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View Code? Open in Web Editor NEWA project to measure starspot properties on M67 sub-subgiant S1063 :ship: :ship:
License: MIT License
A project to measure starspot properties on M67 sub-subgiant S1063 :ship: :ship:
License: MIT License
The referee made a good point that we did not justify the similarity of the K2-bandpass and the V-band, the latter of which is much narrower than the former. What effect does that bandwidth play in our spectral analysis (principally the photometry and alignment)?
To explore this question I overlay the K2 and V-band bandpasses, and fetch a 5200 K (ambient) and 4000 K (spotted) spectrum (logg=4 for simplicity). I compare the two curves to these bandpasses:
The filter-curve weighted integral of the two curves spot and ambient curves yields the emergent flux as a function of spot filling factor:
We see that the curves are very similar. The slope of the K2 curve means a 1% change in filling factor results in an 0.78% flux loss. The V-band result is similar-but-not-identical: a 1% change in filling factor results in an 0.83% flux loss. This makes sense: the V-band is bluer on average than the wider and red-weighted K2-bandpass. So the starspots look like they have slightly more contrast in V than they do in K2-band. But the difference is relatively small. It means that for a fixed starspot areal coverage change from one say Eastern hemisphere to the next say Western hemisphere, we may perceive amplitudes of lightcurve modulation that differ by about 6%: the V band should have about a 6% higher amplitude than the K2 band. The ASAS-SN data quality is not adequate to discern a discrepancy of only a few percent. We therefore conclude that treating these bands as identical for the purposes of starspot contrast is justifiable given our available photometric quality and sampling.
I have code to do this now.
There were five that showed multi modal behavior
107, 110, 113, 114, and 118
We have copious photometry data! Let's make a figure with these elements:
We've already done this for posters, so we should translate that work into a paper-sized version. We also need to describe in the text what we have done to create this figure and what we learn from it. In particular:
Can we assign the starspot coverage fraction at the global peak-and-valley?
We need ranges in Teff, logg, and [Fe/H] for the emulator.
From the group Slack convo from Natalie:
Range in Teff: 5250 K down to the spot lower temp. Maybe 3000?
Log g: 3.0-4.0
[Fe/H]: -0.1 to 0.1
Since the Phoenix model grid is quantized according to Table ~1 in Husser et al. 2013, I will adopt:
Teff: [3000 - 5300]
logg: [3.0 - 4.0]
[Fe/H]: [-0.5 - 0.5]
Notes:
This source has K2 EPIC ID here:
EPIC 211414597
RA, DEC: 08 51 13.354 +11 51 40.15
It appears to be in an M67 super stamp. Which campaigns is it in? C5, C16, and C18?
We have both Overleaf and an ms.tex file in the GitHub version control. The GitHub version is the master version. The overleaf link can be used to share with collaborators, or work interactively. You have to ask Natalie for the Overleaf link.
So that we can break down the writing task into smaller pieces.
just in case someone stumbles upon it, there's no confusion
Orders 104 and 105 ran, but didn't actually work. Here is the terminal output:
104
/Users/ngosnell/anaconda3/envs/astroconda/lib/python3.5/site-packages/emcee/ensemble.py:335: RuntimeWarning: invalid value encountered in subtract
lnpdiff = (self.dim - 1.) * np.log(zz) + newlnprob - lnprob0
/Users/ngosnell/anaconda3/envs/astroconda/lib/python3.5/site-packages/emcee/ensemble.py:336: RuntimeWarning: invalid value encountered in greater
accept = (lnpdiff > np.log(self._random.rand(len(lnpdiff))))
real 0m11.095s
user 0m17.103s
sys 0m1.789s
105
/Users/ngosnell/anaconda3/envs/astroconda/lib/python3.5/site-packages/emcee/ensemble.py:335: RuntimeWarning: invalid value encountered in subtract
lnpdiff = (self.dim - 1.) * np.log(zz) + newlnprob - lnprob0
/Users/ngosnell/anaconda3/envs/astroconda/lib/python3.5/site-packages/emcee/ensemble.py:336: RuntimeWarning: invalid value encountered in greater
accept = (lnpdiff > np.log(self._random.rand(len(lnpdiff))))
real 0m10.826s
user 0m17.284s
sys 0m1.725s
The run.out file is exactly like successful orders and the and log.log files are two lines long:
04/22/2018 09:43:56 PM - INFO - SampleThetaPhi 0 - Initializing model on Spectrum 0, order 0.
04/22/2018 09:43:56 PM - DEBUG - SampleThetaPhi 0 - Loading stored Chebyshev parameters.
The emcee_chain.npy
file has 5000 non-zero entries, but they are all identical, as if the walkers didn't walk:
Need to go back and figure out why these orders aren't working!
I came up with 604921030968952832 as the Gaia DR2 source ID.
I checked to see if its in the (admittedly space, polychromatic) lightcurves that come for some Gaia DR2 sources. It was not.
We're reviving this project! Where do we stand?
Proposed Solution: I've since improved the reduction around Hydrogen lines, it might be worth spot-checking, but not critical (only affect some orders).
Proposed Solution: Run more orders! Maybe all of them?
Proposed Solution: Dunno about this! We could write some code that finds the most recent saved sample and starts from there?
Proposed Solution: We need to git pull Starfish on TACC, make sure we're on the intended branch, and always remember to source activate the correct environment.
Proposed Solution Natalie and I look at the spectrum.
/work/03342/gully/maverick/science/subsub/notebooks
and /home/03342/gully/science/subsub/
.Proposed Solution: Use the /work/
path because it has more storage capacity. We should rename the $subsub
alias to the work
one.
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