Title: Stochastic Gravitational Lensing and the Nature of Dark Matter
1Stochastic Gravitational Lensingand the Nature
of Dark Matter
- Chuck Keeton
- Rutgers University
with Arthur Congdon (Rutgers), Greg Dobler
(Penn), Scott Gaudi (Harvard), Arlie Petters
(Duke), Paul Schechter (MIT)
Gravitational lens database -- http//cfa-www.harv
ard.edu/castles
2Outline
- Cold Dark Matter 101
- Gravitational Lensing 101/201
- Evidence for dark matter substructure
- catastrophe theory
- Stochastic gravitational lensing
- random critical point theory
- marked spatial point processes
- Some statistical issues
- Bayesian inference
- small datasets
- testing relations, not just parameters
3The Preposterous Universe
Can we go beyond merely quantifying dark matter
and dark energy, to learn about fundamental
physics?
4The Cold Dark Matter (CDM) Paradigm
- Dark matter is assumed to be
- cold non-relativistic
- collisionless only feels gravity
- axions, neutralinos, lightest supersymmetric
particle, - Successful in explaining large-scale properties
of the universe. - global geometry, distribution of galaxies, cosmic
microwave background, - Successful in describing many features of
galaxies and clusters. - the missing mass
- But several challenges (crises?) related to the
distribution of dark matter on small scales.
5CDM halos are lumpy
cluster of galaxies,1015 Msun
- Predictions
- Hierarchical structure formationsmall objects
form first, then aggregate into larger objects. - Small objects are dense, so they can maintain
their integrity during mergers. - Large halos contain the remnants of their many
progenitors - substructure. - Clump-hunting How to find them?
single galaxy,1012 Msun
(Moore et al. 1999 also Klypin et al. 1999)
6CDM halos are lumpy
cluster of galaxies,1015 Msun
vs.
- Clusters look like this - good!
single galaxy,1012 Msun
(Moore et al. 1999 also Klypin et al. 1999)
7CDM halos are lumpy
cluster of galaxies,1015 Msun
vs.
single galaxy,1012 Msun
(Moore et al. 1999 also Klypin et al. 1999)
8A Substructure Crisis?
- CDM seems to overpredict substructure. What does
it mean? - Particle physics
- Maybe dark matter isnt cold and collisionless.
(CDM is wrong!) - Maybe it is warm, self-interacting, fuzzy,
sticky, - Astrophysics
- We only see clumps if they contain stars and/or
gas. - Maybe astrophysical processes suppress star
formation in small objects, so most clumps are
invisible.
9A Substructure Crisis?
- CDM seems to overpredict substructure. What does
it mean? - Particle physics
- Maybe dark matter isnt cold and collisionless.
(CDM is wrong!) - Maybe it is warm, self-interacting, fuzzy,
sticky, - Astrophysics
- We only see clumps if they contain stars and/or
gas. - Maybe astrophysical processes suppress star
formation in small objects, so most clumps are
invisible.
Need to search for a large population of
invisible objects!
10Strong Gravitational Lensing
S
?
?
L
O
Lens equation
The bending is sensitive to all mass, be
itluminous or dark, smooth or lumpy.
11Point Mass Lens
- Bending angle
- Lens equation
- Two images for every source position.
- Source directly behind lens ?Einstein ring with
radius qE.
sources
lens
2 images of each source
Einstein ring radius
Of course, there is not much hope of observing
this phenomenon directly. (Einstein, 1936
Science 84506)
12Microlensing!
Data mining Need to distinguish microlensing
from variable stars.
(MACHO project)
13Lensing by GalaxiesHubble Space Telescope Images
Double
Quad
Ring
(Zwicky, 1937 Phys Rev 51290)
14Radio Lenses
Quad
10 442
Double
15What is lensing good for?
- Strong lensing
- Multiple imaging of some distant source.
- Used to study the dark matter halos of galaxies
and clusters of galaxies. - Microlensing
- Temporary brightening of a star in our galaxy.
- Used to probe for dark stellar-mass objects in
our own galaxy. - Weak lensing
- Small, correlated distortions in the shapes of
distant galaxies. - Used to study the large-scale distribution of
matter in the universe.
16Extended Mass Distributions 2-d Gravity
- Work with 2-d angle vectors on the sky.
- Interpret bending angle as 2-d gravity force ?
gradient of 2-d gravitational potential. - Extended mass distribution
- General lens equation
17Fermats Principle
- Time delay surface
- Lens equation
- Lensed images are critical points of ?.
- minimum
- saddle
- maximum
18Lensing and Catastrophe Theory
- Reinterpet lens equation as a mapping
- Jacobian
- The critical points of the mapping ? are
important - Observability image brightness given by
19Catastrophes in Lensing
1
3/2
5/4
Critical curves det J 0 (Two curves.)
Caustics Image number changes by ?2 Fold and
cusp catastrophes.
20Substructure ? complicated catastrophes!
(Bradac et al. 2002)
21(Schechter Wambsganss 2002)
22Parametric Mass Modeling
- Data
- Positions and brightnesses of the images. 3?Nimg
- (Maybe a few other observables.)
- Parameters
- Mass and shape of lens galaxy. 3
- Tidal shear field. 2
- Position and brightness of source. 3
- Substructure. ?
Public software -- http//www.physics.rutgers.edu/
keeton/gravlens
23Lensing and Substructure
- Fact
- In 4-image lenses, the image positions can be fit
by smooth lens models. - The flux ratios cannot.
- Interpretation
- Flux ratios are perturbed by substructure in the
lens potential. (Mao Schneider
1998 Metcalf Madau 2001 Dalal Kochanek
2002) - Recall
- positions determined by ?i fitrue ? fismooth
- brightnesses determined by fij fijtrue
fijsmooth fijsub
24Substructure Statistics
- Can always(?) add one or two clumps and get a
good model. - More interesting are clump population statistics.
Are they - Consistent with known populations of
substructure? - (globular clusters, dwarf galaxies, )
- Consistent with CDM predictions?
- None of the above?
25From Lensing to Dark Matter Physics
- Find lenses with flux ratio anomalies.
- catastrophe theory
- How do the statistics of anomalies depend on
properties of the substructure population? - random critical point theory
- marked spatial point processes
- Measure properties of substructure population.
- Bayesian inference
- small datasets
- Compare with CDM predictions.
- testing relations, not just parameters
- How do substructure population statistics depend
on physical properties of dark matter?
26Link 1 Finding flux ratio anomalies(CRK,
Gaudi Petters 2003 ApJ 598138 2005 ApJ 63535)
- Do the anomalies really indicate
substructure?Or just a failure of imagination in
our (parametric) lens models? - Complaints about model dependenceReal problem
is use of global failures to probe local
features. - Fortunately, catastrophe theory enables a local
lensing analysis that leads to some generic
statements
Use mathematical theory to develop a statistical
analysis to apply to astronomical data.
27 folds A1-A2 ? 0
PG 1115080
28 cusps A-BC ? 0
B2045265 (Fassnacht et al. 1999)
29Theory of fold catastrophes in lensing
- Jacobian
- Fold critical point (in appropriate coordinates)
- General perturbation theory analysis near fold
point - At lowest order, the two images mirror one
another.
30- Connect to observables
- Rfold vanishes with the distance between the
images. - But with an unknown coefficient!
31(No Transcript)
32Derive p(Rfold d1,d2)
- Afold depends on
- ?f derivatives
- Physical parameters galaxy shapes -- from
observed galaxy samples tidal shear -- from
theoretical models - Monte Carlos
- Generate 106 mock quads.
- Extract conditional probability density.
- What is the range of Rfold in realistic smooth
lenses? - If real lenses lie outside this range, they must
not be smooth. - ??????????????????? substructure.
- Analysis relies on generic properties of fold
catastrophes.
33Archetypal lenses
34Real lenses
35Real lenses
36The Fold and Cusp Relations
- Violations of the generic relations
- 5 anomalies among 12 fold lenses
- 3 anomalies among 4 cusp lenses
- (No firm conclusions about 6 cross lenses)
- Catastrophe theory reveals generic features
which guide data analysis - and provide a rigorous foundation for
substructure studies.
Substructure exists, and is relatively common.
37Link 2 Theory of Stochastic Lensing
- Now must understand what happens when we add
substructure. - Formally, system is described by
- where qi and pi are random variables.
- Images are critical points of ??? random critical
point theory. - Positions qi are independent and identically
distributed and pi are independent of qi (we
hope) ? marked spatial point process.
38What I want
- Given distributions for qi and pi, I want to
compute distributions for the image properties --
especially P(m). - Analytically, if possible.
- Explore large parameter spaces.
- Gain general insights, not just specific results.
- Clumps are independent and identically
distributed ? could use characteristic function
method. - But I cant do the (inverse) Fourier transforms.
39Physical Insight
- Newton gravity outside a spherical object is
insensitive to the objects internal structure. - ??????????????????????????????????????????????????
???
40Some analytic results
Implication To lowest order, all that matters is
the average density in substructure.
41Open questions
minimum
saddle
- For certain kinds of substructure, minima and
saddles respond in opposite directions. - But which direction?
- Why?
- How generic is that result?
- Signal seems to be present in data what does it
tell us about substructure?
(Schechter Wambsganss 2002)
42Some statistical issues
- Given p(msub), use Bayesian inference to
constrain substructure parameters. - Current data 22 quad lenses
- 8 anomalies in 16 fold/cusp lenses
- ? anomalies in 6 cross lenses
- Future samples 100s or 1000s, each with its own
probability density. - To test dark matter physics, will want to examine
relations.
43Conclusions
- Gravitational lensing is a unique probe of dark
matter. - Flux ratio anomalies ??substructure ? dark matter
physics. - Can do brute force analysis. But
interdisciplinary approach yields much deeper
results. - We can reliably identify anomalies.
- We can understand what aspects of substructure we
can measure. - We will eventually understand how substructure
probes dark matter physics. - We pose interesting math/stats questions then
use the answers to do exciting physics/astronomy!
44OLD SLIDES
45Optics
converging lens
diverging lens
46Gravitational Optics
47Gravitational Deflection of Light
r
M
Predicted by Einstein, observed by SirArthur
Eddington in the solar eclipse of 1919.