Files in this item



application/pdfMcLaughlin_Sean.pdf (240kB)
(no description provided)PDF


Title:Statistical Computing for Galaxy Modeling and Gravitational Lens Detection
Author(s):McLaughlin, Sean
Contributor(s):Brunner, Robert J.; More, Anupreeta; KAVIL IPMU; CFHTLS
Lens Residual Model
Galaxy Modeling
Abstract:Strong gravitational lenses are a directly observable consequence of general relativity and one of the most exotic phenomena in the sky. However, they are extremely difficult to detect in survey images; though thousands are predicted to be visible from Earth, scientists only know of a few hundred. I've written a program that rapidly models the lensing galaxy and subtracts it away. It then looks at residuals in the image and analyses them for lens-like properties. This is an example of one of nearly a thousand simulated strong lenses the program was tested against. It shows the original image, the residuals after model subtraction, and the final result after the residuals have been analyzed. My advisor and I believe this technique shows promise as a strong lens detection technique in current and upcoming large scale surveys. Awarded First Prize in the Undergraduate Image of Research Contest 2015. For more information about the Image of Research--Undergraduate Edition go to:
Issue Date:2015-04
Rights Information:Copyright 2015 Sean McLaughlin
Date Available in IDEALS:2015-04-30

This item appears in the following Collection(s)

Item Statistics