Tracing Dark and Luminous Matter in COSMOS: Key Astrophysics and Practical Restrictions James Taylor (Caltech) -- Cosmos meeting -- Kyoto, Japan -- May

Tracing Dark and Luminous Matter in COSMOS:Key Astrophysics and Practical Restrictions

James Taylor (Caltech) -- Cosmos meeting -- Kyoto, Japan -- May 24 -- 2005

COSMOS high-z convergence mapRichard Massey

Tracing the Matter Distribution with Lensing:Key Astrophysics


1) Cosmological Parameters: Precision Measurements within the LCDM Paradigm

* Power spectrum: total + evolution (shear power spectrum -> amplitude and evolution of fluctuations)

* Features in the Power Spectrum (baryon wiggles)

* Clustering, Higher Moments (power spectrum + Gaussianity)

* Lens-Source Distance Ratios (equation of state/background cosmology)

* Numbers of Individual Objects (cluster number counts, catalogs for follow-up)

* Halo properties?

Bread and butter science; cosmic variance a problem

2) Testing the LCDM, The Nature of Dark Matter, Fundamental Physics

* Small-scale power (<- power spectrum features, CDM self-interaction, annihilation, decay, baryon coupling)

* Halo Shapes (CDM vs. alternatives, constraints on modified gravity)

* Halo Central Densities (CDM physics, power spectrum)

* Halo Substructure (same + CDM-baryon interaction)

Fundamentally important but plain vanilla model has survived similar tests so far

3) Mass versus Light (Baryons versus CDM)

* Halo Occupation (galaxy formation; group and cluster luminosity functions)

* Galaxy Environment (only statistical, but extend observed low-z trends to high z )

* (Individual) Galaxy Properties vs. Halo Properties (from gg lensing; fundamental issue in galaxy formation)

* Halo Central Densities (adiabatic contraction, feedback, galaxy formation physics)

Tracing the Matter Distribution with Lensing:Key Astrophysics


1) Cosmological Parameters: Precision Measurements within the LCDM Paradigm

* Power spectrum: total + evolution (shear power spectrum -> amplitude and evolution of fluctuations)

* Features in the Power Spectrum (baryon wiggles)

* Clustering, Higher Moments (power spectrum + Gaussianity)

* Lens-Source Distance Ratios (equation of state/background cosmology)

* Numbers of Individual Objects (cluster number counts, catalogs for follow-up)

* Halo properties?

Bread and butter science; cosmic variance a problem

2) Testing the LCDM, The Nature of Dark Matter, Fundamental Physics

* Small-scale power (<- power spectrum features, CDM self-interaction, annihilation, decay, baryon coupling)

* Halo Shapes (CDM vs. alternatives, constraints on modified gravity)

* Halo Central Densities (CDM physics, power spectrum)

* Halo Substructure (same + CDM-baryon interaction)

Fundamentally important but plain vanilla model has survived similar tests so far

3) Mass versus Light (Baryons versus CDM)

* Halo Occupation (galaxy formation; group and cluster luminosity functions)

* Galaxy Environment (only statistical, but extend observed low-z trends to high z )

* (Individual) Galaxy Properties vs. Halo Properties (from gg lensing; fundamental issue in galaxy formation)

* Halo Central Densities (adiabatic contraction, feedback, galaxy formation physics)

Expectations: Number of virialized halos

N(>M)

Halo Mass (Mo)

Mass function integrated from z = 0 - 1.5, over 2 s.d.

(cosmic variance from sigma(Vol) + shot noise)

possible weak lensing detections

current detections

Expectations: Number of Lensing Detections

Treat halos as isothermal spheres of velocity dispersion Shear signal goes as:

S = 2.4% (15’/ap) (/1000 km/s)2(Dls/Dos)

Given @20 galaxies/’2 Need a 10’ aperture to overcome intrinsic noise

Sensitivity drops at high z Dls/Dos

Overall, expect, approx. 1 source at S/N @ 3-410 @ 2-3, 100 @ 1-2 in current maps

So only a few objects are obvious detections, but there is signal in thelow-sigma peaks

Z = 0.2 - 1.0

dz = 0.05 slices

N(>S)

(km/s)

Expectations: Completeness and Contamination

Hennawi & Spergel (2004): n vs efficiency ee = real/(real+contamination)

Expectations: Completeness and Contamination

Hennawi & Spergel (2004): n vs efficiency ee = real/(real+contamination)

How to Compare Mass Maps and Light Maps?

Problem: low signal-to-noise in both mapson the scales of interest (5-10’), complicated systematics / projection effects

Two strategies: - consider theoretical expectations - search adaptively around peaks





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Shear vs. photo-z around peaks, along promising lines of sight

Shear vs. photo-z around peaks, along promising lines of sight

Summary

* Lots of well-defined science to do with weak lensing: testing the concordance model, constraining parameters, relating mass and light

* Cosmic variance a problem for statistical tests; intrinsic difficulties (low S/N, projection effects) a problem for object-based tests

* Need to use luminous data to maximum effect (role as test-bed for future surveys)

* Example: even without sophisticated filtering, detect approx. 5-10 good cluster candidates along various lines of sight

* Can also do semi-statistical studies? (binning over med. S/N data)


Example: Galaxy Properties by Projected Environment

Bin galaxies by local convergence in the medium-redshift map 7 bins

should sort by mean density, especially between z = 0.2 and 0.9


Z = 0.2 - 0.9

Z = 0.2 - 0.4

Convergence BinConvergence Bin

Convergence Bin

T log(M)


Z = 0.2 - 0.9

Z = 0.2 - 0.4

Convergence BinConvergence Bin

Convergence Bin

T log(M)

Documents

Tracing Dark and Luminous Matter in COSMOS: Key Astrophysics and Practical Restrictions James Taylor (Caltech) -- Cosmos meeting -- Kyoto, Japan -- May