Survey Science Group Workshop

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 …