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AGN Variability

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Log( Time Lag (Days) ) Quasar Variability vs. BH Mass. Where BH Mass ... B = (% blazars kept by the cut) / (% stars kept by the cut) ... – PowerPoint PPT presentation

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Title: AGN Variability


1
AGN Variability
2
Outline
  • AGN Variability
  • The Data Calibration
  • Optical Variability of Pre-identified Quasars and
    Blazars
  • Search for Blazars by their Optical Variability

3
AGN Emission Orientation
  • Type I Quasars
  • You see the disk
  • broad line region
  • Type II Quasars
  • You see the torus
  • narrow line region
  • Blazars
  • You see the jet

4
Type I Quasar Optical Variability
  • Quasars are known to vary
  • 10 over months to years
  • few percent over hours to days
  • Standard picture optical flux mainly from the
    accretion disk variability due to disk
    instabilities?
  • Or, variability not intrinsic to the AGN?
  • Starbursts in the host galaxy
  • Microlensing

5
Quasar Optical Variability
  • Quantitative predictions
  • Characteristic timescales of variability
  • Shape of the quasar light curves
  • Relation between variability and average flux
  • Qualitative associations
  • Relationship between variability and
  • X-ray loudness
  • Radio loudness
  • Black hole mass

6
Blazar Search via Optical Variability
  • Most blazars have been found in radio and/or
    X-rays
  • The SEDs have two peaks (synchrotron, Compton?)
    in IR-UV ?-ray
  • Optical selection effects ? different SED peak
    frequencies?
  • Possible serendipitous discoveries

7
Absolute Calibration
  • Zeropoints
  • Calculated using overlap with SDSS
  • Corrections by x coordinate, object flux, sky
    brightness
  • 112 CCDs 2 filter sets 10 chip regions 6
    mag bins 6 sky brightness bins 80,640
    multiplicative constants
  • Extinction Correction
  • Correct to our best night,
  • which should be approximately
  • photometric
  • Calculate a correction for
  • each RA degree (15 minutes)

8
Absolute Calibration
  • Quality cuts
  • Scan/area based
  • Astrometry, galactic latitude, FWHM, sky level,
    extinction, error on standards
  • Measurement based
  • Bad flag, neighbor cut,
  • bright star proximity cut
  • Good to 10 in flux

Average Individual Mag
9
Relative Calibration
  • The absolute calibration is not intended for
    variability studies
  • Better for variability relative calibration
  • Goal most consistent measurements
  • Not necessarily accurate magnitudes
  • Correct the data using our most stable scan as
    the standard
  • Make more detailed corrections
  • Makes stricter quality cuts

10
Calibration Challenges
  • Flat fielding problems
  • Scattered light in the camera
  • Unreliable PSF photometry of extended objects
  • Quickly changing weather
  • Surprises!

11
Relative Calibration
  • For each quarter square degree zone
  • Apply the zeropoints
  • Select the best scan
  • Take the scan with the narrowest
  • ltmeasgt - measscan
  • distribution

12
Relative Calibration
  • Y (time, RA) dependent corrections
  • To correct for changing weather
  • Fit linear correction vs. time over intervals of
    4 minutes
  • X dependent corrections
  • To correct for flat fielding problems, scattered
    light
  • Bin the data by x, correct for any discrete jumps

13
Relative Calibration
  • Quality cuts
  • Noise
  • Extended object cuts PSF/aperture comparison,
    strict neighbor cut
  • Check for outlier scans
  • Good to 3 in flux

Average Individual Mag
14
The Quasars
15
The Quasar Sample
  • 25,007 SDSS spectroscopically identified QSOs

Time Lag between Measurements
Measurements of Each
16
The Quasar Sample
Gunn r Magnitude
Redshift
17
The Structure Function
  • Variability measure
  • SF(?t) v(p/2)lt?m(?t)gt2 - lts2gt
  • SF(?t) vlt(?m(?t))2gt - lts2gt
  • where ?m(?t) m(t1) m(t2)
  • A robust measure for irregularly spaced data
  • Related to, for example, the autocorrelation
    function
  • SF(?t)2 2(s2 ?(?t))
  • Where s2 is the variance of the data
  • ?(?t) is the autocorrelation function

18
Quasar SF vs. Rest Frame Time Lag
Structure Function
Time Lag (days)
19
Quasar Variability vs. Time Lag Slope of the
Ensemble Structure Function
SF(?t) v( (p/2)lt ?m(?t)gt2 - lts2gt )
SF(?t) v(lt (?m(?t))2gt)
20
Quasar Variability vs. Time LagComparison with
Theory
Experiment SF Slopes
Theoretical SF Slopes
From Hawkins, MNRAS 329, 76 (2002)
21
Quasar Variability vs. Luminosity
  • Poissonian processes (such as a simple starburst
    model) predict a slope of -0.5 dL/L
  • (Cid Fernandes et al., ApJ 544123 2000)
  • SDSS measured a slope
  • -0.246 0.005
  • We measure a slope-0.285 0.002

Log( Variability )
Log( L2500 )
Where the variability vlt?m2gt - lts2gt SF
averaged over all measured time lags.
22
Quasar Flare Asymmetry
?Blue pairs that get
fainter ?Red pairs that get
brighter
Structure Function
Time Lag (Days)
We see no flare asymmetry. This is
Consistent with microlensing Inconsistent
with starbursts Inconclusive for disk
instabilities
23
Quasar Variability vs. X-ray Loudness
Log( Structure Function )
Variability
X-ray Loudness ? Louder
Quieter ?
Log( Time Lag (Days) )
Where the variability vlt?m2gt - lts2gt SF
averaged over all measured time lags.
24
Quasar Variability vs. BH Mass
Variability
Log BH Mass (x Msun)
Where BH Mass (107.69 Msun )( FWHM(Hß or
MgII) / 3000km/s )v( ?L?(5100Å) / (1044 ergs/s)
) As described by Salviander et al., ApJ 662, 131
2007 Thought to be accurate to a factor of 3.
25
Quasar Variability vs. Eddington Ratio
Log( Variability )
Variability
Log( L2500 )
Eddington Ratio
The Eddington ratio a luminosity / mass
26
Variability of Type II QSOs?
  • Identified by flux ratios of narrow to broad
    lines
  • Zakamska et al., AJ 1262125 2003 published 291
    candidate Type II QSOs from the SDSS (as of 2003)
  • I added 378 SDSS quasars with OIII?5007/Hß gt 3
  • Seen through the torus
  • Disk and broad line region hidden
  • Narrow lines dominant

27
Variability of Type II QSOs?
Type II QSO SF vs Time Lag
SF for all quasars (blue)
Structure Function
Structure Function
Time Lag (Days)
Time Lag (Days)
and a sample of stars (black)
28
The Blazar Sample
  • 149 BL Lacs
  • 198 FSRQs
  • Taken from multiple sources X-ray radio
    searches, serendipitous optical spectroscopy

FR I
FR 2
FSRQs
BL Lacs
29
Blazar Optical Variability
  • Can vary by gt100 over days!
  • From jet effects such as
  • Uneven injection rate at the base causing
    internal shocks
  • Changing jet orientation due to internal
    instabilities and surrounding gas

30
Blazar Variability vs. Time Lag
BL Lacs
FSRQs
Structure Function
Structure Function
Time Lag (Days)
Time Lag (Days)
31
BL Lac Structure Function
Single Flare Simulation Flares of length 0 to 30
days, amplitude 2 magnitudes
Real Data
Structure Function
Structure Function
Time Lag (Days)
Time Lag (Days)
32
FSRQ Structure Function
Single Flare Simulation Flares of length 0 to
1600 days, amplitude 1 magnitude
Real Data
Structure Function
Structure Function
Time Lag (Days)
Time Lag (Days)
33
Blazar Search
  • 7600 square degrees search area
  • galactic latitude gt 40 to minimize contamination
  • Select objects seen to jump gt0.4 magnitudes
    between 2 scans in both R and I
  • ? 3955 variables

Blazars
Variables
Quasars
34
Sample Lightcurve of a QUEST Variable (found to
be a QSO)
R magnitude?
I magnitude?
35
Object Identification To Date
  • 468/3955 are previously published
  • 168 quasars
  • 34 blazars
  • 75 radio and/or X-ray sources
  • 77 SDSS UV excess QSO candidates
  • 28 QUEST I Variables
  • 15 galaxies
  • 1 white dwarf

36
Object Identification To Date
  • 13 spectra taken
  • 6 quasars (some FSRQs?)
  • (incl. 5 radio sources)
  • 4 BL Lacs (featureless) (incl. 3 radio sources)
  • 2 CVs
  • 1 star
  • Telescope time proposed on the Palomar 200
    telescope for more spectroscopic followup

37
Future Work
  • Model SF results using a more realistic
    parameterization
  • Include wavelength information (other filters) in
    the variability analysis
  • Look more into type IIs

38
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39
Absolute Calibration
Completeness
Purity
40
Relative Calibration
Completeness
Purity
41
The Quasar Sample
Time Lag between Measurements
Yearly Cycles
Monthly Cycles
42
Quasar Variability vs. Radio Properties
Radio to Optical Ratio
Radio Luminosity
Helfand et al. AJ 1211872 2001
43
QUEST Variables Characterization by Color
  • Downgrade objects that fit well to stellar
    template spectra
  • Use QUEST, SDSS, GALEX, 2MASS data
  • Fits are most discriminating in areas covered by
    all of the surveys
  • Diagnostics of the cut effectiveness
  • Q ( quasars kept by the cut) / ( stars kept
    by the cut)
  • B ( blazars kept by the cut) / ( stars kept
    by the cut)

44
QUEST Variables Characterization by Color
  • 4 combinations of coverage
  • SDSS GALEX 2MASS QUEST
  • (Q, B) (5.8, 4.9)
  • 86 objects, 17 appear non-MS
  • SDSS 2MASS QUEST
  • (Q, B) (6.5, 5.6)
  • 149 objects, 27 appear non-MS
  • GALEX 2MASS QUEST
  • (Q, B) (2.3, 5.1)
  • 2047 objects, 226 appear non-MS
  • 2MASS QUEST
  • (Q, B) (1.5, 4.5)
  • 1673 objects, 228 appear non-MS
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