JWST Duplication Checking

Introduction

As with HST, JWST observations that duplicate existing, planned, or approved observations will be allowed only if investigators provide a scientific justification in their proposal and that request is approved. Consult the JWST Duplicate Observations Policy for details. Broadly speaking, observations you are considering might duplicate observations in the current or prior cycles if your target is of the same astrophysical source, or there is significant spatial overlap of fields, and the following apply:

• Similar imaging passband, or overlapping spectral range

• Similar (spectral) resolution

• Similar exposure depth

Observations with a different scientific instrument than one you are considering might still duplicate if the observing configuration and capabilities are similar (e.g., NIRCam and NIRISS imaging, or NIRCam and NIRSpec spectroscopy).

This notebook illustrates how to use the python package astroquery.mast to search the Mikulski Archive for Space Telescopes (MAST) for potential duplicate observations. It is also possible to perform these searches with the MAST Portal, but often less efficiently.

Special Disclaimer

The complete footprint of approved (but not executed) mosaicked or parallel observations is only approximate. That is, while the primary location is reported for an observation, the exact orientation. of the aperture is not known until the observation is scheduled for execution. Moreover metadata in MAST about planned/approved observations may not suffice to determine whether your intended observation is a genuine duplication, particularly for slit or MOS spectroscopy. You are responsible for evaluating the details of the planned observations by using the accepted program's APT file (and/or the Aladin display in APT, as appropriate) to determine if the potential duplications are genuine.

Table of contents

• Strategy
• Setup
• Utility Routines
• Queries by Target/Position
• Search by Target Name
• Single Moving Target
• Checking a List of Targets
• Loading Targets from CSV
• Evaluating Potential Duplications
• Trappist-1
• V* XX Cha
• M 57
• Appendix: Caveats
• Source Name
• Cone Search vs. Area Search
• Additional Resources

Strategy

The following strategy, applied to each target or field, will identify potentially duplicative observations.

1. Search for common targets or fields. If no existing or planned observation coincides with your intended target, you are done.

2. If there is a spatial overlap, determine if the instrument(s) and observing configurations you plan to use are the same or similar to the existing observations. If there is no commonality, you are done.

3. If there is spatial overlap and common instruments/configuration, determine in detail the overlap in passband/spectral coverage, and exposure depth.

4. If there is a likely duplication for an intended target, do one of the following:

   • Include in your proposal a scientific case for the duplicating observation(s)

   • Alter your intended observation(s) in a way that does not duplicate

   • Choose a different target

Setup

Begin by importing some essential python packages: general utilities in astropy, and query services in astroquery.mast.

# Give the notebook cells more of the available width
from IPython.display import display, HTML
display(HTML("<style>.container { width:99% !important; }</style>"))

import astropy
from astropy import table
from astropy.table import Table, unique
from astropy import units as u
from astropy.coordinates import Angle
from astroquery.mast import Mast
from astroquery.mast import Observations

Utility Routines

The following utility routine will create URLs to the parent programs of matching observations.

APT_LINK = '(http://www.stsci.edu/cgi-bin/get-proposal-info?id={}&observatory=JWST)'

def get_program_URL(program_id):
    '''
    Generate the URL for program status information, given a program ID. 
    '''
    return APT_LINK.format(program_id)

Queries by Target/Postion

All of the queries below search for JWST observations, using a search radius larger than fields of view (FoV) of JWST apertures, to allow for the possibility that the FoV may be rotated when approved-but-unexecuted observations are actually scheduled. Your queries will typically be more efficient if you restrict your search to JWST data by including the parameter: obs_collection = "JWST".

Searching for source names is not recommended when checking for potential duplications with fixed targets because the matches are not reliable, consistent, or complete. The exception would be for matching Object names of well known solar system bodies.

The best approach is to use an independent source for the coordinates of your desired target, including existing JWST or HST images if any exist. Failing that, the Mast.resolve_object() method will return coordinates in the ICRS reference frame, which you can use to verify whether a target name resolves to the coordinates you intend. See the Appendix for details.

Search by Target Name

This example shows how to query for a single target with a standard name, HD 104237 which is a T-Tauri star. We first resolve the name and verify that the coordinates are correct, using the Mast class and the resolve_object() method.

# Resolve the coordinates if necessary
coords = Mast.resolve_object('HD 104237')
print(coords)

<SkyCoord (ICRS): (ra, dec) in deg
    (180.02119525, -78.19293492)>

In this case the resolved coordinates agree with those in Simbad, so it is safe to execute a simple cone search (a search within a specified radius of a place on the sky) to find JWST existing or planned observations. The astroquery.mast package provides the method Observations.query_criteria() to specify the parameters for the search; provide them as key=value pairs. The full set of query parameters for this method may be found on CAOM Field Descriptions.

# If the coordinates are ok
obs = Observations.query_criteria(
        obs_collection='JWST'
        ,objectname='HD 104237'
        ,radius='30s'
        )
print('Number of matching observations: {}'.format(len(obs)))

Number of matching observations: 0

WARNING: NoResultsWarning: Query returned no results. [astroquery.mast.discovery_portal]

If the number of matches is zero, there are no potential JWST duplications with this target.

Single Moving Target

Moving targets, by definition, do not lend themselves to searches by position. This kind of search in MAST is limited to a modest set of solar system bodies with recognized names. Note the use of a wildcard character (*) to trigger a match, even when the target name includes other text.

obs = Observations.query_criteria(
        obs_collection="JWST"
        ,target_name="Io*"
        )
    
print(f'Number of matching observations: {len(obs)}')

Number of matching observations: 34

There are several JWST observations of Io, including some that are planned but have not executed as of the beginning of Cy-2 (i.e., calib_level = -1). The details are in the returned table of results, the most essential of which can be viewed below.

out_cols = ['target_name','instrument_name','filters','calib_level','t_exptime','proposal_id']
obs[out_cols].show_in_notebook()

Table length=34

idx	target_name	instrument_name	filters	calib_level	t_exptime	proposal_id
0	IO	MIRI/IFU	--	-1	2664.038	4565
1	IO	MIRI/IFU	--	-1	222.003	4565
2	IO	MIRI/IFU	--	-1	222.003	4565
3	IO	MIRI/IFU	--	-1	222.003	4565
4	IO	MIRI/IFU	--	-1	222.003	4565
5	IO	MIRI/IFU	--	-1	222.003	4565
6	IO	MIRI/IFU	--	-1	222.003	4565
7	IO	MIRI/IFU	--	-1	222.003	4565
8	IO	MIRI/IFU	--	-1	222.003	4565
9	IO	MIRI/IFU	CH12-LONG	2	3194.071	4078
10	IO	MIRI/IFU	CH12-LONG	2	3194.071	4078
11	IO	MIRI/IFU	CH12-LONG	2	3194.071	4078
12	IO	MIRI/IFU	CH34-LONG	2	3194.071	4078
13	IO	MIRI/IFU	CH34-LONG	2	3194.071	4078
14	IO	MIRI/IFU	CH34-LONG	2	3194.071	4078
15	IO	MIRI/IFU	CH4	3	2109.032	4078
16	IO	MIRI/IFU	CH3	3	2109.032	4078
17	IO	MIRI/IFU	CH4	3	2109.032	4078
18	IO	MIRI/IFU	CH1	3	2109.032	4078
19	IO	MIRI/IFU	CH2	3	2109.032	4078
20	IO	MIRI/IFU	CH2	3	2109.032	4078
21	IO	MIRI/IFU	CH3	3	2109.032	4078
22	IO	MIRI/IFU	CH1	3	2109.032	4078
23	IO	MIRI/IFU	CH4	3	790.8870000000001	1373
24	IO	MIRI/IFU	CH3	3	790.8870000000001	1373
25	IO	MIRI/IFU	CH2	3	790.8870000000001	1373
26	IO	MIRI/IFU	CH1	3	790.8870000000001	1373
27	IO	NIRISS/AMI	F430M;NRM	3	1697.4	1373
28	IO	NIRSPEC/IFU	F290LP;G395H	3	343.576	1373
29	IO	NIRSPEC/IFU	F170LP;G235H	3	687.152	1373
30	IO	NIRSPEC/IFU	F100LP;G140H	3	4668.448	1373
31	IO	NIRSPEC/IFU	F170LP;G235H	3	687.152	1373
32	IO	NIRSPEC/IFU	F290LP;G395H	3	343.576	1373
33	IO	NIRSPEC/IFU	F100LP;G140H	3	5135.288	1373

You may need to examine the specifics of the programs that obtained the observations to know whether your intended observations would duplicate. Here extend the results table with the unique Program Titles and URLs for the program status pages, which may offer clues:

obs['title'] = [x[:80] for x in obs['obs_title']]
unique(obs['proposal_id','title']).pprint(max_width=-1)
obs['proposal_URL'] = [get_program_URL(x) for x in obs['proposal_id']]
unique(obs['proposal_id','proposal_URL']).pprint(max_width=-1)

proposal_id                                      title                                      
----------- --------------------------------------------------------------------------------
       1373 ERS observations of the Jovian System as a demonstration of JWST capabilities fo
       4078 Mass-loss from Ios volcanic atmosphere: A unique synergy with the Juno Io fly-by
       4565              HST-Juno Io Campaign: Connecting Volcanos to the Plasma Environment
proposal_id                                proposal_URL                              
----------- -------------------------------------------------------------------------
       1373 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=1373&observatory=JWST)
       4078 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=4078&observatory=JWST)
       4565 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=4565&observatory=JWST)

There are images, spectra, coronagraphic, and IFU observations of this target that could conflict with your intended proposal. Proposed images in passbands that overlap the IFU data would have to be examined closely for duplication.

Checking a List of Targets

It is often useful to search for individual targets with the MAST Portal because the results are easily visualized. But it is more efficient to search over a large number of targets using astroquery.mast.

Loading Targets from CSV

For efficiency, make a CSV (comma-separated variable) list of your targets, one per row. The list can alternatively be read from a local file: just substitute the file name for targ_table in the first argument of the Table.read() method. The list can contain many fields, but at a minimum must contain the target name and the equitorial coordinates.

For stellar targets, it is best to use a large enough radius to make your search robust against position uncertainties and proper motion between J2000 and the current epoch.

The first row of the file will be interpreted as a column name in the table. This is important.

targ_table = '''
target_name, RA, DEC, Radius, Description
Trappist-1, 23:06:29.3684948589, -05:02:29.037301866, 30s, Exoplanet host star
V* XX Cha, 11:11:39.559, -76:20:15.04, 30s, Variable star with debris disk
M 31, 00:42:44.330, +41:16:07.50, 12.0m, Andromeda Galaxy
M 57, 18:53:35.0967659112, +33:01:44.883287544, 2m, Planetary nebula
'''
targets = Table.read(targ_table, format='ascii.csv')

Next, make new columns to hold the coordinates and ranges in units of degrees.

targets['ra_deg'] = [Angle(x+' hours').degree for x in targets['RA']]
targets['dec_deg'] = [Angle(x+' degree').degree for x in targets['DEC']]
targets['radius_deg'] = [Angle(x).degree for x in targets['Radius']]
targets['N_obs'] = 0  # field to hold the count of matched observations 
targets

Table length=4

target_name	RA	DEC	Radius	Description	ra_deg	dec_deg	radius_deg	N_obs
str10	str19	str19	str5	str30	float64	float64	float64	int64
Trappist-1	23:06:29.3684948589	-05:02:29.037301866	30s	Exoplanet host star	346.62236872857875	-5.041399250518333	0.008333333333333333	0
V* XX Cha	11:11:39.559	-76:20:15.04	30s	Variable star with debris disk	167.91482916666666	-76.33751111111111	0.008333333333333333	0
M 31	00:42:44.330	+41:16:07.50	12.0m	Andromeda Galaxy	10.684708333333331	41.26875	0.2	0
M 57	18:53:35.0967659112	+33:01:44.883287544	2m	Planetary nebula	283.39623652462996	33.029134246539996	0.03333333333333333	0

It can save some effort to determine the number of JWST Observations that match each of your targets using the query_criteria_count() method. Note that the coordinate parameters must be specified as lower and upper bounds of a range (i.e., a python list), so use the coord_ranges() utility function.

It is good practice to first check the number of matching observations before fetching the results themselves, in case the number of results is very large. This is more important when querying MAST missions with a very large number of observations, such as HST. This type of search is typically fairly fast.

# get the counts of each target
for t in targets: 
    t['N_obs'] = Observations.query_criteria_count(
        obs_collection='JWST'
        ,coordinates=f"{t['ra_deg']} {t['dec_deg']}"
        ,radius=t['radius_deg']
        )
targets['target_name','N_obs'].show_in_notebook()

WARNING: InputWarning: Coordinate string is being interpreted as an ICRS coordinate provided in degrees. [astroquery.utils.commons]

Table length=4

idx	target_name	N_obs
0	Trappist-1	295
1	V* XX Cha	14
2	M 31	0
3	M 57	143

For targets where no JWST Observations exist, there is no potential for duplication.

Evaluating Potential Duplications

To examine the matching Observations for the other targets in more detail, use the query_criteria() method. Also, use a cone search (i.e., specify a coordinate pair and a radius), rather than an area search over a region in RA and Dec; see the Appendix for details. Note that a new column called “obs” is first added to the table to contain the results of the Observation search.

targets['obs'] = None
for t in targets: 
    t['obs'] = Observations.query_criteria(
        obs_collection='JWST'
        ,coordinates=f"{t['ra_deg']} {t['dec_deg']}"
        ,radius=t['radius_deg']
        )

WARNING: NoResultsWarning: Query returned no results. [astroquery.mast.discovery_portal]

Targets with matching JWST Observations are examined in the following sub-sections.

Trappist-1

Trappist-1 is a well known exo-planet host star. If the intended observations are timeseries spectroscopy, the search would naturally be limited to a small area of sky. There are a several unique JWST observations of this target, so it is important to examine the relevant details.

out_cols = ['target_name','instrument_name','filters','t_exptime','proposal_id']
obs = targets[0]['obs']
unique(obs[out_cols]).show_in_notebook()

Table length=17

idx	target_name	instrument_name	filters	t_exptime	proposal_id
0	TRAPPIST-1	MIRI/IMAGE	F1500W	11535.841	2304
1	TRAPPIST-1	MIRI/IMAGE	F1500W	11574.692	2304
2	TRAPPIST-1	MIRI/IMAGE	F1500W	74151.9	3077
3	TRAPPIST-1	MIRI/IMAGE	F1500W	138234.537	3077
4	TRAPPIST-1	NIRISS/SOSS	CLEAR;GR700XD	988.92	2589
5	TRAPPIST-1	NIRISS/SOSS	CLEAR;GR700XD	11965.932	1201
6	TRAPPIST-1	NIRISS/SOSS	CLEAR;GR700XD	15130.476	2589
7	TRAPPIST-1	NIRISS/SOSS	CLEAR;GR700XD	15723.828	2589
8	TRAPPIST-1	NIRSPEC/SLIT	CLEAR;PRISM	9770.112	1201
9	TRAPPIST-1	NIRSPEC/SLIT	CLEAR;PRISM	11855.698	2420
10	TRAPPIST-1	NIRSPEC/SLIT	CLEAR;PRISM	11870.008	1331
11	TRAPPIST-1	NIRSPEC/SLIT	CLEAR;PRISM	11929.94	1981
12	TRAPPIST-1	NIRSPEC/SLIT	CLEAR;PRISM	13751.556	2420
13	TRAPPIST-1	NIRSPEC/SLIT	CLEAR;PRISM	15085.324	2589
14	TRAPPIST-1B	MIRI/IMAGE	F1280W	13983.427	1279
15	TRAPPIST-1B	MIRI/IMAGE	F1500W	15690.076	1177
16	UNKNOWN	NIRSPEC/SLIT	OPAQUE;MIRROR	0.03	2742

You will need to examine the specifics of the programs that obtained the observations to know for certain which of the 7 known exoplanets was being observed, and therefore whether your intended observations would duplicate. Here are the unique Program Titles, which may offer clues:

obs['title'] = [x[:80] for x in obs['obs_title']]
unique(obs['proposal_id','title']).pprint(max_width=-1)

proposal_id                                      title                                      
----------- --------------------------------------------------------------------------------
       1177                                       MIRI observations of transiting exoplanets
       1201  NIRISS Exploration of the Atmospheric diversity of Transiting exoplanets (NEAT)
       1279                                               Thermal emission from Trappist-1 b
       1331                                              Transit Spectroscopy of TRAPPIST-1e
       1981 Tell Me How Im Supposed To Breathe With No Air: Measuring the Prevalence and Div
       2304                  Hot Take on a Cool World:  Does Trappist-1c Have an Atmosphere?
       2420     Probing the Terrestrial Planet TRAPPIST-1c for the Presence of an Atmosphere
       2589                             Atmospheric reconnaissance of the TRAPPIST-1 planets
       2742                                       NIRSpec darks for detector reconfiguration
       3077                                          TRAPPIST-1 Planets: Atmospheres Or Not?

The Program Status Pages offer the complete specifications for each existing program:

obs['proposal_URL'] = [get_program_URL(x) for x in obs['proposal_id']]
unique(obs['proposal_id','proposal_URL']).pprint(max_width=-1)

proposal_id                                proposal_URL                              
----------- -------------------------------------------------------------------------
       1177 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=1177&observatory=JWST)
       1201 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=1201&observatory=JWST)
       1279 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=1279&observatory=JWST)
       1331 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=1331&observatory=JWST)
       1981 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=1981&observatory=JWST)
       2304 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=2304&observatory=JWST)
       2420 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=2420&observatory=JWST)
       2589 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=2589&observatory=JWST)
       2742 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=2742&observatory=JWST)
       3077 (http://www.stsci.edu/cgi-bin/get-proposal-info?id=3077&observatory=JWST)

There are MIRI imaging observations (likely Time-series) in multiple bands, and both NIRISS and NIRSpec spectroscopic observations of this target that could conflict with your intended proposal.

V* XX Cha

This pre-main-sequence star has a debris disk, and might be worth a coronagraphic observation. The search area is small (20 arcsec radius) to exclude nearby targets.

out_cols = ['target_name','instrument_name','filters','t_exptime','calib_level','proposal_id']
obs = targets[1]['obs']
unique(obs[out_cols]).show_in_notebook()

Table length=7

idx	target_name	instrument_name	filters	t_exptime	calib_level	proposal_id
0	V-XX-CHA-2	MIRI/IFU	CH1	3696.348	3	1282
1	V-XX-CHA-2	MIRI/IFU	CH2	3696.348	3	1282
2	V-XX-CHA-2	MIRI/IFU	CH3	3696.348	3	1282
3	V-XX-CHA-2	MIRI/IFU	CH4	3696.348	3	1282
4	V-XX-CHA-2	MIRI/IMAGE	F1280W	3696.348	3	1282
5	V-XX-CHA-2	NIRSPEC/IFU	F290LP;G395H	32.21	2	1282
6	V-XX-CHA-2	NIRSPEC/IFU	F290LP;G395H	1288.416	3	1282

While JWST spectra from MIRI and NIRSpec exist, there is no potential for duplication with a coronagraphic observation.

M 57

The Ring Nebula (NGC 6720) is well observed, particularly with HST and, recently, with JWST. We searched a 4-arcmin region around the source to include potential spectral Observations in the nebular periphery. The following table shows the unique combinations of instrument configurations.

out_cols = ['target_name','instrument_name','filters','t_exptime','proposal_id']
obs = targets[3]['obs']
unique(obs[out_cols]).show_in_notebook()

Table length=43

idx	target_name	instrument_name	filters	t_exptime	proposal_id
0	NGC6720	MIRI/IMAGE	F1000W	444.0079999999999	1558
1	NGC6720	MIRI/IMAGE	F1130W	444.0079999999999	1558
2	NGC6720	MIRI/IMAGE	F1280W	444.0079999999999	1558
3	NGC6720	MIRI/IMAGE	F1500W	444.0079999999999	1558
4	NGC6720	MIRI/IMAGE	F1800W	444.0079999999999	1558
5	NGC6720	MIRI/IMAGE	F2100W	444.0079999999999	1558
6	NGC6720	MIRI/IMAGE	F2550W	444.0079999999999	1558
7	NGC6720	MIRI/IMAGE	F560W	444.0079999999999	1558
8	NGC6720	MIRI/IMAGE	F770W	444.0079999999999	1558
9	NGC6720	NIRCAM/IMAGE	F150W2;F162M	483.15599999999984	1558
10	NGC6720	NIRCAM/IMAGE	F212N	483.15599999999984	1558
11	NGC6720	NIRCAM/IMAGE	F300M	483.15599999999984	1558
12	NGC6720	NIRCAM/IMAGE	F335M	483.15599999999984	1558
13	NGC6720-MRS-POSITION-1	MIRI/IFU	CH1	2763.936	1558
14	NGC6720-MRS-POSITION-1	MIRI/IFU	CH2	2763.936	1558
15	NGC6720-MRS-POSITION-1	MIRI/IFU	CH3	2763.936	1558
16	NGC6720-MRS-POSITION-1	MIRI/IFU	CH4	2763.936	1558
17	NGC6720-MRS-POSITION-1	MIRI/IMAGE	F1000W	921.312	1558
18	NGC6720-MRS-POSITION-1	MIRI/IMAGE	F1130W	921.312	1558
19	NGC6720-MRS-POSITION-1	MIRI/IMAGE	F770W	921.312	1558
20	NGC6720-MRS-POSITION-2	MIRI/IFU	CH1	2763.936	1558
21	NGC6720-MRS-POSITION-2	MIRI/IFU	CH2	2763.936	1558
22	NGC6720-MRS-POSITION-2	MIRI/IFU	CH3	2763.936	1558
23	NGC6720-MRS-POSITION-2	MIRI/IFU	CH4	2763.936	1558
24	NGC6720-MRS-POSITION-2	MIRI/IMAGE	F1000W	921.312	1558
25	NGC6720-MRS-POSITION-2	MIRI/IMAGE	F1130W	921.312	1558
26	NGC6720-MRS-POSITION-2	MIRI/IMAGE	F770W	921.312	1558
27	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F070LP;G140M	145.889	1558
28	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F070LP;G140M	583.556	1558
29	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F100LP;G140M	145.889	1558
30	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F100LP;G140M	583.556	1558
31	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F170LP;G235M	145.889	1558
32	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F170LP;G235M	583.556	1558
33	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F290LP;G395M	145.889	1558
34	NGC6720-NIRSPEC-POSITION-1	NIRSPEC/IFU	F290LP;G395M	583.556	1558
35	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F070LP;G140M	145.889	1558
36	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F070LP;G140M	583.556	1558
37	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F100LP;G140M	145.889	1558
38	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F100LP;G140M	583.556	1558
39	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F170LP;G235M	145.889	1558
40	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F170LP;G235M	583.556	1558
41	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F290LP;G395M	145.889	1558
42	NGC6720-NIRSPEC-POSITION-2	NIRSPEC/IFU	F290LP;G395M	583.556	1558

There are both MIRI and NIRCam images in many passbands, and MIRI and NIRSpec spectroscopic IFU Observations of this target that could conflict with the intended proposal.

To retain this target it would be necessary to obtain spectra in a different location, or to use a different instrument/configuration/data-taking mode (e.g., time-series of the central star). It may be helpful to see the footprints of these Observations in the MAST Portal, or to view the observation specifications in Program GO-1558.

Appendix: Caveats

Source Name

It is possible to search MAST for individual sources by name, in one of two ways: Object Name or by Target Name.

• Object Name: MAST invokes an astrophysical name resolver (e.g., NED or Simbad) to look up source coordinates. Not all object names are recognized by resolvers. Also, different resolvers sometimes return substantially different coordinates; MAST will pick one of them (but not tell you which one). Sometimes the coordinates returned by the resolvers differ by substantial amounts, often because they refer to different sources.

  • A classic case is the bright star μ Eri from the Bayer Greek letter system, and the star MU Eri in the general catalog of variable stars. in MAST,

    • Searching for * mu. eri (or just plain mu eri matches μ Eri (RA = 4:45:30.15, Dec = -3:15:16.777)

    • Searching for V* mu eri matches MU Eri (RA = 2:48:10.566, Dec = -15:18:04.03)

• Target Name: This search matches to target names specified by Investigators in observing proposals to refer to sources. These are not guaranteed to match standard names for astrophysical sources, and often do not.

Searching by source names is not recommended when checking for potential duplications with fixed targets because the matches are not reliable, consistent, or complete. The exception would be for matching Object names of well known solar system bodies.

The best approach is to use an independent source for the coordinates of your desired target. Failing that, the Mast.resolve_object() method will return coordinates in the ICRS reference frame, which you can use to verify whether a target name resolves to the coordinates you intend.

Cone Search vs Area Search

MAST offers two basic kinds of spatial search:

• cone: a region of sky defined by a pair of coordinates and a search radius (it is a “cone” in the sense that the area of the search expands as the source distance increases).

• area: a region of sky bounded by ranges in each of the equitorial coordinates, RA and Dec.

These searches use different methods to identify overlaps with Observations in MAST. The cone search matches if any part of the observation aperture intersects any part of the cone. The area search matches only if the center of the observation aperture lies within the search region.

Searching by area is not recommended when checking for potential duplications with fixed targets because the matches may not include genuine overlaps of existing or planned observations.

The best approach is to use a cone search centered on the coordinates of your desired target.

Additional Resources

• astropy documentation

• astroquery documentation for querying MAST

• Queryable fields in the MAST/CAOM database

• The MAST Portal web interface

About this notebook

This notebook was developed by Archive Sciences Branch staff. For support, please direct questions to the Archive HelpDesk at archive@stsci.edu, or through the JWST HelpDesk Portal.

Last update: 2024 Jan