While I did create the lists for brown dwarfs using Gaia DR2, I tought of searching for faint (Gmag>19) and red (BP-RP>2.2) sources. After crossmatching with WISE and checking with wiseview (http://ascl.net/1806.004) and/or BANYAN Sigma (http://adsabs.harvard.edu/abs/2018arXiv180109051G), we did submit good targets for follow up to the “advanced vetting form” of backyard worlds (www.backyardworlds.org).
As I used different methods, also for brighter targets, I was able to fill two useful diagrams. The first is something like a HR-diagram for brown dwarfs. With this new knowledge I decided that
is a good cut to get mostly brown dwarfs. I might miss some, but it is better than the simple constraints I used before.
The second diagram shows the relationship between brightness and distance. With this I hope to predict the spectral type. It is not very accurate. The second constraint to exclude most of the M-dwarfs is
Now you can further reduce the sample to avoid bad astrometry in Gaia DR2. For example you could
- crossmatch the sample with 2MASS or WISE and limit the number with color constraints (e.g. W1-W2>0.2 and J-W2>1.5)
- search in the sample for any object with a high probability in BANYAN Sigma
- search only for high proper motion objects
I used the last option and searched only for high proper motion objects. You can copy this query in “Advanced (ADQL)” (here) and click on “submit query”.
SELECT TOP 500 source_id,ra,dec,parallax,parallax_error,pmra,pmra_error,pmdec,pmdec_error,phot_g_mean_mag,bp_rp FROM gaiadr2.gaia_source WHERE (parallax>14 AND (phot_g_mean_mag>-0.0006*(1/(parallax/1000))*(1/(parallax/1000))+0.1075*(1/(parallax/1000))+15.8) AND (phot_g_mean_mag>-1.0309*bp_rp+21.978) AND (((pmra<-200 OR pmra>200) AND (pmdec<-200 OR pmdec>200)) OR ((pmra<-400 OR pmra>400) OR (pmdec<-400 OR pmdec>400))))
You will get a list of object with every information you need to proceed.
After cleaning the list from objects that are only a confusion of Gaia the two diagrams will look like this (objects that are a confusion by Gaia are red circles filled with light gray):
This is a useful information for the upcoming Gaia DR3. In the second diagram you can see that almost every object that Gaia is confusing with real targets have BP-RP<2.8. When Gaia DR3 is released I can use the above query and just add BP-RP>2.8. A (almost) clean sample should appear.
On the other hand: There are a lot of good objects in this area, filled with noise (see below).
Here are the same diagrams cleaned and with submitted objects and objects that are in Neowise or SIMBAD without a described spectral type:
There are three objects that stand out, located on the lower right of the second diagram:
2MASS J22521073-1730134, wich has a spectral type of L4.5+T3.5
additionally there is 2MUCD, which was cut from my sample because it was moving too slow. 2MUCD has a spectral type of L6.5.
I don’t know if these four brown dwarfs are in any way special or if it has to do with my method. We have submitted some targets in this gap, I just don’t know if they are good targets or if they are again the product of a confused Gaia spacecraft.
After finishing a more careful search I did create a 3-dimensional animation of the brown dwarfs I found (rotation is added to display the 3rd dimension/ The brown dwarfs do not rotate around a common centre, please keep this in mind):
The yellow point is the position of the solar system
White are the known L-dwarfs
Reddish Orange are the known T-dwarfs
Blue are the “good” L-dwarf candidates (including 1-2 T-dwarf candidates)
The current sample include an “insteresting” comover, which I submitted. It comoves with a known L1 dwarf. Because this pair is only 24 parsec distant and the seperation is not very large it could be a binary? This is exciting because Gaia does not have much T-dwarfs in their sample and all mid-late T-dwarfs in the current data release are known.
Only this one was not known.
To get an idea where you can find brown dwarfs in a HR-diagram I did select some “good” sources from Gaia DR2 with the quality flag and combined them with the final sample of brown dwarfs. To show where the brown dwarfs are in the HR-diagram I did color them in red on the left.
The Main Sequence, white dwarfs and giant stars look familiar, but the brown dwarfs do interrupt the nice shape of the main sequence and instead of getting redder the fainter they are, they get bluer.
Update: I did search for additional brown dwarfs without the color (BP-RP), by only using the first constraint and a proper motion limit:
This will show only sources with a proper motion larger than 90 mas/yr. In a second step I did crossmatch the resulting list with Allwise and cut the bad sources (W1-W2 and J-W2). This way I did get some good sources that don’t have their color recorded in Gaia DR2.
To get a better distance estimate I did use Bailer-Jones+ 2018, which has almost every Gaia DR2 source.
As you can see: The closer and the brighter a source is the more accurate is the distance estimate.
The candidates are too numerous to show them with the error bars in one diagram, so I did create another diagram, showing the completeness of my search and how my estimate of the spectral type works:
I could not find a candidate closer than 10 parsec, but 25 candidates closer than 25 parsec, which has an impact on future studies about the number of brown dwarfs in the Milky Way. The majority of the candidates are farther than 35 parsec.
This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).
Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement.
This work makes use of Bailer-Jones et al. 2018
This work makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration.