🌎🕯🗺 Gaia Photometry¶

Often you need to know the magnitude of a star. Fortunately, the space-based Gaia survey has observed the entire sky with incredible precision; basically any star you can see with a moderate ground-based telescope has already been observed by Gaia. Common reasons you might need to download stars from Gaia would be to locate where to put apertures in an image or to use a star you observed as a flux calibrator; this page demonstrates two little tools that might be helpful for those purposes!

Downloading Gaia Data 💾¶

To get a table of positions and photometry, we can use the get_gaia function. This is a wrapper to astroquery and the fabulous Gaia archive, designed to be quick and easy to use.

In [1]:

from astropy.coordinates import SkyCoord
import astropy.units as u
from astr3510 import get_gaia

from astropy.coordinates import SkyCoord import astropy.units as u from astr3510 import get_gaia

To download some stars, specify a center and a radius, and let the function download data within that radius of that location. This will both download the star magnitudes directly measured with Gaia (G_gaia, BP_gaia, RP_gaia) and use color transformations to estimate the magnitudes in other common filters (g_sloan, r_sloan, i_sloan, V_johnsoncousins, R_johnsoncousins, I_johnsoncousins). With the results, you should have a decent estimate of the brightness of any star you want!

In [2]:

random_center = SkyCoord(ra=123.45*u.deg, dec=67.89*u.deg)
random_radius = 10*u.arcmin
random_stars = get_gaia(random_center, radius=random_radius)

random_center = SkyCoord(ra=123.45*u.deg, dec=67.89*u.deg) random_radius = 10*u.arcmin random_stars = get_gaia(random_center, radius=random_radius)

INFO: Query finished. [astroquery.utils.tap.core]

In [3]:

random_stars

random_stars

Out[3]:

QTable length=511

source_id	ra	dec	G_gaia_mag	RP_gaia_mag	BP_gaia_mag	parallax	parallax_error	pmra	pmra_error	pmdec	pmdec_error	distance_from_center	r_sloan_mag	i_sloan_mag	g_sloan_mag	V_johnsoncousins_mag	R_johnsoncousins_mag	I_johnsoncousins_mag
	deg	deg	mag	mag	mag	mas	mas	mas / yr	mas / yr	mas / yr	mas / yr	deg	mag	mag	mag	mag	mag	mag
int64	float64	float64	float32	float32	float32	float64	float32	float64	float32	float64	float32	float64	float32	float32	float32	float32	float32	float32
1096857033044992512	123.46358938838631	67.88971682015931	20.226247787475586	18.9457950592041	21.279850006103516	2.4612139436267366	0.5596178770065308	-1.5109944465762766	0.3861945867538452	-0.9993581676749135	0.646277129650116	0.005120868239371059	20.55800437927246	19.56468391418457	22.2702579498291	21.203420639038086	20.067562103271484	18.998441696166992
1096857101765237760	123.43892343048769	67.8956124547175	21.295581817626953	20.320524215698242	21.499958038330078	———	———	———	———	———	———	0.0069969087815531265	21.252859115600586	20.969985961914062	22.02094841003418	21.562204360961914	21.033828735351562	20.53368377685547
1096856994390017152	123.45645641263971	67.88125775716301	19.707828521728516	18.38322639465332	20.979854583740234	3.0573802467382465	0.3179308772087097	11.880533201188976	0.22325950860977173	-7.393675877038789	0.30488893389701843	0.00906763744984822	20.247432708740234	19.007596969604492	22.09683609008789	20.911039352416992	19.622631072998047	18.409908294677734
1096857067406032640	123.41929334070166	67.89178083196823	16.634456634521484	15.85244083404541	17.314313888549805	1.2050908672850105	0.048259854316711426	-5.567979326150691	0.03303448110818863	-12.077443510338655	0.04770999401807785	0.011695937379322676	16.615947723388672	16.201696395874023	17.64654541015625	17.0322265625	16.364782333374023	15.734864234924316
1096858510515041408	123.47577477788626	67.89700846015798	19.78288459777832	18.77142333984375	20.774452209472656	0.976072598519347	0.3294190466403961	-0.6670059327289899	0.23502284288406372	-5.061786742454724	0.31464746594429016	0.011969100518846922	19.925397872924805	19.189992904663086	21.412328720092773	20.509124755859375	19.557979583740234	18.662395477294922
1096857754600039168	123.49999720110058	67.88908128599442	20.955039978027344	19.92739486694336	21.314929962158203	———	———	———	———	———	———	0.018839214907547794	20.92664909362793	20.54891586303711	21.889101028442383	21.31561279296875	20.68536949157715	20.090198516845703
1096858574938003200	123.46783490647054	67.90936044690477	18.45643424987793	17.441452026367188	19.556238174438477	1.1080267906264099	0.1423102468252182	6.302811485122927	0.09683824330568314	2.3875680980172596	0.14534229040145874	0.020495447027742007	18.654342651367188	17.837873458862305	20.223045349121094	19.263147354125977	18.25058937072754	17.297353744506836
1096858574938005888	123.43623401557618	67.91233256108121	14.924246788024902	14.474855422973633	15.206657409667969	0.6235000607444191	0.021513553336262703	-2.598814995200761	0.015005433931946754	-0.8877672011204992	0.021025778725743294	0.022931369613166257	14.90665340423584	14.801634788513184	15.253921508789062	15.039621353149414	14.719002723693848	14.412050247192383
1096856277132046976	123.49405239672897	67.87329615053547	19.948223114013672	19.456560134887695	20.21337127685547	0.8301177083096152	0.3782431483268738	0.660914915822167	0.2582669258117676	-3.218612381323739	0.34905076026916504	0.02353474996760117	19.927539825439453	19.81319808959961	20.29794692993164	20.07021713256836	19.738399505615234	19.421058654785156
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1096861774690195200	123.14975326849779	68.01123088350226	16.916234970092773	16.282197952270508	17.327877044677734	0.2078815736899861	0.058080703020095825	-2.808386118175398	0.04185868799686432	-3.6260015231907197	0.0544656477868557	0.16553890346406566	16.873727798461914	16.64703369140625	17.51544952392578	17.13039207458496	16.665719985961914	16.224905014038086
1096761890930958848	123.24776438541268	67.7430013300241	14.152748107910156	13.552937507629395	14.589509963989258	2.2858515375881505	0.015925053507089615	-5.5572599447806	0.010669785551726818	-4.79061307718862	0.015232610516250134	0.16564329021784238	14.110501289367676	13.887518882751465	14.743611335754395	14.36355972290039	13.903173446655273	13.466348648071289
1096863149079727360	123.256741372855	68.03897948697701	16.10749626159668	15.485198020935059	16.5721492767334	0.20533020759581544	0.03904438391327858	1.117794587712151	0.02873515710234642	0.8237606307027106	0.03848066180944443	0.16569279366906325	16.064191818237305	15.820507049560547	16.74494743347168	16.337182998657227	15.85300064086914	15.394023895263672
1096861637251242880	123.10170381740276	67.99191724025559	15.049181938171387	14.546202659606934	15.380851745605469	0.7811855057495742	0.023990202695131302	4.12753010552377	0.016851527616381645	-4.718451642753252	0.022892599925398827	0.16582829787732484	15.020024299621582	14.876336097717285	15.462923049926758	15.19316577911377	14.82618522644043	14.47619915008545
1096765464343757824	123.07334676334233	67.80412654206437	15.187824249267578	14.685460090637207	15.519084930419922	0.6838498394764968	0.02623923309147358	3.194437324222604	0.01638740487396717	-9.645988862461584	0.021891755983233452	0.1659686910976007	15.158766746520996	15.01546859741211	15.600707054138184	15.331504821777344	14.96498966217041	14.615436553955078
1096766800076504192	123.0099793304518	67.87725952087362	16.725833892822266	16.19869613647461	17.086366653442383	0.2674047225333326	0.0514051653444767	1.1434576673148544	0.03617595508694649	0.10167435330908503	0.048395272344350815	0.16615284375907466	16.691946029663086	16.527929306030273	17.18456268310547	16.885997772216797	16.494796752929688	16.1223087310791
1096863144782865152	123.27317851734385	68.04252052176678	20.672447204589844	20.024959564208984	20.881399154663086	6.329621303711603	0.9460204243659973	-19.149605794546076	0.7373940944671631	-13.546277576323979	1.0426164865493774	0.16632746815327087	20.641239166259766	20.489234924316406	21.104543685913086	20.822961807250977	20.446054458618164	20.08684730529785
1096761238095922816	123.42685316330157	67.72385932226457	19.928386688232422	18.73736000061035	20.758501052856445	1.670723691410339	0.41950082778930664	-1.8159542550555168	0.29341042041778564	-6.6369528544514615	0.41385066509246826	0.1663646569910922	20.079315185546875	19.33116340637207	21.579856872558594	20.667375564575195	19.706342697143555	18.80147933959961
1096749521425137280	123.48182863404683	67.72406176226178	18.01885223388672	17.27911376953125	18.689733505249023	0.512780625711869	0.10643969476222992	-1.549766181443848	0.07013402134180069	-1.3352525633127426	0.10564824193716049	0.16636708946284962	17.993247985839844	17.604337692260742	18.976953506469727	18.390769958496094	17.749021530151367	17.14310646057129

Columns from this table can be extracted via their names.

In [4]:

random_stars['ra']

random_stars['ra']

Out[4]:

$[123.46359,~123.43892,~123.45646,~\dots,~123.27318,~123.42685,~123.48183]\mathrm{{}^{\circ}}$

We can also specify the center by using SkyCoord's ability to look up stars by common names.

In [5]:

some_center = SkyCoord.from_name('GJ1214')
some_stars = get_gaia(some_center)

some_center = SkyCoord.from_name('GJ1214') some_stars = get_gaia(some_center)

INFO: Query finished. [astroquery.utils.tap.core]

In [6]:

some_stars

some_stars

Out[6]:

QTable length=875

source_id	ra	dec	G_gaia_mag	RP_gaia_mag	BP_gaia_mag	parallax	parallax_error	pmra	pmra_error	pmdec	pmdec_error	distance_from_center	r_sloan_mag	i_sloan_mag	g_sloan_mag	V_johnsoncousins_mag	R_johnsoncousins_mag	I_johnsoncousins_mag
	deg	deg	mag	mag	mag	mas	mas	mas / yr	mas / yr	mas / yr	mas / yr	deg	mag	mag	mag	mag	mag	mag
int64	float64	float64	float32	float32	float32	float64	float32	float64	float32	float64	float32	float64	float32	float32	float32	float32	float32	float32
4393265392168829056	258.8314799887317	4.960575338342743	12.996782302856445	11.68291187286377	14.912440299987793	68.29864790496704	0.06518708169460297	580.202152322342	0.059069931507110596	-749.7132787585067	0.046714574098587036	0.004213553583360604	14.281705856323242	12.260824203491211	16.261287689208984	14.842987060546875	13.164945602416992	11.584444046020508
4393265594029572864	258.82548059022554	4.959673415391515	19.814598083496094	18.7404842376709	20.92361831665039	-0.12201931576844059	0.4233180284500122	0.7886772319541978	0.38949310779571533	-5.90216430988526	0.31440091133117676	0.005436663367761337	20.050561904907227	19.18158721923828	21.666542053222656	20.672658920288086	19.622066497802734	18.633102416992188
4393265594029578624	258.8303453443598	4.969318799593391	18.467039108276367	17.849897384643555	18.9268798828125	0.32598400597497745	0.14732687175273895	-2.3171063464633663	0.13715088367462158	-2.8002450271574886	0.11037397384643555	0.0055955418154212495	18.423870086669922	18.184314727783203	19.095197677612305	18.692920684814453	18.213462829589844	17.75888442993164
4393265594029575936	258.8345934758168	4.965356067428126	19.528406143188477	18.817964553833008	20.048349380493164	0.9195919172227879	0.2980462312698364	-0.13105104020166408	0.29258519411087036	-2.780651379773647	0.230753093957901	0.005855239245568904	19.487468719482422	19.182281494140625	20.303503036499023	19.8166446685791	19.26363754272461	18.74053192138672
4393265598326066432	258.8260166383157	4.969221589104122	21.041614532470703	19.73952293395996	22.038986206054688	———	———	———	———	———	———	0.006035423410204868	21.349946975708008	20.386186599731445	23.041173934936523	21.99078941345215	20.874629974365234	19.82403564453125
4393265392167890176	258.8331333378074	4.9586369446744065	17.20298957824707	16.52166175842285	17.653566360473633	0.31761288226776757	0.08060498535633087	-2.6388754129907195	0.07629198580980301	-1.8090458983625795	0.05639905482530594	0.0067554765457613535	17.1595516204834	16.897018432617188	17.88279151916504	17.450260162353516	16.944679260253906	16.46577262878418
4393265594029575424	258.8221023063075	4.964097257256533	18.891849517822266	18.464885711669922	19.212743759155273	-0.08964745632392115	0.19999991357326508	-0.21041661007722506	0.18089303374290466	-5.859332991385228	0.14873191714286804	0.006772384266162155	18.87225341796875	18.761253356933594	19.234365463256836	19.011449813842773	18.68364715576172	18.37002944946289
4393265353511402752	258.8275448277946	4.956599989525407	18.19046974182129	18.28221321105957	18.134431838989258	0.128803443046689	0.1276603788137436	-2.2870076084982003	0.1191125214099884	-14.33279722520088	0.09272509813308716	0.007435501213667212	18.35614585876465	18.585100173950195	17.99251365661621	18.210838317871094	18.253276824951172	18.281362533569336
4393265392167889664	258.8328976491856	4.957613805209845	16.265377044677734	15.51598834991455	16.87837028503418	0.76954057935162	0.048896461725234985	-4.000658586016978	0.04738306254148483	-8.340730069161536	0.03560008108615875	0.0074532985723650075	16.234233856201172	15.86851978302002	17.17344093322754	16.61379623413086	15.996045112609863	15.412535667419434
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
4393268308448906368	258.72897310940243	4.963472468196353	19.786701202392578	18.916301727294922	20.808021545410156	0.19950324277927545	0.35724377632141113	1.720337020375147	0.3665202260017395	-6.160889755693347	0.30260518193244934	0.09955077068142124	19.882102966308594	19.221895217895508	21.282590866088867	20.437091827392578	19.546154022216797	18.70703887939453
4393275115973872128	258.8294812377683	5.0634971814688114	18.059717178344727	17.4281063079834	18.5201473236084	0.10891950096582698	0.12421425431966782	-2.5535336119216034	0.12789541482925415	-1.3509734707538876	0.09003755450248718	0.09958655503775107	18.016359329223633	17.770557403564453	18.70192527770996	18.291358947753906	17.80476188659668	17.343536376953125
4390261934419773952	258.9199204847354	4.922753388828661	20.119403839111328	19.462875366210938	20.767452239990234	-0.4009253301230668	0.4742431938648224	-2.4164993371569627	0.5000970363616943	-2.018081806711649	0.3630990982055664	0.09958761635388078	20.083026885986328	19.74432945251465	20.968515396118164	20.440725326538086	19.85149383544922	19.294599533081055
4393262467293345920	258.78715760018787	4.873393994658311	17.87934684753418	17.42167091369629	18.19889259338379	0.17389487264683223	0.11520089209079742	0.0072955718401033	0.09989719837903976	-4.234450077111919	0.07727477699518204	0.09961421234303547	17.856271743774414	17.734285354614258	18.245620727539062	18.00690460205078	17.665912628173828	17.34005355834961
4393263498085508480	258.7464218179167	4.907450994487482	17.84841537475586	17.252365112304688	18.27007484436035	0.06147753884283451	0.10275927931070328	-3.608316414650199	0.09851474314928055	-0.6464691458675303	0.08229614049196243	0.09969850104903731	17.80680274963379	17.59146499633789	18.422075271606445	18.052385330200195	17.600858688354492	17.172277450561523
4393264361375716992	258.92231618290253	4.9280466284948	18.882038116455078	17.304718017578125	19.79410743713379	———	———	———	———	———	———	0.09974216346382465	19.330183029174805	18.19590950012207	21.128589630126953	19.99004554748535	18.764585494995117	17.611148834228516
4393269927653385472	258.76972258111397	5.04440980073196	15.45716667175293	14.876876831054688	15.867270469665527	0.6121189038834349	0.03552864491939545	-4.4141787868072395	0.033296313136816025	-0.966707238307875	0.025193918496370316	0.09977418975288643	15.41669750213623	15.212335586547852	16.00615119934082	15.651449203491211	15.212702751159668	14.796011924743652
4393269687132214656	258.74330938418376	5.016032320994322	19.42879295349121	18.631284713745117	20.06942367553711	0.33799186631762845	0.3193487226963043	2.2610459821616113	0.3499622941017151	-6.655832456359581	0.2663625180721283	0.09993209431067575	19.406841278076172	19.00441551208496	20.4157772064209	19.814477920532227	19.158958435058594	18.540180206298828
4393269893293365504	258.75858952711974	5.035265196488171	21.10805892944336	———	———	———	———	———	———	———	———	0.09998460449950151	nan	nan	nan	nan	nan	nan

Visualizing Gaia Data 🎨¶

It'd be nice to be able to see this information in a way that's not just a giant table of data. Let's use the plot_gaia tool to plot one of the tables we've already downloaded.

In [7]:

from astr3510 import plot_gaia

from astr3510 import plot_gaia

In [8]:

plot_gaia(some_stars)

plot_gaia(some_stars)

We can change options to modify the appearance of this finder chart, including changing which filter is used to set the relative sizes of the points.

In [9]:

plot_gaia(some_stars, 
          filter='i_sloan',
          faintest_magnitude_to_show=17,
          faintest_magnitude_to_label=13,
          size_of_zero_magnitude=200,
          unit=u.arcsec)

plot_gaia(some_stars, filter='i_sloan', faintest_magnitude_to_show=17, faintest_magnitude_to_label=13, size_of_zero_magnitude=200, unit=u.arcsec)

With these tools, you can access a table of data and a quick visualization for any patch of the sky you care about!

In [10]:

cluster_center = SkyCoord.from_name("NGC 457")
cluster_stars = get_gaia(cluster_center)
plot_gaia(cluster_stars, faintest_magnitude_to_label=10)

cluster_center = SkyCoord.from_name("NGC 457") cluster_stars = get_gaia(cluster_center) plot_gaia(cluster_stars, faintest_magnitude_to_label=10)

INFO: Query finished. [astroquery.utils.tap.core]