Lecture 2: AGN Survey and Luminosity Function Xiaohui Fan AGN Summer School, USTC AGN Summer School, USTC May 25, 2007 Background: 46,420 Quasars from

Lecture 2: AGN Survey and Lecture 2: AGN Survey and Luminosity FunctionLuminosity Function

Xiaohui FanXiaohui Fan

AGN Summer School, USTCAGN Summer School, USTC

May 25, 2007May 25, 2007

Background: 46,420 Quasars from the SDSS Data Release Three

Goal

• Derive the density of AGNs as function of bolometric luminosity, redshift

(Lbol, z, type)

• Relates to:– Characterizing accretion history:

• Distribution functions of black hole activity as function of MBH, accrection rate and radiative efficiency and redshift

– Probing galaxy/BH coevolution– Test unification model

Basic Issues• Instead of (Lbol, z, type), we observe:

– N(f, z, AGN type, selection criteria)– Selection effect

• Incompleteness due to selection criteria (correctable)

• Selection bias (e.g., optical survey missing obscured sources)

– Bolometric correction– Redshift effect

• Flux-limited vs. volume limited, truncated data set• Limited luminosity range at any given redshift,

parametric vs. non-parametric• K-correction

Outline

1. AGN surveys

2. LF parameterization and selection effects

3. Evolution of optical AGN LFs• Density vs. luminosity evolution

• Downsizing

4. Putting things together:• Soltan argument and constraints of BH accretion

properties

5. Quasar Clustering

References• Textbook:

– Peterson Chaps 10 and 11

• Recent Review– Osmer, astro-ph/0304150

• Optical– Richards et al. 2006, AJ, 131, 2766

• X-ray– Brandt and Hasinger, 2005, ARAA, 43, 827

• Luminosity function methodology – Fan et al. 2001, AJ, 121, 31

• Luminosity function across wavelength– Hopkins et al. 2007, ApJ, 654, 731

• Soltan argument– Yu and Tremaine 2002, MRNAS, 335, 965

Observational Properties of AGNs

• Textbook definition– Small angular sizes (compact)

– Cosmological distance

– High luminosity?

– Broad-band continuum emission

– Emission Lines indicative of hard ionizing source

– Variability

– Polarization (subset)

• AGN surveys utilize one or more of these properties

How to find AGNs

• High luminosity AGNs:– LAGN >> Lgal

– AGN light dominates

– Point source in the wavelength observed

– Distinct SED

• Optical Color Selection– Sandage (1971)

– 2dF (2000):

• 400 deg2

• 25000 quasars

SDSS at Your Service

Courtesy of Arizona graduate students

SDSS Overview

• Primary Telescope: 2.5m wide-field (2.5 deg)

• Imaging Survey (wide-field 54 CCD imager)– Main Survey: 10000 deg2

– Five bands, 3000 – 10000 Å

– rlim ~ 22.5, zlim ~ 20.5

• Spectroscopic Survey– 106 galaxies (r<17.8)

– 105 quasars ( 0 < z < 6.5)

– Interesting stars, radio/x-ray sources etc.

SDSS Color Selection

• Color selection– Type-1 quasars– Low-z

• UV-excess (UVX), Palomar-Green (PG), 2dF etc.

• Contaminants: brown dwarfs

– High-z• Lyman break, SDSS,

DPOSS, APM• Contaminants: late type

stars, brown dwarfs

• >90% of known AGNs are color-selected

Stellar locus

quasarZ=3

Z=4

Z=5

Richards et al. 2002

Selection effect of color selection• z=2.5-3.0 gap

– Quasars have similar colors to F stars

• Missing redder or reddened quasars

• Missing obscured/type-2 objects

• Only sensitive to high level of activity, high AGN/host contrast

Slitless Spectroscopy

• Identify broad emission line from prism plates– Large Bright Quasar Survey (LBQS)– Hamburg ESO Survey (HES)– Palomar Grism Transit Survey

• Selection Effect– Strong redshift dependence– Biases towards strong emission line– Mostly on photographic plates, difficult to calibrate– Problem with crowded field

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

X-ray Surveys

• X-ray sky is dominated by AGNs

• X-ray selection sensitive to both type-1 and modestly obscured type-2 sources

• Chandra/XMM deep fields capable of reaching very low luminosity

• Host galaxy not an issue until ~10-5~-6 Eddington luminosity

Brandt and Hasinger 2005

Other Selection Methods• Radio

– Where everything started (Schmidt 1963)– ~10% quasars are radio-loud– FIRST and NVSS surveys– Does radio-loud quasars evolve the same way as radio-quiet ones?

• Near-IR selection– KX (K-band excess) method– Less affected by reddening

• mid-IR selection– Dust emission peaks at rest-frame 10-50 microns– Select both type 1 and type 2– Can select Compton-thick sources

• Variability• Proper motion survey• Serendipity (Spinrad method)

Quest to the Highest Redshift Quasars

•

SD

SS

Rad

io

AP

M

CC

D

IR survey(UKIDSS,VISTA, LBT)

So how far could each of these techniques go?

• Lyman break:– Quasars: 6.4– Galaxies: 7-8

• Slitless spectroscopy– Quasars: 4.7– Galaxies: 5.5

• multiwavelength– Quasars: 5.2 (X-ray), maybe 7?– Quasar: 5.8 (IR)– Quasar: 6.1 (radio)– Galaxies: 5.2 (radio)

• Variability:– Quasar: 4.5

• Luck:– Quasars: 4.3– Galaxies: 5.8

Surveys of low-luminosity AGNs

• Low-luminosity type 1 and type 2 sources in X-ray samples

• Emission-line selected sources in galaxy redshift surveys:– Optical wavelength: LAGN< L host

– Spectra dominated by host galaxy; stellar/ISM component

– CfA redshift survey sample (1980s)– Ho, Filippenko and Sargent (1997) sample: high S/N

spectra of 486 nearby galaxies; half shows AGN signatures

– SDSS selection: Hao et al., Kauffmann et al., Greene et al., Zakmaska et al. (excellent Ph . D. theses!!)

Selection of low-luminosity AGNs

• Stellar spectra subtraction– Best-fit templates constructed from Principle

Component Analysis

• Bladwin-Phillips-Telrivich Digram– Separating AGNs from starbursts

Hao et al.

Kauffmann et al.

Two extremes from galaxy surveys

• The smallest broad-line AGNs (Greene, Ho, Barth)

Greene et al.

The most luminous type-2 quasars

Zakamska et al.

Outline

1. AGN surveys

2. LF parameterization

3. Evolution of optical and X-ray selected AGNs• Density vs. luminosity evolution

• Downsizing

• The highest redshift quasars


properties


46,420 Quasars from the SDSS Data Release Three

wavelength4000 A 9000 A

reds

hift

0

1

2

3

5

Ly

CIV

CIIIMgII

HOIII

FeII

FeII

Ly forest


M-z distribution from SDSS

Luminosity Functions:1/VA Estimator (non-parametric)

minmax

11

zVzVVn

AX

minmax

11

zVzVVn

AX

Given a single object, X, visible within some volume, VA

Object Detectable

Object Too Faint

i iA

X VL

,

1̂ i iA

X VL

,

1̂

For a number of objects i: dLLLLi i : dLLLLi i :

This 1/VA estimator is a maximum likelihood estimator

This 1/VA estimator is a maximum likelihood estimator

TooBright

Issue: Binning; selection effcts

Parameterization

SIMPLE POINTS:• There is no difference in PDE vs. PLE for power-law LF;• But LF will eventually turn over for the total number to converge;• The real LF is likely more complex

Parameterization

• Quasar LF: double power-law

• Luminosity-dependent density evolution (Schmidt and Green 1983): (L,z) = (L,z) (L,z=0)

overall density evolves;Shape (bright and faint end slopes) evolves as well

(L) *

(L /L*) h (L /L*) l

(M) '*

100.4[M M * ][ h 1] 100.4[M M * ][l1]

Selection FunctionExample: optical color

selection• Color of quasar is a function of:

– Redshift

– Spectral property:

• Continuum slope

• Emission line strength

• For high-z : random distribution of absorption systems along line of sight

– Luminosity: error distribution in the survey

XF et al. 2001

f~-

Model selection function

• Construct model quasar color sets that includes realistic distributions of quasar spectral properties and observed error distributions, then run selection algorithm on model data set – -> p(L,z,SED)

• Limitations– Accuracy relies on assumptions on spectral property

distributions (which sometimes is derived from the same survey)

– Can never correct for objects that survey is insensitive to: optical: obscured sources, very red quasars etc.

– Correction is large (and sensitive) in some cases (e.g. optical: z~2.8


Outline

1. AGN surveys



• Downsizing



properties


Luminosity Function from 2dF Quasar Survey

Boyle et al. 2001

Luminosity function from 2QZ

• Best fit model: pure luminosity evolution:

: cosmic look-back time; L*() ~ exp(6) ~ 6; ~ -3.3; ~ -1.0

• However…• M* constant apparent mag

• Selection effect??• Faint end slope poorly determined

• From 2001 to 2004 papers

Croom et al. 2004

or L(z) ~ exp(6)

What’s the Faint End Slope of QLF?

Hao et al. 2004

z=0 Faint slope measurement

Ranges from -1.o to -2.0…

lead to large uncertainties in

in the total luminosity and

mass density of quasar pop.

SDSS quasar LF


SDSS quasar LF

• Strong evolution in bright end slope at z>3– Can’t be luminosity evolution all the way

• But doesn’t go faint enough at low-z to differentiate PLE from PDE or else


density evolution of luminous quasars

Exponential decline of quasar density at high redshift, different from normal galaxies Richards et al. 2006,

Fan e al. 2005

SFR of galaxies

Density of quasars

Bouwens et al.

X-ray AGN LF

• Result 1: Downsizing of AGN activity– Quasar density peaks at z~2-3

– AGN density peaks at z~0.5 - 1

– Paradox 1:

• Most of BH accretion happens in quasars at high-z

• Most of X-ray background in Seyfert 2s at low-z

X-ray LF

• Result 2:– PLE doesn’t work; need luminosity-dependent density evolution

to characterize evolution of the entire LF

Miyaji et al. 2006

X-ray LF

• Result 3:– Type 2 fraction a strong function of luminosity– Paradox 2:

• At high (quasar) luminosity: type 2 <20%; optical color selection is highly complete since all are type 1s, and includes most of luminosity AGN population emitted in the Universe

• At low (Seyfert) luminosity: type 2 ~80%; optical color selection miss most of the AGNs in the Universe in terms of number

Outline

1. AGN surveys



• Downsizing



properties


Putting things together: Evolution of bolometric

LF• Hopkins et al. (2007):– Combines QLFs in optical, X-ray and IR

– Over z=0-6 and the whole L range

– Accounting for distribution of absorbing column and luminosity-dependent SEDs

– Findings:

• PLE doesn’t work

• Both bright and faint-end slope evolve with z

• Luminosity-dependent density evolution provides good fit for all data

Downsizing in all bands

General Evolutionary Trends

• And a calculator: www.cfa.harvard.edu/~phopkins/Site/qlf.htmlhttp://www.cfa.harvard.edu/~phopkins/Site/qlf.html..

http://www.cfa.harvard.edu/~phopkins/Site/qlf.html

http://www.cfa.harvard.edu/~phopkins/Site/qlf.html

Putting things together: Soltan’s argument

• Soltan’s argument: QSO luminosity function (L,t) traces the accretion history of local remnant BHs (Soltan 1982), if BH grows radiatively

0

0

0

bol

2

bol

20 0 0

( , ) : local BH mass function,

( , ) : QSO luminosity function,

(1 ): efficiency,

(1 )( , ) d d ( , );

local accreted

.

M

M

t

n M t

L t

LM

c

LMn M t dM t L L t

c

Total mass density accreted = total local BH mass density

New estimates of BH mass densities

• Total local BH mass density:

– local BH mass function nM(M,t0):• SDSS early-type galaxy sample n(,t0) (Bernardi et al. 2001)• the tight M• – relation (Tremaine et al. 2002)

•,local=(2.50.4)105 M/Mpc3 (h=0.65) (Yu & Tremaine 2002)

• BH mass density accreted due to optically bright QSO phases:

(L,t): 2dF QSO Redshift survey (Boyle et al. 2000) •,acc=2.1105[0.1(1- ) /] M/Mpc3 (Yu & Tremaine 2002)

• Bright quasar phase can account for most of the BH mass growth; low efficiency accretion and obscured AGN not very important

0.1 if acc,local,

The history of BH mass density accreted during quasar phase

Yu and Tremaine 2002

Expanding Soltan’s Argument

Fitting QLF with local BHMF

Outline

1. AGN surveys



• Downsizing



properties


Galaxies are strongly clustered

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

How about quasars?

2dF

SDSS

Difficulty:Quasars are rare!Very large survey needed

quasars are as strongly clustered as galaxies

Idea of biased galaxy formation

Idea of biased galaxy/quasar formation

• Bias: the relative strength of clustering between galaxy (quasar) and underlying dark matter

• Biasing is unavoidable for rare, high-z systems• Bias factor (clustering strength) is a strong function of the

mass of dark matter halo that hosts galaxy (quasar) as well as redshift

• For a given cosmology: clustering strength constrains dark matter halo mass and its evolution

Clustering of Quasars

• What does quasar clustering tell us?– Correlation function of quasars vs. of dark matter

– Bias factor of quasars average DM halo mass

– Clustering probably provides the most effective probe to the statistical properties of quasar host galaxies at high-redshift

– Combining with quasar density quasar lifetime and duty cycle

Evolution of Quasar Clustering

• SDSS quasar survey– Clustering strength strong func.

of redshift

– Quasar lifetime ~10-100Myrs

– Quasars reside in 2-6x1012h-1Msun

DM halos

Shen et al. 2007

z=2.9-3.5

z>3.5

Summary• AGN Surveys

– All selection methods suffer from selection effect which needs to be taken into account carefully

– Optical surveys, esp. color selection are biased against obscured, reddened quasars and have low completeness at z=2.5-3.0

• AGN Luminosity Function– AGN density is strong function of redshift, and peaks at z~2– AGN LF is double power-law, with slopes also strong function of

redshift– Luminosity-dependent density evolution best describes all data– Local BH density can be accounted for by accretion in quasar

phase using Soltan’s argument

• AGN clustering– AGN are strongly clustered and strongly biased– Quasar clustering increases with redshift– Quasar clustering consistent with 107 yr lifetime and 1012-13 Msun

halo mass

Documents

Lecture 2: AGN Survey and Luminosity Function Xiaohui Fan AGN Summer School, USTC AGN Summer School, USTC May 25, 2007 Background: 46,420 Quasars from