Dark Energy Studies: Challenges to Computational Cosmology
Abstract
The ability to test the nature of dark mass-energy components in the universe through large-scale structure studies hinges on accurate predictions of sky survey expectations within a given world model. Numerical simulations predict key survey signatures with varying degrees of confidence, limited mainly by the complex astrophysics of galaxy formation. As surveys grow in size and scale, systematic uncertainties in theoretical modeling can become dominant. Dark energy studies will challenge the computational cosmology community to critically assess current techniques, develop new approaches to maximize accuracy, and establish new tools and practices to efficiently employ globally networked computing resources.
Cite
@article{arxiv.astro-ph/0510194,
title = {Dark Energy Studies: Challenges to Computational Cosmology},
author = {James Annis and Francisco J. Castander and August E. Evrard and Joshua A. Frieman and Enrique Gaztanaga and Bhuvnesh Jain and Andrey V. Kravtsov and Ofer Lahav and Huan Lin and Joseph Mohr and Paul M. Ricker and Albert Stebbins and Risa H. Wechsler and David H. Weinberg and Jochen Weller},
journal= {arXiv preprint arXiv:astro-ph/0510194},
year = {2007}
}
Comments
5 pages, theory white paper submitted to the Dark Energy Task Force