Day 1-2 (07/11-12)
- Day 1: Reviewed papers Chris sent, met with Chris and Eske on Zoom to discuss expectations, project outline on wiki page
- Day 2: Set up FASRC account. Followed the "User Quick Start Guide" on FASRC page
- set up 2FA, FASRC VPN, terminal access, and watched a few data transfer videos
- Used rsync to load Eske's target directory /n/holystore01/LABS/stubbs_lab/Lab/Auxtel_data/spectrum_data onto computer
- Went into lab and met Eske, Ali, and Mark in person. Very cool people.
- Opened Jupyter notebook; looked up astropy documentation to open fits files
- Successfully opened fits file to view contents inside, retrieved and displayed table data, displayed file header information, and plotted data
Day 3 (07/13)
- In Jupyter notebook, filtered all the fits files in '/spectrum_data' to print out star name and date/time of observation
- Stored names of files in record type that are all associated with one star; looks like there are 4 observed stars in the dataset Eske gave me.
Day 4 (07/14)
- Found data files missing the table of equivalent widths that Eske gave me
spec_data_2022062800336.fits HD205905 2022-06-29
- Plotted H2O and O2 equivalent widths against air masses for each star on each night (four stars on four nights based on data Eske gave me)
- Noticed that some files do not have O2 data (may have variants like O2(Z) or O2(B), though)
First Impressions of Data:
- The equivalent widths of H20 seem to have much more variability than those of O2
- May be some outliers in the data (particularly for the first two plots with the negative equivalent widths, may need to check on those data points
Findings
Links to Notebook:
Github repo of project code: https://github.com/ariscjj/stubbs
In notebook: https://github.com/ariscjj/stubbs/blob/master/Extract_H20.ipynb (added Chris as a collaborator on the github)
...
are the a and b values consistent for the oxygen line? Shouldn't depend on the star or the night
are the a and b values consistent with zero for all stars for all nights?
etc.
Identify instances of missing equivalent widths, to tell our friends who do these reductions.
Make a list of bad-data instances, so we can screen them out of our analysis.
stretch
...
goals:
1)
Many of these stars have "known" spectra. They're called CALSPEC standards. See https://www.stsci.edu/hst/instrumentation/reference-data-for-calibration-and-tools/astronomical-catalogs/calspec
...
If you spline the CALSPEC spectra onto same wavelength scale as our wavelength-calibrated spectra, fit our spectra as a function of airmass (the actual spectra, not the equivalent widths), extrapolate to zero airmass, and divide that by the known stellar spectrum we should recover the instrumental throughput function.
2)
Using the spectra we have, for wavelengths less than 700 nm pick some clean regions and compute flux in 3-4 different intervals to investigate continuum reduction.