1 / 45

Probing Small-Scale Structure in Galaxies with Strong Gravitational Lensing

Probing Small-Scale Structure in Galaxies with Strong Gravitational Lensing. Arthur Congdon • Rutgers University. Strong Gravitational Lensing. S. quasar, z ~ 1 - 5. . L. O. galaxy, z ~ 0.2 - 1. Lens equation:. where.

Download Presentation

Probing Small-Scale Structure in Galaxies with Strong Gravitational Lensing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Probing Small-Scale Structure in Galaxies with Strong Gravitational Lensing Arthur Congdon • Rutgers University

  2. Strong Gravitational Lensing S quasar,z ~ 1-5  L O galaxy, z ~ 0.2-1 Lens equation: where Lensing is sensitive to all mass, be itluminous or dark, smooth or lumpy

  3. Lensing by a Singular Isothermal Sphere (SIS) • Reduced deflection angle: • Lens equation: • Source directly behind lens producesEinstein ringwith angular “radius” qE

  4. SIS Lensing Courtesy of S.Rappaport

  5. SIS with Shear • Lens equation: • 1, 2 or 4 images can be produced

  6. SIS with Shear Courtesy of S.Rappaport

  7. “Double” Lensing by Galaxies:Hubble Space Telescope Images “Quad” “Ring” CASTLES ~ www.cfa.harvard.edu/castles

  8. Quasars as Lensed Sources • Radio emission comes from extended jets • Optical, UV and X-ray emission comes mainly from the central accretion disk

  9. Via Lactea CDM simulation (Diemand et al. 2007)

  10. Via Lactea CDM simulation (Diemand et al. 2007) • Hierarchical structure formation:small objects form first, then aggregate into larger objects

  11. Via Lactea CDM simulation (Diemand et al. 2007) • Hierarchical structure formation:small objects form first, then aggregate into larger objects • Large halos contain the remnants of their many progenitors - substructure

  12. cluster of galaxies,~1015 Msun vs. Clusters look like this - good! single galaxy,~1012 Msun (Moore et al. 1999)

  13. cluster of galaxies,~1015 Msun vs. Galaxies don’t - bad? single galaxy,~1012 Msun (Moore et al. 1999)

  14. Missing Satellites Problem Strigari et al (2007)

  15. Multipole Models of Four-Image Gravitational Lenses with Anomalous Flux Ratios MNRAS 364:1459 (2005)

  16. Four-Image Lenses Source plane Image plane

  17. Universal Relations for Folds and Cusps • Flux relation for a fold pair (Keeton et al. 2005): • Flux relation for a cusp triplet (Keeton et al. 2003): • Valid for all smooth mass models • Deviations small-scale structure

  18. Flux Ratio Anomalies • Many lenses require small-scale structure(Mao & Schneider 1998; Keeton, Gaudi & Petters 2003, 2005) • Could be CDM substructure(Metcalf & Madau 2001; Chiba 2002) • Fitting the lenses requires(Dalal & Kochanek 2002) • Broadly consistent with CDM • Is substructure the only viable explanation?

  19. “Minimum Wiggle” Model • Allow many multipoles, up to mode kmax • Models underconstrained  large solution space • Minimize departures from elliptical symmetry. B2045+265

  20. Multipole Formalism • • Convergence: • • Lens potential: • • 2-D Poisson equation: • Fourier expansion:

  21. Observational Constraints • Lens equation: • Image positions give 2n constraints • Magnification: • Flux ratios give n-1 constraints • Combine 3n-1 constraints into a single matrix equation:

  22. Solving for Unknowns • Use SVD to solve for parameters when kmax>4: • Minimize departure from elliptical symmetry (i.e., minimize wiggles): • Adding shear leads to nonlinear equations

  23. Solution for B2045+265

  24. Solution for B2045+265 Isodensity contours (solid) and critical curves (dashed)

  25. What Have We Learned from Multipoles? • Multipole models with shear cannot explain anomalous flux ratios • Isodensity contours remain wiggly, regardless of truncation order • Wiggles are most prominent near image positions; implies small-scale structure • Ruled out a broad class of alternatives to CDM substructure

  26. Analytic Relations for Magnifications and Time Delays in Gravitational Lenses withFold and Cusp Configurations Submitted to J. Math. Phys.

  27. Lens TimeDelays Robust probe of dark matter substructure? Q0957+561 Kundićet al. (1997)

  28. Local Coordinates Caustic (source plane) Critical curve (image plane) fold cusp

  29. Perturbation Theory for Fold Lenses Lens Potential: • Lens Equation: • For small displacements: (u1, u2) (eu1, eu2)

  30. Expand image positions in ε: Solve for coefficients to find: Image separation:

  31. Time-Delay Relation for Fold Pairs Scaled Time Delay: Use perturbation theory to get differential time delay: Time-delay anomalies may provide a more sensitive probe of small-scale structure than flux-ratio anomalies

  32. Comparison to “Exact” Numerical Solution Analytic scaling is astrophysically relevant (qE) (qE)

  33. Using Differential Time Delays to Identify Gravitational Lenses with Small-Scale Structure In preparation for submission to ApJ

  34. Dependence of Time Delay on Lens Potential and Position along Caustic • Use h as proxy for time delay • Model lens galaxy as SIE with shear • Higher-order multipoles are not so important here

  35. Variation of halong Caustic

  36. Variation of halong Caustic

  37. Variation of halong Caustic

  38. Time Delays for aRealistic Lens Population • Perform Monte Carlo simulations: • use galaxies with distribution of ellipticity, octopole moment and shear • use random source positions to create mock four-image lenses • use Gravlens software (Keeton 2001) to obtain image positions and time delays • create time delay histogram for each image pair

  39. Matching Mock and Observed Lenses

  40. Histograms for Scaled Time Delay: Folds PG 1115+080 SDSS J1004+4112

  41. Histograms for Scaled Time Delay: Cusps RX J0911+0551 RX J1131-1231

  42. Histograms for Time Delay Ratios: Folds HE 0230-2130 B1608+656

  43. What Have We Learned from Time Delay Analytics and Numerics? • Time delay of the close pair in a fold lens scales with the cube of image separation • Time delay is sensitive to ellipticity and shear, but not higher-order multipoles • For a given image separation and lens potential, the time delay remains constant if the source is not near a cusp • Monte Carlo simulations reveal strong time-delay anomalies in RX J0911+0551 and RX J1131-1231

  44. Acknowledgments I would like to thank my collaborators, Chuck Keeton and Erik Nordgren

More Related