meeting 2023 11 20 n57 - JacobPilawa/TriaxSchwarzschild_wiki_5 GitHub Wiki
- We're reviving the N57 work now that the mock fire is mostly put out -- here is the state of where things left off.
- High Level Details
- D = 66.9 ± 2.9 (Jensen+2021) – this is 10 Mpc different from the previous distance measurement of 76.3 Mpc
- GMOS PA: +41.0 E of N, Mitchell PA: +41.1;
- GMOS PSF: Using Avg. weighted FWHM = 0.81"; Mitchell PSF: 0.5 (from N1453+N2693)
- 215 GMOS bins (8 moments), 41 Mitchell bins (6 moments) = 256 total bins, 1966 total kinematic constraints
- Also had done some preliminary sersic fits to determine R_core; could be interesting to revisit
And here is an exhaustive table of the different cubes we ran
Cube Name | Date | Summary |
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Cube A1 | Feb 3, 2022 | 6d hypercube, with gNFW profile. A bit undersampled, seemed to miss minimum. |
Cube A2 | Feb 10, 2022 | Submitted 1000 more models to cover higher black hole and higher halo region. Points chosen to have ~uniform density in the space. |
Cube A1A2 Scaled | Feb 22, 2022 | Scalings. Scaled the 13 models above to 13 different scales between 0.9 and 1.1, giving ~26,000 models total. |
Cube B | March 1, 2022 | Rejection sampled cube incorrectly built from 26,000 scaled models. ~1000 rejection sampled models. The error was in applying the "scale" to the models. Also scaled these models. |
Cube B Prime | March 15, 2022 | Corrected the scaling issue from Cube B and ran ~1000 more models. Also scaled these models. |
Cube C | March 21, 2022 | Rejection cube of 1000 models built from Cube A1A2 + Cube B Prime. |
Lipka Tests | March-April 2022 | 729 models at fixed masses, testing any effect of the Lipka m_eff on the shapes for N57. |
Cube D | May 17, 2022 | Built another rejection sampled cube based on the 1sigma contours (instead of 2 sigma contours) to try to solve the issue bi-modality issue in Tmaj. Didn't seem to improve things that much. |
First, here was the before-and-after imposing a prior on Tmaj cornerplot. As a quick reminder, these cornerplots were produced by running Emily's thinning routine on all scaled models (selecting best scaled version), but they differ in that the updated version uses a Gaussian prior with mean 0.55 and width 0.1 to avoid the bimodality.
Original | Imposed Prior |
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Best Fit kinematics
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Best Fit Sigma Profile
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- Here are some details and diagnostics on the problematic bins:
First, here are some plots without any masks applied.
GMOS Bin Map | Kinematic Maps | One-sided radial plot | Two-sided radial plot |
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Here's a version where I mask only the bins at the "corners" of the GMOS data. I think this is certainly better, but there are two more bins which I am in favor of removing which are shown in the next bullet.
GMOS Bin Map | Kinematic Maps | One-sided radial plot | Two-sided radial plot |
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And here's a version where the GMOS corners are removed, as well as two more bins along the perimeter which have sigmas slightly below the Mitchell data. I think that this is the best version of the GMOS masking.
GMOS Bin Map | Kinematic Maps | One-sided radial plot | Two-sided radial plot |
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And lastly, here's what I think ends up looking the best -- this has the GMOS corners masked, as well as the two additional bins along the perimeter. I also masked the two innermost Mitchell bins, and this GREATLY improves how the radial profiles appear.
GMOS Bin Map | Kinematic Maps | One-sided radial plot | Two-sided radial plot |
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Same as prev. bullet | Same as prev. bullet | ![]() |
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- And here are some plots comparing my data vs. Irina's vs. symmetrized and not:
And here are some comparsions to Irina's data -- I can't plot them in the same 1-to-1 style because we're using different binning schemes, but I think largely these data look consistent except for maybe the region near the very center?
All Kinematics | Mitchell Only | Irina's Input |
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Our original MGE fit was a great fit to the data, but it did have a "bump" of excess stellar mass near the center. We had been playing around with removing this by imposing a lower bound on sigma in our MGE fitting routine, and limiting this to be greater than or equal to 4 pixels seemed to do the job. We had submitted 100 models to test the effect of the new MGE on the best fit parameters, and we saw essentially no change between the two MGEs.
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Here are some of the diagnostics of the new MGE fit and resulting parameters:
Original MGE Components
I [Lsun/pc^2] | Sig [arcsec] | q | PA |
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6323.48 | 0.0965161 | 0.919959 | 0 |
6376 | 0.623279 | 0.949906 | 0 |
3966.81 | 1.09067 | 0.949906 | 0 |
3966.66 | 1.76526 | 0.843897 | 0 |
2643.14 | 3.05067 | 0.88211 | 0 |
698.844 | 5.58128 | 0.833226 | 0 |
653.081 | 8.53716 | 0.869193 | 0 |
190.653 | 18.5895 | 0.799925 | 0 |
69.162 | 46.7209 | 0.799925 | 0 |
"4pixel" MGE Components
I [Lsun/pc^2] | Sig [arcsec] | q | PA |
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4768.46 | 0.4 | 0.887837 | 0 |
6239.64 | 0.811965 | 1 | 0 |
5130.89 | 1.62907 | 0.851777 | 0 |
2880.44 | 3.03036 | 0.877635 | 0 |
916.088 | 6.22377 | 0.841813 | 0 |
315.076 | 9.35045 | 0.900791 | 0 |
172.662 | 13.4426 | 0.795679 | 0 |
123.189 | 27.7333 | 0.801938 | 0 |
24.8487 | 87.5 | 0.632801 | 0 |
Comparison of the past and present deprojected 3D luminosity densities of our MGEs for refence
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images/230811/lum_density_complete.png |
1d chi2 vs. parameters
No Color | Colored by BH | Colored by ML |
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Cornerplots
K=40 | K=60 | K=80 | |
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nu=0.5 | ![]() |
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nu=1.5 | ![]() |
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Plots of the Mbh vs. environmental measure from HDC
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results from the NED Constrained Cone Search but for the galaxies above -- NGC 57 is certainly the most isolated when considering only the small constrained cone searches, but remains in the top 3 lowest numbers of neighbors when expanding beyond the lower sets of bins.
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- I ended up running Emily's V(R, Theta) fitting routine for a few choices of bins and with/without the Mitchell data included.
- I'll begin just by summarizing results previously found for N57 from MASSIVE VII, X, and XIV:
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1+d_g = 2.3
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nu_10 = 4.9
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M_K = -25.75
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PA_Kin_GMOS = 100 +/- 22
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PA_Kin_mitchell = N/A
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PA_Phot = 40.2 +/- 0.5
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Psi = 59.3 +/- 22
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Note that these values (for the angles) are more or less in agreement with what I am finding below for V(R, Theta) fitting.
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Results considering only the GMOS data alone with a varied number of radial bins:
5 Bins | 7 Bins | 9 Bins | 11 Bins |
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And a few examples of only using the Mitchell data:
2 Bins | 4 Bins | 6 Bins | 8 Bins |
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And here's a case where I've included the Mitchell data as well -- didn't spend too long making this look too pretty because the bounds were a bit hard to get rid. I can return to this if we want Mitchell's V in our final plot.
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