Difference between revisions of "SSW2022 Activities"

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Then click "update" and close the pop-up window.
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##"Download table" to, well, download the table. Save it as an IPAC table file ("IPAC format") to make things easier for the next step.

Revision as of 22:20, 5 October 2022

Introduction

The Sagan Summer Workshop (SSW) is held annually and is meant to be a week-long summer "school" for early career astronomers (advanced undergraduates and graduate students/postdocs. The conferences traditionally have a substantial hands-on component. Each year, they pick a different theme. In 2022, the theme was Exoplanet Science in the Gaia Era. Several of the hands-on components from earlier in the week can be done using IRSA tools, so this is what we have reproduced here. See the SSW website for recordings of the talks that led into these hands-on sessions, as well as detailed instructions as to how to do these exercises using the Google Colab Notebooks provided by the workshop team.

Monday Afternoon, Part 1

  1. Query the Gaia Catalog of Nearby Stars (GCNS) for all stars within 20 pc. - as of the time I am writing this, the GCNS isn't available at IRSA, so you have to either go directly to the ESA Gaia Archive to get it, or get it from VizieR, like at this ftp site. The GCNS is large, but you can get it in csv format, which IRSA tools understand. To make this process easier, though, here is a truncated csv version of this catalog.
    1. Download and uncompress that copy, or download your own copy from VizieR.
    2. Load that csv catalog into IRSA Viewer by clicking on the catalogs tab, then "Load Catalog File."
    3. Filter down the catalog to only have the stars within 20 pc -- turn on filters and restrict the file to have only Plx>50. You should be left with ~2600 stars.
  2. Make an observed Gaia color-magnitude diagram for this sample.
    1. Use IRSA Viewer to make a plot of G vs. B-R -- the columns in the zipped csv file above are x=BPmag-RPmag and y=Gmag. Don't forget to reverse the y axis! Pin the plot so that you can compare it to other plots.
  3. Make an absolute Gaia color-magnitude diagram for this sample. - that is, correct for distance because you have the parallax!
    1. Use IRSA Viewer to make a new plot of absolute G vs. B-R. Hint: Gmag- (5*log10(1000/Plx) - 5).
    2. Pin it so that you can compare the first plot with this one.
    3. What are some things that are the same and different between these two plots? Why?
    4. What happens to the outliers if you plot absolute G vs. G-R instead of G vs. B-R? (Why?)
  4. Make an absolute SDSS color-magnitude diagram for this sample. - the SDSS photometry is included in the GCNS catalog, and you still have the parallax, of course.
    1. The SDSS filters are the columns "gmag", "rmag", "imag", and "zmag". Try g vs. g-i. You may have to cope with some outliers either by filtering the catalog or changing the limits of the plot.
    2. Why does the SDSS CMD look like it does? Why is it worse or better than the Gaia CMD?

Monday Afternoon, Part 2

  1. Query the Exoplanet Archive
    1. Go to the Exoplanet Archive, and find the Planetary Systems Composite Data Table.
    2. Go up the the upper left of the screen and click on "select columns." "Clear all" then select the columns corresponding to the columns in the SSW example :
name in Google Colab name in Exoplanet UI
pl_name Names / Planet Name
hostname Names / Host Name
ra System Data / Position / RA (pick the one in degrees, not sexagesimal)
dec System Data / Position / Dec (pick the one in degrees, not sexagesimal)
sy_gaiamag System Data / Photometry / Gaia Magnitude
st_teff Stellar data / Stellar Effective Temperature
st_logg Stellar data / Stellar Surface Gravity
st_met Stellar data / Stellar Metallicity (in dex)
st_lum Stellar data / Stellar Luminosity
st_rad Stellar data / Stellar Radius
st_age Stellar data / Stellar Age

Then click "update" and close the pop-up window.

    1. "Download table" to, well, download the table. Save it as an IPAC table file ("IPAC format") to make things easier for the next step.