RECORD
Finding Apparent Horizons in Numerical Relativity
General Relativity and Quantum Cosmology · Submitted 7 Aug 1995
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim We find this symbolic differentiation method of computing the $H(h)$ Jacobian to be {\em much} more efficient than the usual numerical perturbation method, and also much easier to implement than is commonly thought.
The compiled record
The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
Open the compiled record
The abstract, sentence by sentence
This paper presents a detailed discussion of the ``Newton's method'' algorithm for finding apparent horizons in 3+1 numerical relativity. We describe a method for computing the Jacobian matrix of the finite differenced $H(h)$ function by symbolically differentiating the finite difference equations, giving the Jacobian elements directly in terms of the finite difference molecule coefficients used in computing $H(h)$. Assuming the finite differencing scheme commutes with linearization, we show how the Jacobian elements may be computed by first linearizing the continuum $H(h)$ equations, then finite differencing the linearized (continuum) equations. We find this symbolic differentiation method of computing the $H(h)$ Jacobian to be {\em much} more efficient than the usual numerical perturbation method, and also much easier to implement than is commonly thought. When solving the discrete $H(h) = 0$ equations, we find that Newton's method generally converges very rapidly. However, if the initial guess for the horizon position contains significant high-spatial-frequency error components, Newton's method has a small (poor) radius of convergence. This is {\em not} an artifact of insufficient resolution in the finite difference grid; rather, it appears to be caused by a strong nonlinearity in the continuum $H(h)$ function for high-spatial-frequency error components in $h$. Robust variants of Newton's method can boost the radius of convergence by O(1) factors, but the underlying nonlinearity remains, and appears to worsen rapidly with increasing initial-guess-error spatial frequency. Using 4th~order finite differencing, we find typical accuracies for computed horizon positions in the $10^{-5}$ range for $\Delta\theta = \frac{\pi/2}{50}$.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | This paper presents a detailed discussion of the ``Newton's method'' algorithm for finding apparent horizons in 3+1 numerical relativity. | contribution 0.99 | 0.68 | 0.08 | asserted 0.97 |
| s1 | We describe a method for computing the Jacobian matrix of the finite differenced $H(h)$ function by symbolically differentiating the finite difference equations, giving the Jacobian elements directly in terms of the finite difference molecule coefficients used in computing $H(h)$. | method 0.86 | 0.93 | 0.06 | asserted 1.00 |
| s2 | Assuming the finite differencing scheme commutes with linearization, we show how the Jacobian elements may be computed by first linearizing the continuum $H(h)$ equations, then finite differencing the linearized (continuum) equations. | method 0.94 | 0.79 | 0.05 | asserted 0.71 |
| s3 | We find this symbolic differentiation method of computing the $H(h)$ Jacobian to be {\em much} more efficient than the usual numerical perturbation method, and also much easier to implement than is commonly thought. | result 0.79 | 0.92 | 0.32 | asserted 1.00 |
| s4 | When solving the discrete $H(h) = 0$ equations, we find that Newton's method generally converges very rapidly. | result 1.00 | 0.93 | 0.17 | asserted 1.00 |
| s5 | However, if the initial guess for the horizon position contains significant high-spatial-frequency error components, Newton's method has a small (poor) radius of convergence. | limitation 0.70 | 0.91 | 0.09 | asserted 0.98 |
| s6 | This is {\em not} an artifact of insufficient resolution in the finite difference grid; rather, it appears to be caused by a strong nonlinearity in the continuum $H(h)$ function for high-spatial-frequency error components in $h$. | interpretation 0.96 | 0.86 | 0.13 | hedged possibility 0.51 |
| s7 | Robust variants of Newton's method can boost the radius of convergence by O(1) factors, but the underlying nonlinearity remains, and appears to worsen rapidly with increasing initial-guess-error spatial frequency. | result 0.62 | 0.76 | 0.17 | asserted 0.75 |
| s8 | Using 4th~order finite differencing, we find typical accuracies for computed horizon positions in the $10^{-5}$ range for $\Delta\theta = \frac{\pi/2}{50}$. | result 1.00 | 0.96 | 0.08 | asserted 1.00 |
What was examined, and what was not
- arXiv listing abstract v4
- full text
- figures and tables
- references and citing sentences
- relations to other papers
- P abstract
- S sections
- T body sentences
- C citations
- R cross-paper relations
The paper
Original abstract
This paper presents a detailed discussion of the ``Newton's method'' algorithm for finding apparent horizons in 3+1 numerical relativity. We describe a method for computing the Jacobian matrix of the finite differenced $H(h)$ function by symbolically differentiating the finite difference equations, giving the Jacobian elements directly in terms of the finite difference molecule coefficients used in computing $H(h)$. Assuming the finite differencing scheme commutes with linearization, we show how the Jacobian elements may be computed by first linearizing the continuum $H(h)$ equations, then finite differencing the linearized (continuum) equations. We find this symbolic differentiation method of computing the $H(h)$ Jacobian to be {\em much} more efficient than the usual numerical perturbation method, and also much easier to implement than is commonly thought. When solving the discrete $H(h) = 0$ equations, we find that Newton's method generally converges very rapidly. However, if the initial guess for the horizon position contains significant high-spatial-frequency error components, Newton's method has a small (poor) radius of convergence. This is {\em not} an artifact of insufficient resolution in the finite difference grid; rather, it appears to be caused by a strong nonlinearity in the continuum $H(h)$ function for high-spatial-frequency error components in $h$. Robust variants of Newton's method can boost the radius of convergence by O(1) factors, but the underlying nonlinearity remains, and appears to worsen rapidly with increasing initial-guess-error spatial frequency. Using 4th~order finite differencing, we find typical accuracies for computed horizon positions in the $10^{-5}$ range for $\Delta\theta = \frac{\pi/2}{50}$.
Human review
References
How later papers used it
46 later papers cite it
1 later paper by other authors is listed below: 1 used its method or tool.
Uses its method or tool 1 of 41 papers with this label
-
Detected a black hole forming near the origin shortly after the chain's components merged using the thorn from this paper.
Dipoles and chains of solitons in the Friedberg-Lee-Sirlin model (2024) · 0.96 · paraphrased: the licence does not allow quoting
How the literature uses it
41 arXiv papers cite this in 47 sentences
Papers citing it · 4 sentences without a confident label
Builds on it 1 paper
-
This is an extension of the widely used method developed in [ref] .
Horizons in a binary black hole merger I: Geometry and area increase · The optical scalars and marginally trapped surfaces · 0.81
Uses its method or tool 37 papers
-
We monitored the evolving system for the formation of an apparent horizon, a null trapped surface which implies the existence of an event horizon at some larger radius [ref] .
The evolution of conifolds · Apparent horizons · 0.87
-
It employs the BSSN formulation of the Einstein equations [ref] , uses the moving puncture method [ref] , the Carpet package for mesh refinement [ref] , the spectral solver described in [ref] for 3+1 initial data and Thornburg's AHFinderDirect [ref] .
Numerical relativity for D dimensional axially symmetric space-times: formalism and code tests · The numerical treatment · 0.99
-
The various horizons are located using the method described in [ref] .
The Shear at the Common Dynamical Horizon in Binary Black Hole Mergers and its Imprint in their Gravitational Radiation · Numerical Simulations · 1.00
Discussion
Know something about this paper? Leave a comment, or highlight any passage above to comment on it.