Pith. sign in

REVIEW 4 cited by

Initial Data for Numerical Relativity

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv gr-qc/0007085 v1 pith:3WMYXATL submitted 2000-07-31 gr-qc

Initial Data for Numerical Relativity

classification gr-qc
keywords datainitialnumericaleinsteinequationsformalismsrelativityused
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Initial data are the starting point for any numerical simulation. In the case of numerical relativity, Einstein's equations constrain our choices of these initial data. We will examine several of the formalisms used for specifying Cauchy initial data in the 3+1 decomposition of Einstein's equations. We will then explore how these formalisms have been used in constructing initial data for spacetimes containing black holes and neutron stars. In the topics discussed, emphasis is placed on those issues that are important for obtaining astrophysically realistic initial data for compact binary coalescence.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Black Hole Black Boxes: Numerical Black Hole Metrics via AInstein Neural Networks

    gr-qc 2026-07 conditional novelty 6.0

    Unsupervised Lorentzian PINNs with embedded S^{2} topology recover maximally extended Schwarzschild and yield candidate Petrov type-I vacuum black-hole metrics with genuinely trapped interiors.

  2. Solving Hamiltonian Constraint Equation with Physics-Informed Neural Networks

    gr-qc 2026-07 conditional novelty 5.5

    PINNs with specialized techniques solve the nonlinear Hamiltonian constraint for generic binary black hole initial data, matching traditional NR accuracy.

  3. Thermodynamics of boosted Schwarzschild black holes

    gr-qc 2026-07 conditional novelty 5.0

    A boosted Schwarzschild black hole has temperature T_H=(8πMγ)^{-1}, chemical potentials μ^i=-v^i, entropy S=4πP^aP_a, and first law dS=8πM u_a dP^a.

  4. Dynamical Boson Stars

    gr-qc 2012-02 unverdicted novelty 2.0

    Boson stars are particle-like solutions in general relativity that model dark matter, black hole mimickers, and binary systems.