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Astrophysics Luncheon Seminar

Gravitational Lensing as a Tool for Cosmology: Sources of Bias and Techniques for Achieving its Full Potential
Presented by Michael Troxel
University of Texas at Dallas

Monday, November 25, 2013
12:00 noon in 169-336

Gravitational lensing has been identified as a critical tool in studying the evolution of large scale structure in the universe, as well as shedding light on the nature and influence of dark matter and dark energy. One of the primary systematic biases in weak lensing due to large scale structure (or cosmic shear) is the intrinsic alignment (IA) of galaxies, which poses a barrier to precision weak lensing measurements. Methods for identifying and removing its effects on cosmological information are key to the success of current and planned lensing surveys. We have expanded model-independent techniques to indirectly isolate and remove the IA contamination from the lensing signal. These self-calibration techniques take advantage of complimentary survey information to self-calibrate the lensing signal, which along with the unique lensing and IA geometry and separation dependencies, allow us to reconstruct the various IA correlations at the level of the spectrum and bispectrum. For cross-correlations, we have demonstrated that the self-calibration approach can reduce the IA bias over most relevant scale and redshift ranges by up to a factor of 10 or more. In the case of auto-correlations, we have demonstrated the feasibility of implementing the self-calibration for conservative estimates of photo-z accuracy in planned surveys. This could reduce a potential 10-20% bias in some cosmological information down to the 1-2% level. In both cases, the self-calibration has the added benefit of preserving the IA signal, that itself provides additional information which can be used in studying the formation and evolution of large scale structure in the universe. We have also investigated some impacts on kinematic and lensing information derived from the use of exact relativistic models for structures and cosmology with some level of anisotropies. We have found, for example, that ignoring substructure level anisotropies in structures could bias mass estimates by up to 10%.

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