Quasar lenses as a cosmological probe

Masamune Oguri (NAOJ)
10/02/2010, QGC2010@Daejeon

Dark energy
Mysterious energy that
accelerates the universe
Modiﬁed gravity? Void?
Now, only astronomical
observations provide
a clue to its nature

http://map.gsfc.nasa.gov/

Astro2010: next 10yr science in the US
ground #1 ­ LSST

space #1 ­ WFIRST

Dark energy, dark matter,time-domain astronomy

Dark energy,
extra-solar planetProbing dark energy
MethodProbe

CMB anisotropyDA(z=1091)

Supernova IaDL(z)Baryon Acoustic Oscillation

DA(z), H(z)Weak lensing

G(z) (growth rate)

Cluster of galaxies

G(z) (growth rate)

Know systematics: example
Cosmological constraint
from type-Ia supernovae
Diﬀerent light-curve ﬁtting
methods yield inconsistent
results→ Results are alreadysystematics-limited !

based on Kessler et al. (2009)

Know systematics: example
Cosmological constraint
from type-Ia supernovae

Possible approaches?

Diﬀerent light-curve ﬁtting
methods yield inconsistent
1. work hard to reduce systematics
results

2. use many independent
methodsfor→ Results are alreadycross-checking systematics-limited !

based on Kessler et al. (2009)

Quasar lensingobserverlens= galaxysource= quasar

SDSS J1226­0006(Inada et al. 2003)

SDSS J0924+0219(Inada et al. 2003)
HST images (NASA/ESA/M. Oguri)Cosmology w/ quasar lenses
1. Strong lensing probability
2­1→ cosmic volume DA(z) H(z)2. Time delays between quasar images→ Hubble constant H0+ distance ratio DA(z)DA(zs)/DA(z,zs)Cosmology w/ quasar lenses
1. Strong lensing probability
2­1→ cosmic volume DA(z) H(z)2. Time delays between quasar images→ Hubble constant H0+ distance ratio DA(z)DA(zs)/DA(z,zs)

“Classical” lensing test
Fukugita et al. (1990), Turner (1990)

w/o dark energy

w/ dark energy

observerobservergalaxyquasar

galaxyquasar“standard volume”

Lensing test of dark energy
The probability that a quasar at zs is lensed
velocity function = galaxy
lensing cross section
number density (observed) (depend on galaxy proﬁle)zsp=dz0dngal
dvdvdr⇥sellensdz
selection function

cosmological volume DA(z)2H(z)-1
lensing power [DA(z,zs)/DA(zs)]2→ dark energy!

Sloan Digital Sky Survey
SDSS-I (2000-2005) & SDSS-II (2005-2008)
Imaging
8000 deg2 in ﬁve
optical bands
Spectroscopy
galaxies/quasars
selected fromimaging data

SDSS quasar lens search (SQLS)­ Survey of lensed quasars using the SDSS
spectroscopic quasar catalog­ Select candidates from morphology/color­ Follow-up observations for conﬁrmation
Team(PI) Masamune Oguri (NAOJ)
Bob Becker (UC Davis)
Joe Hennawi (MPIA)
Bart Pindor (Melbourne)(PI) Naohisa Inada (U Tokyo)
Gordon Richards (Drexel)
Issha Kayo (IPMU)
Don Schneider (PSU)
Chris Kochanek (OSU)
Min-Su Shin (Michigan)
Tomoki Morokuma (U Tokyo) Michael Strauss (Princeton)+ many others...

SDSS quasar lens search (SQLS)
Public web page, up-to-date info on SQLS
http://www-utap.phys.s.u-tokyo.ac.jp/~sdss/sqls/(Search “SDSS quasar lens search” on google/yahoo/bing/...)

Itʼs never easy...

[Hennawi et al. AJ, 131, 1 (2006)]

Itʼs never easy...
extendedobject ?
1Binary quasar...
[Inada et al. AJ, 135, 496 (2008)]

SDSS quasar lens search (SQLS)Current Status>98% of the survey done
46 conﬁrmed new lensed quasars
2 probable new lensed quasars
13 previously known lensed quasars→ 61 lensed quasars !
(cf. ~120 lensed quasars known to date)Constraining dark energy# of lenses as a function of image separation θvs. model predictions with diﬀerent ΩΛ (assume ﬂat)
The number is sensitive
to dark energy, withlarger ΩΛ being morelenses

Result from DR7: ΩM-ΩΛyrainPmilerCombine lens resultwith SDSS BAO(Eisenstein et al. 2005)

ΩM = 0.26

+0.03
­0.02

ΩΛ = 0.86

+0.09
­0.12

Consistent with“standard” modelResult from DR7: dark energyyrani

Pil mer

Assume a ﬂat universe
SQLS+BAO:ΩM = 0.24

+0.03
­0.02

w = ­1.40

+0.30
­0.25

Lens probability: summary­ Strong lensing probability of quasars is sensitive
to the evolution of cosmic volume, and hence
to dark energy­ We (SQLS) have construct the largest sample ofquasar lenses appropriate for statistical studies­ The result is consistent with the current standard
cosmological model, providing independent
conﬁrmation of dark energy

Cosmology w/ quasar lenses
1. Strong lensing probability
2­1→ cosmic volume DA(z) H(z)2. Time delays between quasar images→ Hubble constant H0+ distance ratio DA(z)DA(zs)/DA(z,zs)

Time delay

Arrival time
diﬀerence due togeometrical +gravitational eﬀect(observed for ~20 lenses so far)Δt
Poindexter et al. (2007)

Time delay

source quasar

lens galaxyDA(0,zl)DA(zl,zs)DA(0,zs)

DA (0, zl )DA (0, zs )tij = (1 + zl )( iDA (zl , zs )j)measure thisFermat potential (Blandford & Narayan 1986)(depend on image conﬁg. and lens potential)

probing the distance ratio­1H0

H0 and dark energy
The characteristic scale of CMB
is sound horizon at recombination( rs ~150 Mpc in comoving)rs

Constraint on dark energy from
CMB is only through this (→DA),
meaning that H0 and dark energy
are always degenerateDA(z=1091)

What we really measure is theangle subtended by rs, i.e.,θs = rs / DA(z=1091)
θs→ accurate H0 is a key to improve DE constraint!

Distance ratio cosmography
Time delays also probe
dark energy directly
through distance ratioDA(zl)DA(zs)/DA(zl,zs)
The unique distancecombination lead tothe unique degeneracy
direction, making it
valuable DE probe(see also Linder 2004)

LSST Science Book (arXiv:0912.0201)

However, ...
The biggest problem:
lens mass model
The resulting constraint
on H0 depends strongly
on assumed mass model!

(example for 4-image lens PG1115+080)

Two approaches
1. “Golden lens” approach
Investigate a singe lens in great detail toconstrain its mass proﬁle, and then use
it to constrain cosmological parameters(e.g., Suyu et al. 2010)

2. “Ensemble of lenses” approach
Combine many lenses to average out thelens mass model uncertainty

Two approaches
1. “Golden lens” approach
Investigate a singe lens in great detail toconstrain its mass proﬁle, and then use
it to constrain cosmological parameters(e.g., Suyu et al. 2010)

2. “Ensemble of lenses” approach
Combine many lenses to average out thelens mass model uncertainty

Statistics of time delays
Oguri ApJ, 660, 1 (2007)

A new statistical technique to combine
many time delay measurements
1. Deﬁne “reduced time delay” that quantiﬁes thecomplexity of the lens potential
2. Derive reduced time delays as a function of image
conﬁgurations and construct p(delay|image conﬁg.)
3. Compare it with observed delays to get constraints
on cosmological parametersreduced time delay

H0=50 km/s/Mpc

reduced time delay

image conﬁguration

image conﬁguration

reduced time delay

H0=70 km/s/Mpc

reduced time delay

image conﬁguration

image conﬁguration

reduced time delay

H0=90 km/s/Mpc

reduced time delay

image conﬁguration

image conﬁguration

Statistical constraint on H0
Oguri ApJ, 660, 1 (2007)­ Combined analysis oftime delays for 18 lenses­ Fixing other cosmologicalparameters, the Hubble
constant is constrained to
H0=70 6 km/s/Mpc

Future: LSST(Large Synoptic Survey Telescope)#1 in Astro2010
8.4-m telescope in Chili
Survey from ~2017
Cover the entire visible sky
every few days

http://www.lsst.org→ Time-domain data for
1/2 of the whole sky!

Lensed QSOs/SNe in LSST
Oguri & Marshall MNRAS, 405, 2579 (2010)~3,200 lensed quasars~130 lensed SNe(~35% is Ia)

Time delays will be measured for all of these!

Forecasting DE measurement
Oguri & Marshall MNRAS, 405, 2579 (2010)

w(z)=w0+[z/(1+z)]wa(CMB - Planck, SN - JDEM, Δt - LSST)

Future time delays can help to constrain w(z)Time delay: summary­ Time delays can be a unique probe of dark energy,
through H0 and distance ratio DA(zl)DA(zs)/DA(zl,zs)­ The current limiting factor is the mass distributionin lensing galaxy; we can get around this usingnovel statistical technique­ Currently time delays are already putting interestingcosmological constraints­ In the future, statistics of time delays can be a
powerful cosmological probe thanks to planned
time-domain surveys (e.g., LSST)

Thank you!
감사합니다!