020200	3	2000.9155	1	3	-1	3	0	--	--	--	--	--	--
0.078846	127.433857	1.723263	0.07	0.07	17	08294412+0143237	15.678	0.08	0.081	16.3	15.207	0.105	0.105	12.3	14.965	0.138	0.138	7.9	AAB	222	111	ccc	665616	4.5	317	804020596	0	0	804020593	s	2000-01-30	57	223.085	22.561	17.9	2451573.6743	1.14	0.83	1.22	14.517	0.097	14.072	0.112	14.179	0.144	6219	235	sw	0	1	U	4.0	139	15.8	14.4	1	--	43955	1010949	80	J082944.13+014323.7	127.433877	1.723272	0.007	0.007	90	23.802	20.411	19.039	17.728	17.018	0.743	0.024	0.012	0.007	0.013	1237653665248968930	6	1	0000B01812021010	3	2000.9155	--	--	--	--	0	--	--	--	--	--	--
0.036173	127.531902	1.729757	0.06	0.06	90	08300765+0143471	14.155	0.033	0.036	66.1	13.84	0.032	0.033	43.4	13.806	0.048	0.049	22.9	AAA	222	111	000	666646	14.1	82	804039539	0	0	804039541	s	2000-01-30	58	223.13	22.65	96.6	2451573.6811	1.03	0.88	1.01	14.136	0.051	13.972	0.048	13.85	0.118	6247	156	sw	0	1	U	0.2	230	15.8	15.0	1	--	43956	1010982	198	J083007.65+014347.1	127.531908	1.729749	0.001	0.001	90	17.145	15.741	15.246	15.079	15.039	0.008	0.003	0.003	0.003	0.005	1237653665249034332	6	1	0000001010020000	3	2000.9155	-3	3	1	3	0	--	--	--	--	--	--
0.676936	127.53577	1.730293	0.37	0.35	45	08300858+0143490	17.047	0.231	0.231	4.6	16.123	0.19	0.19	5.3	15.872	0.302	0.303	3.4	DCD	222	111	000	60605	14.1	262	804039541	0	0	804039539	s	2000-01-30	58	223.131	22.654	82.7	2451573.6811	0.95	0.74	0.98	16.537	0.399	17.529	1.515	16.04	0.705	6249	170	sw	0	1	0	--	--	--	--	0	--	43956	1010982	198	J083008.62+014348.6	127.535921	1.730181	0.023	0.02	90	23.847	21.895	20.462	19.034	18.355	0.756	0.075	0.032	0.017	0.032	1237653665249035083	6	1	0000001010000100	3	2000.9155	--	--	--	--	0	--	--	--	--	--	--

For the SDSS DR9 table this action has given us all the columns. So before we move on, we restrict the table to the columns, we are actually interested in.

sdss_mass = sdss_mass[
    "2MASS",
    "RAJ2000",
    "DEJ2000",
    "Jmag",
    "Hmag",
    "Kmag",
    "SDSS9",
    "RAdeg",
    "DEdeg",
    "umag",
    "gmag",
    "rmag",
    "imag",
    "zmag",
    "cl",
]

print(f"We are currently working with {len(sdss_mass)} sources")

We are currently working with 717 sources

Step #3: Filtering#

In this step we select all those sources from our cross-matched catalogue that have colours and fluxes as expected for brown dwarfs.

The selection cirteria for Brown Dwarfs are:

umag > 22.0 –> magnitude in u-band fainter than 22.0mag
gmag > 22.2 –> magnitude in g-band fainter than 22.2mag
Jmag - Hmag < 0.3 –> J-H band colour smaller than 0.3mag
Hmag - Kmag < 0.3 –> H-K band colour smaller than 0.3mag

We now apply these selection criteria to our table of point sources.

# Add columsn with J-H and H-K colour
sdss_mass["J-H"] = sdss_mass["Jmag"] - sdss_mass["Hmag"]
sdss_mass["H-K"] = sdss_mass["Hmag"] - sdss_mass["Kmag"]
# Limit sources to those that fulfil the selection criteria
index_bd = (
    (sdss_mass["umag"] > 22.0)
    & (sdss_mass["gmag"] > 22.2)
    & (sdss_mass["J-H"] < 0.3)
    & (sdss_mass["H-K"] < 0.3)
)
candidates = sdss_mass[index_bd]
print(f"We have {len(candidates)} candidates for Brown Dwarfs")

We have 2 candidates for Brown Dwarfs

candidates

Table length=2

2MASS	RAJ2000	DEJ2000	Jmag	Hmag	Kmag	SDSS9	RAdeg	DEdeg	umag	gmag	rmag	imag	zmag	cl	J-H	H-K
str16	float64	float64	float64	float64	float64	str19	float64	float64	float64	float64	float64	float64	float64	int64	float64	float64
08304878+0128311	127.703265	1.47532	16.289	16.14	16.358	J083048.81+012831.0	127.703377	1.475293	25.322	24.514	25.492	25.878	19.401	3	0.1490000000000009	-0.21799999999999997
08304512+0134404	127.688007	1.577901	16.18	16.021	15.769	J083045.23+013443.5	127.688491	1.578759	24.004	22.299	21.03	20.478	20.53	6	0.15899999999999892	0.25200000000000067

Note that we are using slightly different selection criteria here in the notebook than in the original tutorial. The reason is the following. The CDS XMatch service uses VizieR tables with their default filtering. For the SDSS DR 9 table, VizieR will filter to only use primary sources and disregard secondary sources, which is not the case when downloading the VizieR table with e.g. TOPCAT. Now the primary SDSS source for this brown dwarf is classified as an extended source by the automated SDSS pipeline, probably because it is hardly detected and very faint. So if we remove all extended sources we also throw away the target of our studies. Hence, the filtering in this notebook is less strict to allow

Step #4: Verification of the Brown Dwarf candidates#

Visualization#

The ipyaladin package allows to run an instance of Aladin Lite in your Jupyter notebook.

aladin1 = Aladin(
    survey="P/SDSS9/color",
    fov=0.03,
    target="{:.4f} {:.4f}".format(candidates["RAJ2000"][0], candidates["DEJ2000"][0]),
)
aladin1

As with any instance of Aladin Lite you can zoom in and out by scrolling your mouse. In the top left corner of the widget, you may chose which survey to look at, add layers, search for sources, …

You can also add tables to the widget by:

aladin1.add_table(candidates)

If you now click on the small square indicating the location of the source, the widget will show the corresponding table values in the lower part of the widget.

As you can see at one of the locations hardly anything is visible and at the location of the other brown dwarf candidate, there is a bright star. To further investigate these two sources, we now query Simbad for them.

Check in Simbad#

In the Simbad database, an object type is assigned to every entry. So if this Brown Dwarf candidate is in the Simbad database, we might learn more about the object type:

# First candidate has an index 0
customSimbad = Simbad()
customSimbad.remove_votable_fields("coordinates")
customSimbad.add_votable_fields(
    "ra(2;A;ICRS;J2000;2000)",
    "dec(2;D;ICRS;J2000;2000)",
    "otype",
)
candidate_coord = SkyCoord(
    ra=candidates["RAJ2000"][0],
    dec=candidates["DEJ2000"][0],
    unit=u.deg,
)
candidate_simbad = customSimbad.query_region(candidate_coord, radius=10 * u.arcsec)
candidate_simbad

Table length=1

MAIN_ID	RA_2_A_ICRS_J2000_2000	DEC_2_D_ICRS_J2000_2000	OTYPE	SCRIPT_NUMBER_ID
	"h:m:s"	"d:m:s"
object	str13	str13	object	int32
2MASS J08304878+0128311	08 30 48.7836	+01 28 31.152	BrownD*	1

# First candidate has an index 1
customSimbad = Simbad()
customSimbad.remove_votable_fields("coordinates")
customSimbad.add_votable_fields(
    "ra(2;A;ICRS;J2000;2000)",
    "dec(2;D;ICRS;J2000;2000)",
    "otype",
)
candidate_coord = SkyCoord(
    ra=candidates["RAJ2000"][1],
    dec=candidates["DEJ2000"][1],
    unit=u.deg,
)
candidate_simbad = customSimbad.query_region(candidate_coord, radius=1 * u.arcmin)
candidate_simbad

/home/manon.marchand/miniconda3/envs/cds-tutos/lib/python3.10/site-packages/astroquery/simbad/core.py:135: UserWarning: Warning: The script line number 3 raised an error (recorded in the `errors` attribute of the result table): '8:30:45.12168 +1:34:40.4436': No astronomical object found :
  warnings.warn("Warning: The script line number %i raised "

Indeed the first candidate is classified as a brown dwarf. Within 10arcsec of the second source, no entry is found in Simbad although this is the brighter star. The reason for this might be the following: sources in Simbad are sources that have individually been discussed in the literature. If no papers have been published specifcially about this object, it will not appear in Simbad. However, as the object was included in the SDSS tables it is included in VizieR through the table it belongs to.

If we now want to see, in which papers the Brown Dwarf 2MASS J08304878+0128311 was included, we may use the following query in Simbad.

tap_simbad = pyvo.dal.TAPService("https://simbad.cds.unistra.fr/simbad/sim-tap")

query = """
SELECT BIBCode, Journal, Title, "year", Volume,
       Page || '-' || Last_Page AS "Pages", DOI 
FROM ref JOIN has_ref ON oidbibref = oidbib 
         JOIN ident ON has_ref.oidref = ident.oidref 
WHERE id = '2MASS J08304878+0128311'
ORDER BY "year" DESC; 
"""

result = tap_simbad.search(query).to_table()
result

Table length=20

bibcode	journal	title	year	volume	Pages	doi
object	object	object	int16	int32	object	object
2020AJ....159..257B	AJ	The Hawaii infrared parallax program. IV. A comprehensive parallax survey of L0-T8 dwarfs with UKIRT.	2020	159	257-257	10.3847/1538-3881/ab84f4
2016ApJ...827...25B	ApJ	The orbit of the L dwarf + T dwarf spectral binary SDSS J080531.84+481233.0.	2016	827	25-25	10.3847/0004-637X/827/1/25
2016A&A...589A..49S	A&A	Photometric brown-dwarf classification. II. A homogeneous sample of 1361 L and T dwarfs brighter than J = 17.5 with accurate spectral types.	2016	589	49-49	10.1051/0004-6361/201527359
2016ApJ...817..112S	ApJ	A proper motion survey using the first sky pass of NEOWISE-reactivation data.	2016	817		10.3847/0004-637X/817/2/112
2015ApJ...810..158F	ApJ	Fundamental parameters and spectral energy distributions of young and field age objects with masses spanning the stellar to planetary regime.	2015	810		10.1088/0004-637X/810/2/158
2014ApJ...793...75R	ApJ	Strong brightness variations signal cloudy-to-clear transition of brown dwarfs.	2014	793		10.1088/0004-637X/793/2/75
2013MNRAS.433.2054S	MNRAS	NPARSEC: NTT Parallaxes of Southern Extremely Cool objects. Goals, targets, procedures and first results.	2013	433	2054-2063	10.1093/mnras/stt876
2013MNRAS.433..457B	MNRAS	76 T dwarfs from the UKIDSS LAS: benchmarks, kinematics and an updated space density.	2013	433	457-497	10.1093/mnras/stt740
2012ApJ...752...56F	ApJ	The Brown Dwarf Kinematics Project (BDKP). III. Parallaxes for 70 ultracool dwarfs.	2012	752		10.1088/0004-637X/752/1/56
2012ApJ...748...74L	ApJ	The properties of the 500 K dwarf UGPS J072227.51-054031.2 and a study of the far-red flux of cold brown dwarfs.	2012	748		10.1088/0004-637X/748/2/74
2012ApJ...757..110B	ApJ	Discovery of a very low mass triple with late-M and T dwarf components: LP 704-48/SDSS J0006-0852AB.	2012	757		10.1088/0004-637X/757/2/110
2011ApJS..197...19K	ApJS	The first hundred brown dwarfs discovered by the Wide-field Infrared Survey Explorer (WISE).	2011	197		10.1088/0067-0049/197/2/19
2010A&A...515A..92S	A&A	Hip 63510C, Hip 73786B, and nine new isolated high proper motion T dwarf candidates from UKIDSS DR6 and SDSS DR7.	2010	515	92-92	10.1051/0004-6361/201014264
2010ApJ...710.1142B	ApJ	SpeX spectroscopy of unresolved very low mass binaries. I. Identification of 17 candidate binaries straddling the L dwarf/T dwarf transition.	2010	710	1142-1169	10.1088/0004-637X/710/2/1142
2009yCat....1.2023S	yCat	Catalogue of stellar spectral classifications.	2009	1
2009AJ....137....1F	AJ	The brown dwarf kinematics project I. Proper motions and tangential velocities for a large sample of late-type M, L, and T dwarfs.	2009	137	1-18	10.1088/0004-6256/137/1/1
2008ApJ...676.1281M	ApJ	A cross-match of 2MASS and SDSS: newly found L and T dwarfs and an estimate of the space density of T dwarfs.	2008	676	1281-1306	10.1086/524721
2008MNRAS.390.1517C	MNRAS	Proper motions of field L and T dwarfs - II.	2008	390	1517-1526	10.1111/j.1365-2966.2008.13855.x
2006ApJ...637.1067B	ApJ	A unified near-infrared spectral classification scheme for T dwarfs.	2006	637	1067-1093	10.1086/498563
2004AJ....127.3553K	AJ	Near-infrared photometry and spectroscopy of L and T dwarfs: the effects of temperature, clouds, and gravity.	2004	127	3553-3578	10.1086/420707

For further reading you could now go to ADS and search for the publications via their bibcode (enter in the search field bibcode:...) or their doi (doi:...).

To design similar queries for your own research, have a look at Simbad database schema.