Selection of Cepheids from PS1 and WISE data

The thought is to use the known sample of 85 Cepheids (with PS1 data) to do explore
by hand cuts.  The basic philosophy is:

1. Cepheids have to appear as bright sources in W1 and W2. Why? According to Freedman et al 2006-ish (LMC-based) even the short-period (2-day) least luminous Cepheids have M_W1 or M_W2 of about -3.55. So, if we consider a DM_max=15 for now, and A_V~15mag (A_W1~0.7mag), then we have m_W1 and m_W2 < 12.5
2. Cepheids have intrinsic W12 colors in a narrow range, -0.07<W12<0.2
   
3. The 84 Cepheids with PS1 data fall into a well defined patch of Hernitschek's variability amplitude omega_best and time-scale tau_best space: 0.08<omega_best<0.5 and 0.7days < tau_best<30days.
   

Taking the test regions from Laura (15' around Cepheids?) , we go from 1Million sources to 220, and still retain 79 of the 84 Cepheids

Note added: a W12 -- (J-K) cut may also be interesting

That leads to a candidate list that is very peaked to the plane

or, as seen on sky:

The file with the candidate sample is n this fits file: https://www.dropbox.com/s/5zoi4o9diip01pg/Hernitschek_catalog_WISEbright_W12-JKcut_omnega-tau-cut.fits?dl=0

Is the next step to run period fitting on these 7000 candidates?

Topcat GPS1 exercises

This is the basic color-color locus of stars

Went to the 30deg around the anticenter,

and picked red stars with low proper motion (RA82DEC0)

among those, there are stars that are very red in r-z. If we pick those they have a distinct angular distribution away from the plane, and in W1 apparent magnitude.

What are they?

If I look at a proper motion selected sub-sample in TGAS, I see

taken  together we see (at 350 pc???

according to TGAS)

What is it?

Puzzlingly the colors are those of giants not dwarfs

Things don't quite fit with a 1Gyr isochrone

Bringing in APASSS settles it; it's a lounging stellar population at 350 pc

That's a query to look at the wide area


SELECT
   *
   FROM gps1.main as ps1
   WHERE
      1=CONTAINS(POINT('ICRS', ra, dec),
                 CIRCLE('ICRS', 82. ,0., 15.))
   AND
ps1.magi BETWEEN 13. and 19.
   and
        (ps1.magg - ps1.magr) between 1.05 and 1.40
   and
        (ps1.magr - ps1.magi) between 1.0 and 2.0
   and
(3.6e6*sqrt( power(pmra,2) + power(pmde,2))) < 7.

This is the spatial distribution of the stars (that don't move and lie on the color-mag sequence)

if we superimpose the much brighter TGAS stars (in red), we get (Y-axis flipped)

What I learned about ADQL queries at the Gaia sprint; WD binaries

Morgan F. ran some tutorial with me on ADQL etc..

the idea is to find WD wide binary candidates that commove with TGAS

stars within 300 pc. Go to TOPCAT;  preload a table of TGAS stars within

300 pc; activate that table and then go to TAP queries; select GAVO; select gps1; 

Then:

SELECT

   TOP 10000  *

   FROM gps1.main AS db

   JOIN TAP_UPLOAD.t2 AS tc

   ON 1= CONTAINS(POINT('ICRS', db.ra, db.dec),

                 CIRCLE('ICRS', tc.ra, tc.dec, (10.3*tc.parallax/3600.))) 

   WHERE  db.e_pmra * 3.6e6 < 5. AND db.e_pmde * 3.6e6 < 5.

AND

                 SQRT( (power(tc.pmra-db.pmra*3.6e6 , 2) + power(tc.pmdec-db.pmde*3.6e6 , 2)) /

                 (power(db.e_pmra* 3.6e6,2)+power(db.e_pmde* 3.6e6,2)) ) < 5

Morgan's version of that query yielded nice results.

speeding up iCannon

In a thesis meeting with Christina, Joe brought up the following idea: currently we fit the pixel fluxes (and their variance) in the Cannon, why do we not fit the projection of the data onto a set of principal components? That would be far fewer data points?