This is an old revision of this page, as edited by Hillman (talk | contribs) at 04:57, 18 August 2005 (Deleted redundant section (had link to entire artlcle, so why did this one end with a section stating the field equation, with no discussion of numerical issues using that information?)). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.
Revision as of 04:57, 18 August 2005 by Hillman (talk | contribs) (Deleted redundant section (had link to entire artlcle, so why did this one end with a section stating the field equation, with no discussion of numerical issues using that information?))(diff) ← Previous revision | Latest revision (diff) | Newer revision → (diff)Numerical relativity is a subfield of computational physics that aims to establish numerical solutions to Einstein's field equations in general relativity. Despite promising results, accurate and validated algorithms for Einstein's equations remain elusive. The size and complexity of the equations along with persisting inquiries in fundamental issues of relativity theory are attributed the cause of thus far unsuccessful attempts at resolution. Nonetheless, the field has prodigiously expanded in recent years as engaging research continues.
Numerical relativity attempts to acquire a comprehensive understanding of the complex nature of strong dynamical gravitational fields. Another topic under investigation in numerical relativity is the initial value problem of vacuum relativity. This involves partial differential equations, discretization techniques for these equations, treatment of black hole spacetimes, and the imposition of boundary conditions.
Numerical relativity research is distinct from work on classical field theories as many techniques implemented in these areas are inapplicable in relativity. Many facets are however shared with large scale problems in other computational sciences like computational fluid dynamics, electromagnetics, and solid mechanics. Numerical relativists often work with applied mathematicians and draw insight from numerical analysis, scientific computation, partial differential equations, and geometry among other mathematical areas of specialization.
See also
Links
http://www.emis.ams.org/journals/LRG/Articles/lrr-2003-3/node19.html
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