Combining Weak and Strong Cluster Lensing cont.jmerten/talks/grp180708.pdf · 2008. 7. 18. · We...
Transcript of Combining Weak and Strong Cluster Lensing cont.jmerten/talks/grp180708.pdf · 2008. 7. 18. · We...
Combining Weak and Strong Cluster Lensingcont.
July 18, 2008
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 1 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
The Method
We combine weak and strong galaxy cluster lensing in thefollowing way:
Reconstruction quantity is the lensing potential ψ
Maximum-likelihood approach
χ2(ψ) = χ2w (ψ) + χ2
s (ψ)
Fully non-parametric
Grid-based
Weak lensing input: ellipticity catalogue
Strong lensing input: critical curve or arc position
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 2 / 17
Weak Lensing
State-of-the-artobservations allow only fora (∼ 10x10) pixelreconstruction grid
Furthermore galaxies arenot distributedhomogeneously over thefield
Solution: Adaptive-averaging-processProblem:Grid points becomecorrelated
χ2w (ψ) =
∑i ,j
(ε− Z (z)γ(ψ)
1− Z (z)κ(ψ)
)i
C−1ij
(ε− Z (z)γ(ψ)
1− Z (z)κ(ψ)
)j
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 3 / 17
Strong Lensing
The exact position of thecritical curve is notobservable
Position of arcs is a verygood approximation forthe location of the criticalcurve
Arc positions are knownwith high accuracy
Using weak lensing gridresolutions would result ininformation loss
χ2s (ψ) =
∑i
|detA(ψ)|2iσ2
i
=∑
i
|(1− Z (z)κ(ψ))2 − |Z (z)γ(ψ)|2|2iσ2
i
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 4 / 17
Cluster Gallery
So far we did reconstructions of:
Purely synthetic simulationsFeed real calculated cluster values into the code togetherwith full critical curve
Realistic simulations by using Massimo’s simulator codeRay-tracing lensing simulation including realistic noise(background galaxy shape, PSF, seeing, foregrounds)
One reconstruction of a real galaxy clusterMS 2137 using VLT and HST images
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 5 / 17
Cluster Gallery
So far we did reconstructions of:
Purely synthetic simulationsFeed real calculated cluster values into the code togetherwith full critical curve
Realistic simulations by using Massimo’s simulator codeRay-tracing lensing simulation including realistic noise(background galaxy shape, PSF, seeing, foregrounds)
One reconstruction of a real galaxy clusterMS 2137 using VLT and HST images
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 5 / 17
Cluster Gallery
So far we did reconstructions of:
Purely synthetic simulationsFeed real calculated cluster values into the code togetherwith full critical curve
Realistic simulations by using Massimo’s simulator codeRay-tracing lensing simulation including realistic noise(background galaxy shape, PSF, seeing, foregrounds)
One reconstruction of a real galaxy clusterMS 2137 using VLT and HST images
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 5 / 17
Cluster Gallery
So far we did reconstructions of:
Purely synthetic simulationsFeed real calculated cluster values into the code togetherwith full critical curve
Realistic simulations by using Massimo’s simulator codeRay-tracing lensing simulation including realistic noise(background galaxy shape, PSF, seeing, foregrounds)
One reconstruction of a real galaxy clusterMS 2137 using VLT and HST images
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 5 / 17
A Synthetic Example
Figure: Fieldsize: 120”x120”; 2000 background galaxies, full criticalcurve
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 6 / 17
A Synthetic Example
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 7 / 17
The only 1D profile-plot I will show!
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 8 / 17
Realistic Simulation
Figure: Fieldsize 400”x400”; 1826background galaxies
Figure: Simulated CCD-imagewith Subaru characteristics
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 9 / 17
Realistic Simulation
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 10 / 17
Realistic Simulations cont. / g1
Name: g1
Fieldsize: 1280”x1280”
Weak lensing: 13797 galaxies
Strong lensing: Full critical curve
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 11 / 17
Realistic Simulations cont. / g51
Name: g51
Fieldsize: 1900”x1900”
Weak lensing: 30839 galaxies
Strong lensing: Full critical curve
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 12 / 17
MS 2137
Figure: Fieldsize 405”x405”; 1500background galaxies, arcsincluded
Figure: HST/WFPC2 image, firstradial arc to be discovered (Fortet al. 1992)
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 13 / 17
MS 2137
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 14 / 17
Outlook (large scale)
Comparison of weak, strong and combinedlensing-reconstructions with Massimo.
Web interface for the lensing simulator andreconstructions of a big simulated cluster sample withPeter and Massimo.
Application to more real data.
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 15 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Outlook (small scale): The ∇,4,∇4-Project
Flexion
Flexion finite differences schemes
Testing their implementation
Flexion χ2(ψ)-function
Fast χ2-minimisation algorithm
Testing its implementation
Reconstructions of synthetic clusters
Realistic simulations including flexion
Multiple image systems
...
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 16 / 17
Have a nice semester break!
Julian Merten (ZAH/ITA) Cluster Mass Reconstruction July 18, 2008 17 / 17