Einstein

Einstein.jl is a high-performance suite designed to compute arbitrary-precision solutions of PDEs in general relativity.

https://github.com/auroradysis/einstein.jl

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Keywords

chebyshev finite-difference general-relativity pde pde-solver regge-wheeler-zerilli teukolsky
Last synced: 6 months ago · JSON representation ·

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Einstein.jl is a high-performance suite designed to compute arbitrary-precision solutions of PDEs in general relativity.

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chebyshev finite-difference general-relativity pde pde-solver regge-wheeler-zerilli teukolsky
Created about 1 year ago · Last pushed 7 months ago
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README.md

Einstein

Stable Dev Build Status Coverage Code Style: Blue Aqua

[!WARNING]
I'm still actively developing it and migrating code from private repositories to this one, so it may currently lack some features.

Motivation and Purpose

After developing hundreds of PDE solvers for various projects, I decided to create Einstein.jl because I couldn't find a library that was both highly convenient and effective for solving partial differential equations (PDEs) in the context of general relativity (GR).

When solving GR PDEs in spherical symmetry or even axisymmetry, the requirements are often far more demanding than in 3+1 cases. These include the need for very long-time simulations, conservation of quantities, highly accurate late-time behavior, and precise computation of quasinormal modes. While I have addressed these challenges individually in the past, I grew tired of copying and pasting solutions from old repositories. Instead, I decided to develop a comprehensive, feature-rich, and highly efficient library. This is my answer to those challenges.

Description

Einstein.jl is a high-performance suite designed to compute arbitrary-precision solutions of PDEs in GR. It is planned to support solving the following built-in equations (some of which were developed for previous projects and will be ported to this library):

Spatial Discretization

  • [x] Chebyshev collocation at Chebyshev points of the first and second kinds (Most of algorithms are translated from Chebfun)
  • [x] Finite difference method
    • [x] local barycentric Lagrange interpolation
  • [x] Hermite finite difference method
  • [x] ~~Rectangular collocation method (Most of algorithms are translated from Chebfun)~~ (Removed, see v1 branch)
  • [x] ~~Ultraspherical spectral method (Most of algorithms are translated from Chebfun)~~ (Removed, see v1 branch)
    • For boundary value problems, I recommend using ApproxFun.jl.
  • [ ] Ultraspherical rectangular collocation (tomtrogdon/URCMethod.jl: A Jupyter notebook with an implementation of the URC method)

General Utilities

  • [x] Correctly rounded floating-point dot/sum using xsum or Kahan summation
  • [x] Spin-weighted spheroidal harmonics using the Cook-Zalutskiy spectral method

Quasinormal Modes

  • [ ] Compute quasinormal modes for the Schwarzschild black hole using the Regge-Wheeler-Zerilli equation.
    • [ ] Continued fraction method to determine the eigenvalue
    • [x] Ultraspherical spectral method in hyperboloidal coordinates to determine the eigenfunction.
    • [x] Dolan and Ottewill Regge poles expansion method
    • [ ] WKB approximation
    • [ ] Direct integration method
  • [x] Compute quasinormal modes for the Kerr black hole using the Teukolsky equation.
    • [x] Continued fraction method for the radial equation (translated from duetosymmetry/qnm)
    • [x] Cook-Zalutskiy spectral method for the angular sector (translated from duetosymmetry/qnm)
    • [x] Direct integration method for the radial equation
    • [x] Ultraspherical spectral method in hyperboloidal coordinates to determine the eigenfunction.
  • Utilities
    • [x] Modified Lentz method for continued fractions
    • [ ] WKB approximation for general potentials

Some examples and tutorials are available in the examples folder, which are provided as Pluto.jl notebooks or Jupyter notebooks.

  • [x] Scalar QNMs of RN AdS black hole using the ultraspherical spectral method.

Time Domain

  • Spherical Symmetry

    • [ ] Regge-Wheeler-Zerilli equation
    • [ ] Hyperboloidal coordinates
    • [ ] Kerr-Schild coordinates
    • [ ] Tortoise coordinates
    • [ ] Klein-Gordon equation
    • [ ] Hyperboloidal coordinates
    • [ ] Kerr-Schild coordinates
    • [ ] Tortoise coordinates
    • [ ] Einstein equations with a scalar field
    • [ ] Z4 formulation
    • [ ] Hyperboloidal coordinates
  • Axisymmetry

    • [ ] Teukolsky equation
    • [ ] Hyperboloidal coordinates
    • [ ] Kerr-Schild coordinates
    • [ ] Tortoise coordinates
    • [ ] Klein-Gordon equation
    • [ ] Hyperboloidal coordinates
    • [ ] Kerr-Schild coordinates
    • [ ] Tortoise coordinates

While the ChebyshevSuite is inspired by algorithms from Chebfun, it has been significantly enhanced in this package to improve performance and support arbitrary-precision calculations.

Acknowledgments

This package is inspired by the following projects, and some of the algorithms are translated / adapted from them:

The author would like to thank the developers of these projects for their contributions to the scientific computing community.

Other Related Projects

Owner

  • Name: Zhen Zhong
  • Login: AuroraDysis
  • Kind: user
  • Location: Lisbon, Portugal
  • Company: Instituto Superior Técnico

Theoretical Physics

Citation (CITATION.bib)

@misc{Einstein.jl,
  author  = {Zhen Zhong <auroradysis@gmail.com> and contributors},
  title   = {Einstein.jl},
  url     = {https://github.com/AuroraDysis/Einstein.jl},
  version = {v1.0.0-DEV},
  year    = {2024},
  month   = {12}
}

@article{fornberg2021algorithm,
  title     = {An algorithm for calculating Hermite-based finite difference weights},
  author    = {Fornberg, Bengt},
  journal   = {IMA Journal of Numerical Analysis},
  volume    = {41},
  number    = {2},
  pages     = {801--813},
  year      = {2021},
  publisher = {Oxford University Press}
}

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juliahub.com: Einstein

Einstein.jl is a high-performance suite designed to compute arbitrary-precision solutions of PDEs in general relativity.

  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 0
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Dependent repos count: 3.2%
Average: 9.8%
Dependent packages count: 16.3%
Last synced: 7 months ago

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