The Fundamental Plane of Quasars

Timothy Scott Hamilton

NASA/GSFC, National Research Council

…Putting the “fun” back in “Fundamental Plane”!

QSO Fundamental Plane

AbstractThe “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.

Full Sample

• 70 low-z QSOs from Hubble Space Telescope archives– MV < -23

– redshifts 0.06 < z < 0.46– WFPC2 broad-band filters

Restricted Sample

• Require: – Host: Elliptical or elliptical bulges of spirals

• Effective radius (re ) and effective magnitude e

– Nuclear x-ray luminosity (Lx )• Literature data from ROSAT (mostly) and other missions.

• Eliminated 4 outliers

Restricted sample has 38 QSOs.

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.

Cosmic-ray cleaned, before PSF removal

Image Analysis: PG 0052+251

Image Analysis: PG 0052+251

PSF model

Image Analysis: PG 0052+251

PSF + host models

Image Analysis: PG 0052+251

PSF-subtracted host

PG 0052+251 Bulge

Before After

Physical Parameters

• Obtain MV(nuc) from fitted PSF scaling.• re directly from host model.• MV(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.

Varieties of Hosts

SB

E

S

S?

MS 0801.9+2129

Q 2215-037

PG 0052+251

PG 1309+355

Host vs. Nuclear Luminosity

Look for multiple correlations

MV(host) vs. MV(nuc) shows a weak correlation.

Look for host—nuclear correlations among several parameters at once.

Principal Components Analysis

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.

First-Run PCA

• Used MV(nuc), MV (bulge), & log re

• 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.

Improved PCA

• Use MV(nuc), e , & log re

• 96% of variance explained by 2 eigenvectors.– Plane is thinner.– Only 4% variance in third eigenvector.

The “Fundamental Plane” of quasars.

X-ray PCA

• Perform PCA using x-ray nuclear luminosities:

log LX, e , & log re

• First two eigenvectors explain 95% of variance.

Subsample PCA results

Sample

% of variance explained

Optical Fundamental Plane

X-ray Fundamental Plane

All 95.9 94.9

LE 97.9 97.4

QE 97.6 98.1

QS 94.5 98.7

L 97.9 97.4

Q 95.5 95.6

E 96.5 96.0

S 91.6 86.1

QSO FP

• QSO optical fundamental plane:

MV(nuc) = 3.1 e - 13 log re - 76

• QSO x-ray fundamental plane:

log LX = -1.9 e + 7.9 log re + 78

Accuracy of QSO FP

Optical fundamental plane vs. data X-ray fundamental plane vs. data

Derivation from Normal FP?

• Normal galaxy FP (Scodeggio et al. 1998):

log re = 1.35 c + 0.35 e + Constant• Use MBH ~ c relation to get black hole

masses.• Obtain MV(nuc) from MBH?

– No!» …and why not?

Black Hole vs. Nucleus

QSO Fundamental Plane:Comparison with Derivation

• QSO FP derived from normal galaxy fundamental plane:log re = -0.41 MV(nuc) + 0.35 e + Constant

• QSO FP (correct form, from PCA):log re = -0.074 MV(nuc) + 0.23 e + Constant

This argues that we do not have the complete story.

Edge-on views of plane

Complete sample Radio-louds in ellipticals

Size—Surface Magnitude

Size—Surface Magnitude

• Indicator of galaxy merger history?– Equal-sized mergers shallow slope– Big swallows small steep slope

• Group by RL/RQ– Inconclusive.

• …Dead-end for interpretation?

Size—Surface Magnitude

FP Tilt

• Quasar FP is composed of different overlapping, tilted planes for different subsamples.

• Subsamples have same re ~ e slopes but different tilts relative to MV(nuc) .– So host behavior is ~same, but it is connected to the

nucleus in different ways.

Is slope characteristic of accretion mechanism?

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?

Possible Outcomes1. 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.

• ?!?

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.