meeting 2026 02 18 gw - JacobPilawa/TriaxSchwarzschild_wiki_6 GitHub Wiki

Context

  • Following up on some questions that came up in the meeting/over email from the last day.
  • In particular, I have an updated three panel plot showing the effects of the k-corrections. I also have some plots trying to break down the mass difference (between K-band and W1/W2 based methods) into a variety of slices/panels/views.

Diagnostics

Three Panel K-Correction Plot

  • This is a very brief update, but was asked about in the email exchange:
    • I created a version of the K-Correction plot which splits the effect of the K-Correction into panels showing the K/W1 magntiude (top), the W1-W2 color (middle), and the net effect on the stellar mass inferred from each method (bottom panel). This is an extension of Figure 4 in the Overleaf, and looks like this:
KCorr Panels

Breaking W1 vs. K-band Masses into Redshift/Mass Bins

  • Now here's the fun bit -- I've tried visualizing the difference in masses as a function of redshift and stellar mass in a variety of ways. This first set of plots are new views for the "fiducial" Cluver case, but I've included all versions in the next section. Qualitatively they're all quite similar.
  • First, here's the fiducial Cluver+14_Clipped case vs. the LM24 relation.
    • The first and second plot are showing the mass difference for all galaxies as a function of redshift and as a function of K-band mass.
    • The next two panels break down the results into 4 redshift bins and 4 mass bins so you can more carefully tease out the dependence.
    • At least to my eye, the "All vs. z, Broken into M* bins" is most striking.
      • At least when I bin the data in this way, it seems like splitting the data into mass bins and plotting as a function of redshift reveals mostly a mass-dependent correction. It seems like these data are roughly "constant" versus redshift, but the amplitude of this constant increases with increasing mass.
      • This is further reinforced looking at the panel where the data are split into redshift bins, all of which have approximately the same fit line.
All vs. z All vs. M* All vs. M*, Broken into redshift bins All vs. z, Broken into M* bins
  • Here's a different version of the same data that I'm quite fond of. In each of these plots, I'm showing two panels:
    • In each panel, I divide the data into a bunch of bins defined by redshift and stellar mass, and I compute the mass difference (and standard deviation) in these bins.
    • The left panel shows the mean difference for galaxies in that (M*, z) bin, and the right panel shows the number of galaxies inside of that bin.
    • I've included a second set of plots showing the standard deviation of the mass difference in that bin for an idea of the "spread" of differences inside that cell.
    • At least to my eye, it seems like the M* dependnece is a bit stronger than the redshfit dependence?
Case LM24 vs. Jarrett+13 LM24 vs. Cluver14 LM24 vs. Cluver14_Clipped LM24 vs. Cluver14_Resolved LM24 vs. Jarrett+23 LM24 vs. Jarrett+23_Simple
Mean Difference
STD of the Difference

1-dimension slices through the heatmaps above

  • Instead of plotting this in 2d, I also split this into 1d panels binned by redshift/stellar mass:
Case LM24 vs. Jarrett+13 LM24 vs. Cluver14 LM24 vs. Cluver14_Clipped LM24 vs. Cluver14_Resolved LM24 vs. Jarrett+23 LM24 vs. Jarrett+23_Simple
All vs. z
All vs. M*
All vs. M*, Broken into redshift bins
All vs. z, Broken into M* bins
I've also created the same table but plotted against the Cappellari K-band relation instead of the LM24 relation.
Case Cappellari vs. Jarrett+13 Cappellari vs. Cluver14 Cappellari vs. Cluver14_Clipped Cappellari vs. Cluver14_Resolved Cappellari vs. Jarrett+23 Cappellari vs. Jarrett+23_Simple
All vs. z
All vs. M*
All vs. M*, Broken into redshift bins
All vs. z, Broken into M* bins
⚠️ **GitHub.com Fallback** ⚠️