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'''Numerical relativity''' is a subfield of ] that aims to establish numerical |
'''Numerical relativity''' is a subfield of ] that aims to establish ]s to ]s in ]. Numerical relativists use ]s to study ]s, ]s, and other phenomena predicted by ] ]. The goal of numerical relativity is to study ]s that cannot be studied by analytic means. The focus is therefore primarily on ]s. Numerical relativity has been applied in many areas: ] ], ], ] ]s and ]s, and the ]s and neutron stars, for example. In any of these cases, Einstein's equations can be formulated in several ways that allow us to evolve the dynamics. While ] methods have received a majority of the attention, characteristic and ] based methods have also been used. All of these methods begin with a snapshot of the ]s on some ], the initial data, and evolve these data to neighboring hypersurfaces. | ||
Despite promising results, accurate and validated ] 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. | Despite promising results, accurate and validated ] 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. |
Revision as of 21:18, 1 December 2005
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Numerical relativity is a subfield of computational physics that aims to establish numerical solutions to Einstein's field equations in general relativity. Numerical relativists use supercomputers to study black holes, gravitational waves, and other phenomena predicted by Einstein's Theory of General Relativity. The goal of numerical relativity is to study spacetimes that cannot be studied by analytic means. The focus is therefore primarily on dynamical systems. Numerical relativity has been applied in many areas: cosmological models, critical phenomena, perturbed black holes and neutron stars, and the coalescence of black holes and neutron stars, for example. In any of these cases, Einstein's equations can be formulated in several ways that allow us to evolve the dynamics. While Cauchy methods have received a majority of the attention, characteristic and Reggi calculus based methods have also been used. All of these methods begin with a snapshot of the gravitational fields on some hypersurface, the initial data, and evolve these data to neighboring hypersurfaces.
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 in 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.
Computational aspects
For D spatial dimensions in a simulation of, for example, a black hole spacetime where physical phenomena are reduced to a set of difference equations (restricted to finite difference methods) with a corresponding two dimensional NxN array of mesh points, and a mesh size of h, the CPU time has order O(N) and the memory required has order O(N). Coupled, non-linear, elliptic systems have O(N) computational work, where N is the number of discrete unknowns.
See also
Links
http://www.emis.ams.org/journals/LRG/Articles/lrr-2003-3/node19.html
http://xxx.lanl.gov/abs/gr-qc/9808024
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