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Numerical {3 + 1} General Relativistic Hydrodynamics: A Local Characteristic Approach

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Banyuls, Francesc, Font, Jose A., Ibanez, Jose Ma., Marti, Jose Ma., Miralles, Juan A.·1997·The Astrophysical Journal

Abstract

We present a general procedure to solve numerically the three-dimensional general relativistic hydrodynamic system of equations within the framework of the {3 + 1} formalism. The equations are written in conservation form to exploit their hyperbolic character. We derive the theoretical ingredients that are necessary in order to build up a numerical scheme based on the solution of local Riemann problems. Hence the spectral decomposition of the Jacobian matrices of the system, i.e., the eigenvalues and eigenvectors, is explicitly shown. We have taken advantage of the analytic solution of the relativistic Riemann problem, recently derived in Minkowski spacetime, to extend the well-known battery of standard shock tube tests to general spacetimes as an important tool for calibrating any hydrocode. A selection of spherical and nonspherical accretion scenarios is presented and compared with the corresponding analytic or numerical solutions obtained by previous authors.

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Metadata

Authors
Banyuls, F., Font, J. A., Ibanez, J. M., Marti, J. M., & Miralles, J. A.
Venue
The Astrophysical Journal
Published
1997-02-10
Volume
476
Issue
1
Pages
221-231
ISSN
  • 0004-637X (ISSN-L)
  • 1538-4357
OpenAlex
W4240909640
Cited by
352
References
0
FWCI
6.58
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Numerical {3 + 1} General Relativistic Hydrodynamics: A Local Characteristic Approach. https://app.cochat.ai/papers/10.1086/303604
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Banyuls, F., Font, J. A., Ibanez, J. M., Marti, J. M., & Miralles, J. A. (1997). Numerical {3 + 1} General Relativistic Hydrodynamics: A Local Characteristic Approach. The Astrophysical Journal. https://doi.org/10.1086/303604

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.