Survey Science Group Workshop
2013-02-15
박명구 , 한두환 ( 경북대 )
Quasar gravitational lens Quasar lensing
– quasars lensed by galaxies/clusters/dark ob-jects
– images: 2 to 4– separation
0.34” ~ 15.9” mostly in 0.5” ~ 4”
CASTLES– CfA-Arizona Space Telescope LEns Sur-
vey– lensed quasars (as of 2013/02)
Class A: 82 cases (I’d bet my life.)Class B: 10 cases (I’d bet your life.)Class C: 8 cases (I’d bet your life and
you should worry.)
Quasar Lensing & SDSS Quasar lensing
– multiple image quasars lensed by galaxy/clus-ter
– SDSS quasar sample lensing probability: ~10-3 100 lens systems expected from spectroscopic sam-
ple of 105 SDSS quasars 1000 lens systems plausible from 106 quasars ex-
pected in 104 deg2 well-defined sample??
– Well-defined selection function needed for statistical analysis
Statistics of lensing Tests
– probability of lensing (number of lensed quasars)
– configuration of lensing image number, separation, ge-
ometry brightness ratio
Depends on– cosmology– lenses
mass distribution spatial distribution evolution in z
– sources evolution in z
Probability Test Fukugita et al. (1992)
– Hewitt-Burbidge catalogue– expected number
: 3 : 5 : 18 : 46
– observed number 4 out of Hewitt-Burbidge catalogue
– large rejected Kochanek (1996)
– likelihood test for probability and separation– at 95% CL
Lee & Park (1994, 1998) Im et al. (1997) Chiba & Yoshii (1997, 1999)
Chae et al. (2003)– radio selected sam-
ple
Complications in lensing statistics– mass model of individual galaxy– sample construction– selection effects of surveys– magnification bias
faint sources get brightened and detectedsource distribution in luminosity and z
needed
Sloan digital sky survey Quasar Lens Search (SQLS)
– Algorithm to find lens candidates from quasars
typical FWHM for SDSS imaging data ≈ 1.”4small separation () system
– blended– morphological selection
large separation () system– deblended– color selection
brightness ratio
– Follow-up confirmationspectroscopic observationphotometric observation
– SDSS image
– Follow-up imaging
– Spectroscopic confirmation
Constraints on Dark Energy and Evolution of Massive Galaxies
Oguri et al. (2012) SDSS DR7 quasar catalog: 105,783 QSOs Selection function
26 strongly lensed quasars
Theoretical model– singular isothermal ellipsoid
– velocity function
– redshift evolution
– quasar luminosity function
– lensing cross sectionover lensing
area– lensing probability
– quasars should be brighter than lens
– completeness function– probability distribution
– numbers of lensed quasars
– likelihood
image separation distribution
flat universe
without galaxy evolution
with galaxy evolution
redshift evolution of velocity function
Worries– quasar luminosity function and its evolu-
tion– galaxy velocity function and its evolu-
tion– galaxy number evolution and its evolu-
tion
Image Separation Statistics 한두환 advantages & disadvantages
– less sensitive to dark energy– magnitude bias not required– source information not needed
Sample– 17 SQLS quasars of with source and
lens redshifts– 76 SQLS quasars with source redshifts
JVAS vs SQLS
Curvature test– mean image separation– magnitude selection: lens should be
bright enough
– Spearman rank correlation testfor
– 76 lensed QSOs
Image Separation Test Theoretical model
– singular isothermal sphere
– velocity function
– lensing probability
– differential probability
– expected vs observed
concordance model
Likelihood
z > 2.2 sample
MC check– generate mock sample from theoretical
probability distribution: 100, 1000– apply the same test
With galaxy evolution
constraints on galaxy evolution
Summary Lensing statistics
– contains information on cosmology and galaxies
– need to be careful– the more, the better: eBOSS, BigBOSS …