Testing cosmology with galaxy clusters, the CMB and galaxy clustering
Towards an understanding of galaxy clusters
Transcript of Towards an understanding of galaxy clusters
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Towards an understanding of galaxy clusters
Julian Merten
Institut für Theoretische Astrophysik
Ruprecht-Karls Universität Heidelberg
ITP Cosmology Colloquium
Heidelberg, Oct. 26 2011
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Outline- Clusters of galaxies in the context of
structure formation
- Reconstructing mass distributions, as good as possible, as fast as possible
- Two applications: Pandora’s cluster meets the CLASH
- Sensible comparisons to simulations
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Structure forms hierarchically
ti
me
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Clusters of galaxies
∼ 1015M⊙ & Mpc scales
Appear to be DM dominated(85% DM, 13% hot gas, 2% stars)
Baryonic component not dominant, though not negligible
All main components are observable in three wavelength regimes
Powerful gravitational lenses => Cosmic laboratories
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Cosmic laboratoriesdark matter revealed through grav. lensing
the galaxies and the gascan be observed directly
computers createsimulated clusters
quite accurately
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Cosmic laboratoriesdark matter revealed through grav. lensing
the galaxies and the gascan be observed directly
computers createsimulated clusters
quite accurately
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Puzzling clusters
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Puzzling clusters
Ludlow+ 11
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Puzzling clusters
Ludlow+ 11
Ascasibar+ 06
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Puzzling clusters
Ludlow+ 11
Ascasibar+ 06
Rosati+ 09
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Puzzling clusters
Ludlow+ 11
Ascasibar+ 06
Rosati+ 09 Clowe+ 06
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Puzzling clusters
Ludlow+ 11
Ascasibar+ 06
Rosati+ 09 Clowe+ 06Coe+ 10
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Puzzling clusters
Ludlow+ 11
Ascasibar+ 06
Rosati+ 09 Clowe+ 06Coe+ 10
Postman & CLASH 11
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Shedding light
?
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Real world
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Cluster mass reconstructionsWish list Solution
nonparametric
wide range of scales
multiple constraints
single fit
fast also with errors
grid-based approach
AMR
multicomponent chi^2
reconstruct lensing potential
massively parallel implementation
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Useful observational constraints
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Gravitational lensingAstronomy picture of
the dayOct. 17
CLASH collab.
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Still to come
Charles Majer, Eleonora Sarli
& Agnese Fabris working on that
Newman 11+
Korngut 11+
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Numerical implementation
AMR
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Numerical implementation
Finite differencing on the grid
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Graphics processing units
Intrinsically massively parallel chip design
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Graphics processing units
We aquired new hardware, current speedup ~100,
pipeline development for Euclid, LSST, etc...
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Applications
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The case of Abell 2744
8 Orbits in Hubble Cycle17, PI: R. Dupke
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The case of Abell 2744
JM+ 11, we identified 34 multiple images
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The case of Abell 2744
before
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The case of Abell 2744
JM+11, MNRAS in press
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Pandora’s Cluster
NASA, ESA, CXC, D. Coe & J. Merten
Astronomy picture of
the dayJun. 29
Merten & Coe
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Pandora’s Cluster
JM+ 11, MNRAS in press
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Pandora’s Cluster
JM+ 11
This will becomea real challenge forsimulations
Collaboration withV. Springel’s groupin Heidelberg
A first search in MXXL was alreadysuccessful
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The CLASH
To map the DM profile and substructure to unprecedented precision
To detect SN 1a out toz ~ 2.5
To detect and analyse galaxies out to z > 7
To study the structure and evolution of galaxies in and behind the clusters
Science DriversOne of three HST/MCT programmes ~550 orbits
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The team
Granada, autumn of 2010
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The team
Heidelberg, two weeks ago
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The observing programme
25 clusters
20 X-ray selected
5 spec. lenses
0.18 < z < 0.9
use Hubbles full power
20 orbits and 16 filters /cluster
ACS/WFC3 in parallel
excellent photo z’s
BPZ / LePhare
follow-up time > CLASH
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That’s not all
BVRIZ Subaru imaging for almost all CLASH clusters
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That’s not all
VLT/Magellan specs for arcs and cluster members
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That’s not all
Bolocam / AMiBA / Mustang SZE observations
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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First results
The CLASH collaboration, some published some in prep.
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Simulations
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Two kinds of simulations
big box, many clusters,
few physics
small box, few clusters,
more physics
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Problems while comparing to simulations
- big boxes are usually DM only
- high-res cluster sims deliver only small samples
- impact of gas physics not completely clear yet
- not easy to compare apples and apples
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Problems while comparing to simulations
- big boxes are usually DM only
- high-res cluster sims deliver only small samples
- impact of gas physics not completely clear yet
- not easy to compare apples and apples
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Problems while comparing to simulations
- big boxes are usually DM only
- high-res cluster sims deliver only small samples
- impact of gas physics not completely clear yet
- not easy to compare apples and apples
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Problems while comparing to simulations
- big boxes are usually DM only
- high-res cluster sims deliver only small samples
- impact of gas physics not completely clear yet
- not easy to compare apples and apples
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Possible solutions
- Look into the simulations yourself, identify sensible quantities
- MultiDark, MXXL, DIANOGA, MUSIC
- Simulate an observation, pipeline is already available
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Summary
Clusters are a good example for a cosmic laboratory
Multiwavelength, multiscale observations of clusters seem to lead on simulations right
now
How to compare high-quality samples to simulations in an optimal way is not clear at
the moment