hot stars for SDSS-V (addendum 2)

Following up on the original post, I did the following variant:

The goal is to find massive stars, essentially by their two characteristics:
 they are luminous (abs(K)<-1, and they are hot, i.e. blue in unreddened colors.
The selection here is focussed on stars with some Gaia detection; even if the parallax
measurement is seemingly "marginal", it is powerful at ruling out all the low velocity stars.
The remaining challenge then is to separate luminous giant from luminous hot stars in the the presence of severe reddening. This can be done ad-hoc by devising self-dereddening colors, or (YST has done that with me) by taking BP,G,RP,J,H,K,W1 for stars with Apogee T_eff and training a neural net to predict T_eff in the presence of severe reddening; this seems to work beautifully, except that the training set is limited to 3500K<T_eff<8000K; this can be overcome.

Upshot of all of this: HWR's  naive view is that this works well (completeness and purity), as long as there is some Gaia information. Clean selection of massive stars that are H<12 or H<13, yet undetected in Gaia (say, G>19) remains a challenge, even conceptually.

Inspired by the hot-cool star separation (previous post, among absK<0),

I ran the query:

SELECT  g.*, tm.*, sqrt(g.phot_g_n_obs)/g.phot_g_mean_flux_over_error as variability
FROM gaiadr2.gaia_source AS g
INNER JOIN gaiadr1.tmass_best_neighbour AS xmatch
 ON g.source_id = xmatch.source_id
INNER JOIN gaiadr1.tmass_original_valid AS tm
 ON tm.tmass_oid = xmatch.tmass_oid
WHERE
tm.h_m < 12.
and
g.phot_g_mean_mag < 18.
and
( g.bp_rp < 1.  or  ( tm.j_m - tm.ks_m - 0.25*(g.phot_g_mean_mag - tm.ks_m) < 0.) )
and 
g.bp_rp < 2.
and
tm.j_m - tm.ks_m - 0.25*(g.phot_g_mean_mag - tm.ks_m) > -0.2
and
parallax < power(10.,(10.-tm.ks_m-1.)/5.)

which yielded:

I made a cut at bp_rp < 2, to cut out reddened variable sources.

Then I took the "massive stars regime"  at

then we get on sky for 40.000 objects:

those with 3sig parallaxes are:

Aside? Should I be worried that I don's see Orion?

Now let me just show what the plot looks like with the Teff estimates, derived from
BP,G,RP,J,H,K,W1 (trained to predict APOGEE Teff; courtesy Yuan-Sen Ting)

Here is a plot of NN-inferred (from colors) T_eff in the color-color plane:

The limiting (maximal) Teff is a consequence of the limited training set. The on-sky distibution of stars >6000K (16.000) of them at H<11.5 is here: (not bad?)

Addendum: November 2019

After the initial cuts, if one j_m - h_m - 0.13*(phot_g_mean_mag-ks_m) < 0.06, i.e.
makes another cut on on of these self-dereddened colors, one gets very "clean" samples.


In position space, they look like this:

and color coded by their G-K color (reddening), like this:

Detecting invisible companions to stars

The goal of the project is to develop strategies for how to detect "unseen massive" companions to regular stars, i.e. stars similar to the Sun (main sequence stars).

What do we mean by "unseen companions"?
Stars like the Sun can orbit (or be orbited) by a range of other astronomical objects:
-- by stars similar to them (binary stars)
-- by low-mass objects, foremost planet(s) or 'brown dwarfs'
-- by "stellar remnants", which could mean 'white dwarfs'(WD), 'neutron stars'(NS), or 'black
    holes'(BH); we presume that most stars that were massive enough to 'burn up their nuclear fuel'
    by now leave such remnants behind; as the mass of the progenitor stars increases,
    they leave behind WDs (M_init < 5M_sun), NS (5<M_init/M_sun<8), or BH (M_init >8M_sun)


In the present context, WD's are boring; NS are kind-of-boring, unless they have very masses (>2.xM_sun): the most massive NS constrain the neutron star equation of state. BH's left behind by stars are very exciting.

There are basically the reasons why BH's are exciting:
 -- they are so exotic, and we know so little about "stellar mass BHs"
 -- they are the ingredients in the most exciting gravitational wave events
 -- they tell us how stars die (see also below)

Why care about BH's in binary systems? So far, nobody has a good idea how to ever find a free-floating stellar-mass BH...

The only "stellar mass BHs" we know in the galaxy are ~15 'X-ray Binaries'. Those are systems where the orbit is so small that mass from the normal star gets torn off by tidal forces and streams onto the BH. In the course of this this material heats up very hot and shines in X-rays.
See: http://www-astro.physics.ox.ac.uk/~podsi/lec_c1_4_c.pdf
or
 [some very compact stellar evolution background at: http://www- astro.physics.ox.ac.uk/%7Epodsi/b3_stellar.pdf ]


We want to find many more BH's around normal stars, and those that orbit at greater distances. Why?
Having many more BH's tells us their "mass function"; as we know the mass function (i.e. mass probability distribution) of the progenitors, that provides information on "which star turns into what BH".
Why do we care about BH's orbiting more distant? If BH's form in Supernova explosions, then there is likely a recoil, as the explosion will not be perfectly symmetric. It is possible that only tightly bound stars stay in a binary after forming the BH. However, there are also theories that some stars form BHs simply by collapsing to a BH, without ever exploding as a supernova; then, there is of course no recoil.

for background, see e.g. http://www-astro.physics.ox.ac.uk/~podsi/lec_mm03.html
and this very relevant paper: https://arxiv.org/pdf/1710.04657.pdf
and
https://arxiv.org/pdf/1704.03455.pdf
[Note: these Gaia data will only be available in 2022.. we don't want to wait that long.]

How to find BH's orbiting other stars?
The most obvious approach would be to get spectra at many epochs, to get v_*(t). Taking spectra of millions of stars at many epochs is "expensive".

To search for them we should look for flux variations! E.g. the Gaia mission is mapping 10^9 stars, each >100 times.
And indeed, the tidal forces of an unseen companion "stretch" the stars, make it ellipsoidal. If we see it from the side, it has  larger projected area and is a bit brighter: this is called ellipsoidal distortion.

See: https://arxiv.org/abs/1106.2713 . Actually there are two more effects (as this paper shows); but the ellipsoidal distortions will be the strongest effect.

So, what to calculate and explore in this thesis?

Let's look at (and understand) the predicted amplitude A and the period P of the light modulation, as a function of the "underlying physical parameters": orbital separation, a, and the mass of the unseen object M_dark, for a, say, star of M_*=1M_sun; the amplitude also depends on the orbital inclination (if you look at a system "face on" --perpendicular to the orbital plane -- there is no variation).
[See the initial part of https://arxiv.org/abs/1106.2713 ]
I.e. derive A = f(M_dark,M_*,a,sin(i)), P= f(M_dark,M_*,a,sin(i)), and then ask
how M_dark depends on the observables (A,P,M_*), on sin(i) and on the quantity we want M_dark.

The first question is to answer: what physical properties can be determine from (an observed combination of) A and P alone? Are there unique signatures of BH companions (as opposed to
NS or WD)

What additional do we learn if we could determine the orbital inclination?

Then we will look at the (very model dependent) statistics of "how many BH's companions should show discernible signatures?" This is at the heart of the papers mentioned above:
https://arxiv.org/pdf/1710.04657.pdf
and
https://arxiv.org/pdf/1704.03455.pdf

So, how to start:
Work your way through the papers:
-- about populations:
https://arxiv.org/pdf/1710.04657.pdf
and
https://arxiv.org/pdf/1704.03455.pdf

-- about lightcurve variations due to unseen companions:
https://arxiv.org/abs/1106.2713

Variability in White Dwarfs (physics and Sample Selection)

Continuing on with my exploration of 'what variability in Gaia DR2 can do', I looked
at the Warwick GDR2 WD sample; variability == sqrt(phot_g_n_obs)/phot_g_mean_flux_over_error .
I restricted the following to G<18, as there the expected "shot-noise" contribution to this definition of variability is < 0.02mag.

If one looks at the WD sample, one sees that variability is very non-uniformly spread across the CMD, in good part as expected:

 or with larger dots

If I split the sample into a "non-variable" and variable" one, I get the following density maps.

Non-variable

and variable

I (as an absolute WD amateur) see three things:
-- variability is great to eliminate contaminants among faint (M=13) red (BP-RP~1.3) WDs
-- DAV (ZZ Ceti) stick out nicely, of course
-- are the hot variable WDs DBV stars??

Is any of that known (in this prettyness), is any of it interesting?