Pith. sign in

REVIEW 5 cited by

Extrinsic Curvature and the Einstein Constraints

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/0207095 v2 pith:BCM64PQW submitted 2002-07-24 gr-qc

Extrinsic Curvature and the Einstein Constraints

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

The Einstein initial-value equations in the extrinsic curvature (Hamiltonian) representation and conformal thin sandwich (Lagrangian) representation are brought into complete conformity by the use of a decomposition of symmetric tensors which involves a weight function. In stationary spacetimes, there is a natural choice of the weight function such that the transverse traceless part of the extrinsic curvature (or canonical momentum) vanishes.

discussion (0)

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

Forward citations

Cited by 5 Pith papers

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

  1. Black hole-neutron star binaries with high spins and large mass asymmetries: III. Properties of the ejected material and its electromagnetic signatures

    gr-qc 2026-07 conditional novelty 6.0

    High-spin, high-mass-ratio black hole–neutron star mergers eject 0.02–0.06 solar masses of neutron-rich (Y_e≈0.05) debris whose kilonovae are infrared-bright, optically dark, and match late-time AT2017gfo while stayin...

  2. Data-Driven Acceleration of Eccentricity Reduction for Binary Black Hole Simulations

    gr-qc 2026-04 unverdicted novelty 6.0

    A Gaussian Process Regression model trained on an archive of eccentricity-reduced binary black hole simulations predicts initial conditions that achieve low eccentricity with zero or one iteration.

  3. 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.

  4. Biased parameter inference of eccentric, spin-precessing binary black holes

    gr-qc 2025-10 unverdicted novelty 5.0

    Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.

  5. Implementation of multi-grid Poisson solver in numerical relativity and its application to gravitational collapse of massive star

    astro-ph.HE 2026-06 unverdicted novelty 4.0

    A grid-based multi-grid Poisson solver is implemented in numerical relativity, tested on puncture black holes and neutron stars, and used in a neutrino-radiation hydrodynamics simulation of 9 solar mass star collapse ...