1. The Fundamental Plane of Quasars Timothy Scott Hamilton NASA/GSFC, National Research Council …Putting the “fun” back in “Fundamental Plane”!

2. QSO Fundamental Plane Abstract The “Fundamental Plane” for quasars relates the nuclear luminosity to the size and surface brightness of the host galaxy. Quasars lie on a thin plane within this phase space. Comparisons with the elliptical galaxy fundamental plane could tell us about the formation history of quasars. The “tilt” of the plane might be a characteristic of the type of active galaxy.

3. Full Sample 70 low-z QSOs from Hubble Space Telescope archives –M V < -23 –redshifts 0.06 < z < 0.46 –WFPC2 broad-band filters

4. Restricted Sample Require: –Host: Elliptical or elliptical bulges of spirals Effective radius (r e ) and effective magnitude  e  –Nuclear x-ray luminosity (L x ) Literature data from ROSAT (mostly) and other missions. Eliminated 4 outliers Restricted sample has 38 QSOs.

5. Image Analysis 1.Standard HST pipeline and cosmic-ray removal. 2.Fit PSF structure to core—color, focus, centering. 3.Fit 2-D PSF+host models simultaneously. 4.Subtract PSF model to reveal host.

6. Cosmic-ray cleaned, before PSF removal Image Analysis: PG 0052+251

7. PSF model

8. Image Analysis: PG 0052+251 PSF + host models

9. Image Analysis: PG 0052+251 PSF-subtracted host

10. PG 0052+251 Bulge BeforeAfter

11. Physical Parameters Obtain M V (nuc) from fitted PSF scaling. r e directly from host model. M V (host) from PSF-subtracted image, with model used only to fill in missing data and extrapolate to infinite radius. Bulge and disk fitted separately. X-ray luminosity & black hole masses from literature.

12. Varieties of Hosts SB E S S? MS 0801.9+2129 Q 2215-037 PG 0052+251 PG 1309+355

13. Host vs. Nuclear Luminosity

14. Look for multiple correlations M V (host) vs. M V (nuc) shows a weak correlation. Look for host—nuclear correlations among several parameters at once.  Principal Components Analysis

15. Principal Components Analysis (PCA) Looks for correlations in multi-dimensional data. Rotates coordinate axes to align with directions of greatest variance—finds the eigenvectors. If there are strong correlations, the dataset might be described by smaller number of parameters.

16. First-Run PCA Used M V (nuc), M V (bulge), & log r e First two eigenvectors account for 89% of variance. –QSOs lie roughly in a thick plane defined by first 2 eigenvectors. –Third eigenvector (11%) accounts for thickness of plane.

17. Improved PCA Use M V (nuc),  e, & log r e 96% of variance explained by 2 eigenvectors. –Plane is thinner. –Only 4% variance in third eigenvector.  The “Fundamental Plane” of quasars.

18. X-ray PCA Perform PCA using x-ray nuclear luminosities: log L X,  e, & log r e First two eigenvectors explain 95% of variance.

19. Subsample PCA results Sample % of variance explained Optical Fundamental Plane X-ray Fundamental Plane All95.994.9 LE97.997.4 QE97.698.1 QS94.598.7 L97.997.4 Q95.595.6 E96.596.0 S91.686.1

20. QSO FP QSO optical fundamental plane: M V (nuc) = 3.1  e - 13 log r e - 76 QSO x-ray fundamental plane: log L X = -1.9  e + 7.9 log r e + 78

21. Accuracy of QSO FP Optical fundamental plane vs. data X-ray fundamental plane vs. data

22. Derivation from Normal FP? Normal galaxy FP (Scodeggio et al. 1998): log r e = 1.35  c + 0.35  e + Constant Use M BH ~  c relation to get black hole masses. Obtain M V (nuc) from M BH ? –No! »…and why not? 

23. Black Hole vs. Nucleus

24. QSO Fundamental Plane: Comparison with Derivation QSO FP derived from normal galaxy fundamental plane: log r e = -0.41 M V (nuc) + 0.35  e + Constant QSO FP (correct form, from PCA): log r e = -0.074 M V (nuc) + 0.23  e + Constant  This argues that we do not have the complete story.

25. Edge-on views of plane Complete sample Radio-louds in ellipticals

26. Size—Surface Magnitude

27. Indicator of galaxy merger history? –Equal-sized mergers  shallow slope –Big swallows small  steep slope Group by RL/RQ –Inconclusive. …Dead-end for interpretation?

28. Size—Surface Magnitude

29. FP Tilt Quasar FP is composed of different overlapping, tilted planes for different subsamples. Subsamples have same r e ~  e slopes but different tilts relative to M V (nuc). –So host behavior is ~same, but it is connected to the nucleus in different ways.  Is slope characteristic of accretion mechanism?

30. Testing Meaning of QSO FP Analyze lower-luminosity AGN: –Seyferts, radio galaxies, blazars, Low- Luminosity AGN, etc. Do other AGN classes have fundamental planes? How do those planes compare with the QSO FP?

31. Possible Outcomes 1.Plane is parallel to QSO FP but shifted. Host type has little effect on AGN type. What creates the difference? 2.Plane is tilted to QSO FP. FP slope is characteristic of AGN type. Slope directly tied to accretion mechanism? 3.They share the QSO FP. AGN power scales directly with the galaxy properties! Even across types. Argument for unification. 4.No trend whatsoever. QSOs have special property not shared by other AGN. High-powered objects more closely connected with their host properties. ?!?

32. Status of Project LLAGN (sample of Ho et al. 2001) show evidence of a fundamental plane (90% of variance). –Strong encouragement for additional work! Proposals for Chandra observations. Hubble and Chandra archival data next.