Physics-informed neural networks reproduce the Schwarzschild and q-metric spacetimes with small error, but the q-metric result relies on an ansatz that already contains the exact solution.
Quadrupolar metrics
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abstract
We review the problem of describing the gravitational field of compact stars in general relativity. We focus on the deviations from spherical symmetry which are expected to be due to rotation and to the natural deformations of mass distributions. We assume that the relativistic quadrupole moment takes into account these deviations, and consider the class of axisymmetric static and stationary quadrupolar metrics which satisfy Einstein's equations in empty space and in the presence of matter represented by a perfect fluid. We formulate the physical conditions that must be satisfied for a particular spacetime metric to describe the gravitational field of compact stars. We present a brief review of the main static and axisymmetric exact solutions of Einstein's vacuum equations, satisfying all the physical conditions. We discuss how to derive particular stationary and axisymmetric solutions with quadrupolar properties by using the solution generating techniques which correspond either to Lie symmetries and B\"ackund transformations of the Ernst equations or to the inverse scattering method applied to Einstein's equations. As for interior solutions, we argue that it is necessary to apply alternative methods to obtain physically meaningful solutions, and review a method which allows us to generate interior perfect-fluid solutions.
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gr-qc 1years
2026 1verdicts
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Solving Einstein's Vacuum Equations with Physics-Informed Neural Networks: Boundary Conditions and Domain Decomposition
Physics-informed neural networks reproduce the Schwarzschild and q-metric spacetimes with small error, but the q-metric result relies on an ansatz that already contains the exact solution.